The 100 Most Cited Papers About Brain Metastases

Affiliations.

  • 1 Department of Neurosurgery, Pediatric Hospital of Athens, Goudi, Athens, Attica, Greece. Electronic address: [email protected].
  • 2 Department of Neurosurgery, 251 Greek Air Force Hospital, Goudi, Athens, Attica, Greece.
  • 3 Department of Neurosurgery, Centre Hospitalier de Wallonie, Picarde-CHwapi A.S.B.L, Tournai, Belgium.
  • 4 Department of Neurosurgery, Pediatric Hospital of Athens, Goudi, Athens, Attica, Greece.
  • PMID: 32147557
  • DOI: 10.1016/j.wneu.2020.02.156

Background: A vast amount of articles centered on brain metastases have been published.

Objective: To present the 100 most-cited articles dedicated to brain metastasis and to accomplish a broad literature review.

Methods: In December 2019, we performed a title-focused search using the Thomson Reuters Web of Science database to identify the most cited articles centered on brain metastatic disease. Our search query term was based on using the following algorithm: "brain metastases" OR "brain metastasis" OR "brain metastatic disease" OR "cerebral metastases" OR "cerebral metastasis" OR "cerebral metastatic disease." Afterward, we reviewed the results to certify that they were relevant to the purposes of our research protocol. The 100 most cited papers were chosen and further analyzed.

Results: Our search resulted in 11,579 articles, published from 1975 until the completion of our survey. The most cited article, by Patchell et al., was published in 1990, with 1862 citations, and an average of 62.07 citations per year, whereas the last in our list, by Gaspar et al., was published in 2010, with 195 total citations, and an average of 19.50 citations per year. Countries with the highest-cited articles included the United States (75 records), followed by Canada (16 records).

Conclusions: We discovered the top 100 most-cited articles centered on brain metastasis, all of which show a potentially increased level of interest, because they are meaningful scientific reports. In addition, we reviewed the historical development and advances in brain metastasis research and relevant points of interest, alongside the relevant contributions of different authors, fields of special interest, and countries. Many of the most cited articles were written by authors whose specialty was not neurosurgery or by neurosurgeons who were supported by colleagues from other medical fields. As a consequence, many of these articles were not published in neurosurgery-dedicated journals.

Keywords: Analysis; Articles; Bibliometric; Brain metastasis; Citation.

Copyright © 2020 Elsevier Inc. All rights reserved.

Publication types

  • Bibliometrics*
  • Brain Neoplasms / secondary*
  • Brain Neoplasms / surgery
  • Journal Impact Factor
  • Neurosurgery
  • Neurosurgical Procedures
  • Periodicals as Topic
  • Publications

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  • Data Descriptor
  • Open access
  • Published: 14 April 2023

A comprehensive dataset of annotated brain metastasis MR images with clinical and radiomic data

  • Beatriz Ocaña-Tienda   ORCID: orcid.org/0000-0001-8931-3836 1 ,
  • Julián Pérez-Beteta   ORCID: orcid.org/0000-0003-0317-6215 1 ,
  • José D. Villanueva-García 1 ,
  • José A. Romero-Rosales   ORCID: orcid.org/0000-0001-5154-3740 1 ,
  • David Molina-García   ORCID: orcid.org/0000-0002-6104-3894 1 ,
  • Yannick Suter   ORCID: orcid.org/0000-0003-1822-948X 2 ,
  • Beatriz Asenjo 3 ,
  • David Albillo   ORCID: orcid.org/0000-0002-4496-6849 4 ,
  • Ana Ortiz de Mendivil 5 ,
  • Luis A. Pérez-Romasanta 6 ,
  • Elisabet González-Del Portillo 6 ,
  • Manuel Llorente 4 ,
  • Natalia Carballo 4 ,
  • Fátima Nagib-Raya 3 ,
  • Maria Vidal-Denis 3 ,
  • Belén Luque 1 ,
  • Mauricio Reyes   ORCID: orcid.org/0000-0002-2434-9990 2 ,
  • Estanislao Arana 7 &
  • Víctor M. Pérez-García   ORCID: orcid.org/0000-0002-6575-495X 1  

Scientific Data volume  10 , Article number:  208 ( 2023 ) Cite this article

5116 Accesses

3 Citations

21 Altmetric

Metrics details

  • Applied mathematics
  • Translational research

Brain metastasis (BM) is one of the main complications of many cancers, and the most frequent malignancy of the central nervous system. Imaging studies of BMs are routinely used for diagnosis of disease, treatment planning and follow-up. Artificial Intelligence (AI) has great potential to provide automated tools to assist in the management of disease. However, AI methods require large datasets for training and validation, and to date there have been just one publicly available imaging dataset of 156 BMs. This paper publishes 637 high-resolution imaging studies of 75 patients harboring 260 BM lesions, and their respective clinical data. It also includes semi-automatic segmentations of 593 BMs, including pre- and post-treatment T1-weighted cases, and a set of morphological and radiomic features for the cases segmented. This data-sharing initiative is expected to enable research into and performance evaluation of automatic BM detection, lesion segmentation, disease status evaluation and treatment planning methods for BMs, as well as the development and validation of predictive and prognostic tools with clinical applicability.

Background & Summary

Brain metastases (BMs) represent the most common intracranial neoplasm in adults. They affect around 20% of all cancer patients 1 , 2 , 3 , 4 , 5 , 6 , and are among the main complications of lung, breast and colorectal cancers, melanoma or renal cell carcinomas 1 , 2 , 3 , 4 . The increasing availability of systemic treatments has improved the prognosis of patients with primary tumors, leading to an increase in the probability of developing BMs 2 , 3 , 6 , 7 .

BMs often appear as multiple lesions, with only around 25% of patients harboring a single BM 2 , 8 . On magnetic resonance imaging (MRI) studies, they are found to present contrast-enhancing features. Contrast-enhanced T1-weighted (CE-T1-W) MRI is the gold standard imaging sequence for BMs, providing information about lesion size, morphology and surrounding healthy structures 7 , 9 . T2-weighted imaging and fluid attenuation inversion recovery (FLAIR) MRI sequences are also used to help in identifying BMs, due to the surrounding edema found in many BM lesions 1 , 5 , 7 .

Treatment of BMs typically includes a combination of radiotherapy, chemotherapy, immunotherapy, targeted therapies, and/or surgery 1 , 2 , 3 . Radiotherapy schemes include whole brain radiation therapy and stereotactic radiosurgery (SRS). SRS is considered the standard of care in patients with limited metastatic burden 6 , 7 , 9 , 10 , 11 .

The clinical management of BMs undergoing radiotherapy requires time-consuming processes such as lesion identification and segmentation 2 , 3 , 12 . Time spent on those tasks could be reduced with the aid of semi-automatic or automatic computer-guided algorithms. Machine learning (ML) and deep learning (DL) techniques are being developed for different problems related to BMs, such as: automatic BM detection 5 , 6 , 7 , 12 , 13 , 14 , segmentation 11 , 13 , 14 , 15 and differential diagnosis of BMs from other brain tumors 7 , 12 , 16 . AI algorithms may also reduce human errors in all of those jobs that result from heavy workloads, allowing for increased reproducibility 6 , 12 .

Another problem in which AI can be helpful is the differentiation between post-treatment BM progression and radiation necrosis, a transient inflammatory effect after SRS. These two situations have overlapping features on MRI sequences, which makes it challenging to distinguish them visually 7 , 9 , 10 . Incorrect classification leads to unnecessary treatments and substantial patient harm. For this reason, AI methods have have been developed to automatically distinguish them 7 , 9 .

Finally, the development of prognostic and predictive metrics using the information contained in medical images is of the utmost importance because of the clinical implications. For BMs, the Graded Prognostic Assessment (GPA) index is the most popular clinically-validated prognostic scale 1 , 3 . However, it does not use any imaging information, but only clinical variables. In this sense, the field of Radiomics has the potential to improve the prognostic and predictive value of GPA and set the ground for novel indexes 17 , 18 . Radiomic-based research in brain tumors has been huge, and a variety of parameters have been studied 4 , 7 , 16 , 19 , 20 , 21 , 22 . Additionally, while morphological features obtained from MRI have proven effective in the setting of other brain tumors, little research has been done on their utility for BMs. 23 , 24 , 25 , 26 , 27 , 28 , 29 . The calculation of those biomarkers relies on brain tumor segmentations. Several approaches constructed using ML and DL algorithms have been proposed in the literature to automate this procedure 11 , 12 , 30 , 31 , 32 , 33 , 34 . However, due to the lack of large BM public datasets, there is no common ground on which they can be properly compared.

Publicly available datasets of BMs are limited. The most popular repository of images for cancer research is The Cancer Imaging Archive (TCIA) 35 , including more than 140 imaging repositories of different human cancers. However, in the case of BMs, only one database including 156 whole brain MRI studies have been found available 14 . This leads to the fact that while there is a good amount of public data for the much less frequent primary brain tumors such as glioblastoma, available datasets for BMs are scarce.

This study tries to solve that problem by contributing longitudinal magnetic resonance imaging studies of 75 BM patients, harboring 260 BM lesions, for a total of 637 imaging studies. Imaging studies include pretreatment post-contrast T1-w sequences, and most of them include other sequences such as T1, T2, FLAIR, DWI, etc. Semi-automatic segmentations of 154 different BMs for a total of 593 post-contrast T1-W segmentations are also provided with the dataset. These data are accompanied by an extensive database including clinical data and a set of morphological and radiomic-based features obtained from the segmentations.

MRI studies in our dataset have four times the number of segmentations than those currently publicly available 14 . Additionally, we make public three excel files, one of which contains clinical data, including patient information, details about the primary tumor, details about treatments, and the date of the patient’s death, as opposed to the already published one, which only contains information about the histology of the primary tumor.

Subject characteristics

Data collected include the follow-up imaging studies and clinical data of 75 BM patients from 5 different medical institutions. Inclusion criteria was defined as: deceased adult patients with pathologically confirmed diagnosis of BM between January 1, 2005 and December 31, 2021, availability of imaging studies with at least the post-contrast T1-w high-resolution sequence (pixel spacing ≤2 mm., slice thickness ≤2 mm., no gap between slices), no noise or artifacts in the images, and availability of basic clinical data (age at diagnosis, sex, treatment schemes followed, survival, etc.). Primary tumors were: Non-small cell lung cancer (NSCLC) (n = 38), small cell lung cancer (SCLC) (n = 5), breast cancer (n = 22), melanoma (n = 6), ovarian cancer (n = 2), kidney cancer (n = 1) and uterine cancer (n = 1).

The 75 patients included had a total of 260 BMs with a total of 637 imaging studies. Of those, 593 studies were semi-automatically segmented as described below.

Image acquisition

All post-contrast T1-W sequences were obtained after intravenous administration of a single dose of contrast. The 593 imaging sequences segmented were acquired with a 1-T (n = 8), 1.5-T (n = 550) or 3.0-T (n = 35) MR imaging scanners. Regarding the MR imaging  vendors, General Electric (n = 225), Philips (n = 197), and Siemens (n = 171) medical systems were used. Other image parameters are described in Table  1 .

Segmentation procedure

Segmentation was performed using an in-house semi-automatic segmentation procedure 26 , 28 . Tumors were automatically delineated by using a gray-level threshold chosen to identify the largest contrast-enhancing tumoral volume. Then, a biomedical engineer/applied mathematician (B. O.-T.) carefully corrected each segmentation, slice by slice, using a brushing/pixel-removing tool. The segmentation process is summarized in Fig.  1 . The outcome was cross-checked by three researchers with more than seven years of expertise on MRI (D. M.-G., J. P.-B., V. M. P.-G.) and then corrected by one of the radiologists participating in the study (B.A, A.O.M, D.A, L.A.P.-R., E.A.). The raw medical images in DICOM format were used in this procedure, so they were not modified to perform the tumor segmentations.

figure 1

Image segmentation procedure. From the MR images (T1-W with contrast), each slice was semi-automatically segmented and manually corrected. Once every slice was segmented, the last step was the three-dimensional reconstruction of the tumor.

Clinical data and anonymization

Clinical data were collected for the 75 patients. For each patient, age at diagnosis and sex, primary tumor type and subtype, molecular markers (e.g. EGFR, ALK and ROS1 for lung cancer) and tumor stage were taken. Also, the GPA index 1 , 3 , was included for a subset of institutions. Regarding each BM, the ID (a number to differentiate it from other BMs in the same patient), location in the brain (frontal, temporal, parietal and occipital, right and left side), date of appearance on MRI, and treatments received were recorded. For each treatment, the type of treatment, doses, fractions, date of start and date of end were recorded. The dates of follow-up MRI studies available were also included. Radionecrosis was confirmed for 39 lesions.

The first step of the data anonymization was performed at the institutions of origin of the data. Such a step included patient and center data anonymization. An additional more profound anonymization was performed using the clinical trials processor from the medical imaging resource center 36 . Within that step, all private DICOM tags and all tags containing sensitive or identifying information as well as all dates were modified such that for every subject, the imaging study where the first BM was initially identified corresponds to January 1st, 1900. The anonymized times were computed taking as reference that time point, in days, which means that negative numbers identified treatments prior to the diagnosis of the BM. The relative differences in times for the different events for each patient were preserved. The last anonymization step was a defacing process that made impossible the facial reconstruction. After this whole process, patient records were finally reviewed independently by three of the authors (B. O.-T., J. P.-B., and J. A. R.-R.).

Morphological parameters

Different morphological parameters were computed from the segmentations and gathered in the database, including the following:

For each focus, three different types of volumes were computed: the contrast-enhancing ( V CE ), necrotic (or non-enhancing) ( V N ) and total volume ( V  =  V CE  +  V N ).

Contrast-enhancing spherical rim width (CE rim width)

Obtained for each focus from the CE and necrotic volumes as

By assuming that the areas of necrotic tissue and the entire tumor are spherical, this feature calculates the average width of the CE areas. Additional information and illustrations of tumors with high and low CE rim widths, can be found in 29 .

Obtained by reconstructing the tumor surface using the Matlab “isosurface” command from the discrete sets of voxels characterizing the tumor.

Surface regularity

It is a dimensionless ratio between the volume of the segmented tumor divided by the volume of a spherical tumor with the same surface. For each focus, it was calculated as

The range for this parameter is 0 (for tumors with highly uneven surfaces) and 1 (for spherical tumors). Additional information and illustrations of tumors with high and low CE rim widths, can be found in 17 .

Maximum diameter

It provides the largest longitudinal measure of the tumor and is computed for each focus as the maximum distance between two points located on the surface of the CE tumor.

Radiomic-based features

A total of 110 different features were extracted with the open-source Python package PyRadiomics version 2.2.0 37 . This feature dataset includes 16 shape descriptors and different measures of the intensity distribution and texture within the segmentation labels. The intensity features include simple first-order statistics (19 features), those derived from the gray-level co-occurrence matrix (GLCM, 24 features), gray-level run-length matrix (GLRLM, 16 features), gray-level size-zone matrix (GLSZM, 16 features), neighboring gray-tone difference matrix (NGTDM, 5 features), and gray-level dependence matrix (14 features). The features were extracted from the original image sequence after z-score normalization, intensity scaling by a factor of 100 and subsequently shifting by 300 (i. e. three standard deviations) to ensure most intensity values are positive for the first-order features and geometry tolerance 0.04. Other specific tasks may require different feature extraction procedures 18 .

No voxel resampling prior to feature extraction was used to maintain the information as unaltered as possible. Since the algorithm to extract image features is shared, any user can redo the extraction by applying any resampling.

Atlas location features

Affine registration was used to align all subjects to MNI atlas space 38 using the mri_robust_register 39 . The centroid of each separate metastasis lesion was listed and may be used to efficiently identify the location and affected brain region.

Ethical approval

We have complied with all relevant ethical regulation and all subjects included in the study are deceased. Human data were obtained in the framework of the study OpenBTAI (Open database of Brain Tumors for studies in Artificial Intelligence), a retrospective, multicenter, nonrandomized study approved by the corresponding institutional review boards: Fundación Instituto Valenciano de Oncología (2021-05), Hospital Universitario HM Sanchinarro (21.06.1858-GHM), Hospital Universitario 12 de Octubre (21/711), Hospital General Universitario de Ciudad Real (12/2021), Hospital Regional Universitario de Málaga (24/06/2021), Hospital Universitario y Politécnico La Fe (2021-504-1), MD Anderson Cancer Center (01/06/2021), Hospital Universitario de Salamanca (2021 10 879), Complejo Hospitalario Universitario de Toledo (29/9/2021-770) and Hospital Universitario Marqués de Valdecilla (14/2021 – 10/09/2021).

Data Records

All data records collected for this manuscript are available at the Figshare Repository 40 and on the webpage https://molab.es where the number of cases will be expanded.

Raw medical images for each follow-up study have been stored using the Digital Imaging and Communications in Medicine image file format (DICOM, ISO 12052). Tumor segmentations and the corresponding images have been stored in The Neuroimaging Informatics Technology Initiative (NIfTI) format, maintaining raw medical image coordinates, since no preprocessing was used to perform the manual segmentations. We have uploaded six zip files with the DICOMS images, one containing all the segmentations (files ended _msk.nii) and one containing the corresponding images (files ended _img.nii) to each of the segmentations available. Also, three excel files containing: (1) all the clinical data, (2) morphological parameters measured directly from the segmentations, and (3) radiomic-based features computed for each follow-up study segmented are included together with the imaging data.

