Texture analysis of diffusion kurtosis imaging for differentiating malignant from benign sinonasal lesions: added value to conventional imaging features

Abstract

Objectives: To evaluate the performance of texture analysis (TA) of diffusion kurtosis imaging (DKI) in differentiating malignant from benign sinonasal lesions, and its added value to the conventional imaging features. Methods: Fifty-eight patients with malignant and 40 patients with benign sinonasal lesions were retrospectively enrolled. Conventional CT and MRI features were reviewed. Texture parameters were obtained and compared between two groups. Multivariate logistic regression analysis was used to identify the most valuable variables. Receiver operating characteristic curves were performed to assess the differentiating performance of independent variables and their combination. Results: There were significant differences in tumor necrosis, bone erosion and soft tissue invasion between the two groups (all p < 0.05). There were significant differences in the 10th and entropy of Apparent diffusion coefficient map, the mean, 10th and entropy of D map, the mean and 90th of K map between the two groups (all p < 0.002). The bone erosion, entropy of D, and mean of K were independent variables associated with malignant tumors. Receiver operating characteristic analyses indicated that the combination of three features possessed better differentiating performance than bone erosion alone (p = 0.003). Conclusion: TA of DKI could supply incremental value to conventional imaging features for pre-operative differential diagnosis between benign and malignant sinonasal lesions. Advances in knowledge: The present study is the first to combine conventional imaging features and the TA of DKI in the differential diagnosis between benign and malignant sinonasal lesions. Our findings suggest that TA of DKI could supply incremental value to conventional imaging features.