Longitudinal CE-MRI-based Siamese network with machine learning to predict tumor response in HCC after DEB-TACE

Longitudinal CE-MRI-based Siamese network with machine learning to predict tumor response in HCC after DEB-TACE

Abstract Background Accurate prediction of tumor response after drug-eluting beads transarterial chemoembolization (DEB-TACE) remains challenging in hepatocellular carcinoma (HCC), given tumor heterogeneity and dynamic changes over time. Existing prediction models based on single timepoint imaging d...

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Bibliographic Details
Main Authors: Nan Wei, René Michael Mathy, De-Hua Chang, Philipp Mayer, Jakob Liermann, Christoph Springfeld, Michael T Dill, Thomas Longerich, Georg Lurje, Hans-Ulrich Kauczor, Mark O. Wielpütz, Osman Öcal
Format: Article
Language:English
Published: BMC 2025-08-01
Series:Cancer Imaging
Subjects:
Deep learning
Machine learning
Siamese network
HCC
Tumor response
Online Access:https://doi.org/10.1186/s40644-025-00926-5
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https://doi.org/10.1186/s40644-025-00926-5

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