Journal Article

Pretreatment prediction of immunoscore in hepatocellular cancer: a radiomics-based clinical model based on Gd-EOB-DTPA-enhanced MRI imaging

Peng, Sui, Kuang, Ming, Han, Xiao, Feng, Shiting, Gu, Dongsheng, Jia, Yingmei, Tian, Jie, Wei, Jingwei, Li, Xin, Liu, Fei, Li, Bin, Tang, Mimi, Chen, Shuling, Hou, Yang

2019

Overview

ObjectivesImmunoscore evaluates the density of CD3+ and CD8+ T cells in both the tumor core and invasive margin. Pretreatment prediction of immunoscore in hepatocellular cancer (HCC) is important for precision immunotherapy. We aimed to develop a radiomics model based on gadolinium-ethoxybenzyl-diethylenetriamine (Gd-EOB-DTPA)-enhanced MRI for pretreatment prediction of immunoscore (0–2 vs. 3–4) in HCC.Materials and methodsThe study included 207 (training cohort: n = 150; validation cohort: n = 57) HCC patients with hepatectomy who underwent preoperative Gd-EOB-DTPA-enhanced MRI. The volumes of interest enclosing hepatic lesions including intratumoral and peritumoral regions were manually delineated in the hepatobiliary phase of MRI images, from which 1044 quantitative features were extracted and analyzed. Extremely randomized tree method was used to select radiomics features for building radiomics model. Predicting performance in immunoscore was compared among three models: (1) using only intratumoral radiomics features (intratumoral radiomics model); (2) using combined intratumoral and peritumoral radiomics features (combined radiomics model); (3) using clinical data and selected combined radiomics features (combined radiomics-based clinical model).ResultsThe combined radiomics model showed a better predicting performance in immunoscore than intratumoral radiomics model (AUC, 0.904 (95% CI 0.855–0.953) vs. 0.823 (95% CI 0.747–0.899)). The combined radiomics-based clinical model showed an improvement over the combined radiomics model in predicting immunoscore (AUC, 0·926 (95% CI 0·884–0·967) vs. 0·904 (95% CI 0·855–0·953)), although differences were not statistically significant. Results were confirmed in validation cohort and calibration curves showed good agreement.ConclusionThe MRI-based combined radiomics nomogram is effective in predicting immunoscore in HCC and may help making treatment decisions.Key Points• Radiomics obtained from Gd-EOB-DTPA-enhanced MRI help predicting immunoscore in hepatocellular carcinoma.• Combined intratumoral and peritumoral radiomics are superior to intratumoral radiomics only in predicting immunoscore.• We developed a combined clinical and radiomicsnomogram to predict immunoscore in hepatocellular carcinoma.

• Publisher: Springer Nature B.V
• Subject: Calibration / Cancer / CD3 antigen / CD8 antigen / Decision trees / Feature extraction / Gadolinium / Hepatectomy / Hepatocellular carcinoma / Immunotherapy / Invasiveness / Lesions / Liver cancer / Lymphocytes / Lymphocytes T / Magnetic resonance imaging / Mathematical models / Nomograms / Performance prediction / Radiomics / Statistical analysis