Technical Validation

Data collection.

The collaborating expert board-certified neuroradiologists identified and collected the 637 follow-up studies of the 75 BM patients included in the study. Only confirmed BM patients were included in the study, and primary tumors for each patient were pathologically confirmed and verified prior to inclusion in the study.

Data curation and testing of the inclusion criteria was performed by a biomedical engineer/applied mathematician with more than seven years experience in management of medical images (B. O.-T., D. M.-G., J. P.-B. and V. M. P.-G.) and then cross-checked by a different expert.

Segmentation method

All semi-automatic segmentations performed in this study were carefully validated by an expert radiologist after have been performed by experienced experts in the management of medical images and cross-checked by a different expert. A reproducibility study for the methodology was performed in 26 , showing its reliability.

Each segmentation mask contains two labels for each BM: labels ending in 1 correspond to contrast-enhancing (CE) parts of the tumor; labels ending in 2 represent the non-enhancing or necrotic area of the tumor. Features were extracted for CE and necrotic zones and also were computed for the combination of both.

Comparison between measurements obtained and radiomic features

Two excel files are provided with features from the segmented images. One of them contains some morphological variables computed directly from the manual segmentation while the other is a radiomic-based set of features.

Usage Notes

The whole dataset can be downloaded from the figshare repository 40 . To process the provided images and segmentations, it is highly recommended that medical imaging tools be used, which handle consistently the physical space and orientation of the images. We verified that all the Nifti files (segmentations and images) can be loaded correctly with FSLeyes v1.3.0 ( https://www.fsl.fmrib.ox.ac.uk ) (FMRIB Centre, Oxford, UK) and DICOM files could be easily loaded using Horos v3.3.6 ( https://www.horosproject.org ).

Code availability

We provide the code used to extract the features with PyRadiomics at https://github.com/ysuter/OpenBTAI-radiomics . For reproducibility and convenience in case any user wants to customize the extraction, all the.py files needed and a “readme” file are available.

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Acknowledgements

This research has been supported by grants awarded to V.M. P.-G. by the James S. Mc. Donnell Foundation, United States of America, 21st Century Science Initiative in Mathematical and Complex Systems Approaches for Brain Cancer (collaborative award 220020560, https://doi.org/10.37717/220020560 ), Ministerio de Ciencia e Innovación, Spain (grant numbers PID2019-110895RB-I00 and PDC2022-133520-I00) and Junta de Comunidades de Castilla-La Mancha (SBPLY/21/180501/000145). BOT is supported by the Spanish Ministerio de Ciencia e Innovación (grant PRE2020-092178).

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Mathematical Oncology Laboratory (MOLAB), University of Castilla-La Mancha, Ciudad Real, Spain

Beatriz Ocaña-Tienda, Julián Pérez-Beteta, José D. Villanueva-García, José A. Romero-Rosales, David Molina-García, Belén Luque & Víctor M. Pérez-García

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Yannick Suter & Mauricio Reyes

Radiology Department, Hospital Regional Universitario de Málaga, Málaga, Spain

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Radiology Department, MD Anderson Cancer Center, Madrid, Spain

David Albillo, Manuel Llorente & Natalia Carballo

Radiology Department, Sanchinarro University Hospital, HM Hospitales, Madrid, Spain

Ana Ortiz de Mendivil

Radiation Oncology Department, Hospital Universitario de Salamanca, Salamanca, Spain

Luis A. Pérez-Romasanta & Elisabet González-Del Portillo

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Contributions

B.O.-T., J.P.-B., D.M.-G., M. R., E.A. and V. M.P.-G. designed research; B.O.-T. performed the segmentations; Y.S. performed full data anonymization; B.A., D.A., A.O.M., L.A.P.-R., E.G.P., M.L., N.C., F.N.-R., M.V.-D., B.L. and E.A. collected data; B.O.-T., D.M.-G., J.P.-B., J.A.R.-R. and V.M.P.-G. analyzed data; D.M.-G. and V.M.P.-G. wrote the paper; All authors revised and corrected the manuscript. B.O.-T. and J.P.-B. contributed equally to the paper and V.M.P.-G and E. A. are both joint senior authors of this manuscript.

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Correspondence to Beatriz Ocaña-Tienda or Estanislao Arana .

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Ocaña-Tienda, B., Pérez-Beteta, J., Villanueva-García, J.D. et al. A comprehensive dataset of annotated brain metastasis MR images with clinical and radiomic data. Sci Data 10 , 208 (2023). https://doi.org/10.1038/s41597-023-02123-0

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Search strategy, selection criteria, and levels of validation, pet tracers for imaging of patients with brain metastasis, clinical applications for pet imaging in patients with brain metastasis, current limitations and future perspective, conflict of interest statement..

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PET imaging in patients with brain metastasis—report of the RANO/PET group

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Norbert Galldiks, Karl-Josef Langen, Nathalie L Albert, Marc Chamberlain, Riccardo Soffietti, Michelle M Kim, Ian Law, Emilie Le Rhun, Susan Chang, Julian Schwarting, Stephanie E Combs, Matthias Preusser, Peter Forsyth, Whitney Pope, Michael Weller, Jörg C Tonn, PET imaging in patients with brain metastasis—report of the RANO/PET group, Neuro-Oncology , Volume 21, Issue 5, May 2019, Pages 585–595, https://doi.org/10.1093/neuonc/noz003

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Brain metastases (BM) from extracranial cancer are associated with significant morbidity and mortality. Effective local treatment options are stereotactic radiotherapy, including radiosurgery or fractionated external beam radiotherapy, and surgical resection. The use of systemic treatment for intracranial disease control also is improving. BM diagnosis, treatment planning, and follow-up is most often based on contrast-enhanced magnetic resonance imaging (MRI). However, anatomic imaging modalities including standard MRI have limitations in accurately characterizing posttherapeutic reactive changes and treatment response. Molecular imaging techniques such as positron emission tomography (PET) characterize specific metabolic and cellular features of metastases, potentially providing clinically relevant information supplementing anatomic MRI. Here, the Response Assessment in Neuro-Oncology working group provides recommendations for the use of PET imaging in the clinical management of patients with BM based on evidence from studies validated by histology and/or clinical outcome.

Brain metastases (BM) often occur in advanced malignancies but may also be an initial disease manifestation in, for example, CUP (cancer of unknown primary). BM derive most frequently from lung cancer (40–50% of all BM), breast cancer (15–20%), melanoma (5–20%), renal cancer (5–10%), and cancers of the gastrointestinal tract (5%). 1 The prognosis of patients with BM is usually poor, with a general median survival of several weeks in untreated patients and up to several months following oncological treatment. Some molecularly defined patient subsets, such as those positive for human epidermal growth factor receptor 2 breast cancer or anaplastic lymphoma kinase non–small cell lung cancer, may demonstrate significantly longer survival. Outcomes continue to improve with advances in systemic and regional therapy.

Regional treatment options for BM are neurosurgical resection, radiotherapy (eg, radiosurgery, fractionated external beam radiotherapy), and combinations thereof. 2 Systemic treatment options such as targeted therapy and immunotherapy that can control both intracranial and extracranial disease are improving. 3 Depending on the number of BM and the performance status of the patient, radiotherapy is an effective treatment of BM, either as whole-brain radiation therapy (WBRT) or, increasingly, as stereotactic radiosurgery (SRS). 4 Furthermore, surgery is frequently combined with postoperative radiotherapy, particularly in patients with single BM or oligometastatic brain disease. 5 Despite various treatment options, BM recurrence is common.

Contrast-enhanced magnetic resonance imaging (MRI) is the cornerstone of metastatic brain tumor evaluation. This technique has widespread availability and excellent spatial resolution, but can exhibit low specificity, resulting in substantial diagnostic challenges. 6–8 These challenges include discriminating BM from potential mimics that also demonstrate nodular or ring enhancement. Furthermore, MRI signal abnormalities—including T2 or fluid attenuated inversion recovery (FLAIR) hyperintensity, newly diagnosed contrast-enhancing lesions, or an increase in the extent of contrast enhancement—are nonspecific findings that can be caused by a variety of entities, including infection, inflammation, ischemia, demyelination, and treatment-related effects. In particular, reactive changes after surgery, radiotherapy, and systemic drug treatment can be difficult to distinguish from true disease relapse. This phenomenon of worsening treatment-related changes mimicking progression, termed pseudoprogression, is of clinical importance as potentially effective treatment might be erroneously terminated prematurely. 9 , 10 Pseudoprogression is a concern not only following radiation-based therapies, but also following immunotherapy, where a not well-characterized subset of patients manifests delayed response to therapy or therapy-induced inflammation that can simulate progressive disease. 11 , 12

Successful management of patients with BM relies on accurate and early assessment of treatment response. The ability to predict or quickly detect lack of response to treatment may enable the early discontinuance of a particular therapy, thereby preventing additional toxicity and allowing for the earlier initiation of alternative therapy. Despite promising efforts in defining response criteria for BM, 10 , 13 limitations remain, particularly with newer systemic treatment options such as targeted therapy and immunotherapy. Modalities which provide additional information on tumor physiology, including metabolism and proliferation, are increasingly applied problem-solving tools in patients with BM.

One promising method to investigate tumor physiology is positron emission tomography (PET). PET uses a variety of radioactive tracers that target various metabolic and molecular processes. PET imaging can provide relevant additional information that enables improved disease assessment, especially in clinically equivocal situations. Notwithstanding other PET tracers, the use of PET with radiolabeled amino acids, in particular, has been validated as an important diagnostic tool in brain cancer. 6 , 14–16 The overexpression of L-type amino acid transporters (LATs) in BM makes intracranial metastases a compelling target for amino acid PET imaging. 17

In this review, the Response Assessment in Neuro-Oncology (RANO) working group provides evidence-based recommendations for the use of PET imaging using tracers of amino acid transport and other targets, including glucose metabolism, in the management of patients with BM.

A PubMed search of the published literature was performed with the combination of the search terms “brain metastasis/metastases,” “PET,” “positron,” “FDG,” “amino acid,” “methionine,” “FET,” “FDOPA,” “FLT,” “TSPO,” “PSMA,” “radiotherapy,” “radiation-induced changes/radiation injury,” “radionecrosis,” “pseudoprogression,” “treatment monitoring,” “assessment of treatment response,” and “immunotherapy” prior to and inclusive of August 2018. Additionally, articles identified through searches of the authors’ own files were included in the search. Results of the search were evaluated by the working group with respect to the level of evidence and the grade of validation of the PET studies examined. As described previously, 14 , 15 any study that correlated PET findings with histopathology was considered to represent the highest degree of validation. Next, correlation with MRI and with the patient’s clinical course was considered the second level of validation. Only papers constituting levels 1–3 evidence according to the Oxford Centre for Evidence-based Medicine (the Oxford 2011 Levels of Evidence) were included. In brief, a randomized controlled trial fulfills the criteria for Oxford level 1, a prospective cohort study corresponds to Oxford level 2, and a retrospective study is consistent with Oxford level 3.

In the following paragraphs, available PET tracers which address various pathophysiological pathways or molecular entities in BM are summarized.

Glucose PET

18 F-2-fluoro-2-deoxy-D-glucose (FDG) represents the most widely used tracer in oncologic PET imaging and has evolved over the last several decades into the paramount clinical PET modality for cancer detection. 18 Due to the long half-life of the fluorine-18 isotope (110 minutes), in-house production of this tracer is not necessary, overcoming logistic problems that occur with isotopes of shorter half-life. Thus, FDG can be transported to all PET centers, alleviating the need for on-site cyclotron-based manufacturing. Increased FDG uptake is commonly seen in highly proliferating cancer cells because of increased expression of glucose transporters and hexokinase, the enzyme that converts glucose (and FDG) to a phosphorylated product. Related to increased glycolysis, the uptake of FDG in neoplastic tissue is generally higher than in non-neoplastic tissue. However, the high and regionally variable FDG uptake in normal brain parenchyma often makes the delineation of tumors in the brain difficult 14 ( Fig. 1 ). Furthermore, inflammatory tissue can exhibit high FDG tracer uptake, also diminishing diagnostic specificity. 6

A 56-year-old female patient with a brain metastasis originating from a papillary thyroid carcinoma treated with radiosurgery. Follow-up MR imaging 15 months later (top row, left) is consistent with stable disease according to RANO criteria for brain metastases. Most probably due to the lesion size, the corresponding FDG PET (top row, right) shows no increased metabolic activity. During the next 12 months, the size of contrast enhancement increased marginally (bottom row, left). Notwithstanding the small lesion size on anatomical MRI, the corresponding FDOPA PET (bottom row, right) shows clearly increased metabolic activity indicating brain metastasis relapse.

A 56-year-old female patient with a brain metastasis originating from a papillary thyroid carcinoma treated with radiosurgery. Follow-up MR imaging 15 months later (top row, left) is consistent with stable disease according to RANO criteria for brain metastases. Most probably due to the lesion size, the corresponding FDG PET (top row, right) shows no increased metabolic activity. During the next 12 months, the size of contrast enhancement increased marginally (bottom row, left). Notwithstanding the small lesion size on anatomical MRI, the corresponding FDOPA PET (bottom row, right) shows clearly increased metabolic activity indicating brain metastasis relapse.

Amino Acid PET Tracers

For decades, radiolabeled amino acids have been used in neuro-oncological practice. 19 11 C-methyl-L-methionine (MET), an essential amino acid labeled with the isotope carbon-11, has been the most commonly employed. 18 , 20 The relatively short half-life of carbon-11 (20 minutes) limits its use to PET facilities with an on-site cyclotron. Consequently, other amino acids labeled with the positron-emitting isotope 18 F, which has a half-life of 110 minutes, have been developed, resulting in improved distribution, efficiency, and cost-effectiveness. 21 For example, O -(2-[ 18 F]fluoroethyl)-L-tyrosine (FET) was developed in the late 1990s, and its use has grown rapidly, particularly in western Europe, in recent years. 22–24 Clinical results in glioma patients with PET using FET appear to be comparable to MET. 25–27 In 2014, FET was approved as a medical drug in Europe (Switzerland). 28

Another 18 F-labeled amino acid analogue is 3,4-dihydroxy-6-[ 18 F]-fluoro-L-phenylalanine (FDOPA), which was initially developed to evaluate dopamine synthesis in the basal ganglia and has also increasingly been used for imaging brain tumors. 29 In the United States and western Europe FDOPA is approved for characterization of presynaptic dopaminergic activity in patients with Parkinsonian syndromes.

In both gliomas and BM, increased uptake of MET, FET, and FDOPA is due to large neutral LATs, which are overexpressed in neoplastic tissue (subtypes LAT1 and LAT2). 17 , 30–32 Overexpression of LAT1, and therefore robustness of amino acid tracer uptake, closely correlates with malignant phenotype and proliferation of gliomas. 33 Compared with MET and FDOPA, FET has high metabolic stability. After transport by LAT into neoplastic tissue, FET is not metabolized, 25 whereas both MET and FDOPA show incorporation into protein, participation in other metabolic pathways, or metabolic degradation. 34

Acquisition of dynamic FET PET data allows characterization of the temporal pattern of FET uptake by deriving a time-activity curve (TAC). It has been demonstrated that TAC parameters (eg, configuration, time-to-peak, slope) contain additional diagnostic information, which may be particularly valuable in the differentiation of BM recurrence from radiation-induced changes. 35–37 Similarly, the ability of dynamic FET PET to distinguish recurrent glioma from radiation-induced treatment effect has also been described. 38 , 39 Dynamic FET PET imaging is also helpful for glioma grading 40 , 41 and for determining the prognosis of untreated gliomas. 42 , 43 Such utility has yet to be observed for dynamic MET or FDOPA PET. 44 , 45

Lastly, the amino acid PET tracer α- 11 C-methyl-L-tryptophan (AMT) has recently been employed for brain tumor imaging in some centers. 46 However, despite promising results in terms of differential diagnosis in patients with newly diagnosed brain tumors, including BM, the current literature is relatively small. 47

Other PET Tracers

Only a few studies have used non-FDG and non–amino acid PET tracer imaging in patients with BM. Tracers such as 18 F-sodium fluoride ( 18 F-NaF), 3′-deoxy-3′- 18 F-fluorothymidine ( 18 F-FLT), 82 rubidium, as well as PET tracers targeting the endothelial prostate-specific membrane antigen (PSMA) have been used mostly for BM visualization and the assessment of treatment response. 48–54 Choline derivatives (eg, 18 F-choline), which are in use for the diagnosis of recurrent prostate cancer, have also been reported to label BM. 55 , 56 Animal studies have found that PET imaging using agents targeting the mitochondrial translocator protein (TSPO), which is upregulated on activated microglia, may be helpful for BM detection at an early stage of development. 57 Despite promising results, experience with these tracers is based mainly on single cases in patients with BM, and their usefulness needs to be confirmed in larger studies.

