Cyst-X: AI-Powered Pancreatic Cancer Risk Prediction from Multicenter MRI in Centralized and Federated Learning

• URL: http://arxiv.org/abs/2507.22017v1
• Date: Tue, 29 Jul 2025 17:06:22 GMT
• Title: Cyst-X: AI-Powered Pancreatic Cancer Risk Prediction from Multicenter MRI in Centralized and Federated Learning
• Authors: Hongyi Pan, Gorkem Durak, Elif Keles, Deniz Seyithanoglu, Zheyuan Zhang, Alpay Medetalibeyoglu, Halil Ertugrul Aktas, Andrea Mia Bejar, Ziliang Hong, Yavuz Taktak, Gulbiz Dagoglu Kartal, Mehmet Sukru Erturk, Timurhan Cebeci, Maria Jaramillo Gonzalez, Yury Velichko, Lili Zhao, Emil Agarunov, Federica Proietto Salanitri, Concetto Spampinato, Pallavi Tiwari, Ziyue Xu, Sachin Jambawalikar, Ivo G. Schoots, Marco J. Bruno, Chenchang Huang, Candice Bolan, Tamas Gonda, Frank H. Miller, Rajesh N. Keswani, Michael B. Wallace, Ulas Bagci,
• Abstract summary: Pancreatic cancer is projected to become the second-deadliest malignancy in Western countries by 2030.<n>Cystic-X is an AI framework that predicts IPMN malignancy using multicenter MRI data.
• Score: 6.438326994525642
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Pancreatic cancer is projected to become the second-deadliest malignancy in Western countries by 2030, highlighting the urgent need for better early detection. Intraductal papillary mucinous neoplasms (IPMNs), key precursors to pancreatic cancer, are challenging to assess with current guidelines, often leading to unnecessary surgeries or missed malignancies. We present Cyst-X, an AI framework that predicts IPMN malignancy using multicenter MRI data, leveraging MRI's superior soft tissue contrast over CT. Trained on 723 T1- and 738 T2-weighted scans from 764 patients across seven institutions, our models (AUC=0.82) significantly outperform both Kyoto guidelines (AUC=0.75) and expert radiologists. The AI-derived imaging features align with known clinical markers and offer biologically meaningful insights. We also demonstrate strong performance in a federated learning setting, enabling collaborative training without sharing patient data. To promote privacy-preserving AI development and improve IPMN risk stratification, the Cyst-X dataset is released as the first large-scale, multi-center pancreatic cysts MRI dataset.

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