Apparent Diffusion Coefficient Histogram Analysis of Adenoid Cystic Carcinoma of the Head and Neck: Correlation with Histological Grade and Exploratory Survival Analysis

Background: In this study, we aimed to evaluate the feasibility of a whole-tumor histogram analysis of apparent diffusion coefficient (ADC) values derived from diffusion-weighted imaging (DWI) for predicting adenoid cystic carcinoma (ACC) histological grade and solid-component status. Methods: This retrospective study included 168 patients with primary head and neck ACC who underwent preoperative 3.0 T MRI with DWI, randomly allocated with stratification by grade to a derivation cohort (n = 107) and an internal validation cohort (n = 61). Whole-tumor ADC histogram features were extracted and reduced through correlation analysis, and the two most discriminative features were combined in a logistic regression model. Overall survival was explored using Cox regression. Results: ADC10 alone (the 10th percentile of ADC) had areas under the receiver operating characteristic curve (AUCs) of 0.821 (95% confidence interval [CI] 0.727–0.899) and 0.780 (95% CI 0.643–0.895) for grade III in the derivation and validation cohorts, and 0.743 and 0.709 for solid-component status; adding the low-ADC volume did not improve discrimination (DeLong p ≥ 0.468). The model output was associated with overall survival in the pooled cohort (hazard ratio per standard deviation, 1.627) but not in the validation cohort or after adjustment for grade. Conclusions: ADC10 showed promising discrimination of grade III ACC in internal validation, with no gain from adding the low-ADC volume; the prognostic value is unconfirmed, and multicenter external validation is warranted.