Identification of Newly Diagnosed and Untreated Brain Metastasis Using FDG and Amino Acid PET

Although conventional MRI is the method of choice for the detection of BM, some centers include the head for whole-body FDG PET/CT staging examinations of cancer patients. However, the value of this procedure is highly questionable based on the limited sensitivity of FDG PET for brain tumors related to the physiologically high levels of glucose metabolism in healthy brain parenchyma. 58 , 59 Indeed, a prospective study has shown that, in comparison to contrast-enhanced standard MRI for intracranial staging in newly diagnosed lung cancer, FDG PET has poor sensitivity (27%) for BM detection. 60 Similarly, a recent meta-analysis including more than 900 patients found that contrast-enhanced MRI has a higher cumulative sensitivity (77%) than FDG PET (21%) for the diagnosis of BM in lung cancer patients. 61

The increased expression of amino acid transporters in BM compared with healthy brain tissue renders radiolabeled amino acids suitable for PET imaging based on high tumor-to-background contrast. 17 Compared with FDG PET, the sensitivity of amino acid PET using FET to depict larger (>1 cm in diameter) BM seems to be clearly higher (approximately 90% of BM were FET positive based on a maximum tumor/brain ratio ≥1.6). 62 However, detection of lesions with <1 cm diameter may be considerably inferior to that of MRI. For example, in a pilot study of patients with newly diagnosed and untreated BM which correlated FET uptake characteristics with MRI parameters, the sensitivity of standard MRI for the detection of BM was 100%. 62 Currently, the most sensitive and commonly used imaging modality for the detection of BM remains thin-slice contrast-enhanced MRI.

Amino acid PET using the tracer FET has higher diagnostic accuracy for the detection of BM than FDG PET (evidence level 2).

FDG or amino acid PET is limited in detecting smaller metastases, particularly those less than 1 cm in diameter.

The imaging modality of choice for the detection of BM is contrast-enhanced MRI.

Differential Diagnosis of Newly Diagnosed and Untreated Brain Metastasis Using FDG and Amino Acid PET

FDG PET is limited in its ability to differentiate BM from mimics such as glioblastoma: it has been shown that there is no significant difference in FDG standardized uptake values (SUVs) between these entities. 63 , 64 Differentiation between CNS lymphoma and BM based on FDG PET is more promising, as lymphoma may be substantially more FDG avid than BM. 63 , 64 Initial data suggest that SUVs of the radiolabeled amino acid AMT are lower in BM than in glioblastomas. 47 Further studies are required to firmly establish the added value of PET ligands to differentiate various lesions that have similar MRI characteristics.

High levels of LAT expression in cancer cells have been reported to correlate with aggressive tumor features and a worse prognosis. 65 , 66 LAT expression also appears to be higher in recurrent compared with newly diagnosed BM. 17 However, there are no studies yet investigating the prognostic value of amino acid PET in patients with BM. Possible limitations include the observation that uptake intensity as well as LAT expression levels are highly variable, even in metastases of the same primary tumor type. 65 , 66 Thus, the site of origin of BM cannot be based on amino acid PET findings. 62

In contrast to glioma, the size and volume of a BM are usually well delineated on contrast-enhanced MRI. Thus, amino acid PET does not add valuable information for biopsy or treatment planning as has been found for newly diagnosed gliomas. 67 , 68

There is limited evidence to support the use of PET to distinguish between BM and high-grade glioma (evidence level 3).

Evidence is lacking for the use of amino acid PET to determine prognosis in patients with BM.

Differentiation of Radiation-Induced Changes from Brain Metastasis Recurrence Using FDG and Amino Acid PET

Oncologists of all subspecialties are often confronted with the clinical problem of differentiating tumor recurrence from treatment-related changes following radiation therapy, and in particular after high-dose focal radiation (ie, radiosurgery or fractionated stereotactic radiation therapy). Currently, conventional MRI does not reliably differentiate local brain tumor recurrence or progression from radiation-induced changes including radiation necrosis. In gliomas, radiation necrosis usually manifests within 6–12 months after standard fractionated radiotherapy and occurs in approximately 5–25% of all treated patients. 69 , 70 For patients with BM treated by radiosurgery, a similar rate of radiation necrosis (approximately 25%) has been reported, 71 although the incidence depends on the radiation dose and irradiated brain volume. Indeed, in some cases the risk of radiation necrosis may be as high as 50%. 71 It should be noted that this wide variation in reported incidence is also likely a consequence of varying definitions of treatment-related changes in retrospective studies, including clinical data such as whether the patient is symptomatic or not. Treatment-related changes represent a spectrum of pathophysiology that may be purely radiographic and lack associated symptoms, but also may be symptomatic, refractory to corticosteroids, and require neurosurgical or other intervention.

In recent years, FDG PET has been studied as an additional neuroimaging tool to differentiate treatment-related effects from true BM progression ( Table 1 ). Unfortunately, these investigations included few patients and were limited by variations in methodology such as thresholds used for the differentiation of radiation-induced changes from BM recurrence. Perhaps as a result, the diagnostic performance of FDG PET varied considerably (range of sensitivity, 40–95%; range of specificity, 50–100%) ( Table 1 ). Dual phase FDG PET may be superior to standard (single phase) scans 72 but limited by long time intervals between scans (median time between FDG PET scans, 3.8 hours; range, 2–5.7 hours), 72 hampering routine clinical use. The diagnostic performance of FDG PET also seems to be inferior to several other imaging methods, such as MET PET, 73 MRI-based perfusion imaging with arterial spin labeling, 74 MR spectroscopy, 75 and diffusion-weighted imaging 73 , 76 ( Table 1 ).

Overview of studies regarding the differentiation of radiation-induced changes from brain metastasis recurrence using FDG PET

ASL = arterial spin labeling; DCE PWI = dynamic contrast-enhanced perfusion-weighted imaging; DWI = diffusion-weighted imaging; FDG = 18 F-2-fluoro-2-deoxy-D-glucose; L/GM = lesion to gray matter ratio; MET = 11 C-methyl-L-methionine; na = not available; MRS = single- and multi-voxel proton MR spectroscopy; p.i. = post-injection; TBR mean/max = mean or maximum standardized uptake value of the lesion divided by the maximum standardized uptake value of the reference region; SUV max = maximum standardized uptake value

Amino Acid PET

Amino acid PET has also been investigated as an imaging modality to distinguish treatment effect from tumor in clinical practice ( Table 2 ). It has been demonstrated that MET PET may differentiate recurrent BM from radiation-induced changes using an easily applicable semi-quantitative regions-of-interest analysis for the calculation of tumor/brain ratios. MET PET has demonstrated a sensitivity and specificity of 70–80% in differentiating treatment effect from recurrent tumor. 79– , 81 It has also been shown that FDOPA PET is able to differentiate recurrent BM from radiation-induced changes with high sensitivity and specificity (81% and 84%, respectively) 82 ( Fig. 1 ). Another study has reported an accuracy of 91% for differentiating radiation-induced changes from BM progression after radiosurgery for FDOPA PET, outperforming perfusion MRI parameters 91% to 76%. 83 A similar high diagnostic performance has also been demonstrated for FET PET; using tumor/brain ratios and dynamic parameters, FET PET differentiated radiation-induced changes from locally recurrent BM with a sensitivity of 95% and specificity of 91% 35 ( Fig. 2 ). Dynamic FET PET studies in a larger number of patients demonstrated a sensitivity and specificity of 80–90%. 36 , 37 Furthermore, the diagnostic performance of amino acid PET seems to be superior to both FDG PET and MRI-based perfusion- and diffusion-weighted imaging 73 , 83 ( Table 2 ). Across all available amino acid PET studies for this indication, histological confirmation of diagnosis (ie, BM recurrence or radiation injury) ranges 11–56% ( Table 2 ). The cost-effectiveness of amino acid PET has been demonstrated in Europe for the differentiation of recurrent BM and radiation-induced changes 84 and various other indications. 85–87

Overview of studies regarding the differentiation of radiation-induced changes from brain metastasis recurrence using amino acid PET

DSC PWI = dynamic susceptibility contrast-enhanced perfusion-weighted imaging; DWI = diffusion-weighted imaging; FDG = 18 F-2-fluoro-2-deoxy-D-glucose; FDOPA = 3,4-dihydroxy-6-[ 18 F]-fluoro-L-phenylalanine; FET = O -(2-[ 18 F]fluoroethyl)-L-tyrosine; sL/GM = lesion to gray matter ratio; MET = 11 C-methyl-L-methionine; na = not available; p.i. = post-injection; TBR mean/max = mean or maximum standardized uptake value of the lesion divided by the maximum standardized uptake value of the reference region

A 50-year-old female patient with a brain metastasis secondary to non–small cell lung cancer underwent hybrid PET/MR imaging. Six months after stereotactic radiosurgery, MRI suggests tumor recurrence. In contrast, FET PET shows no increased metabolic activity (TBRmean = 1.3), and the TAC shows a steadily increasing FET uptake, indicating radiation injury. The diagnosis was confirmed by subsequent hybrid PET/MR imaging 3 months later demonstrating improvement of imaging findings without a therapeutic intervention.

A 50-year-old female patient with a brain metastasis secondary to non–small cell lung cancer underwent hybrid PET/MR imaging. Six months after stereotactic radiosurgery, MRI suggests tumor recurrence. In contrast, FET PET shows no increased metabolic activity (TBR mean = 1.3), and the TAC shows a steadily increasing FET uptake, indicating radiation injury. The diagnosis was confirmed by subsequent hybrid PET/MR imaging 3 months later demonstrating improvement of imaging findings without a therapeutic intervention.

Recent literature highlights the value of PET radiomics in assessing tumor phenotypes. 89 Radiomics enables the high-throughput extraction of a large number of quantitative features from imaging of a standard modality (usually MRI and PET). 90 , 91 One application of radiomics is the use of textural feature analysis which objectively and quantitatively describes intrinsic properties of tumors, particularly heterogeneity. Using FET PET, it has been demonstrated that radiomic textural feature analysis provides non-invasive quantitative information useful for distinguishing treatment-related changes from disease progression. 92 Combined FET PET and MRI radiomics using textural features achieved a diagnostic specificity of more than 90%. 93

Amino acid PET is useful in distinguishing posttherapeutic reactive changes following radiotherapy from recurrent BM. Present studies consistently show high diagnostic accuracy (evidence level 2).

FDG PET can also be used for this indication, but studies to date report highly variable diagnostic accuracy (evidence level 2).

At present, direct comparisons of advanced MRI versus PET are limited. Amino acid PET may be more useful than advanced MRI, whereas FDG PET appears to be inferior (evidence level 3).

When using PET for this indication, amino acid tracers should be preferred. Dynamic FET PET may further improve diagnostic accuracy.

Differentiation of Treatment-Related Changes of Immunotherapy from Brain Metastasis Recurrence using FDG and Amino Acid PET

Immuno-oncology is a rapidly developing therapeutic field with potential applications in CNS malignancies, particularly in patients with BM. 94 Early phase studies have illustrated diagnostic challenges associated with the assessment of radiological changes in response to immunotherapy, wherein a subset of patients manifests delayed response to therapy or therapy-induced inflammation that mimics progressive disease. Following immunotherapy, long-term survival and tumor regression may occur after what was believed to represent initial disease progression or even after the appearance of new lesions. 11 Pseudoprogression may occur in patients with BM treated with immunotherapy using checkpoint inhibitors such as cytotoxic T lymphocyte-associated antigen 4 (eg, ipilimumab) and programmed cell death 1 receptor inhibitors (eg, pembrolizumab, nivolumab). 11 , 12 , 95 , 96 A pilot study showed the potential of FET PET to identify pseudoprogression in patients with BM originating from melanoma treated with immune checkpoint inhibitors. 97 Data on FDG PET for this indication are currently not available.

At present, there is limited evidence of the potential benefit of amino acid PET for differentiating pseudoprogression from true disease progression following checkpoint inhibitor blockade (evidence level 3).

Assessment of Treatment Response

As stated above, standard MRI is limited in its ability to differentiate BM relapse from treatment-related effects such as radionecrosis or pseudoprogression, all of which can induce contrast enhancement and T2/FLAIR hyperintensity. The use of FDG as a tracer for the assessment of treatment response in PET imaging is hampered by high physiologic brain uptake, limiting the discrimination between tumor and normal brain metabolic activity. 14 Furthermore, in light of newer systemic treatment options such as targeted therapy and immunotherapy, tools which provide additional information on cellular physiology (eg, metabolism, proliferation) have become increasingly useful.

The PET tracer FLT is an analog to the nucleoside thymidine and was developed as a PET agent to assess cellular proliferation by tracking the thymidine salvage pathway. 98 Recently, FLT has been applied to assess response to the chemotherapeutic agent ANG1005 (a drug conjugate consisting of paclitaxel covalently linked to angiopep-2, designed to cross the blood–brain barrier) in patients with BM originating from breast cancer and was found to supplement the information derived from contrast-enhanced MRI by clarifying equivocal MRI findings. 50

In BM from malignant melanoma being treated with targeted therapy and immunotherapy, a small study found in a subset of patients that metabolic responders may show a proliferative reduction on FLT PET despite apparent morphologic progression on standard MRI (ie, pseudoprogression). 54

Studies evaluating amino acid PET for the assessment of treatment response are lacking. Theoretically, amino acid PET has the potential to add valuable information to standard MRI for the assessment of treatment response; validation in clinical studies is required. An illustrative example for this potential indication is presented in Fig. 3 .

A 45-year-old female patient with a brain metastasis secondary to a BRAF-mutated malignant melanoma treated with dabrafenib and trametinib. Comparison of contrast-enhanced MR and FET PET images at baseline (left column) and follow-up 8 weeks later (right column). At follow-up, a clear decrease of the tumor/brain ratios (−35%) is observed, whereas the MRI shows no significant change of both the contrast enhancement and FLAIR signal defined as stable disease according to RANO criteria for brain metastases. The metabolic response was associated with an overall survival of 9 months after treatment initiation.

A 45-year-old female patient with a brain metastasis secondary to a BRAF-mutated malignant melanoma treated with dabrafenib and trametinib. Comparison of contrast-enhanced MR and FET PET images at baseline (left column) and follow-up 8 weeks later (right column). At follow-up, a clear decrease of the tumor/brain ratios (−35%) is observed, whereas the MRI shows no significant change of both the contrast enhancement and FLAIR signal defined as stable disease according to RANO criteria for brain metastases. The metabolic response was associated with an overall survival of 9 months after treatment initiation.

Currently only preliminary evidence exists for a potential benefit of PET for the assessment of treatment response following systemic therapies (evidence level 3).

At present, the differentiation of radiation injury from BM recurrence using amino acid PET has been the most thoroughly investigated indication ( Table 3 ), repeatedly demonstrating high diagnostic accuracy. However, it should be noted that these data were derived mainly from retrospective analyses performed in single centers, and diagnoses were not consistently confirmed histologically. Prospective multicenter studies are therefore needed to validate initial results of these proof-of-principle investigations. Challenges of prospective validation are several, including heterogeneity of patient population (ie, various originating cancers, number of BMs, and varying treatment regimens). Amino acid PET tracer availability and cost present additional obstacles.

Summary of recommendations

++ high diagnostic accuracy; (++) high diagnostic accuracy, but limited data available; + limited diagnostic accuracy; − not helpful; na = only preliminary or no data available; *increased accuracy when using dynamic FET PET

Contrary to gliomas and transosseous meningiomas, the majority of BM can be easily delineated by conventional MRI. Thus, PET imaging does not add significant additional information. Detecting multiple, small BM remains a major clinical challenge, potentially impacting not only prognosis, but also treatment (ie, a shift from local treatment such as surgery or SRS to WBRT or systemic treatment options). Due to the limited spatial resolution of PET, miliary disseminated metastatic disease or leptomeningeal metastasis is challenging to assess and may be unapparent by current PET imaging. The still frequent use of FDG PET in the brain is of limited value due to poor lesion-to-background contrast, partially explaining disappointing results in screened cohorts. 99 New PET tracers, such as TSPO ligands, might help to overcome this problem 100 and may eventually assist in radiation treatment planning.

PET imaging in meningiomas using specific somatostatin receptor ligands such as 68 Ga-DOTATATE PET has shown that tracer uptake may correlate with tumor grade as well as the likelihood of response to specific radionucleotide therapy. 101 , 102 Intra-individual variation in patients with multiple lesions has been noted. 103 By analogy, further investigations should aim to non-invasively image intra-individual heterogeneity in patients with multiple BM. Optimal patient management may benefit by improved and well-validated prognostic and predictive imaging markers derived from PET, as by the identification and quantification of target molecules for specific therapy (eg, epidermal growth factor receptor). 104–106 Moreover, this could lead to early response markers of successful treatment that can be determined prior to changes in tumor size. Lastly, more specific PET tracers could potentially better identify BM primary cancer of origin.

