Federated learning enables big data for rare cancer boundary detection
Authors: Pati Sarthak , Baid Ujjwal , Edwards Brandon , Sheller Micah , Wang Shih-Han , Reina G. Anthony , Foley Patrick , Gruzdev Alexey , Karkada Deepthi , Davatzikos Christos , Sako Chiharu , Ghodasara Satyam , Bilello Michel , Mohan Suyash , Vollmuth Philipp , Brugnara Gianluca , Preetha Chandrakanth J. , Sahm Felix , Maier-Hein Klaus , Zenk Maximilian , Bendszus Martin , Wick Wolfgang , Calabrese Evan , Rudie Jeffrey , Villanueva-Meyer Javier , Cha Soonmee , Ingalhalikar Madhura , Jadhav Manali , Pandey Umang , Saini Jitender , Garrett John , Larson Matthew , Jeraj Robert , Currie Stuart , Frood Russell , Fatania Kavi , Huang Raymond Y. , Chang Ken , Balaña Carmen , Capellades Jaume , Puig Josep , Trenkler Johannes , Pichler Josef , Necker Georg , Haunschmidt Andreas , Meckel Stephan , Shukla Gaurav , Liem Spencer , Alexander Gregory S. , Lombardo Joseph , Palmer Joshua D. , Flanders Adam E. , Dicker Adam P. , Sair Haris I. , Jones Craig K. , Venkataraman Archana , Jiang Meirui , So Tiffany Y. , Chen Cheng , Heng Pheng Ann , Dou Qi , Kozubek Michal , Lux Filip , Michálek Jan , Matula Petr , Keřkovský Miloš , Kopřivová Tereza , Dostál Marek , Vybíhal Václav , Vogelbaum Michael A. , Mitchell J. Ross , Farinhas Joaquim , Maldjian Joseph A. , Yogananda Chandan Ganesh Bangalore , Pinho Marco C. , Reddy Divya , Holcomb James , Wagner Benjamin C. , Ellingson Benjamin M. , Cloughesy Timothy F. , Raymond Catalina , Oughourlian Talia , Hagiwara Akifumi , Wang Chencai , To Minh-Son , Bhardwaj Sargam , Chong Chee , Agzarian Marc , Falcão Alexandre Xavier , Martins Samuel B. , Teixeira Bernardo C. A. , Sprenger Flávia , Menotti David , Lucio Diego R. , LaMontagne Pamela , Marcus Daniel , Wiestler Benedikt , Kofler Florian , Ezhov Ivan , Metz Marie , Jain Rajan , Lee Matthew , Lui Yvonne W. , McKinley Richard , Slotboom Johannes , Radojewski Piotr , Meier Raphael , Wiest Roland , Murcia Derrick , Fu Eric , Haas Rourke , Thompson John , Ormond David Ryan , Badve Chaitra , Sloan Andrew E. , Vadmal Vachan , Waite Kristin , Colen Rivka R. , Pei Linmin , Ak Murat , Srinivasan Ashok , Bapuraj J. Rajiv , Rao Arvind , Wang Nicholas , Yoshiaki Ota , Moritani Toshio , Turk Sevcan , Lee Joonsang , Prabhudesai Snehal , Morón Fanny , Mandel Jacob , Kamnitsas Konstantinos , Glocker Ben , Dixon Luke V. M. , Williams Matthew , Zampakis Peter , Panagiotopoulos Vasileios , Tsiganos Panagiotis , Alexiou Sotiris , Haliassos Ilias , Zacharaki Evangelia I. , Moustakas Konstantinos , Kalogeropoulou Christina , Kardamakis Dimitrios M. , Choi Yoon Seong , Lee Seung-Koo , Chang Jong Hee , Ahn Sung Soo , Luo Bing , Poisson Laila , Wen Ning , Tiwari Pallavi , Verma Ruchika , Bareja Rohan , Yadav Ipsa , Chen Jonathan , Kumar Neeraj , Smits Marion , van der Voort Sebastian R. , Alafandi Ahmed , Incekara Fatih , Wijnenga Maarten M. J. , Kapsas Georgios , Gahrmann Renske , Schouten Joost W. , Dubbink Hendrikus J. , Vincent Arnaud J. P. E. , van den Bent Martin J. , French Pim J. , Klein Stefan , Yuan Yading , Sharma Sonam , Tseng Tzu-Chi , Adabi Saba , Niclou Simone P. , Keunen Olivier , Hau Ann-Christin , Vallières Martin , Fortin David , Lepage Martin , Landman Bennett , Ramadass Karthik , Xu Kaiwen , Chotai Silky , Chambless Lola B. , Mistry Akshitkumar , Thompson Reid C. , Gusev Yuriy , Bhuvaneshwar Krithika , Sayah Anousheh , Bencheqroun Camelia , Belouali Anas , Madhavan Subha , Booth Thomas C. , Chelliah Alysha , Modat Marc , Shuaib Haris , Dragos Carmen , Abayazeed Aly , Kolodziej Kenneth , Hill Michael , Abbassy Ahmed , Gamal Shady , Mekhaimar Mahmoud , Qayati Mohamed , Reyes Mauricio , Park Ji Eun , Yun Jihye , Kim Ho Sung , Mahajan Abhishek , Muzi Mark , Benson Sean , Beets-Tan Regina G. H. , Teuwen Jonas , Herrera-Trujillo Alejandro , Trujillo Maria , Escobar William , Abello Ana , Bernal Jose , Gómez Jhon , Choi Joseph , Baek Stephen , Kim Yusung , Ismael Heba , Allen Bryan , Buatti John M. , Kotrotsou Aikaterini , Li Hongwei , Weiss Tobias , Weller Michael , Bink Andrea , Pouymayou Bertrand , Shaykh Hassan F. , Saltz Joel , Prasanna Prateek , Shrestha Sampurna , Mani Kartik M. , Payne David , Kurc Tahsin , Pelaez Enrique , Franco-Maldonado Heydy , Loayza Francis , Quevedo Sebastian , Guevara Pamela , Torche Esteban , Mendoza Cristobal , Vera Franco , Ríos Elvis , López Eduardo , Velastin Sergio A. , Ogbole Godwin , Soneye Mayowa , Oyekunle Dotun , Odafe-Oyibotha Olubunmi , Osobu Babatunde , Shu’aibu Mustapha , Dorcas Adeleye , Dako Farouk , Simpson Amber L. , Hamghalam Mohammad , Peoples Jacob J. , Hu Ricky , Tran Anh , Cutler Danielle , Moraes Fabio Y. , Boss Michael A. , Gimpel James , Veettil Deepak Kattil , Schmidt Kendall , Bialecki Brian , Marella Sailaja , Price Cynthia , Cimino Lisa , Apgar Charles , Shah Prashant , Menze Bjoern , Barnholtz-Sloan Jill S. , Martin Jason , Bakas Spyridon 
Published: December 2022

AbstractAlthough machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing.