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Artificial intelligence in liver cancer — new tools for research and patient management

Nature Reviews Gastroenterology & Hepatology (2024)Cite this article

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Abstract

Liver cancer has high incidence and mortality globally. Artificial intelligence (AI) has advanced rapidly, influencing cancer care. AI systems are already approved for clinical use in some tumour types (for example, colorectal cancer screening). Crucially, research demonstrates that AI can analyse histopathology, radiology and natural language in liver cancer, and can replace manual tasks and access hidden information in routinely available clinical data. However, for liver cancer, few of these applications have translated into large-scale clinical trials or clinically approved products. Here, we advocate for the incorporation of AI in all stages of liver cancer management. We present a taxonomy of AI approaches in liver cancer, highlighting areas with academic and commercial potential, and outline a policy for AI-based liver cancer management, including interdisciplinary training of researchers, clinicians and patients. The potential of AI in liver cancer is immense, but effort is required to ensure that AI can fulfil expectations.

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Fig. 1: Overview of primary liver cancer, clinical challenges during disease progression and where AI can integrate into management.
Fig. 2: Overview of different imaging modalities and subsequent steps for diagnosing primary liver cancer.
Fig. 3: Components of AI pipeline in liver cancer.
Fig. 4: Potential health-care benefits from AI integration in liver cancer management.
Fig. 5: Strategies to improve AI utilization in research and clinical workflows.

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Acknowledgements

J.N.K. discloses support for the research of this work from the German Federal Ministry of Health (DEEP LIVER, ZMVI1-2520DAT111), the German Federal Ministry of Education and Research (TRANSFORM LIVER, 031L0312A) and the European Union’s Horizon Europe and innovation programme (GENIAL, 101096312). D.T. discloses support for the research of this work from the German Federal Ministry of Education and Research (TRANSFORM LIVER, 031L0312A).

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Authors and Affiliations

  1. Département de Pathologie, Assistance Publique Hôpitaux de Paris, Groupe Hospitalier Henri Mondor, Créteil, France

    Julien Calderaro

  2. Institut Mondor de Recherche Biomédicale, MINT-HEP Mondor Integrative Hepatology, Université Paris Est Créteil, Créteil, France

    Julien Calderaro

  3. Else Kroener Fresenius Center for Digital Health (EKFZ), Medical Faculty Carl Gustav Carus, TUD Dresden University of Technology, Dresden, Germany

    Laura Žigutytė & Jakob Nikolas Kather

  4. Department of Diagnostic and Interventional Radiology, University Hospital RWTH Aachen, Aachen, Germany

    Daniel Truhn

  5. Mayo Clinic, Rochester, MN, USA

    Ariel Jaffe

  6. Department of Internal Medicine, Section of Digestive Diseases, Yale School of Medicine, New Haven, CT, USA

    Ariel Jaffe

  7. Department of Medicine I, University Hospital Dresden, Dresden, Germany

    Jakob Nikolas Kather

  8. Medical Oncology, National Center for Tumour Diseases (NCT), University Hospital Heidelberg, Heidelberg, Germany

    Jakob Nikolas Kather

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  1. Julien Calderaro
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  4. Ariel Jaffe
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Contributions

All authors contributed equally to all aspects of the article. L.Ž. and J.N.K. designed the figures.

Corresponding author

Correspondence to Jakob Nikolas Kather.

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Competing interests

J.N.K. declares consulting services for Owkin (France), DoMore Diagnostics (Norway), Panakeia (UK), Scailyte (Switzerland), Mindpeak (Germany) and MultiplexDx (Slovakia); furthermore, he holds shares in StratifAI GmbH (Germany), has received a research grant from GSK and has received honoraria by AstraZeneca, Bayer, Eisai, Janssen, MSD, BMS, Roche, Pfizer and Fresenius. D.T. holds shares in StratifAI GmbH (Germany). The other authors declare no competing interests.

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Nature Reviews Gastroenterology & Hepatology thanks Lorenza Rimassa, who co-reviewed with Valentina Zanuso; Pekka Ruusuvuori; and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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The Cancer Genome Atlas: https://www.cancer.gov/ccg/research/genome-sequencing/tcga

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Calderaro, J., Žigutytė, L., Truhn, D. et al. Artificial intelligence in liver cancer — new tools for research and patient management. Nat Rev Gastroenterol Hepatol (2024). https://doi.org/10.1038/s41575-024-00919-y

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