By altering radioisotopes, PET ligands initially used for diagnostic imaging might also be instrumental for therapy. This concept of “theranostics” has already been introduced into the management of prostate cancer. 107–109 Moreover, PET might help in the future to identify drug delivery into tumor tissue and provide imaging-based data on inter- and intra-individual variability of tumor drug concentration, thereby permitting more relevant information for patient selection and therapy tailoring. 110 , 111

Another methodological innovation which could advance research in patients with BM is the increasing availability of hybrid PET/MR scanners, allowing the simultaneous acquisition of both imaging modalities. For example, the acquisition of dynamic FET PET, contrast-enhanced structural and perfusion-weighted MRI, and other advanced MRI sequences such as MR spectroscopy and functional MRI in a single session (“one-stop shop”) can now be performed. Besides optimizing co-registration of various imaging modalities, this technology appears particularly attractive for BM patients with poor clinical condition by considerably reducing scanning time and avoiding exposure to additional radiation dose associated with a PET/CT scan. From a research perspective, hybrid PET/MR technology provides a convenient platform for comparative imaging studies using amino acid PET and advanced MR imaging, ideally corroborated with neuropathology.

All authors report no conflicts of interest related to the present work.

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Research trends and prospects on brain metastasis from breast cancer: A bibliometric analysis

1 School of Traditional Chinese Medicine, Southern Medical University, Guangzhou, Guangdong, China

Yan-ting You

Xing-hong zhou, li-qian chen, hiu yee kwan.

2 School of Chinese Medicine, Hong Kong Baptist University, Hong Kong, Hong Kong SAR, China

Xiao-shan Zhao

3 Department of Oncology, Affiliated Dongguan People’s Hospital, Southern Medical University, Dongguan, Guangdong, China

Yan-yan Liu

Associated data.

The original contributions presented in the study are included in the article/supplementary material. Further inquiries can be directed to the corresponding authors.

Introduction

Brain metastasis is the terminal event of breast cancer with poor prognoses. Therefore, this article aimed to provide an updated summary on the development, hotspots, and research trends of brain metastasis from breast cancer based on bibliometric analysis.

Publications on breast cancer with brain metastasis retrieved from the Web of Science Core Collection. CiteSpace, VOSviewer, and other online bibliometric analysis platforms were used to analyze and visualize the result.

In totality, 693 researchers from 3,623 institutions across 74 counties and regions published a total of 2,790 papers in 607 journals. There was a noticeable increase in publications in 2006. The United States was the dominant country with the most publications followed by China. University Texas MD Anderson Cancer Center was the most productive institution, while Dana Farber Cancer Institution was the most cited. Journal of Neuro-Oncology published the most papers, while Journal of Clinical Oncology ranked first based on cocited analysis. Nancy U. Lin was the most productive and cited author with high influence. There was a focus on basic research, clinical trials, local therapy, treatment optimization, and epidemiological studies regarding brain metastases from breast cancer. References focused on pathogenesis, prevention, treatment, and prognosis were cited most frequently, among which the clinical trial of novel treatment attracted most attention from researchers. Reference citation burst detection suggested that new therapies such as the novel tyrosine kinase inhibitor and antibody–drug conjugate may lead the research trends in the future.

High-income countries contributed more to the field of breast cancer with brain metastasis, while developing countries like China developed quickly. Furthermore, the success of novel therapies in recent years may lead to the new era of treatment of breast cancer with brain metastasis in the future.

1. Background

Breast cancer has been the most common malignancy in women. There has been a slight increase in breast cancer incidence rates since 2004 ( 1 ), with new cases in women reaching 281,550 in 2021, accounting for 30% of all female cancers ( 2 ). Although with a relatively high survival rate that reaches 90%, the mortality of breast cancer still ranked second in female cancer, approximately 90% of which are associated with complications from recurrent or metastatic diseases ( 3 ). Unfortunately, even patients with early-stage breast cancer will develop distant metastasis, which accounts for one-third of all cancer cases ( 4 ).

The development of breast cancer brain metastasis is regarded as a late event with a worse prognosis compared to metastasis to other organs. Different subtypes of breast cancer vary in the rate of brain metastasis. Triple-negative breast cancer [Triple-negative: hormone receptor (HR)–negative/human epidermal growth factor receptor 2 (HER2)–negative] and HER2+ breast cancer (HR-negative/HER2-positive) have a higher likelihood of developing brain metastasis, with rates of 25%–27% and 11%–20%, respectively. Both luminal A and luminal B subtypes have a lower risk of brain metastasis (l8%–15% and 11%, respectively) ( 5 – 7 ).

Despite the attention of researchers on brain metastasis from breast cancer, there has not yet been a bibliometric analysis reviewing the research output on publications concerning the topic. Herein, we utilized some bibliometric analysis tools to explore the frontiers and hotspots of studies on brain metastasis from breast cancer. Bibliometric analysis employs citation count as an assessment to measure of research quality ( 8 ). As a quantitative method, bibliometric analysis helps to trace the research profiles of different countries, institutions, and researchers that promoted the scientific production, behavior, and development in the related fields ( 9 , 10 ). Bibliometric reviews on breast cancer have covered several topics, focusing on a variety of different treatments including nanomedicine ( 9 ), immunotherapy ( 11 ), the application of pan-cancer studies in treatment ( 12 ), and radiotherapy ( 13 ).

In this study, we used CiteSpace and VOSviewer to analyze papers related to breast cancer brain metastasis and summarized the research findings. We examined the evolution and development of research hotspots in the breast cancer brain metastasis from 2006 to 2022, identifying new hotspots and topics. The aim of this study is to contribute new insights and ideas to research of breast cancer brain metastasis in the future.

2. Material and methods

2.1. data collection.

Articles related to brain metastasis from breast cancer were retrieved from the Science Citation Index Expanded (SCIE) of Web of Science Core Collection, which were all published during 1 January 1992 to 7 October 2022. Search strategy was based on the advanced search option with the following strategy: TS = (“breast cancer” OR “breast carcinoma”) AND TS = (“brain metastas*” OR “cerebral metastas*” OR “intracranial metastas*” OR “central nervous system metastas*” OR “secondary brain tumor”). The full records and cited references of the data were extracted and downloaded in a plain text file and a tab-delimited text file, consisting of publication year, authorship, title, abstract, author keywords, citation count, reference, journal title, institution, and country. Only literature written in English was contained in processes of search and downloading, which were completed within 1 day on 8 October 2022 to avoid errors caused by frequent database updates. A total of 3,096 publications were contained in the first set of data (year: 1992–2022). It may be because the data network was so complex that some functions of CiteSpace [version 6.1.R3 (64-bit)] ran very slowly. Therefore, we limited the time from 1 January 2006 to 7 October 2022 with the same strategy of search and selection mentioned earlier. A total of 2,790 publications were contained in the second set of data (year: 2006–2022). Only the annual number of publications was conducted based on the first set of data. Other analyses including country, institution, author, reference, and keyword were based on the second set of data. Occupying 89% of all the 3,096 publications in recent two decades, the analysis of the second set of data cover provided a snapshot of recent research in brain metastasis from breast cancer. Figure 1 showed the process of publication selection. Furthermore, since this study did not include any animals or experiments, ethical consent was not required.

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Flowchart of the process of publication selection.

2.2. Data analysis and visualization

Two online platforms and three software were used to analyze and visualize publications related to breast cancer brain metastasis. Datawrapper ( https://www.datawrapper.de/ ) was used to draw the map of the regional distribution of publications and BIBLIOMETRIC ( https://bibliometric.com/ ) was used to analyze the annual publications of the most productive countries as well as the collaboration between different countries. Microsoft Excel 2019 was used to analyze the annual distribution of publications on brain metastasis from breast cancer.

CiteSpace is a visualization and analyzation software designed by Prof. Chaomei Chen. It is used to discover the collaborative network and critical and pivotal points in the scientific literature of a specific topic. The analysis is based on the theory of co-occurrence and cocitation. When two publications are cited together by another publication, there is a cocitation relationship between the two publications. Burst detection is another practical function of CiteSpace to discover emerging words or references by analyzing the change of frequency of their citation or occurrence in a short time. We used CiteSpace to draw a matrix network of authors and cocited authors We also detected references with strong citation burst to find the influential references in the related field. Moreover, we detected keywords with strong occurrence burst and drew a timeline of keyword clusters, which concluded the hotspot development in different year and provided insight on the future trends in the related region. The strength of nodes was calculated of cosine, and pathfinder was used to detect the most representative network.

VOSviewer is another useful software to visualize the network map of scientific papers. We used bibliographic coupling analysis and cocitation analysis to visualize institutions and journals. We also used cooccurrence analysis to draw a cluster network of keywords. To avoid the repeat caused by expression difference, we appended the thesaurus so that the software could recognize terms like “metastasis” and “metastases” as the same term. Additionally, this study did not include any animal or experiments; thus, ethical issues were not required.

3.1. Publication output of research on breast cancer brain metastasis

Web of Science Core Collection yielded a total of 3,096 publications related to breast cancer brain metastasis in the recent three decades. As demonstrated in Figure 2 , from 1992 to 2005, the annual output rose slightly with fluctuation. In 2006, the annual number of publications was increased sharply to 57, which almost doubled that of last year. Since then, the number of publications increased substantially in general year by year and peaked in 2020 with a total of 286 publications. For this reason, we used the data from 2006 to 2022 in the follow-up analysis.

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The annual number of publications of breast cancer brain metastasis from 1 January 1992 to 7 October 2022.

3.2. Profile of countries and institutions

A total of 74 countries or regions contributed to the studies on breast cancer brain metastasis. As shown in Figure 3 , the United States was ranked the first and China second and Germany third based on the number of publications. It is worth mentioning that China showed an emerging boost, especially in the recent decade, but the average citation stayed limited ( Table 1 ). Regarding research collaboration, the United States had the broadest range of academic collaborations with countries all around the world ( Figure 4 ).

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Analysis of country based on the number of publications. (A) The number of publications per country. Countries with less publications were colored red, while countries with most publications were colored blue. Countries without publications in the related region were colored gray. (B) The annual publication number and trend of the 10 most productive countries. Different countries were represented by different colors, and the height of each color blot reflected the number of publications of a specific country in a specific year.

Table 1

Five most productive countries.

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The connection among different countries in brain metastasis from breast cancer. Each country was represented by a fragment on the outer part of the circle. The area of the fragment is proportional to the number of publications of the correspondent country and the size of the arc to the strength of cooperation between two countries.

A total of 3,623 institutions participated in the studies of breast cancer brain metastasis, and 404 of them, with at least five publications, are shown in Figure 5 . All of the 404 institutions were divided into seven clusters based on the co-occurrence analysis. Clusters in deep blue, green, and orange, represented by the University Texas MD Anderson Cancer Center, Dana Farber Cancer Institution and University of California, San Francisco, respectively, were the institutions mainly from America. Institutions in the red cluster were mainly from Europe and America. The yellow cluster mainly consisted of institutions from China, and the purple one consisted of institutions from other East Asia countries. The light-blue cluster mainly consisted of institutions from France. When comparing Figures 5A, B , institutions in blue, green, and orange clusters were the most productive ones. Furthermore, as listed in Table 2 , nine of the most productive institutions were located in America. The University Texas MD Anderson Cancer Center was the most productive institution with a total of 131 publications, while the Dana Farber Cancer Institution was the most influential institution with the highest citation per publication and has the strongest link strength with other institutions.

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The co-occurrence cluster and production density of institutions. (A) cluster network analysis of institutions with at least five publications. The size of the node is proportional to the number of publications of a specific institution. The bigger the node, the more productive the institution. When two institutions occurred in the same publication for three times, there is a link between them. The width of the link represents the strength of co-occurrence between two institutions. Nodes and links in the same color belong to the same cluster, meaning the connections between these institutions are more closer according to the VOSviewer analysis. (B) The density map of institutions based on the number of publications. The labels of institutions in red area are the most productive institutions, while labels in the blue area are the less productive ones. From: VOSviewer.

Table 2

10 most productive and cited institutions.

3.3. Profile of journals, cocited journals

VOSviewer was used to conduct the bibliographic coupling analysis and cocitation analysis of journals. A total of 2,790 papers were published in 607 journals, and 6,628 journals were cited in the references. Table 3 demonstrated the leading journals in the related research based on publication and citation. Journal of Neuro-Oncology published the most papers (n = 111), Breast Cancer Research and Treatment second (n = 82), and Cancers third (n = 68). Cocitation analysis is an effective method to discover the most influential journals in a specific topic. In the region of brain metastasis from breast cancer, Journal of Clinical Oncology ranked first with 9,861 citations, followed by Clinical Cancer Research with 4,491 citations and Cancer Research with 4257 citations. Clinical Cancer Research was the only journal both in top 10 based on production and citation, with the highest impact factor (IF = 13.801) in the list of most productive journals, indicating its special position in the related region.

Table 3

10 most productive and most cited journals.

3.4. Profile of authors and cocited authors

CiteSpace was also used to visualize the network of authors based on co-occurrence analysis and cocited analysis. In total, 693 authors contributed to the development of research on breast cancer brain metastasis and 994 authors collaborated in the research. The top 20 authors or cocited authors in every year were selected and visualized in the network. The sizes of the nodes are proportional to the number of publications of the author shown in Figure 6A and the citation in Figure 6B . Links are thicker between two closely collaborated authors. As shown in Figure 6 , Lin NU, Kim S, Lee J, Berghoff A, and Preusser M were the top five authors based on the number of publications. As shown in Table 4 , Lin NU was active in this field all over the years with 65 publications in total. In addition, Lin NU was the most cited author based on cocited analysis with 1,000 citations. Sperduto PW ranked second with 468 citations, Pestalozzi BC ranked third with 326 citations, Patchell RA ranked fourth with 315 citations, and Bachelot T ranked fifth with 288 citations. Centrality is used to assess the relationship of one node with other nodes. When the centrality is over 0.1, the node is considered as a landmark node connected closely with other nodes in a network. The centrality of 10 most productive authors all subceeded 0.1. The centrality of 7 authors among the 10 with most citations exceeded 0.1, of which LIN NU (1.24) was the highest. These authors were the leading researchers in the field of brain metastasis from breast cancer and served as a linking bridge with other researchers.

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Network of authors and cocited authors on breast cancer brain metastasis. Each tree-ring node represents an author. (A) Author network based on cooccurrence analysis. The size of node is proportional to the research output of the author. The color of the tree-ring node represents the publication history of the author. Red tree-ring nodes represent the author who published papers in the recent 2 years, while gray ones represent authors who were productive for a decade. Colorful nodes represent authors with continuous research output. (B) Cocited author network based on cocited analysis. The larger the node, the more times the author is cited. Nodes in warmer colors represent authors cited more recently, while nodes in cooler colors represent the opposite.

Table 4

Top 10 of the most productive authors and cocited authors.

3.5. Keywords of breast cancer brain metastasis

VOSviewer and CiteSpace were used to analyze keywords from different perspectives to provide an overlook of development and trend in the related region. After merging keywords repeated by expression difference, VOSviewer concluded 4,189 keywords and 598 of them occurred more than five times, which were divided into five clusters ( Figure 7 ). The red cluster was the largest one with 210 keywords, containing expression, in-vivo, angiogenesis, microenvironment , and endothelial growth-factor . The green cluster ranked second in size with 201 keywords including phase II trial, chemotherapy, efficacy, open-label , and lapatinib plus capecitabine . The blue cluster ranked third in size with 97 keywords including radiation-therapy, stereotactic radiosurgery, prognostic-factors, quality of life, graded prognostic assessment , and management . The yellow cluster contained 96 keywords including solid tumors, blood-brain barrier, cerebrospinal-fluid, her2-positive breast cancer, drug-delivery , and acquired-resistance . Purple cluster contained 89 keywords including survival, risk, subtype, diagnosis , and recurrence . Accordingly, keywords were roughly clustered into five categories as follows: basic study, clinical trial of new therapy, local therapy, treatment optimization, and epidemiology.

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Co-occurrence analysis of keywords during 2006–2022. Lines between two keywords mean the two words coexisted for more than 10 times. The bigger the node, the more frequent it appears. The stronger the line, the more co-occurrences happen. At least 50 keywords are contained in one cluster. Additionally, keywords connected more closely are divided into the same cluster with the same color. From: VOSviewer.

We also used CiteSpace to perform cluster analysis based on the log likelihood ratio (LLR) and drew a timeline of the development of the hotspots in the related region ( Figure 8 ). The top 10% of keywords in a year were analyzed, which yielded a network of 253 nodes with 305 links. A cluster with the modularity of 0.8114 and the weighted mean silhouette of 0.9291 was yielded, which meant that the result was highly convincing with a significant cluster structure. There were 15 clusters including first-line treatment, epidermal growth factor receptor (EGFR) expression, pyrotinib-based therapy, the prognostic index, and other clusters, demonstrating the development of research focus on breast cancer brain metastasis.

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Cluster timeline of keywords of breast cancer brain metastasis. Each tree-ring node represents a keyword. The size of the node is proportional to the time of the occurrence of the keyword. The color of the tree-ring node represents the occurrence history of the keyword. The label of clusters was produced by LLR analysis, and the colors represent different years.

