Peer-Reviewed Publication
JHEP Rep2026;8(7):101813.March 4, 2026Journal Article
Deep learning-based generation of synthetic multiphasic MRI in hepatocellular carcinoma and cirrhosis.
Sara A Abosabie1, Salma A S Abosabie2, Weicheng Dai3, Junlin Yang3, Moritz Gross1, Jeffrey Weinreb3, Margarita V Revzin3, Gaurav Parmar3, Chenyu You4, MingDe Lin5, Olivia Gaddum1, Bernhard Gebauer6, Lynn Jeanette Savic7, David C Madoff8, James S Duncan9, Julius Chapiro10
1Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT 06520, USA; Department of Radiology, Charité-Universitätsmedizin Berlin, Campus Virchow Klinikum, 13353 Berlin, Germany.
2Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT 06520, USA; Department of Radiology, Charité-Universitätsmedizin Berlin, Campus Virchow Klinikum, 13353 Berlin, Germany; Institute of Experimental Biomedicine, University Hospital Wuerzburg, 97080 Wuerzburg, Germany; Rudolf Virchow Center for Integrative and Translational Bioimaging, Julius Maximilians University of Wuerzburg, 97080 Wuerzburg, Germany.
3Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT 06520, USA.
4Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT 06520, USA; Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, NY 11794, USA.
5Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT 06520, USA; Visage Imaging, Inc., San Diego, CA 91230, USA.
6Department of Radiology, Charité-Universitätsmedizin Berlin, Campus Virchow Klinikum, 13353 Berlin, Germany.
7Department of Radiology, Charité-Universitätsmedizin Berlin, Campus Virchow Klinikum, 13353 Berlin, Germany; Berlin Institute of Health at Charité-Universitätsmedizin Berlin, 10115 Berlin, Germany; Experimental Clinical Research Center (ECRC) at Charité-Universitätsmedizin Berlin and Max-Delbrück-Centrum für Molekulare Medizin (MDC), 13125 Berlin, Germany.
8Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT 06520, USA; Department of Medicine, Section of Medical Oncology, Yale University School of Medicine, New Haven, CT 06520, USA; Department of Surgery, Section of Surgical Oncology, Yale University School of Medicine, New Haven, CT 06520, USA.
9Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT 06520, USA; Department of Medicine, Liver Center, Section of Digestive Diseases, Yale University School of Medicine, New Haven, CT 06520, USA; Department of Biomedical Engineering, School of Engineering and Applied Sciences, New Haven, CT 06520, USA.
10Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT 06520, USA; Department of Medicine, Liver Center, Section of Digestive Diseases, Yale University School of Medicine, New Haven, CT 06520, USA; Department of Biomedical Engineering, School of Engineering and Applied Sciences, New Haven, CT 06520, USA. Electronic address: julius.chapiro@yale.edu.
Abstract
BACKGROUND & AIMS: There is growing interest in reducing contrast medium use and the lengthy scan duration in liver imaging. This proof of concept study evaluated the feasibility of deep learning-based generation of synthetic 3D liver contrast-enhanced multiphasic magnetic resonance imaging (MRI) exams, which are similar to ground-truth exams in hepatocellular carcinoma and cirrhosis.
METHODS: MR…
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