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Advances in the imaging of liver cancer.

Created on 16 Sep 2026

Authors

Ijin Joo, Jeong Min Lee, Maxime Ronot

Published in

Journal of hepatology. Volume 85. Issue 4. Pages 695-711. Epub Jul 02, 2026.

Abstract

Liver cancer remains a major global health burden, with hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (iCCA) accounting for the vast majority of primary liver malignancies. As most patients are diagnosed at advanced stages, imaging plays a central role across the entire care continuum - from surveillance and early detection to diagnosis, staging, prognostic stratification, and treatment response assessment. Recent advances in imaging technology, diagnostic frameworks, and computational analysis have substantially expanded the clinical value of liver imaging. This review summarises key developments in liver cancer imaging, beginning with technical innovations in ultrasound, multiphasic and spectral CT, MRI with hepatobiliary contrast agents, abbreviated MRI protocols, and evolving PET tracers such as FAPI. We then examine the convergence and remaining differences among major diagnostic guideline systems for HCC, including LI-RADS, EASL, AASLD, KLCA-NCC, and APASL, with emphasis on vascular hallmarks, hepatobiliary phase interpretation, and Kupffer-phase contrast-enhanced ultrasound criteria. We also discuss the concept of the HCC-iCCA biological continuum, and how imaging features can reflect this phenotypic spectrum. A major focus is the emerging concept of imaging-based prognostication of HCC, which captures biologically meaningful phenotypes such as proliferative class, macrotrabecular-massive subtype, microvascular invasion likelihood, immune microenvironment signatures, and VETC phenotype. We discuss how these imaging features reflect underlying molecular programmes and may inform treatment allocation beyond tumour size and number. In iCCA, advances in quantitative imaging and contrast-enhanced ultrasound perfusion enable differentiation of small-duct vs. large-duct subtypes and prediction of stromal-rich aggressive variants. Treatment response assessment criteria are reviewed, addressing challenges in evaluating locoregional therapies and immunotherapy. Finally, we examine the emerging roles of radiomics and artificial intelligence, focusing on current validation challenges. Together, these advances demonstrate the evolution of liver cancer imaging from a detection tool to a comprehensive platform for biological characterisation and personalised treatment guidance.

PMID:
42744522
Bibliographic data and abstract were imported from PubMed on 16 Sep 2026.

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