3.6. Cocited references

CiteSpace was used to visualize the network of references of records between 2006 and 2022. The top 5% of the most cited references each year were contained in the cocited analysis, and the network was refined by the pathfinder pruning method. As shown in Figure 9 , 930 references were detected and 10 of the most cocited publications are listed in Table 5 . Seven out of the top 10 co-cited publications were clinical trials, namely, five randomized controlled trials, one population-based cohort, and one retrospective cohort. The other most cocited publications included one genome wide association study (GWAS) study, one basic study, and one review. The most cited publication was “Lapatinib plus capecitabine in patients with previously untreated brain metastases from HER2-positive metastatic breast cancer (LANDSCAPE): a single-group phase 2 study ( 14 )” by Bachelot T et al., which was cited 160 times. It is worth mentioning that the sources of these publications strongly overlapped with the list of the most cited journals, which confirmed the importance of these references and journals in the studies of breast cancer brain metastasis.

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Top 30 references with the strongest citation bursts. The blue line reflects the duration of the citation of the paper. The red segment reflects the duration of the burst.

Table 5

Top 10 cocited references.

Burst detection is an effective method to find out the hotspots in different times and conclude the developmental route of a specific field supported by CiteSpace. The publication of the phase II trial of tucatinib, trastuzumab, and capecitabine for HER2-positive metastatic breast cancer ( 15 ) gained the most attention from researchers in the related field (burst strength: 55.25). The publications of another two clinical trials focused on the effects of neratinib plus capecitabine ( 17 ) and lapatinib ( 16 ) separately was ranked the second (burst strength: 47.49) and third (burst strength: 45.8), respectively. The recent publication that most appealed researchers’ attention was “Trastuzumab Deruxtecan in Previously Treated HER2-Positive Breast Cancer ( 23 )”, whose citation can be dated from 2020 with an increasing trend.

4. Discussion

4.1. general trends.

With reference from the number of publications, the publication trend of the breast cancer brain metastasis research field can be divided into two stages. From 1992 to 2005, the publications increased slowly with fluctuation. It may be due to the following two reasons. The first one is that radiotherapy was the mainstream of treatment for brain metastasis and the controversial effect of chemotherapy ( 24 ) limited the development of clinical trials. The second one is that patients with brain metastasis were always excluded from clinical trials in this period and medical oncologists were reluctant to leave the advanced patients with brain metastasis without other therapy but just the target therapy of clinical trial, which make it difficult to have enough number of patients and assess the efficacy of chemotherapy ( 25 ). In 2005, several randomized trials have confirmed the efficacy of chemotherapy in treating brain metastasis ( 24 , 26 – 28 ) and more clinical trials were ongoing, especially those focused on trastuzumab ( 28 ), which may lead to the publication boosted in 2006. From 2006 onward, the number of publications in breast cancer brain metastasis increased gradually.

In this study, we summarized the research collaboration in different dimensions as well as research focus and hotspots to understand the development and trend of breast cancer brain metastasis. A total of 693 researchers from 3,623 institutions in 74 counties and regions attributed 2,790 publications in 607 journals, indicating that breast cancer brain metastasis attracted wide attention from researchers all over the world. The United States was the leading country in the related field based on the analysis of institutions and authors’ publications and citations. Moreover, the institutions in the United States exhibited a high degree of collaboration with research institutions from all around the world, especially those from Europe. On the other hand, China had emerged as the most promising country in the last decade. Although the academic influence and research collaboration are still limited, researchers and institutions in China demonstrate diligent effort to promote the development of studies on breast cancer brain metastasis. Furthermore, regionally limited collaborations were observed based on institution analysis. Spatial isolation caused by the COVID-19 pandemic has increased the development of online meetings, which serve as a means to break the spatial boundaries between countries and accelerate the research development significantly.

Journal and cocited journal analysis listed the most productive and influential journals in the related field. The 10 top productive journals covered both basic study and clinical study, while half of the top 10 cited journals focused on clinical research, which corresponded to the result of the cocited analysis of references. It implies that clinical research has an important clinical significance in breast cancer brain metastasis. In our study, we list the 10 most productive authors and 10 most frequently cited authors. These authors contributed to the foundation of the related region. The most productive and cited author was Nancy U. Lin, who contributed 65 publications in the field. She has led and participated in numerous clinical trials on breast cancer brain metastases ( 16 , 29 , 30 ) and has participated in the development of guidelines in this field ( 31 , 32 ). In addition, Nancy U. Lin was the one with highest centrality in top 10 cocited authors, which showed her great influence in the related field.

Cocitation analysis is used to evaluate the relevance between papers, and papers with higher cocitation were considered as the milestones of a specific region. Analyzing the publications cocited most frequently helped to set up the basic knowledge and research focus of breast cancer brain metastasis. The cocited paper ranked first, second, third, fourth, and ninth based on citations were all phase 2 trials of different therapies for patients with brain metastasis from HER-2 positive breast cancer. As mentioned before, HER2-positive is the breast cancer subtype that most frequently develops brain metastasis when compared to other subtypes. Former studies found that the active therapy of HER-2 positive breast cancer, trastuzumab, seemed to increase the risk of brain metastasis. Therefore, new therapy was innovated to solve these clinical problems, including lapatinib plus capecitabine, tucatinib plus trastuzumab and capecitabine, lapatinib, neratinib plus capecitabine, and trastuzumab emtansine (T-DM1). “Lapatinib plus capecitabine in patients with previously untreated brain metastases from HER2-positive metastatic breast cancer (LANDSCAPE): a single-group phase 2 study” published by Bachelot T et al. in The Lancet Oncology was the most cited paper (160 citations). This study has confirmed the efficacy of lapatinib plus capecitabine as the first-line treatment of HER-2-positive breast cancer brain metastasis ( 14 ). The second cited paper was “Tucatinib, Trastuzumab, and Capecitabine for HER2-Positive Metastatic Breast Cancer” published by Murthy RK et al. in The New England Journal of Medicine in 2020. The novel HER-2 inhibitor, tucatinib, demonstrated inspiringly active efficacy in patients with brain metastasis from HER2-positive breast cancer. Progression-free survival in the first year was 24.9% in the tucatinib-combination group and 0% in the placebo-combination group ( 15 ). The fourth paper was “TBCRC 022: A Phase II Trial of Neratinib and Capecitabine for Patients with Human Epidermal Growth Factor Receptor 2–Positive Breast Cancer and Brain Metastases” published by Freedman RA et al., which confirmed the efficacy of neratinib plus capecitabine against refractory HER2-positive breast cancer brain metastasis ( 17 ). The ninth paper confirmed the capacity of T-DM1 to lengthen the overall survival of patients with HER2-positvie breast cancer brain metastasis when compared with lapatinib plus capecitabine treatment. The fifth cited paper was “Genomic Characterization of Brain Metastases Reveals Branched Evolution and Potential Therapeutic Targets” published by Brastianos PK et al., which clarified the value of sequence of primary biopsies by detecting alterations in the assistance of the prediction of distant metastasis including brain metastasis ( 18 ). The eighth cited paper was an evaluation of different graded prognostic assessment (GPA) indices via multi-institutional retrospective analysis ( 21 ). The seventh cited paper was the only basic study in the 10 most cited papers, which anchored COX2, HBEGF, and ST6GALNAC5 as the key genes mediating breast cancer brain metastasis ( 20 ). These references can be divided into categories: pathogenesis, prevention, treatment, and prognosis of breast cancer brain metastasis, among which treatment was the most dominant area.

4.2. Focus and hotspots

Keyword analysis was employed to identify the trends of development and research hotspots in the related fields. The co-occurrence analysis of VOSviewer divided the keywords into five clusters. We divided the five clusters into the following five categories: basic study, clinical trial, local therapy, treatment optimization, and epidemiology. Keywords with high frequency highlighted the focus within the branch category. In the red cluster, expression, cell, in vivo , and growth were the most common keywords, which were the fundamental elements of basic studies. The green cluster contained keywords such as phase II trial, trastuzumab, efficacy, open-label , and lapatinib plus capecitabine . The LANDSCAPE trial set the lapatinib plus capecitabine as the first-line therapy, and more clinical trials were registered and conducted. The combination of target therapy and chemotherapy was the mainstream in clinical trials, which complemented each other clinically ( 33 – 36 ). Local therapy was represented by the blue cluster, which included keywords such as radiation-therapy, stereotactic radiosurgery, surgical resection, prognostic-factors, management , and graded prognostic assessment . Local therapies remained the cornerstone of treatment for patients with brain metastasis from breast cancer. These therapies include surgical resection, stereotactic radiotherapy, and whole brain radiotherapy. The approach chosen for treatment is individualized based on the extent and characteristics of the brain metastasis ( 37 , 38 ). For patients with endocrine-resistant breast cancer who develop brain metastasis and are resistant to most chemotherapies, surgical tumor resection and stereotactic radiotherapy have demonstrated efficacy in improving overall survival and reducing symptoms associated with brain metastasis, which remains crucial in optimizing outcomes for this population ( 39 ). Keywords in the yellow cluster were mainly related to treatment optimization including nanoparticles and focused ultrasound , which were used in preclinical trials, and the multidisciplinary crosstalk seemed to improve the efficacy of treatment at present ( 40 , 41 ). The purple cluster was mainly related to epidemiology with keywords such as survival, risk, subtype, diagnosis , and recurrence . The development of research trends reflected by keywords were sorted out from the cluster timeline.

Burst detection was an effective method to discover the hotspots and identify potential future developmental trends. In this study, we found the references with citation burst. The burst of four references began in 2020, and the burst is still ongoing, including three clinical trials and a review. The first clinical trial was the phase II trial of tucatinib, trastuzumab, and capecitabine for HER2-positive metastatic breast cancer ( 15 ), earning the most attention of researchers in the related field (burst strength: 55.25) within 2 years. As mentioned earlier, tucatinib demonstrated apparent positive efficacy, especially in patients with brain metastasis, which was a milestone of the treatment of breast cancer brain metastasis with a tyrosine kinase inhibitor (TKI). Another clinical trial burst in 2020 was “TBCRC 022: A Phase II Trial of Neratinib and Capecitabine for Patients With Human Epidermal Growth Factor Receptor 2–Positive Breast Cancer and Brain Metastases,” which provided new possibility to the treatment of refractory HER2-positive breast cancer brain metastases ( 17 ). The third clinical trial burst recently was “Trastuzumab Deruxtecan in Previously Treated HER2-Positive Breast Cancer,” A novel antibody–drug conjugate (ADC), trastuzumab deruxtecan, showed durable antitumor activity in patients with HER2-positive metastatic breast cancer ( 23 ). The outstanding success of treating HER2-positive breast cancer and other solid tumors may represent a new era of tumor treatment ( 42 ). The last reference burst in 2 years was a review that concluded the molecular mechanisms and clinical therapies of brain metastasis ( 43 ), which provided an overview of the current understanding of brain metastasis from preclinical and clinical perspectives.

In conclusion, our analysis of keywords and citation bursts provides insight into trends and hotspots in research on brain metastasis from breast cancer. The success of novel therapies, such as TKIs and ADCs, may represent a new era of treatment in patients suffering brain metastasis from breast cancer. Our findings suggest that future research in this region may focus on these novel therapies and optimizing treatment approaches for brain metastasis.

5. Strengths and limitations

We summarized the developmental route of the research on breast cancer brain metastasis from January 2006 to October 2022. However, there are also some limitations in our bibliometric study. First, the analysis was based on publications retrieved from the SCIE of Web of Science Core Collection, which did not have papers indexed by other databases such as Scopus and Google. Second, a reference to a document can be either confirmatory or contradictory, which would result in bias in the number of citations. Third, searching based on title, abstracts, and keywords means that some of the manuscripts that involved breast cancer brain metastasis might not be included.

6. Conclusion

In conclusion, there has been a general increase in the annual number of publications on breast cancer brain metastasis from 2006 to 2022. The main findings are as follows:

  • Institutions from all over the world participated in the study of breast cancer brain metastasis. The United States was ranked first in both the number of publications and institutions. The University Texas MD Anderson Cancer Center was the most productive institution, while the Dana Farber Cancer Institution was the most cited. However, the research collaboration between countries and institutions was regionally limited.
  • The Journal of Neuro-Oncology published the most papers (n = 111), while the Journal of Clinical Oncology ranked first with 9,861 citations based on cocited analysis.
  • Nancy U. Lin was the most productive and cited author with high influence in the field.
  • Research on breast cancer brain metastasis was focused on the basic study, clinical trial, local therapy, treatment optimization, and epidemiology.
  • The most cited references were focused on pathogenesis, prevention, treatment, and prognosis, among which treatment attracted the most attention. New therapies developed rapidly in the recent 3 years, and the treatment of brain breast cancer metastasis got a breakthrough with novel TKI and ADC-based therapies, which may be the mainstream treatment in the future.

Data availability statement

Author contributions.

S-QW and YL were responsible for the conception and design of the research. Y-TY, X-HZ, L-QC and HK contributed to the data collection and filter. S-QW and JZ participated in writing the manuscript. X-SZ revised this manuscript critically for intellectual content. This research is administrative supported by Y-FW and Y-YL. All authors contributed to the article and approved the submitted version.

Funding Statement

This work was supported by the National Natural Science Foundation of China ( 81873205, 81803877, 82104629, 81904037), the Natural Science Foundation of Guangdong Province, China (2020B1515120063) and Postdoctoral Science Foundation of China (NO. 2022M711536).

Abbreviations

TKI, tyrosine kinase inhibitor; T-DM1, trastuzumab emtansine; ADCs, antibody–drug conjugates.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Brain Mets

11 th Edition

BRAIN METASTASES RESEARCH AND EMERGING THERAPY CONFERENCE

4 th TO 6 th OCTOBER 2023 • PARIS

EORTIC logo

Dear Friends, We are delighted to welcome you to Paris for the Eleventh Annual Brain Metastases Research and Emerging Therapy Conference. Past successful editions have conforted us to organize again the conference. The meeting will be held, as for previous editions under the auspices of EANS and EORTC but, also in association with the Institut Gustave Roussy since our rewarding partnership initiated during the last 10th edition.

This initiative is devoted to accelerate therapeutic discoveries and, to improve care of patients with metastatic CNS malignancies. We anticipate that this cross-sectional meeting will provide a deeper dive into basic and translational research and, also stimulate innovative and insightful clinical trial on brain metastatic patients. These pre, intra and post diagnosis issues of great unmet need will be addressed in a dynamic and interactive framework. Several topics will be specifically discussed like challenges in precision medicine management and, the actual role of liquid biopsies for CNS metastases patients. The increasing place of new local treatments and, combined strategies in the era of targeted therapies and immune check point inhibitors will also be addressed.

We are convinced that this conference would constitute an unparalleled platform to share basic, translational, and clinical data and explore new treatment paradigms in this patient population. Finally, the scientific committee hopes that this meeting will provide a fantastic opportunity to develop networking with all professionals involved in brain metastases management and, lay the foundation for future collaborative projects.

The program chairs Manmeet Ahluwalia (US), Fabrice Barlési (FR), Frédéric Dhermain (FR), Emilie Le Rhun (CH), Philippe Métellus (FR), Ricardo Soffietti (IT), Michael Weller (CH), Manfred Westphal (DE)

PROGRAM CHAIRS

Ahluwalia

Manmeet Ahluwalia Miami, USA

M anmeet Ahluwalia, MD, FACP is the Dean and Diane Miller Family Endowed Chair in Neuro-Oncology. He is an Associate Professor in the Department of Medicine, Clinic Lerner College of Medicine of Case Western Reserve University (CCLCM) where he subspecializes in treatment of patients with brain tumors and brain metastases. He is the Director, Brain Metastasis Research Program and the Associate Director, Clinical Trials, Operations in the Rose Ella Burkhardt Brain Tumor and Neuro-Oncology Center of the Neurological Institute of Cleveland Clinic. He is the Section Head of NeuroOncology Outcomes and is a staff in the Taussig Cancer Institute, Cleveland Clinic and has joint appointment in the Developmental Therapeutics Program, Case Comprehensive Cancer Center.

D r. Ahluwalia’s research focuses on the development of new therapies for patients with brain tumors and brain metastases. He is currently leading several clinical trials involving new targeted therapies as well as treatments targeting tumor blood vessels (angiogenesis) and cancer stem cells. His results have been presented nationally and internationally and have resulted in over 70 editorials, peer-reviewed manuscripts and book chapters. Dr. Ahluwalia serves as the Associate Editor on Tumor Section of Neurosurgery, the official Journal of Congress of Neurological Surgeons (CNS). He is the Associate Editor of ASCO Post, the newsletter of ASCO. He is the Section Editor of NeuroOncology for HemOnc Today. He serves as a reviewer on multiple journals including Cancer, NeuroOncology, Cancer Research, Journal of NeuroOncology, Expert Reviews in Neurotherapeutics, BMC Cancer, Molecular Cancer Research, Expert Review of Anticancer Therapy, Expert Opinion in Pharmacotherapy, Journal of Neurology & Neurophysiology.

D r. Ahluwalia received his MD degree from the Maulana Azad Medical College, University of Delhi. He completed his residency at Fairview General Hospital and fellowship training at the Roswell Park Cancer Institute.

brain metastases research papers

Fabrice Barlesi Villejuif, France

A specialist in lung cancer, precision medicine and cancer immunology, Prof. Fabrice Barlesi is a major player in research on innovative cancer therapies. He was appointed Medical Director and Director of Clinical Research at Gustave Roussy in early 2020.

