arXiv 2407.088552025-06-28eess.IVcs.CV

BraTS-PEDs：2023年多联盟国际儿童脑肿瘤分割挑战赛结果

BraTS-PEDs: Results of the Multi-Consortium International Pediatric Brain Tumor Segmentation Challenge 2023

Center for Data-Driven Discovery in Biomedicine (D3b)（数据驱动生物医学发现中心）；The Children’s Hospital of Philadelphia（费城儿童医院）；Sheikh Zayed Institute for Pediatric Surgical Innovation（谢赫扎伊德儿童外科创新研究所）；Children’s National Hospital（儿童国家医院）；Department of Neurosurgery（神经外科部门）；Dana-Farber Brigham Cancer Center & Boston Children’s Hospital（达纳-法伯布里弗癌症中心及波士顿儿童医院）；Department of Paediatric Radiology（儿科放射科部门）；University of Utah（犹他大学）；Cincinnati Children’s Hospital Medical Center（辛辛那提儿童医学中心）；Department of Radiology（放射科部门）；Division of Neuroradiology, Department of Radiology, Boston Children’s Hospital, Harvard Medical School（神经放射科，放射科，波士顿儿童医院，哈佛医学院）；College of Arts and Sciences, University of Pennsylvania（艺术与科学学院，宾夕法尼亚大学）；Department of Diagnostic and Interventional Radiology, All India Institute of Medical Sciences（诊断与介入放射科，全印度医学科学院）；Department of Diagnostic & Interventional Imaging, Neuroradiology section, The University of Texas Health at Houston, Texas, USA（诊断与介入成像部门，神经放射科，德克萨斯大学健康科学中心，德克萨斯，美国）；Beth Israel Deaconess Medical Center, Harvard Medical School（贝斯以色列医疗中心，哈佛医学院）；UNIDAD DE PATOLOGIA CLINICA（临床病理部门）

Anahita Fathi Kazerooni, Nastaran Khalili, Xinyang Liu, Debanjan Haldar, Zhifan Jiang, Anna Zapaishchykova, Julija Pavaine, Lubdha M. Shah, Blaise V. Jones, Nak… 展开作者

Anahita Fathi Kazerooni, Nastaran Khalili, Xinyang Liu, Debanjan Haldar, Zhifan Jiang, Anna Zapaishchykova, Julija Pavaine, Lubdha M. Shah, Blaise V. Jones, Nakul Sheth, Sanjay P. Prabhu, Aaron S. McAllister, Wenxin Tu, Khanak K. Nandolia, Andres F. Rodriguez, Ibraheem Salman Shaikh, Mariana Sanchez Montano, Hollie Anne Lai, Maruf Adewole, Jake Albrecht, Udunna Anazodo, Hannah Anderson, Syed Muhammed Anwar, Alejandro Aristizabal, Sina Bagheri, Ujjwal Baid, Timothy Bergquist, Austin J. Borja, Evan Calabrese, Verena Chung, Gian-Marco Conte, James Eddy, Ivan Ezhov, Ariana M. Familiar, Keyvan Farahani, Deep Gandhi, Anurag Gottipati, Shuvanjan Haldar, Juan Eugenio Iglesias, Anastasia Janas, Elaine Elaine, Alexandros Karargyris, Hasan Kassem, Neda Khalili, Florian Kofler, Dominic LaBella, Koen Van Leemput, Hongwei B. Li, Nazanin Maleki, Zeke Meier, Bjoern Menze, Ahmed W. Moawad, Sarthak Pati, Marie Piraud, Tina Poussaint, Zachary J. Reitman, Jeffrey D. Rudie, Rachit Saluja, MIcah Sheller, Russell Takeshi Shinohara, Karthik Viswanathan, Chunhao Wang, Benedikt Wiestler, Walter F. Wiggins, Christos Davatzikos, Phillip B. Storm, Miriam Bornhorst, Roger Packer, Trent Hummel, Peter de Blank, Lindsey Hoffman, Mariam Aboian, Ali Nabavizadeh, Jeffrey B. Ware, Benjamin H. Kann, Brian Rood, Adam Resnick, Spyridon Bakas, Arastoo Vossough, Marius George Linguraru

备注：: Accepted for publication at the Journal of Machine Learning for Biomedical Imaging (MELBA)https://melba-journal.org/2025:005
发表信息：: Machine.Learning.for.Biomedical.Imaging. 3 (2025)
DOI：: 10.59275/j.melba.2025-f6fg

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AI总结：

本文展示了BraTS-PEDs 2023儿童脑肿瘤分割挑战赛结果，该挑战利用多联盟数据评估MRI体积分割算法，发现nnU-Net等集成模型表现最佳，促进了临床与AI合作以改善患儿护理。

摘要：

儿童中枢神经系统肿瘤是儿童癌症相关死亡的主要原因。儿童高级别胶质瘤的五年生存率低于20%。新疗法的开发依赖于需要可重复且准确的集中响应评估的多机构协作临床试验。我们展示了BraTS-PEDs 2023挑战赛的结果，这是首个专注于儿童脑肿瘤的脑肿瘤分割（BraTS）挑战赛。该挑战赛利用了来自致力于儿童神经肿瘤学和临床试验的多个国际联盟的数据。BraTS-PEDs 2023旨在利用BraTS 2023挑战赛中采用的标准化定量性能评估指标，评估从磁共振成像中对儿童脑胶质瘤进行体积分割的算法。表现最佳的儿童肿瘤分析AI方法包括nnU-Net和Swin UNETR的集成、Auto3DSeg，或带有自监督框架的nnU-Net。BraTS-PEDs 2023挑战赛促进了临床医生（神经肿瘤学家、神经放射学家）与AI/成像科学家之间的合作，推动了更快的数据共享和自动化体积分析技术的发展。这些进步可能显著有益于临床试验并改善脑肿瘤患儿的护理。

英文摘要：

Pediatric central nervous system tumors are the leading cause of cancer-related deaths in children. The five-year survival rate for high-grade glioma in children is less than 20%. The development of new treatments is dependent upon multi-institutional collaborative clinical trials requiring reproducible and accurate centralized response assessment. We present the results of the BraTS-PEDs 2023 challenge, the first Brain Tumor Segmentation (BraTS) challenge focused on pediatric brain tumors. This challenge utilized data acquired from multiple international consortia dedicated to pediatric neuro-oncology and clinical trials. BraTS-PEDs 2023 aimed to evaluate volumetric segmentation algorithms for pediatric brain gliomas from magnetic resonance imaging using standardized quantitative performance evaluation metrics employed across the BraTS 2023 challenges. The top-performing AI approaches for pediatric tumor analysis included ensembles of nnU-Net and Swin UNETR, Auto3DSeg, or nnU-Net with a self-supervised framework. The BraTSPEDs 2023 challenge fostered collaboration between clinicians (neuro-oncologists, neuroradiologists) and AI/imaging scientists, promoting faster data sharing and the development of automated volumetric analysis techniques. These advancements could significantly benefit clinical trials and improve the care of children with brain tumors.

机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。