Journal Article

DKFZ-2026-00228

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png The 2024 Brain Tumor Segmentation Challenge Meningioma Radiotherapy (BraTS-MEN-RT) dataset.

LaBella, D. ; Schumacher, K. ; Mix, M. ; Leu, K. ; McBurney-Lin, S. ; Nedelec, P. ; Villanueva-Meyer, J. ; Raleigh, D. R. ; Shapey, J. ; Vercauteren, T. ; Chia, K. ; Ivory, M. ; Barfoot, T. ; Al-Salihi, O. ; Leu, J. ; Halasz, L. M. ; Velichko, Y. ; Wang, C. ; Kirkpatrick, J. P. ; Floyd, S. R. ; Reitman, Z. J. ; Mullikin, T. C. ; Vaios, E. J. ; Bagci, U. ; Sachdev, S. ; Hattangadi-Gluth, J. A. ; Seibert, T. M. ; Farid, N. ; Puett, C. ; Pease, M. W. ; Shiue, K. ; Anwar, S. M. ; Faghani, S. ; Taylor, P. ; Warman, P. ; Albrecht, J. ; Jakab, A. ; Moassefi, M. ; Chung, V. ; Chai, R. ; Aristizabal, A. ; Karargyris, A. ; Kassem, H. ; Pati, S. ; Sheller, M. ; Maleki, N. ; Saluja, R. ; Kofler, F. ; Schwarz, C. G. ; Lohmann, P. ; Vollmuth, P.DKFZ* ; Gagnon, L. ; Adewole, M. ; Hongwei B, L. ; Kazerooni, A. F. ; Tahon, N. H. ; Anazodo, U. ; Moawad, A. W. ; Menze, B. ; Linguraru, M. G. ; Aboian, M. ; Wiestler, B. ; Baid, U. ; Conte, G.-M. ; Rauschecker, A. M. ; Nada, A. ; Abayazeed, A. H. ; Huang, R. ; de Verdier, M. C. ; Rudie, J. D. ; Bakas, S. ; Calabrese, E.

2026
Nature Publ. Group London

Abstract: Meningiomas are the most common primary intracranial tumors, frequently requiring radiotherapy as a part of management. Effective radiotherapy planning for meningiomas necessitates accurate and consistent segmentation of target volumes on MRI, a process that is complex, labor-intensive, and dependent on expert expertise. The 2024 Brain Tumor Segmentation Challenge Meningioma Radiotherapy (BraTS-MEN-RT) Dataset addresses this problem by providing the largest multi-institutional collection of systematically annotated radiotherapy planning MRIs for meningiomas. Publicly accessible, this dataset comprises 570 radiotherapy planning 3D T1-weighted post-contrast MRIs at native resolutions, with 500 cases featuring expert-annotated gross tumor volumes (GTV). Annotations follow standardized radiotherapy planning protocols and include both intact and postoperative meningioma cases, ensuring wide clinical relevance. Contributions from seven diverse medical centers across the United States and the United Kingdom enhance the dataset's generalizability. The dataset aims to accelerate the development of automated segmentation methods for radiotherapy planning, improving workflow efficiency, reducing interobserver variability, and ultimately enhancing patient outcomes.

Note: epub

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Contributing Institute(s):

1. E230 Medizinische Bildverarbeitung (E230)

Research Program(s):

1. 315 - Bildgebung und Radioonkologie (POF4-315) (POF4-315)

Appears in the scientific report 2026

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; ; Article Processing Charges ; BIOSIS Previews ; Biological Abstracts ; Clarivate Analytics Master Journal List ; DOAJ Seal ; Essential Science Indicators ; Fees ; IF >= 5 ; JCR ; SCOPUS ; Science Citation Index Expanded ; Web of Science Core Collection

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