Stefanie J Hectors1,2,3, Sara Lewis1,2, Cecilia Besa1,4, Michael J King1,2, Daniela Said1,2,5, Juan Putra6, Stephen Ward6, Takaaki Higashi7, Swan Thung6, Shen Yao8, Ilaria Laface8, Myron Schwartz9, Sacha Gnjatic10, Miriam Merad11, Yujin Hoshida7, Bachir Taouli12,13. 1. Biomedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY, 10029, USA. 2. Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY, 10029, USA. 3. Department of Radiology, Weill Cornell Medicine, 515 E 71st Street, New York, NY, 10021, USA. 4. Department of Radiology, School of Medicine, Pontificia Universidad Católica de Chile, Avenida Libertador Bernardo O'Higgins 340, 8331150, Santiago, Chile. 5. Department of Radiology, Universidad de los Andes, Avenida Plaza 2501, 7620157, Las Condes, Chile. 6. Department of Pathology, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY, 10029, USA. 7. Liver Tumor Translational Research Program, Harold C. Simmons Comprehensive Cancer Center, Division of Digestive and Liver Diseases, Department of Internal Medicine, University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX, 75390, USA. 8. Division of Hematology and Oncology, Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY, 10029, USA. 9. Recanati/Miller Transplantation Institute, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY, 10029, USA. 10. Department of Oncological Sciences, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY, 10029, USA. 11. Precision Immunology Institute, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY, 10029, USA. 12. Biomedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY, 10029, USA. bachir.taouli@mountsinai.org. 13. Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY, 10029, USA. bachir.taouli@mountsinai.org.
Abstract
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.
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 HCCpatients. 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.
Entities:
Keywords:
Correlation of data; Genomics; Hepatocellular carcinoma; Immunophenotyping; Magnetic resonance imaging
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