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Radiomics of hepatocellular carcinoma

  • Special Section: Liver Transplantation
  • Published:
Abdominal Radiology Aims and scope Submit manuscript

Abstract

The diagnosis of hepatocellular carcinoma relies largely on non-invasive imaging, and is well suited for radiomics analysis. Radiomics is an emerging method for quantification of tumor heterogeneity by mathematically analyzing the spatial distribution and relationships of gray levels in medical images. The published studies on radiomics analysis of HCC provide encouraging data demonstrating potential utility for prediction of tumor biology, molecular profiles, post-therapy response, and outcome. The combination of radiomics data and clinical/laboratory information provides added value in many studies. Radiomics is a multi-step process that requires optimization and standardization, the development of semi-automated or automated segmentation methods, robust data quality control, and refinement of algorithms and modeling approaches for high-throughput data analysis. While radiomics remains largely in the research setting, the strong associations of predictive models and nomograms with certain pathologic, molecular, and immune markers with tumor aggressiveness and patient outcomes, provide great potential for clinical applications to inform optimized treatment strategies and patient prognosis.

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Adapted from Hectors et al. [69]

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  1. Stefanie Hectors

    Present address: Department of Radiology, Weill Cornell Medical College, 1300 York Ave, New York, NY, 10065, USA

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  1. BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA

    Sara Lewis, Stefanie Hectors & Bachir Taouli

  2. Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, 1 Gustave L. Levy Place, 1470 Madison Ave, Box 1234, New York, NY, 10029, USA

    Sara Lewis, Stefanie Hectors & Bachir Taouli

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Lewis, S., Hectors, S. & Taouli, B. Radiomics of hepatocellular carcinoma. Abdom Radiol 46, 111–123 (2021). https://doi.org/10.1007/s00261-019-02378-5

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