Pretreatment Prediction of Immunoscore in Hepatocellular Cancer: A Radiomics Nomogram Based on Gadolinium-Ethoxybenzyl-Diethylenetriamine Enhanced Magnetic Resonance Imaging

Abstract

Background: Pretreatment prediction of Immunoscore in patients with hepatocellular cancer (HCC) is important for precision immunotherapy. We aimed to develop a radiomics nomogram based on Gadolinium-ethoxybenzyl-diethylenetriamine (Gd-EOB-DTPA) enhanced magnetic resonance imaging (MRI) for pretreatment prediction of Immunoscore (0-2 vs. 3-4) in HCC patients. Methods: The 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. A radiomics nomogram was developed by incorporating selected radiomics features and clinical variables. Nomogram discrimination and calibration were assessed. Findings: The combined intratumoral and peritumoral radiomics model showed a better predicting performance in Immunoscore than intratumoral radiomics model (AUC, 0*904 (95% confidence interval [CI]: 0*855-0*953) vs. 0*823 (95% CI: 0*747-0*899), P=0*036). The radiomics nomogram showed an improvement over the combined radiomics model regarding predicting Immunoscore in the training cohort (AUC, 0*926 (95% CI: 0*884-0*967) vs. 0*904 (95% CI: 0*855-0*953)), although the differences were not statistically significant (P=0*128). Results were confirmed in the validation cohort and calibration curves showed good agreement. Interpretation: The radiomics nomogram incorporating clinical data and the combined radiomics features from Gd-EOB-DTPA enhanced MRI images is effective in predicting Immunoscore in HCC patients, and may assist clinicians to make pretreatment decisions for potential benefits of prognosis. Funding: This work is supported by grants from the Guangzhou Science and Technology Program key projects (No. 201803010057) and the National Natural Science Foundation of China (No. 81771908, 81571750). Declaration of Interest: We declare that we have no conflicts of interest. Ethical Approval: The Institutional Ethic Review Board has approved our study and the informed consent was waived.