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arxiv: 2405.09787 · v2 · pith:HZ2QAUPTnew · submitted 2024-05-16 · 📡 eess.IV · cs.CV· cs.LG

Analysis of the BraTS 2023 Intracranial Meningioma Segmentation Challenge

Dominic LaBella , Ujjwal Baid , Omaditya Khanna , Shan McBurney-Lin , Ryan McLean , Pierre Nedelec , Arif Rashid , Nourel Hoda Tahon
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Talissa Altes Radhika Bhalerao Yaseen Dhemesh Devon Godfrey Fathi Hilal Scott Floyd Anastasia Janas Anahita Fathi Kazerooni John Kirkpatrick Collin Kent Florian Kofler Kevin Leu Nazanin Maleki Bjoern Menze Maxence Pajot Zachary J. Reitman Jeffrey D. Rudie Rachit Saluja Yury Velichko Chunhao Wang Pranav Warman Maruf Adewole Jake Albrecht Udunna Anazodo Syed Muhammad Anwar Timothy Bergquist Sully Francis Chen Verena Chung Rong Chai Gian-Marco Conte Farouk Dako James Eddy Ivan Ezhov Nastaran Khalili Juan Eugenio Iglesias Zhifan Jiang Elaine Johanson Koen Van Leemput Hongwei Bran Li Marius George Linguraru Xinyang Liu Aria Mahtabfar Zeke Meier Ahmed W. Moawad John Mongan Marie Piraud Russell Takeshi Shinohara Walter F. Wiggins Aly H. Abayazeed Rachel Akinola Andr\'as Jakab Michel Bilello Maria Correia de Verdier Priscila Crivellaro Christos Davatzikos Keyvan Farahani John Freymann Christopher Hess Raymond Huang Philipp Lohmann Mana Moassefi Matthew W. Pease Phillipp Vollmuth Nico Sollmann David Diffley Khanak K. Nandolia Daniel I. Warren Ali Hussain Pascal Fehringer Yulia Bronstein Lisa Deptula Evan G. Stein Mahsa Taherzadeh Eduardo Portela de Oliveira Aoife Haughey Marinos Kontzialis Luca Saba Benjamin Turner Melanie M. T. Br\"u{\ss}eler Shehbaz Ansari Athanasios Gkampenis David Maximilian Weiss Aya Mansour Islam H. Shawali Nikolay Yordanov Joel M. Stein Roula Hourani Mohammed Yahya Moshebah Ahmed Magdy Abouelatta Tanvir Rizvi Klara Willms Dann C. Martin Abdullah Okar Gennaro D'Anna Ahmed Taha Yasaman Sharifi Shahriar Faghani Dominic Kite Marco Pinho Muhammad Ammar Haider Alejandro Aristizabal Alexandros Karargyris Hasan Kassem Sarthak Pati Micah Sheller Michelle Alonso-Basanta Javier Villanueva-Meyer Andreas M. Rauschecker Ayman Nada Mariam Aboian Adam E. Flanders Benedikt Wiestler Spyridon Bakas Evan Calabrese
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classification 📡 eess.IV cs.CVcs.LG
keywords tumormeningiomasegmentationbratscasesautomatedchallengecoefficient
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We describe the design and results from the BraTS 2023 Intracranial Meningioma Segmentation Challenge. The BraTS Meningioma Challenge differed from prior BraTS Glioma challenges in that it focused on meningiomas, which are typically benign extra-axial tumors with diverse radiologic and anatomical presentation and a propensity for multiplicity. Nine participating teams each developed deep-learning automated segmentation models using image data from the largest multi-institutional systematically expert annotated multilabel multi-sequence meningioma MRI dataset to date, which included 1000 training set cases, 141 validation set cases, and 283 hidden test set cases. Each case included T2, FLAIR, T1, and T1Gd brain MRI sequences with associated tumor compartment labels delineating enhancing tumor, non-enhancing tumor, and surrounding non-enhancing FLAIR hyperintensity. Participant automated segmentation models were evaluated and ranked based on a scoring system evaluating lesion-wise metrics including dice similarity coefficient (DSC) and 95% Hausdorff Distance. The top ranked team had a lesion-wise median dice similarity coefficient (DSC) of 0.976, 0.976, and 0.964 for enhancing tumor, tumor core, and whole tumor, respectively and a corresponding average DSC of 0.899, 0.904, and 0.871, respectively. These results serve as state-of-the-art benchmarks for future pre-operative meningioma automated segmentation algorithms. Additionally, we found that 1286 of 1424 cases (90.3%) had at least 1 compartment voxel abutting the edge of the skull-stripped image edge, which requires further investigation into optimal pre-processing face anonymization steps.

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