Preoperative Radiomics Approach to Evaluating Tumor‐Infiltrating CD8+ T Cells in Patients With Pancreatic Ductal Adenocarcinoma Using Noncontrast Magnetic Resonance Imaging

Background CD8 + T cell in pancreatic ductal adenocarcinoma (PDAC) is closely related to the prognosis and treatment response of patients. Accurate preoperative CD8 + T‐cell expression can better identify the population benefitting from immunotherapy. Purpose To develop and validate a machine learning classifier based on noncontrast magnetic resonance imaging (MRI) for the preoperative prediction of CD8 + T‐cell expression in patients with PDAC. Study Type Retrospective cohort study. Population Overall, 114 patients with PDAC undergoing MR scan and surgical resection; 97 and 47 patients in the training and validation cohorts. Field Strength/Sequence/3 T Breath‐hold single‐shot fast‐spin echo T2‐weighted sequence and noncontrast T1‐weighted fat‐suppressed sequences. Assessment CD8 + T‐cell expression was quantified using immunohistochemistry. For each patient, 2232 radiomics features were extracted from noncontrast T1‐ and T2‐weighted images and reduced using the Wilcoxon rank‐sum test and least absolute shrinkage and selection operator method. Linear discriminative analysis was used to construct radiomics and mixed models. Model performance was determined by its discriminative ability, calibration, and clinical utility. Statistical Tests Kaplan–Meier estimates, Student's t‐test, the Kruskal–Wallis H test, and the chi‐square test, receiver operating characteristic curve, and decision curve analysis. Results A log‐rank test showed that the survival duration in the CD8‐high group (25.51 months) was significantly longer than that in the CD8‐low group (22.92 months). The mixed model included all MRI characteristics and 13 selected radiomics features, and the area under the curve (AUC) was 0.89 (95% confidence interval [CI], 0.77–0.92) and 0.69 (95% CI, 0.53–0.82) in the training and validation cohorts. The radiomics model included 13 radiomics features, which showed good discrimination in the training cohort (AUC, 0.85; 95% CI, 0.77–0.92) and the validation cohort (AUC, 0.76; 95% CI, 0.61–0.87). Data Conclusions This study developed a noncontrast MRI‐based radiomics model that can preoperatively determine CD8 + T‐cell expression in patients with PDAC and potentially immunotherapy planning. Evidence Level 5 Technical Efficacy Stage 2