P rofessor of Medicine at the University of Aix-Marseille, Prof. Barlesi previously headed the Multidisciplinary Oncology and Therapeutic Innovations Department at the Hôpital Nord in Marseille (AP-HM), as well as the Marseille Early Cancer Trials Center (CLIP2), which he created. He holds a PhD in science and management, methods of analysis of health systems and a master’s degree in general hospital management from ESSEC.

P rof. Barlesi also co-founded the French immunology cluster Marseille Immunopôle, whose mission is to bring together the immunology expertise of the Aix-Marseille metropolitan area. In this context, he coordinates the major international research project PIONeeR (Investissement d’avenir RHU 2017) which aims to better understand, prevent and overcome resistance to immunotherapy – anti-PD1(L1) – in lung cancer. He was also vice-president of the PACA cancer cluster.

P rof. Barlesi has authored and co-authored nearly 300 publications in international journals or specialized books. In 2018, the European Society for Medical Oncology (ESMO) and the International Association for the Study of Lung Cancer (IASLC) awarded him the prestigious Heine H. Hansen Award. Fabrice Barlesi is listed as one of the most influential researchers in the world (Highly cited researchers by Web of Science Group).

brain metastases research papers

Frédéric Dhermain Villejuif, France

Born the 17th of March 1961, married, four children. Mail : [email protected] Position: Senior Radiation Oncologist, full-time since 2003, Head of the Brain Tumor Board (250 new patients in 2015).

Areas of interest : Gliomas, Meningiomas, Primary and Secondary Brain tumors in Adults and Pediatrics. Functional Imaging and multi-modality treatments (MRI and PET).

More than 75 publications in: Lancet Neurol, Brain, Mutation Research, Annals of Oncology, Int J Radiat Biol Oncol Phys, Cancer Radiotherapie, Br J Haematology, Europ J Cancer, Radiother Oncology, J Neuro-Oncology, Radiat Oncol, Neurology, Neurosurgery. Chapter in Handbook of Neurology (Springer).

Reviewer for: Neuro-Oncology, Clinical Cancer Research, Oncotarget.

Ongoing scientific subjects: Prognostic impact of Perfusion / Permeability characteristics in intra-cranial tumors, functional MRI and PET in RT of Gliomas compared to conventional MRI and CT scan, Stereotactic therapy and other high-precision RT tools in Brain metastases.

Ph.D Thesis at the University Paris-Sud on “Functional MRI and Gliomas”, Pr Bourhis Director, Dr Ducreux Co-Director (LIMEC, INSERM Unit 788), 1st September 2010.

Experience with IMRT, Proton therapy, Stereotactic Radiotherapy (Cyberknife), Radio-chemotherapy, Multimodality imaging for diagnosis and radiotherapy.

Member of the EORTC Brain Tumor Group (Treasurer), Quality assurance and Imaging sub-comitees, SNO (Society of NeuroOncology), ESTRO and ANOCEF (Board). GCP trained.

Recent Publications

Dhermain F , Deutsch E. Stereotactic radiation and checkpoint inhibitors in melanoma patients with BM: a question of drug, timing or both? Ann Oncol. 2016 Mar;27(3):371-2.

Dhermain F , Barani IJ. Complications from radiotherapy . Handb Clin Neurol. 2016;134:219-34.

Le Rhun E, Dhermain F , Vogin G, Reyns N, Metellus P. Radionecrosis after stereotactic radiotherapy for brain metastases. Expert Rev Neurother. 2016 Aug;16(8):903-14.

Dhermain F , Reyns N, Colin P, Métellus P, Mornex F, Noël G. Stereotactic radiotherapy in brain metastases. Cancer Radiother. 2015 Jan 29. pii: S1278-3218 Le Rhun É, Dhermain F, Noël G, et al. ANOCEF guidelines for the management of brain metastases . Cancer Radiother. 2015 Feb 6. pii: S1278-3218

Martin V, Moyal É, Delannes M, Padovani L, Sunyach MP, Feuvret L, Dhermain F, Noël G, Laprie A. Radiotherapy for brain tumors: which margins should we apply? Cancer Radiother . 2013 Oct;17(5-6):434-43.

brain metastases research papers

Émilie Le Rhun Zurich, Switzerland

D r. Emilie Le Rhun has been Senior Neuro-Oncologist at the Department of Neurosurgery at the University Hospital Lille, France, since 2007 and at the Cancer Center Oscar Lambret since 2005. She is also providing the Neuro-Oncology service for the Hospital in Valenciennes, France, since 2007. She qualified in medicine at the University of Brest, France in 1999. Her medical thesis addressed the neuropsychological features of primary progressive aphasia. Subsequently she obtained her training in Neurology from 1999-2003 at Lille University Hospital and was board-certified in Neurology in 2003 and in Neuro-Oncology for Oncology in 2008. Since November 2016, she has been on sabbatical leave in Zurich, Switzerland, and Toronto, Canada.

D r. Le Rhun`s main research interests are brain metastases, leptomeningeal metastasis and palliative and supportive care. She serves on the editorial board of Neuro-Oncology and has co-authored more than 40 original publications in the field of clinical neuro-oncology research. She is chairing the CNS metastases committee of the European Organization for Research and Treatment of Cancer (EORTC) Brain Tumor Group and the task forces of the Association de Neuro-Oncologie d’Expression Française (ANOCEF) on CNS metastases and cognition, quality of life and supportive care. She also participates in the Guideline Committees on Gliomas, Brain Metastasis and Palliative Care of the European Association of Neuro-Oncology (EANO) and chairs a Joint Guideline Task Force of EANO and the European Society for Medical Oncology (ESMO) on Leptomeningeal Metastasis. In 2015, Dr Le Rhun was elected one of two “Young Neuro-Oncologists” of the EORTC Brain Tumor Group.

brain metastases research papers

Phillippe Métellus Marseille, France

P hilippe METELLUS is Professor of Neurosurgery at the Clairval Hospital Center in Marseille, France. He is specialized in brain tumors and is the actual leader of the Glioma and the Brain Metastases program in France. Besides his clinical activity, he is running translational and basic science research program in the INSERM UMR 911 unit. He obtained his doctorate in medicine (Neurosurgery specialty) from the University of Marseille in 2002 and his PhD in 2011 for his research on angiogenesis and invasion in gliomas. He received a master of Neurosciences from the Paris-Sud University in Paris, and completed his fellowship at the Johns Hopkins University, Baltimore, Maryland, USA (2006) and at The Barrow Neurological Institute in Phoenix, Arizona, USA (2007).

P rof. Philippe METELLUS is authored or co-authored more than 150 peer-reviewed articles and received substantial awards for coordinating a variety of clinical and translational research projects. He is also reviewer for a number of international journals such as Journal of Neuro-Oncology, Neuro-Oncology, The Lancet Oncology, World Neurosurgery, Journal of Neurosurgery… He is a board member of the French National Society of Neurosurgeons. Since 2012, he has been one of the elected members of the Neuro-Oncology section of EANS (European Association of Neurosurgical Societies). In 2013, he has been invited to join the Brain Mets Platform of EORTC (European Organization for Research and Treatment of Cancer) and has been elected member of the Neuro-Oncological committee of the World Federation of Neurological Societies (WFNS).

P rof. Philippe METELLUS clinical and research activities are focused on Gliomas and Brain Metastases. A surgical research program on gliomas located in eloquent areas including awake craniotomies with electroencephalographic recordings has been developed with his neurological team in 2011. Also, a translational research program on Gliomas and Brain Metastases biology is conducted with the oncological transfer laboratory at the Aix-Marseille University. These programs involve a multi-disciplinary brain tumor consortium including, Neurologists, Neuro-Oncologists, Medical Oncologists, Radiation Oncologists, Neuro-Radiologists, Pathologists and the translational oncology university platform. In addition, since November 2016, Prof. Metellus coordinates a “Committee for Research, Clinical Innovation and Education (CRICE)”. This structure, created within Clairval Hospital Center, aims to boost, structure and develop the clinical research within the establishment.

I n 2011 and 2012, Prof. Philippe METELLUS organized the 1st and 2nd Annual Brain Metastases Research and Emerging Therapies Conference in Brain Metastasis. In 2013, for its 3rd edition, this European Conference has been held under the auspices of EORTC, at the request of this European institution. This initiative has been reconducted in 2014 and 2015 with the RTOG (Radiation Therapy Oncology Group) participation, the North American equivalent of the EORTC. This conference has been yet organized in 2016 again under the auspices of EORTC and with the support of French (ANOCEF and SNCF) and European (EANO and EANS) societies and this 6th edition has been granted 9 European CME credits (ECMEC) by the European Accreditation Council for Continuing Medical Education (EACCME).

brain metastases research papers

Riccardo Soffietti Turin, Italy

  • P rofessor of Neurology and Neuro-Oncology, University of Torino, Medical School
  • H ead, Dept. Neuro-Oncology, University and City of Health and Science University Hospital of Turin, Italy.
  • F ounding Member and President of European Association of Neuro-Oncology (EANO) (from 2012 to 2014)
  • M ember of the Education Committee of European Cancer Organization (ECCO)
  • M ember of the Congress Program Committee of the European Academy of Neurology (EAN)
  • C hair of the Subspecialty Scientific Panel of Neuro-Oncology of EAN
  • M ember of the Steering Committee of the Brain Tumor Group of the European Organization for Research and Treatment of Cancer ( EORTC )
  • C oordinator of the EORTC study n° 22952-26001 (Phase III) “No radiotherapy versus whole brain radiotherapy for 1 to 3 brain metastases from solid tumor after surgical resection or radiosurgery”.
  • C hairman of the Research Group for Neuro-Oncology of the World Federation of Neurology
  • C ancer Expertise for research projects of the European Community and of Ministry of Health and Research of Italy, France, Switzerland and Netherlands.
  • A dvisor of the European Medicines Agency (EMA).
  • M ember of the International Group on Response Assessment in Neuro-Oncology (RANO).
  • 3 50 publications (including full papers, chapters in books, monographies, abstracts of International Congresses).
  • E xecutive Editor of Neuro-Oncology
  • M ember of the Editorial Board : Neuro-Oncology Practice, Anticancer Drugs, Journal of Neurology, Current Cancer Therapy Reviews, CNS Oncology and Neurological Sciences.
  • R eferee: Neurology, Lancet Neurology, Brain, European Journal of Neurology, Lancet, Lancet Oncology, Journal of Clinical Oncology, Clinical Cancer Research, Cancer, European Journal of Cancer, The Oncologist, Journal of Neuro-Oncology, Critical Review in Hematology and Oncology, Expert Opinion on Pharmacotherapy, Oncology Research, Tumori, Expert Review of Neurotherapeutics, Expert Review of Anticancer Therapy, Future Oncology, British Medical Cancer Journal.
  • A ward for Excellence in Clinical Research (Society for Neuro-Oncology, US, 2009)

brain metastases research papers

Michael Weller Zurich, Switzerland

D r. Michael Weller has been Chairman of the Department of Neurology at the University Hospital Zurich, Switzerland, since 2008. He qualified in medicine in Cologne, Germany, after completing his thesis on proliferative disorders of the retina. A postdoctoral fellowship at the Department of Clinical Immunology, University Hospital Zurich, Switzerland, followed where he identified death receptor targeting as a potential treatment strategy for malignant gliomas. In 2005, he was appointed Chairman of the Department of General Neurology at the University Hospital Tübingen, Germany, where he had previously received his education in clinical neurology.

D r. Weller has received several awards in recognition of his contributions to cancer research, including the German Cancer Award in 2007. He served as Chairman of the Neuro-Oncology Group of the German Cancer Society from 2001-2008. He is the Chairman of the German Glioma Network of the German Cancer Council, joined the Executive Board of the European Association for Neuro-Oncology (EANO) in 2010 and served as President of EANO for 2014-2016. He is also the Chairman of the Brain Tumor Group of the European Organization for Research and Treatment of Cancer (EORTC) (2015-2018) and hosts the World Federation of Neuro-Oncology Societies (WFNOS) Meeting 2017 in Zurich, Switzerland.

D r. Weller was involved in major practice-changing clinical trials including the registration trial for temozolomide in glioblastoma and served as PI on the NOA-03, NOA-04, NOA-08 and G-PCNSL-SG-1 trials in Germany and the DIRECTOR and ARTE trials in Switzerland. Dr Weller has a research focus on the immunology of gliomas and served as the PI of the phase III immunotherapy trial, ACT IV (Rindopepimut). He is also a member of the editorial boards of the Journal of Neurochemistry, Journal of Neuro-Oncology, Brain, Glia and Neuro-Oncology, and he was the Associate Editor Europe of Neuro-Oncology from 2006-2013.

D r. Weller has co-authored more than 600 original publications in peer-reviewed journals, including The New England Journal of Medicine, Science, Nature, Nature Medicine, Lancet Oncology, PNAS, The Journal of Clinical Investigation, and The Journal of Clinical Oncology.

brain metastases research papers

Manfred Westphal Hamburg, Germany

Professor Manfred Westphal was born in Hamburg, where he also went to school and studied medicine at the University Hospital in Hamburg-Eppendorf (UKE). The academic year of 1978-1979 was spent at the Medical School of the University of Glasgow as scholar of the German National Scholarship Foundation. Based on his scientific research in experimental neuro-endocrinology as a medical student he obtained a research education grant from the German Research Foundation (Deutsche Forschungsgemeinschaft, DFG) and became a research fellow at the University of California San Francisco in the Hormnone Research Laboratory with C.H. Li. His main interest during that time was neuro-endocrinology focusing on peptide biology of opiate peptides, particularly ?-endorphine. He also started to study cell biology of brain tumors with Charles B. Wilson. This work was continued after his return to the University Hospital Hamburg-Eppendorf in 1984 where the Laboratory of Brain Tumor Biology in the department for neurosurgery was founded. Professor Westphal completed his residency at the UKE and in 1999 was appointed acting chairman.

I n 2002 he was elected as director of the Neurosurgical Department at the University of Düsseldorf and shortly afterwards confirmed as director and chair of the Neurosurgical Department at the UKE. With the focus on neurooncology and vascular neurosurgery Professor Westphal has published 265 original papers, in addition to numerous book chapters and book editions. He is member of several scientific associations and was for more than eight years elected member of the study section for neurosciences at the DFG in Bonn. He started the Committee for Neurooncology at the EANS being its chair for 8 years, until he became secretary from 2003 until 2007. Therafter he chaired the Committee for Neuro-Oncology of the World Federation of Neurological Surgery from 2009 to 2013. Since 2004 he represents the EANS as Board Member in the European Brain Council (EBC in Brussels).Prof. Westphal was also president of the German Academy of Neurosurgery for the electoral period of 2013/2014.

Manfred Westphal, MD serves as chairman of the department of neurosurgery at the university medical center Hamburg Eppendorf since 1999. He founded the Hans-Dietrich Herrmann Laboratory for Brain Tumor Biology in 1984 after returning from a postdoctoral fellowship at UCSF Medical Center. His interest has been in clinical and experimental neuro-oncology so besides numerous publications in the field of growth factors, angiogenesis, Invasion and glioma stem cell biology he has chaired or co-chaired four phase III trials including carmustine wafers, convection enhanced delivery of a toxin conjugate, suicide gene therapy with simitagene ceradenovec and a trial anti-EGF-R monoclonal antibody; in addition he participated in many other clinical trials as co-chair or investigator. His clinical and translational studies resulted in 280 peer reviewed articles. In 2014 he shared the Warner Prize for Cancer Research. He served as secretary of the EANS, secretary of the European Brain Council (Brussels) and as president of the German Academy of Neurosurgery. For two periods of totally 9 years he was elected to the neuroscience review oard of the German Research Council (Bonn).

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Original research article, research trends and prospects on brain metastasis from breast cancer: a bibliometric analysis.

brain metastases research papers

  • 1 School of Traditional Chinese Medicine, Southern Medical University, Guangzhou, Guangdong, China
  • 2 School of Chinese Medicine, Hong Kong Baptist University, Hong Kong, Hong Kong SAR, China
  • 3 Department of Oncology, Affiliated Dongguan People’s Hospital, Southern Medical University, Dongguan, Guangdong, China

Introduction: Brain metastasis is the terminal event of breast cancer with poor prognoses. Therefore, this article aimed to provide an updated summary on the development, hotspots, and research trends of brain metastasis from breast cancer based on bibliometric analysis.

Method: Publications on breast cancer with brain metastasis retrieved from the Web of Science Core Collection. CiteSpace, VOSviewer, and other online bibliometric analysis platforms were used to analyze and visualize the result.

Result: In totality, 693 researchers from 3,623 institutions across 74 counties and regions published a total of 2,790 papers in 607 journals. There was a noticeable increase in publications in 2006. The United States was the dominant country with the most publications followed by China. University Texas MD Anderson Cancer Center was the most productive institution, while Dana Farber Cancer Institution was the most cited. Journal of Neuro-Oncology published the most papers, while Journal of Clinical Oncology ranked first based on cocited analysis. Nancy U. Lin was the most productive and cited author with high influence. There was a focus on basic research, clinical trials, local therapy, treatment optimization, and epidemiological studies regarding brain metastases from breast cancer. References focused on pathogenesis, prevention, treatment, and prognosis were cited most frequently, among which the clinical trial of novel treatment attracted most attention from researchers. Reference citation burst detection suggested that new therapies such as the novel tyrosine kinase inhibitor and antibody–drug conjugate may lead the research trends in the future.

