3d quantitative analysis of diffusion-weighted imaging for predicting the malignant potential of intraductal papillary mucinous neoplasms of the pancreas

Purpose: To investigate the predictors of intraductal papillary mucinous neoplasms of the pancreas (IPMNs) with high-grade dysplasia, using 2-dimensional (2D) analysis and 3-dimensional (3D) volume-of-interest-based apparent diffusion coefficient (ADC) histogram analysis. Material and methods: The data of 45 patients with histopathologically confirmed IPMNs with high-grade or low-grade dysplasia were retrospectively assessed. The 2D analysis included lesion-to-spinal cord signal intensity ratio (LSR), minimum ADC value (ADC), and mean ADC value (ADC). The 3D analysis included the overall mean (ADC), mean of the bottom 10 percentile (ADC), mean of the bottom 10-25 percentile (ADC), mean of the bottom 25-50 percentile (ADC), skewness (ADC), kurtosis (ADC), and entropy (ADC). Diagnostic performance was compared by analysing the area under the receiver operating characteristic curve (AUC). Inter-rater reliability was assessed by blinded evaluation using the intraclass correlation coefficient. Results: There were 16 and 29 IPMNs with high-and low-grade dysplasia, respectively. The LSR, ADC, ADC, ADC, ADC, and ADC showed significant between-group differences (AUC = 72-93%; p < 0.05). Inter-rater reliability assessment showed almost perfect agreement for LSR and substantial agreement for ADC and ADC . Multivariate logistic regression showed that ADCoverall mean and ADCentropy were significant independent predictors of malignancy (p < 0.05), with diagnostic accuracies of 80% and 73%, respectively. Conclusion: ADC and ADC from 3D analysis may assist in predicting IPMNs with high-grade dysplasia.