Radiomics Model Based on Gd-DTPA-enhanced Multiparametric MRI Supports Noninvasive Pretreatment Prediction of Immunoscore in Hepatocellular Carcinoma.
TL;DR
A radiomics model integrating intra- and peritumoral MRI features enables noninvasive preoperative immunoscore prediction in HCC, which may provide preliminary support for individualized immunotherapy decision-making, although external validation is warranted.
Abstract
INTRODUCTION This study assessed whether Gd-DTPA-enhanced MRI could predict the immunoscore in HCC noninvasively before therapy, without the need for tissue sampling.
Methods
Retrospectively, surgically treated HCC patients who had a preoperative Gd-DTPA-enhanced MRI exam were enrolled. Eligible patients were randomly allocated to a training set and a validation set following a 3:1 randomization scheme. Immunohistochemistry was performed to quantify CD3-positive and CD8-positive cell densities; patients were stratified into high and low immunoscore groups using the median cutoff. Volumes of interest encompassing hepatic lesions, including intratumoral and peritumoral 10-mm margins, were manually delineated on multiparametric MRI sequences for radiomics feature extraction. Clinical and pathological data were retrieved from electronic medical records. A Support Vector Machine (SVM) was used to develop three predictive models: (1) Intratumoral Radiomics Model (IRM), (2) combined intra- and peritumoral radiomics model (CRM), and (3) Clinical Combined Radiomics Model (CCRM). Model performance was compared using the DeLong test and evaluated via the area under the receiver operating characteristic curve (AUC), calibration curves, and Decision Curve Analysis (DCA).
Results
Of 111 eligible patients, 83 were assigned to the training cohort and 28 to the validation cohort. Baseline characteristics were balanced between cohorts. The CCRM demonstrated the highest AUC values in both cohorts (training: 0.947; validation: 0.913). Compared with IRM, CCRM showed significantly better performance in the validation cohort (p = 0.016) but not in the training cohort (p = 0.084). In the validation cohort, CCRM did not significantly outperform CRM (p = 0.55), whereas a significant difference was observed in the training cohort (p = 0.036). Calibration curves demonstrated good agreement. DCA indicated that the CCRM and the CRM achieved similar overall net benefits, which were higher than those of the IRM across threshold probabilities of 46% to 98%.
Discussion
This radiomics approach suggests the feasibility of using routine Gd-DTPA-enhanced MRI for preoperative immunoscore prediction in HCC, providing preliminary evidence for tumor immune characterization.
Conclusion
A radiomics model integrating intra- and peritumoral MRI features enables noninvasive preoperative immunoscore prediction in HCC, which may provide preliminary support for individualized immunotherapy decision-making, although external validation is warranted.