Conclusion: High-income countries contributed more to the field of breast cancer with brain metastasis, while developing countries like China developed quickly. Furthermore, the success of novel therapies in recent years may lead to the new era of treatment of breast cancer with brain metastasis in the future.

1 Background

Breast cancer has been the most common malignancy in women. There has been a slight increase in breast cancer incidence rates since 2004 ( 1 ), with new cases in women reaching 281,550 in 2021, accounting for 30% of all female cancers ( 2 ). Although with a relatively high survival rate that reaches 90%, the mortality of breast cancer still ranked second in female cancer, approximately 90% of which are associated with complications from recurrent or metastatic diseases ( 3 ). Unfortunately, even patients with early-stage breast cancer will develop distant metastasis, which accounts for one-third of all cancer cases ( 4 ).

The development of breast cancer brain metastasis is regarded as a late event with a worse prognosis compared to metastasis to other organs. Different subtypes of breast cancer vary in the rate of brain metastasis. Triple-negative breast cancer [Triple-negative: hormone receptor (HR)–negative/human epidermal growth factor receptor 2 (HER2)–negative] and HER2+ breast cancer (HR-negative/HER2-positive) have a higher likelihood of developing brain metastasis, with rates of 25%–27% and 11%–20%, respectively. Both luminal A and luminal B subtypes have a lower risk of brain metastasis (l8%–15% and 11%, respectively) ( 5 – 7 ).

Despite the attention of researchers on brain metastasis from breast cancer, there has not yet been a bibliometric analysis reviewing the research output on publications concerning the topic. Herein, we utilized some bibliometric analysis tools to explore the frontiers and hotspots of studies on brain metastasis from breast cancer. Bibliometric analysis employs citation count as an assessment to measure of research quality ( 8 ). As a quantitative method, bibliometric analysis helps to trace the research profiles of different countries, institutions, and researchers that promoted the scientific production, behavior, and development in the related fields ( 9 , 10 ). Bibliometric reviews on breast cancer have covered several topics, focusing on a variety of different treatments including nanomedicine ( 9 ), immunotherapy ( 11 ), the application of pan-cancer studies in treatment ( 12 ), and radiotherapy ( 13 ).

In this study, we used CiteSpace and VOSviewer to analyze papers related to breast cancer brain metastasis and summarized the research findings. We examined the evolution and development of research hotspots in the breast cancer brain metastasis from 2006 to 2022, identifying new hotspots and topics. The aim of this study is to contribute new insights and ideas to research of breast cancer brain metastasis in the future.

2 Material and methods

2.1 data collection.

Articles related to brain metastasis from breast cancer were retrieved from the Science Citation Index Expanded (SCIE) of Web of Science Core Collection, which were all published during 1 January 1992 to 7 October 2022. Search strategy was based on the advanced search option with the following strategy: TS = (“breast cancer” OR “breast carcinoma”) AND TS = (“brain metastas*” OR “cerebral metastas*” OR “intracranial metastas*” OR “central nervous system metastas*” OR “secondary brain tumor”). The full records and cited references of the data were extracted and downloaded in a plain text file and a tab-delimited text file, consisting of publication year, authorship, title, abstract, author keywords, citation count, reference, journal title, institution, and country. Only literature written in English was contained in processes of search and downloading, which were completed within 1 day on 8 October 2022 to avoid errors caused by frequent database updates. A total of 3,096 publications were contained in the first set of data (year: 1992–2022). It may be because the data network was so complex that some functions of CiteSpace [version 6.1.R3 (64-bit)] ran very slowly. Therefore, we limited the time from 1 January 2006 to 7 October 2022 with the same strategy of search and selection mentioned earlier. A total of 2,790 publications were contained in the second set of data (year: 2006–2022). Only the annual number of publications was conducted based on the first set of data. Other analyses including country, institution, author, reference, and keyword were based on the second set of data. Occupying 89% of all the 3,096 publications in recent two decades, the analysis of the second set of data cover provided a snapshot of recent research in brain metastasis from breast cancer. Figure 1 showed the process of publication selection. Furthermore, since this study did not include any animals or experiments, ethical consent was not required.

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Figure 1 Flowchart of the process of publication selection.

2.2 Data analysis and visualization

Two online platforms and three software were used to analyze and visualize publications related to breast cancer brain metastasis. Datawrapper ( https://www.datawrapper.de/ ) was used to draw the map of the regional distribution of publications and BIBLIOMETRIC ( https://bibliometric.com/ ) was used to analyze the annual publications of the most productive countries as well as the collaboration between different countries. Microsoft Excel 2019 was used to analyze the annual distribution of publications on brain metastasis from breast cancer.

CiteSpace is a visualization and analyzation software designed by Prof. Chaomei Chen. It is used to discover the collaborative network and critical and pivotal points in the scientific literature of a specific topic. The analysis is based on the theory of co-occurrence and cocitation. When two publications are cited together by another publication, there is a cocitation relationship between the two publications. Burst detection is another practical function of CiteSpace to discover emerging words or references by analyzing the change of frequency of their citation or occurrence in a short time. We used CiteSpace to draw a matrix network of authors and cocited authors We also detected references with strong citation burst to find the influential references in the related field. Moreover, we detected keywords with strong occurrence burst and drew a timeline of keyword clusters, which concluded the hotspot development in different year and provided insight on the future trends in the related region. The strength of nodes was calculated of cosine, and pathfinder was used to detect the most representative network.

VOSviewer is another useful software to visualize the network map of scientific papers. We used bibliographic coupling analysis and cocitation analysis to visualize institutions and journals. We also used cooccurrence analysis to draw a cluster network of keywords. To avoid the repeat caused by expression difference, we appended the thesaurus so that the software could recognize terms like “metastasis” and “metastases” as the same term. Additionally, this study did not include any animal or experiments; thus, ethical issues were not required.

3.1 Publication output of research on breast cancer brain metastasis

Web of Science Core Collection yielded a total of 3,096 publications related to breast cancer brain metastasis in the recent three decades. As demonstrated in Figure 2 , from 1992 to 2005, the annual output rose slightly with fluctuation. In 2006, the annual number of publications was increased sharply to 57, which almost doubled that of last year. Since then, the number of publications increased substantially in general year by year and peaked in 2020 with a total of 286 publications. For this reason, we used the data from 2006 to 2022 in the follow-up analysis.

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Figure 2 The annual number of publications of breast cancer brain metastasis from 1 January 1992 to 7 October 2022.

3.2 Profile of countries and institutions

A total of 74 countries or regions contributed to the studies on breast cancer brain metastasis. As shown in Figure 3 , the United States was ranked the first and China second and Germany third based on the number of publications. It is worth mentioning that China showed an emerging boost, especially in the recent decade, but the average citation stayed limited ( Table 1 ). Regarding research collaboration, the United States had the broadest range of academic collaborations with countries all around the world ( Figure 4 ).

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Figure 3 Analysis of country based on the number of publications. (A) The number of publications per country. Countries with less publications were colored red, while countries with most publications were colored blue. Countries without publications in the related region were colored gray. (B) The annual publication number and trend of the 10 most productive countries. Different countries were represented by different colors, and the height of each color blot reflected the number of publications of a specific country in a specific year.

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Table 1 Five most productive countries.

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Figure 4 The connection among different countries in brain metastasis from breast cancer. Each country was represented by a fragment on the outer part of the circle. The area of the fragment is proportional to the number of publications of the correspondent country and the size of the arc to the strength of cooperation between two countries.

A total of 3,623 institutions participated in the studies of breast cancer brain metastasis, and 404 of them, with at least five publications, are shown in Figure 5 . All of the 404 institutions were divided into seven clusters based on the co-occurrence analysis. Clusters in deep blue, green, and orange, represented by the University Texas MD Anderson Cancer Center, Dana Farber Cancer Institution and University of California, San Francisco, respectively, were the institutions mainly from America. Institutions in the red cluster were mainly from Europe and America. The yellow cluster mainly consisted of institutions from China, and the purple one consisted of institutions from other East Asia countries. The light-blue cluster mainly consisted of institutions from France. When comparing Figures 5A, B , institutions in blue, green, and orange clusters were the most productive ones. Furthermore, as listed in Table 2 , nine of the most productive institutions were located in America. The University Texas MD Anderson Cancer Center was the most productive institution with a total of 131 publications, while the Dana Farber Cancer Institution was the most influential institution with the highest citation per publication and has the strongest link strength with other institutions.

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Figure 5 The co-occurrence cluster and production density of institutions. (A) cluster network analysis of institutions with at least five publications. The size of the node is proportional to the number of publications of a specific institution. The bigger the node, the more productive the institution. When two institutions occurred in the same publication for three times, there is a link between them. The width of the link represents the strength of co-occurrence between two institutions. Nodes and links in the same color belong to the same cluster, meaning the connections between these institutions are more closer according to the VOSviewer analysis. (B) The density map of institutions based on the number of publications. The labels of institutions in red area are the most productive institutions, while labels in the blue area are the less productive ones. From: VOSviewer.

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Table 2 10 most productive and cited institutions.

3.3 Profile of journals, cocited journals

VOSviewer was used to conduct the bibliographic coupling analysis and cocitation analysis of journals. A total of 2,790 papers were published in 607 journals, and 6,628 journals were cited in the references. Table 3 demonstrated the leading journals in the related research based on publication and citation. Journal of Neuro-Oncology published the most papers (n = 111), Breast Cancer Research and Treatment second (n = 82), and Cancers third (n = 68). Cocitation analysis is an effective method to discover the most influential journals in a specific topic. In the region of brain metastasis from breast cancer, Journal of Clinical Oncology ranked first with 9,861 citations, followed by Clinical Cancer Research with 4,491 citations and Cancer Research with 4257 citations. Clinical Cancer Research was the only journal both in top 10 based on production and citation, with the highest impact factor (IF = 13.801) in the list of most productive journals, indicating its special position in the related region.

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Table 3 10 most productive and most cited journals.

3.4 Profile of authors and cocited authors

CiteSpace was also used to visualize the network of authors based on co-occurrence analysis and cocited analysis. In total, 693 authors contributed to the development of research on breast cancer brain metastasis and 994 authors collaborated in the research. The top 20 authors or cocited authors in every year were selected and visualized in the network. The sizes of the nodes are proportional to the number of publications of the author shown in Figure 6A and the citation in Figure 6B . Links are thicker between two closely collaborated authors. As shown in Figure 6 , Lin NU, Kim S, Lee J, Berghoff A, and Preusser M were the top five authors based on the number of publications. As shown in Table 4 , Lin NU was active in this field all over the years with 65 publications in total. In addition, Lin NU was the most cited author based on cocited analysis with 1,000 citations. Sperduto PW ranked second with 468 citations, Pestalozzi BC ranked third with 326 citations, Patchell RA ranked fourth with 315 citations, and Bachelot T ranked fifth with 288 citations. Centrality is used to assess the relationship of one node with other nodes. When the centrality is over 0.1, the node is considered as a landmark node connected closely with other nodes in a network. The centrality of 10 most productive authors all subceeded 0.1. The centrality of 7 authors among the 10 with most citations exceeded 0.1, of which LIN NU (1.24) was the highest. These authors were the leading researchers in the field of brain metastasis from breast cancer and served as a linking bridge with other researchers.

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Figure 6 Network of authors and cocited authors on breast cancer brain metastasis. Each tree-ring node represents an author. (A) Author network based on cooccurrence analysis. The size of node is proportional to the research output of the author. The color of the tree-ring node represents the publication history of the author. Red tree-ring nodes represent the author who published papers in the recent 2 years, while gray ones represent authors who were productive for a decade. Colorful nodes represent authors with continuous research output. (B) Cocited author network based on cocited analysis. The larger the node, the more times the author is cited. Nodes in warmer colors represent authors cited more recently, while nodes in cooler colors represent the opposite.

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Table 4 Top 10 of the most productive authors and cocited authors.

3.5 Keywords of breast cancer brain metastasis

VOSviewer and CiteSpace were used to analyze keywords from different perspectives to provide an overlook of development and trend in the related region. After merging keywords repeated by expression difference, VOSviewer concluded 4,189 keywords and 598 of them occurred more than five times, which were divided into five clusters ( Figure 7 ). The red cluster was the largest one with 210 keywords, containing expression, in-vivo, angiogenesis, microenvironment , and endothelial growth-factor . The green cluster ranked second in size with 201 keywords including phase II trial, chemotherapy, efficacy, open-label , and lapatinib plus capecitabine . The blue cluster ranked third in size with 97 keywords including radiation-therapy, stereotactic radiosurgery, prognostic-factors, quality of life, graded prognostic assessment , and management . The yellow cluster contained 96 keywords including solid tumors, blood-brain barrier, cerebrospinal-fluid, her2-positive breast cancer, drug-delivery , and acquired-resistance . Purple cluster contained 89 keywords including survival, risk, subtype, diagnosis , and recurrence . Accordingly, keywords were roughly clustered into five categories as follows: basic study, clinical trial of new therapy, local therapy, treatment optimization, and epidemiology.

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Figure 7 Co-occurrence analysis of keywords during 2006–2022. Lines between two keywords mean the two words coexisted for more than 10 times. The bigger the node, the more frequent it appears. The stronger the line, the more co-occurrences happen. At least 50 keywords are contained in one cluster. Additionally, keywords connected more closely are divided into the same cluster with the same color. From: VOSviewer.

We also used CiteSpace to perform cluster analysis based on the log likelihood ratio (LLR) and drew a timeline of the development of the hotspots in the related region ( Figure 8 ). The top 10% of keywords in a year were analyzed, which yielded a network of 253 nodes with 305 links. A cluster with the modularity of 0.8114 and the weighted mean silhouette of 0.9291 was yielded, which meant that the result was highly convincing with a significant cluster structure. There were 15 clusters including first-line treatment, epidermal growth factor receptor (EGFR) expression, pyrotinib-based therapy, the prognostic index, and other clusters, demonstrating the development of research focus on breast cancer brain metastasis.

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Figure 8 Cluster timeline of keywords of breast cancer brain metastasis. Each tree-ring node represents a keyword. The size of the node is proportional to the time of the occurrence of the keyword. The color of the tree-ring node represents the occurrence history of the keyword. The label of clusters was produced by LLR analysis, and the colors represent different years.

3.6 Cocited references

CiteSpace was used to visualize the network of references of records between 2006 and 2022. The top 5% of the most cited references each year were contained in the cocited analysis, and the network was refined by the pathfinder pruning method. As shown in Figure 9 , 930 references were detected and 10 of the most cocited publications are listed in Table 5 . Seven out of the top 10 co-cited publications were clinical trials, namely, five randomized controlled trials, one population-based cohort, and one retrospective cohort. The other most cocited publications included one genome wide association study (GWAS) study, one basic study, and one review. The most cited publication was “Lapatinib plus capecitabine in patients with previously untreated brain metastases from HER2-positive metastatic breast cancer (LANDSCAPE): a single-group phase 2 study ( 14 )” by Bachelot T et al., which was cited 160 times. It is worth mentioning that the sources of these publications strongly overlapped with the list of the most cited journals, which confirmed the importance of these references and journals in the studies of breast cancer brain metastasis.

www.frontiersin.org

Figure 9 Top 30 references with the strongest citation bursts. The blue line reflects the duration of the citation of the paper. The red segment reflects the duration of the burst.

www.frontiersin.org

Table 5 Top 10 cocited references.

Burst detection is an effective method to find out the hotspots in different times and conclude the developmental route of a specific field supported by CiteSpace. The publication of the phase II trial of tucatinib, trastuzumab, and capecitabine for HER2-positive metastatic breast cancer ( 15 ) gained the most attention from researchers in the related field (burst strength: 55.25). The publications of another two clinical trials focused on the effects of neratinib plus capecitabine ( 17 ) and lapatinib ( 16 ) separately was ranked the second (burst strength: 47.49) and third (burst strength: 45.8), respectively. The recent publication that most appealed researchers’ attention was “Trastuzumab Deruxtecan in Previously Treated HER2-Positive Breast Cancer ( 23 )”, whose citation can be dated from 2020 with an increasing trend.

4 Discussion

4.1 general trends.

With reference from the number of publications, the publication trend of the breast cancer brain metastasis research field can be divided into two stages. From 1992 to 2005, the publications increased slowly with fluctuation. It may be due to the following two reasons. The first one is that radiotherapy was the mainstream of treatment for brain metastasis and the controversial effect of chemotherapy ( 24 ) limited the development of clinical trials. The second one is that patients with brain metastasis were always excluded from clinical trials in this period and medical oncologists were reluctant to leave the advanced patients with brain metastasis without other therapy but just the target therapy of clinical trial, which make it difficult to have enough number of patients and assess the efficacy of chemotherapy ( 25 ). In 2005, several randomized trials have confirmed the efficacy of chemotherapy in treating brain metastasis ( 24 , 26 – 28 ) and more clinical trials were ongoing, especially those focused on trastuzumab ( 28 ), which may lead to the publication boosted in 2006. From 2006 onward, the number of publications in breast cancer brain metastasis increased gradually.

