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MRI radiomics features predict immuno-oncological characteristics of hepatocellular carcinoma



To assess the value of qualitative and quantitative MRI radiomics features for noninvasive prediction of immuno-oncologic characteristics and outcomes of hepatocellular carcinoma (HCC).


This retrospective, IRB-approved study included 48 patients with HCC (M/F 35/13, mean age 60y) who underwent hepatic resection or transplant within 4 months of abdominal MRI. Qualitative imaging traits, quantitative nontexture related and texture features were assessed in index lesions on contrast-enhanced T1-weighted and diffusion-weighted images. The association of imaging features with immunoprofiling and genomics features was assessed using binary logistic regression and correlation analyses. Binary logistic regression analysis was also employed to analyse the association of radiomics, histopathologic and genomics features with radiological early recurrence of HCC at 12 months.


Qualitative (r = − 0.41–0.40, p < 0.042) and quantitative (r = − 0.52–0.45, p < 0.049) radiomics features correlated with immunohistochemical cell type markers for T-cells (CD3), macrophages (CD68) and endothelial cells (CD31). Radiomics features also correlated with expression of immunotherapy targets PD-L1 at protein level (r = 0.41–0.47, p < 0.029) as well as PD1 and CTLA4 at mRNA expression level (r = − 0.48–0.47, p < 0.037). Finally, radiomics features, including tumour size, showed significant diagnostic performance for assessment of early HCC recurrence (AUC 0.76–0.80, p < 0.043), while immunoprofiling and genomic features did not (p = 0.098–0929).


MRI radiomics features may serve as noninvasive predictors of HCC immuno-oncological characteristics and tumour recurrence and may aid in treatment stratification of HCC patients. These results need prospective validation.

Key Points

• MRI radiomics features showed significant associations with immunophenotyping and genomics characteristics of hepatocellular carcinoma.

• Radiomics features, including tumour size, showed significant associations with early hepatocellular carcinoma recurrence after resection.

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Apparent diffusion coefficient


Area under the curve


Contrast-enhanced MRI


Computed tomography


Diffusion-weighted imaging


False discovery rate


Hepatocellular carcinoma


Multiplexed immunohistochemical consecutive staining on single slide


Magnetic resonance imaging


Odds ratio


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This study has received funding from the Research Seed Grant no. RSD1608 from the Radiological Society of North America, and grant U01 CA172320 from the National Cancer Institute and the International Liver Cancer Association.

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Correspondence to Bachir Taouli.

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The scientific guarantor of this publication is Bachir Taouli.

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The authors of this manuscript declare no relationships with any companies, whose products or services may be related to the subject matter of the article.

Statistics and biometry

No complex statistical methods were necessary for this paper.

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Written informed consent was waived by the Institutional Review Board.

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Institutional Review Board approval was obtained.


• retrospective

• observational

• performed at one institution

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Hectors, S.J., Lewis, S., Besa, C. et al. MRI radiomics features predict immuno-oncological characteristics of hepatocellular carcinoma. Eur Radiol 30, 3759–3769 (2020).

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  • Hepatocellular carcinoma
  • Magnetic resonance imaging
  • Correlation of data
  • Genomics
  • Immunophenotyping