TY - JOUR
T1 - MRI radiomics features predict immuno-oncological characteristics of hepatocellular carcinoma
AU - Hectors, Stefanie J.
AU - Lewis, Sara
AU - Besa, Cecilia
AU - King, Michael J.
AU - Said, Daniela
AU - Putra, Juan
AU - Ward, Stephen
AU - Higashi, Takaaki
AU - Thung, Swan
AU - Yao, Shen
AU - Laface, Ilaria
AU - Schwartz, Myron
AU - Gnjatic, Sacha
AU - Merad, Miriam
AU - Hoshida, Yujin
AU - Taouli, Bachir
N1 - Funding Information:
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.
Publisher Copyright:
© 2020, European Society of Radiology.
PY - 2020/7/1
Y1 - 2020/7/1
N2 - Objective: To assess the value of qualitative and quantitative MRI radiomics features for noninvasive prediction of immuno-oncologic characteristics and outcomes of hepatocellular carcinoma (HCC). Methods: 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. Results: 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). Conclusions: 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.
AB - Objective: To assess the value of qualitative and quantitative MRI radiomics features for noninvasive prediction of immuno-oncologic characteristics and outcomes of hepatocellular carcinoma (HCC). Methods: 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. Results: 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). Conclusions: 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.
KW - Correlation of data
KW - Genomics
KW - Hepatocellular carcinoma
KW - Immunophenotyping
KW - Magnetic resonance imaging
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U2 - 10.1007/s00330-020-06675-2
DO - 10.1007/s00330-020-06675-2
M3 - Article
C2 - 32086577
AN - SCOPUS:85080908810
SN - 0938-7994
VL - 30
SP - 3759
EP - 3769
JO - European Radiology
JF - European Radiology
IS - 7
ER -