In this study, we summarized the research collaboration in different dimensions as well as research focus and hotspots to understand the development and trend of breast cancer brain metastasis. A total of 693 researchers from 3,623 institutions in 74 counties and regions attributed 2,790 publications in 607 journals, indicating that breast cancer brain metastasis attracted wide attention from researchers all over the world. The United States was the leading country in the related field based on the analysis of institutions and authors’ publications and citations. Moreover, the institutions in the United States exhibited a high degree of collaboration with research institutions from all around the world, especially those from Europe. On the other hand, China had emerged as the most promising country in the last decade. Although the academic influence and research collaboration are still limited, researchers and institutions in China demonstrate diligent effort to promote the development of studies on breast cancer brain metastasis. Furthermore, regionally limited collaborations were observed based on institution analysis. Spatial isolation caused by the COVID-19 pandemic has increased the development of online meetings, which serve as a means to break the spatial boundaries between countries and accelerate the research development significantly.

Journal and cocited journal analysis listed the most productive and influential journals in the related field. The 10 top productive journals covered both basic study and clinical study, while half of the top 10 cited journals focused on clinical research, which corresponded to the result of the cocited analysis of references. It implies that clinical research has an important clinical significance in breast cancer brain metastasis. In our study, we list the 10 most productive authors and 10 most frequently cited authors. These authors contributed to the foundation of the related region. The most productive and cited author was Nancy U. Lin, who contributed 65 publications in the field. She has led and participated in numerous clinical trials on breast cancer brain metastases ( 16 , 29 , 30 ) and has participated in the development of guidelines in this field ( 31 , 32 ). In addition, Nancy U. Lin was the one with highest centrality in top 10 cocited authors, which showed her great influence in the related field.

Cocitation analysis is used to evaluate the relevance between papers, and papers with higher cocitation were considered as the milestones of a specific region. Analyzing the publications cocited most frequently helped to set up the basic knowledge and research focus of breast cancer brain metastasis. The cocited paper ranked first, second, third, fourth, and ninth based on citations were all phase 2 trials of different therapies for patients with brain metastasis from HER-2 positive breast cancer. As mentioned before, HER2-positive is the breast cancer subtype that most frequently develops brain metastasis when compared to other subtypes. Former studies found that the active therapy of HER-2 positive breast cancer, trastuzumab, seemed to increase the risk of brain metastasis. Therefore, new therapy was innovated to solve these clinical problems, including lapatinib plus capecitabine, tucatinib plus trastuzumab and capecitabine, lapatinib, neratinib plus capecitabine, and trastuzumab emtansine (T-DM1). “Lapatinib plus capecitabine in patients with previously untreated brain metastases from HER2-positive metastatic breast cancer (LANDSCAPE): a single-group phase 2 study” published by Bachelot T et al. in The Lancet Oncology was the most cited paper (160 citations). This study has confirmed the efficacy of lapatinib plus capecitabine as the first-line treatment of HER-2-positive breast cancer brain metastasis ( 14 ). The second cited paper was “Tucatinib, Trastuzumab, and Capecitabine for HER2-Positive Metastatic Breast Cancer” published by Murthy RK et al. in The New England Journal of Medicine in 2020. The novel HER-2 inhibitor, tucatinib, demonstrated inspiringly active efficacy in patients with brain metastasis from HER2-positive breast cancer. Progression-free survival in the first year was 24.9% in the tucatinib-combination group and 0% in the placebo-combination group ( 15 ). The fourth paper was “TBCRC 022: A Phase II Trial of Neratinib and Capecitabine for Patients with Human Epidermal Growth Factor Receptor 2–Positive Breast Cancer and Brain Metastases” published by Freedman RA et al., which confirmed the efficacy of neratinib plus capecitabine against refractory HER2-positive breast cancer brain metastasis ( 17 ). The ninth paper confirmed the capacity of T-DM1 to lengthen the overall survival of patients with HER2-positvie breast cancer brain metastasis when compared with lapatinib plus capecitabine treatment. The fifth cited paper was “Genomic Characterization of Brain Metastases Reveals Branched Evolution and Potential Therapeutic Targets” published by Brastianos PK et al., which clarified the value of sequence of primary biopsies by detecting alterations in the assistance of the prediction of distant metastasis including brain metastasis ( 18 ). The eighth cited paper was an evaluation of different graded prognostic assessment (GPA) indices via multi-institutional retrospective analysis ( 21 ). The seventh cited paper was the only basic study in the 10 most cited papers, which anchored COX2, HBEGF, and ST6GALNAC5 as the key genes mediating breast cancer brain metastasis ( 20 ). These references can be divided into categories: pathogenesis, prevention, treatment, and prognosis of breast cancer brain metastasis, among which treatment was the most dominant area.

4.2 Focus and hotspots

Keyword analysis was employed to identify the trends of development and research hotspots in the related fields. The co-occurrence analysis of VOSviewer divided the keywords into five clusters. We divided the five clusters into the following five categories: basic study, clinical trial, local therapy, treatment optimization, and epidemiology. Keywords with high frequency highlighted the focus within the branch category. In the red cluster, expression, cell, in vivo , and growth were the most common keywords, which were the fundamental elements of basic studies. The green cluster contained keywords such as phase II trial, trastuzumab, efficacy, open-label , and lapatinib plus capecitabine . The LANDSCAPE trial set the lapatinib plus capecitabine as the first-line therapy, and more clinical trials were registered and conducted. The combination of target therapy and chemotherapy was the mainstream in clinical trials, which complemented each other clinically ( 33 – 36 ). Local therapy was represented by the blue cluster, which included keywords such as radiation-therapy, stereotactic radiosurgery, surgical resection, prognostic-factors, management , and graded prognostic assessment . Local therapies remained the cornerstone of treatment for patients with brain metastasis from breast cancer. These therapies include surgical resection, stereotactic radiotherapy, and whole brain radiotherapy. The approach chosen for treatment is individualized based on the extent and characteristics of the brain metastasis ( 37 , 38 ). For patients with endocrine-resistant breast cancer who develop brain metastasis and are resistant to most chemotherapies, surgical tumor resection and stereotactic radiotherapy have demonstrated efficacy in improving overall survival and reducing symptoms associated with brain metastasis, which remains crucial in optimizing outcomes for this population ( 39 ). Keywords in the yellow cluster were mainly related to treatment optimization including nanoparticles and focused ultrasound , which were used in preclinical trials, and the multidisciplinary crosstalk seemed to improve the efficacy of treatment at present ( 40 , 41 ). The purple cluster was mainly related to epidemiology with keywords such as survival, risk, subtype, diagnosis , and recurrence . The development of research trends reflected by keywords were sorted out from the cluster timeline.

Burst detection was an effective method to discover the hotspots and identify potential future developmental trends. In this study, we found the references with citation burst. The burst of four references began in 2020, and the burst is still ongoing, including three clinical trials and a review. The first clinical trial was the phase II trial of tucatinib, trastuzumab, and capecitabine for HER2-positive metastatic breast cancer ( 15 ), earning the most attention of researchers in the related field (burst strength: 55.25) within 2 years. As mentioned earlier, tucatinib demonstrated apparent positive efficacy, especially in patients with brain metastasis, which was a milestone of the treatment of breast cancer brain metastasis with a tyrosine kinase inhibitor (TKI). Another clinical trial burst in 2020 was “TBCRC 022: A Phase II Trial of Neratinib and Capecitabine for Patients With Human Epidermal Growth Factor Receptor 2–Positive Breast Cancer and Brain Metastases,” which provided new possibility to the treatment of refractory HER2-positive breast cancer brain metastases ( 17 ). The third clinical trial burst recently was “Trastuzumab Deruxtecan in Previously Treated HER2-Positive Breast Cancer,” A novel antibody–drug conjugate (ADC), trastuzumab deruxtecan, showed durable antitumor activity in patients with HER2-positive metastatic breast cancer ( 23 ). The outstanding success of treating HER2-positive breast cancer and other solid tumors may represent a new era of tumor treatment ( 42 ). The last reference burst in 2 years was a review that concluded the molecular mechanisms and clinical therapies of brain metastasis ( 43 ), which provided an overview of the current understanding of brain metastasis from preclinical and clinical perspectives.

In conclusion, our analysis of keywords and citation bursts provides insight into trends and hotspots in research on brain metastasis from breast cancer. The success of novel therapies, such as TKIs and ADCs, may represent a new era of treatment in patients suffering brain metastasis from breast cancer. Our findings suggest that future research in this region may focus on these novel therapies and optimizing treatment approaches for brain metastasis.

5 Strengths and limitations

We summarized the developmental route of the research on breast cancer brain metastasis from January 2006 to October 2022. However, there are also some limitations in our bibliometric study. First, the analysis was based on publications retrieved from the SCIE of Web of Science Core Collection, which did not have papers indexed by other databases such as Scopus and Google. Second, a reference to a document can be either confirmatory or contradictory, which would result in bias in the number of citations. Third, searching based on title, abstracts, and keywords means that some of the manuscripts that involved breast cancer brain metastasis might not be included.

6 Conclusion

In conclusion, there has been a general increase in the annual number of publications on breast cancer brain metastasis from 2006 to 2022. The main findings are as follows:

a. Institutions from all over the world participated in the study of breast cancer brain metastasis. The United States was ranked first in both the number of publications and institutions. The University Texas MD Anderson Cancer Center was the most productive institution, while the Dana Farber Cancer Institution was the most cited. However, the research collaboration between countries and institutions was regionally limited.

b. The Journal of Neuro-Oncology published the most papers (n = 111), while the Journal of Clinical Oncology ranked first with 9,861 citations based on cocited analysis.

c. Nancy U. Lin was the most productive and cited author with high influence in the field.

d. Research on breast cancer brain metastasis was focused on the basic study, clinical trial, local therapy, treatment optimization, and epidemiology.

e. The most cited references were focused on pathogenesis, prevention, treatment, and prognosis, among which treatment attracted the most attention. New therapies developed rapidly in the recent 3 years, and the treatment of brain breast cancer metastasis got a breakthrough with novel TKI and ADC-based therapies, which may be the mainstream treatment in the future.

Data availability statement

The original contributions presented in the study are included in the article/supplementary material. Further inquiries can be directed to the corresponding authors.

Author contributions

S-QW and YL were responsible for the conception and design of the research. Y-TY, X-HZ, L-QC and HK contributed to the data collection and filter. S-QW and JZ participated in writing the manuscript. X-SZ revised this manuscript critically for intellectual content. This research is administrative supported by Y-FW and Y-YL. All authors contributed to the article and approved the submitted version.

This work was supported by the National Natural Science Foundation of China ( 81873205, 81803877, 82104629, 81904037), the Natural Science Foundation of Guangdong Province, China (2020B1515120063) and Postdoctoral Science Foundation of China (NO. 2022M711536).

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Abbreviations

TKI, tyrosine kinase inhibitor; T-DM1, trastuzumab emtansine; ADCs, antibody–drug conjugates.

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Keywords: breast cancer, brain metastasis, bibliometric analysis, research trend, TKI (tyrosine kinase inhibitor), ADC (antibody-drug conjugate)

Citation: Wu S-q, Liu Y, Zhou J, You Y-t, Zhou X-h, Chen L-q, Kwan HY, Zhao X-s, Wu Y-f and Liu Y-y (2023) Research trends and prospects on brain metastasis from breast cancer: A bibliometric analysis. Front. Oncol. 13:1091249. doi: 10.3389/fonc.2023.1091249

Received: 21 November 2022; Accepted: 13 March 2023; Published: 05 April 2023.

Reviewed by:

Copyright © 2023 Wu, Liu, Zhou, You, Zhou, Chen, Kwan, Zhao, Wu and Liu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Xiao-shan Zhao, [email protected] ; Yi-fen Wu, [email protected] ; Yan-yan Liu, [email protected]

† These authors have contributed equally to this work

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    Brain metastases (BM) affect up to one-third of adults with solid tumor malignancies and are associated with significant cancer patient morbidity, anxiety, and mortality. Approximately 70,000-400,000 patients will develop BM each year in the USA [ 1 - 3 ]. Consequentially, BM represent an important public health care burden that is also ten ...

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    Epidemiology of Brain Metastases Cancer is the second most prevalent cause of death worldwide [ 1 ], with lung, breast, colorectal, and prostate being the most frequently affected organs [ 1 ].

  9. The 100 Most Cited Papers About Brain Metastases

    Introduction. Brain metastasis continues to represent a significant source of morbidity and mortality in patients with different types of systemic cancer, as first recognized by Bucholz in 1898. 1 The true incidence of brain metastasis is difficult to determine accurately. Most previous estimates emerged from historical neurosurgical series, and because neurosurgeons were reluctant to operate ...

  10. Brain metastases: Nanomedicine-boosted diagnosis and treatment

    1. Epidemiology Brain metastases represent a frequent complication of cancers and are more common than primary brain tumors [1]. Each year in the United States, ∼170,000 patients are diagnosed with brain metastases, which is 10-fold more than those diagnosed with primary brain malignancy [1].

  11. National Cancer Institute Collaborative Workshop on Shaping the

    Brain metastases are an increasing global public health concern, even as survival rates improve for patients with metastatic disease. Both metastases and the sequelae of their treatment are key determinants of the inter-related priorities of patient survival, function, and quality of life, mandating a multidimensional approach to clinical care and research. At a virtual National Cancer ...

  12. Special Issue "Diagnosis and Treatment of Brain Metastases"

    The incidence of brain metastasis is increasing as improvements in systemic therapy lead to increased survival. This provides challenging clinical decisions for patients who are trying to balance the risk of progression of disease with treatment-related side effects, and it requires management strategies from diverse multidisciplinary teams.

  13. A comprehensive dataset of annotated brain metastasis MR ...

    21 Altmetric Metrics Abstract Brain metastasis (BM) is one of the main complications of many cancers, and the most frequent malignancy of the central nervous system. Imaging studies of BMs are...

  14. PET imaging in patients with brain metastasis—report of the RANO/PET

    Brain metastases (BM) often occur in advanced malignancies but may also be an initial disease manifestation in, for example, CUP (cancer of unknown primary). ... Only papers constituting levels 1-3 evidence according to the Oxford Centre for Evidence-based Medicine (the Oxford 2011 Levels of Evidence) were included. In brief, a randomized ...

  15. Molecular Profiles of Brain Metastases: A Focus on Heterogeneity

    Brain metastasis is a common and devastating clinical entity. Intratumor heterogeneity in brain metastases poses a crucial challenge to precision medicine. ... provides an outlook for future research directions and describes possible research applications. Feature papers are submitted upon individual invitation or recommendation by the ...

  16. TME-targeted approaches of brain metastases and its clinical

    Recent research has shed light on the potential of TME-targeted and potential treatments for treating Brain metastases, and we'll use that knowledge to discuss the advantages and disadvantages of ...

  17. Research trends and prospects on brain metastasis from breast cancer: A

    Brain metastasis is the terminal event of breast cancer with poor prognoses. Therefore, this article aimed to provide an updated summary on the development, hotspots, and research trends of brain metastasis from breast cancer based on bibliometric analysis. Method

  18. (PDF) BRAIN METASTASES: A REVIEW ARTICLE

    Cerebral metastases or brain metastases (brain mets) is the most common malignant intracranial cancer among all brain tumors. Brain mets are the secondary tumors migrated from the...

  19. IJMS

    Metastasis, particularly brain metastasis, continues to puzzle researchers to this day, and exploring its molecular basis promises to break ground in developing new strategies for combatting this deadly cancer. In recent years, the research focus has shifted toward the earliest steps in the formation of metastasis. In this regard, significant progress has been achieved in understanding how the ...

  20. Automated Segmentation of Brain Metastases with Deep Learning: A ...

    Artificial intelligence has been proposed for brain metastasis segmentation, but it has seldom been clinically validated. Methods: A deep-learning-based brain metastasis segmentation system (BMSS) was trained on a single-institution dataset of three-dimensional contrast-enhanced T1-weighted images from patients with newly diagnosed brain ...

  21. The 100 Most Cited Papers About Brain Metastases

    Request PDF | The 100 Most Cited Papers About Brain Metastases | Background: A vast amount of articles centered on brain metastases have been published. Objective: To present the 100 most-cited ...

  22. Home

    He is the Director, Brain Metastasis Research Program and the Associate Director, Clinical Trials, Operations in the Rose Ella Burkhardt Brain Tumor and Neuro-Oncology Center of the Neurological Institute of Cleveland Clinic. He is the Section Head of NeuroOncology Outcomes and is a staff in the Taussig Cancer Institute, Cleveland Clinic and ...

  23. Frontiers

    IntroductionBrain metastasis is the terminal event of breast cancer with poor prognoses. Therefore, this article aimed to provide an updated summary on the development, hotspots, and research trends of brain metastasis from breast cancer based on bibliometric analysis.MethodPublications on breast cancer with brain metastasis retrieved from the Web of Science Core Collection. CiteSpace ...