Peer-Reviewed Publication
Int J Radiat Oncol Biol Phys2026July 10, 2026Journal Article
Center-specific Federated Learning for Radiation Pneumonitis:A Cross-Center Adaptive Alternating Framework.
Meng Yan1, Zhixiang Wang2, Liyu Ning3, Jie Xuan4, Zheng Zhang5, Hongshui Li6, Yaokai Wang7, Ming Li5, Gengmin Niu5, Inigo Bermejo8, Andre Dekker9, Dirk De Ruysscher9, Leonard Wee9, Lujun Zhao10, Zhen Zhang11
1Department of Radiation Oncology, Key Laboratory of Cancer Prevention and Therapy, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Tianjin, 300060, China; Department of Radiation Oncology (Maastro), GROW Research Institute for Oncology and Reproduction, Maastricht University Medical Centre+, Maastricht, The Netherlands.
2Department of Ultrasound, Beijing Friendship Hospital, Capital Medical University, Beijing 100050, China; Precision and Intelligence Medical Imaging Lab, Beijing Clinical Research Institute, Beijing Friendship Hospital, Capital Medical University, Beijing, 100050, China.
3Department of Radiation Oncology, Shanghai Chest Hospital, School of medicine, Shanghai Jiao Tong University, Shanghai,200030.
4Department of Radiation Oncology, Zhejiang Cancer Hospital; Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences; Zhejiang Key Laboratory of Particle Radiotherapy Equipment, Hangzhou, China.
5Department of Radiation Oncology, Key Laboratory of Cancer Prevention and Therapy, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Tianjin, 300060, China.
6Department of Radiation Oncology, The Second People Hospital of Dezhou, No.55 Fangzhistreet, Dezhou City, Shandong Province, 253000, China.
7Shenzhen University Medical School, Shenzhen University, 3688 Nanhai Avenue, Shenzhen, 518060, P. R. China.
8Data Science Institute (DSI), Hasselt University, Hasselt, Belgium.
9Department of Radiation Oncology (Maastro), GROW Research Institute for Oncology and Reproduction, Maastricht University Medical Centre+, Maastricht, The Netherlands.
10Department of Radiation Oncology, Key Laboratory of Cancer Prevention and Therapy, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Tianjin, 300060, China. Electronic address: zhaolujun@tjmuch.com.
11Department of Radiation Oncology, Zhejiang Cancer Hospital; Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences; Zhejiang Key Laboratory of Particle Radiotherapy Equipment, Hangzhou, China; Department of Radiation Oncology, Key Laboratory of Cancer Prevention and Therapy, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Tianjin, 300060, China; Department of Radiation Oncology (Maastro), GROW Research Institute for Oncology and Reproduction, Maastricht University Medical Centre+, Maastricht, The Netherlands. Electronic address: zhen.zhang@maastro.nl.
Abstract
BACKGROUND AND PURPOSE: Accurate prediction of symptomatic radiation pneumonitis (RP) is critical for radiotherapy, yet the generalization of deep learning models is hindered by restricted access to multi-center data. Although federated learning (FL) bypasses data-sharing restrictions, standard FL algorithms underperform on highly heterogeneous clinical data across institutions. Therefore, this st…
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