Analysis of the 2024 BraTS Meningioma Radiotherapy Planning Automated Segmentation Challenge

• URL: http://arxiv.org/abs/2405.18383v3
• Date: Mon, 21 Jul 2025 22:54:18 GMT
• Title: Analysis of the 2024 BraTS Meningioma Radiotherapy Planning Automated Segmentation Challenge
• Authors: Dominic LaBella, Valeriia Abramova, Mehdi Astaraki, Andre Ferreira, Zhifan Jiang, Mason C. Cleveland, Ramandeep Kang, Uma M. Lal-Trehan Estrada, Cansu Yalcin, Rachika E. Hamadache, Clara Lisazo, Adrià Casamitjana, Joaquim Salvi, Arnau Oliver, Xavier Lladó, Iuliana Toma-Dasu, Tiago Jesus, Behrus Puladi, Jens Kleesiek, Victor Alves, Jan Egger, Daniel Capellán-Martín, Abhijeet Parida, Austin Tapp, Xinyang Liu, Maria J. Ledesma-Carbayo, Jay B. Patel, Thomas N. McNeal, Maya Viera, Owen McCall, Albert E. Kim, Elizabeth R. Gerstner, Christopher P. Bridge, Katherine Schumacher, Michael Mix, Kevin Leu, Shan McBurney-Lin, Pierre Nedelec, Javier Villanueva-Meyer, David R. Raleigh, Jonathan Shapey, Tom Vercauteren, Kazumi Chia, Marina Ivory, Theodore Barfoot, Omar Al-Salihi, Justin Leu, Lia M. Halasz, Yuri S. Velichko, Chunhao Wang, John P. Kirkpatrick, Scott R. Floyd, Zachary J. Reitman, Trey C. Mullikin, Eugene J. Vaios, Christina Huang, Ulas Bagci, Sean Sachdev, Jona A. Hattangadi-Gluth, Tyler M. Seibert, Nikdokht Farid, Connor Puett, Matthew W. Pease, Kevin Shiue, Syed Muhammad Anwar, Shahriar Faghani, Peter Taylor, Pranav Warman, Jake Albrecht, András Jakab, Mana Moassefi, Verena Chung, Rong Chai, Alejandro Aristizabal, Alexandros Karargyris, Hasan Kassem, Sarthak Pati, Micah Sheller, Nazanin Maleki, Rachit Saluja, Florian Kofler, Christopher G. Schwarz, Philipp Lohmann, Phillipp Vollmuth, Louis Gagnon, Maruf Adewole, Hongwei Bran Li, Anahita Fathi Kazerooni, Nourel Hoda Tahon, Udunna Anazodo, Ahmed W. Moawad, Bjoern Menze, Marius George Linguraru, Mariam Aboian, Benedikt Wiestler, Ujjwal Baid, Gian-Marco Conte, Andreas M. Rauschecker, Ayman Nada, Aly H. Abayazeed, Raymond Huang, Maria Correia de Verdier, Jeffrey D. Rudie, Spyridon Bakas, Evan Calabrese,
• Abstract summary: The 2024 Brain Tumor Meningioma Radiotherapy (BraTS-MEN-RT) challenge aimed to advance automated segmentation algorithms.<n>We describe the design and results from the BraTS-MEN-RT challenge.
• Score: 45.3253187215396
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: The 2024 Brain Tumor Segmentation Meningioma Radiotherapy (BraTS-MEN-RT) challenge aimed to advance automated segmentation algorithms using the largest known multi-institutional dataset of 750 radiotherapy planning brain MRIs with expert-annotated target labels for patients with intact or postoperative meningioma that underwent either conventional external beam radiotherapy or stereotactic radiosurgery. Each case included a defaced 3D post-contrast T1-weighted radiotherapy planning MRI in its native acquisition space, accompanied by a single-label "target volume" representing the gross tumor volume (GTV) and any at-risk post-operative site. Target volume annotations adhered to established radiotherapy planning protocols, ensuring consistency across cases and institutions, and were approved by expert neuroradiologists and radiation oncologists. Six participating teams developed, containerized, and evaluated automated segmentation models using this comprehensive dataset. Team rankings were assessed using a modified lesion-wise Dice Similarity Coefficient (DSC) and 95% Hausdorff Distance (95HD). The best reported average lesion-wise DSC and 95HD was 0.815 and 26.92 mm, respectively. BraTS-MEN-RT is expected to significantly advance automated radiotherapy planning by enabling precise tumor segmentation and facilitating tailored treatment, ultimately improving patient outcomes. We describe the design and results from the BraTS-MEN-RT challenge.

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