Utility of apparent diffusion coefficient histogram analysis in differentiating benign and malignant palate lesions

Abstract

ObjectivesTo explore the ability of conventional MRI and histogram analysis of apparent diffusion coefficient (ADC) for differentiating between malignant and benign palatal lesions. Materials and MethodsA retrospective analysis was performed on MRI images of 86 patients with palatal lesions confirmed by histopathology between January 2015 and December 2018. Each lesion was evaluated based on the conventional MRI characteristics, including size, location, morphology, inner texture, enhancement, capsule, bone destruction, and nerve invasion. ADC histogram analysis was fitted to a bimodal Gaussian distribution mixture curve. Nine histogram analysis parameters were extracted from ADC maps and were compared between malignant and benign palatal lesions. Statistical analysis was performed to assess the differential performance of each parameter individually and combined. ResultsOn conventional MRI, the capsule structure and nerve invasion were useful characteristics for the differential diagnosis of palatal lesions. Histogram analysis showed significant differences between the groups in terms of mean ADC values of the lower curve and overall curve of the bimodal histogram, as well as ADC10 and ADC50. The optimal diagnostic threshold of ADC value was ADC50 = 1.17 × 10−3 mm2/s (area under curve [AUC] = 0.934, sensitivity = 93.0 %, specificity = 86.2 %). The combination of conventional MRI and ADC values yielded the best predictive performance, with an AUC of 0.949, and an increase in sensitivity from 80.7 % to 96.5 % and specificity from 58.6 % to 82.8 %, compared to conventional MRI. ConclusionsHistogram analysis of DWI combined with conventional MRI allows accurate differentiation between benign and malignant palatal lesions.