Prediction of different stages of rectal cancer: Texture analysis based on diffusion-weighted images and apparent diffusion coefficient maps
Jiandong Yin, Lirong Song, Hecheng Lu, Zheng Xu
Abstract
BACKGROUND: N1-2) in rectal cancer. AIM: To predict different stages of rectal cancer using texture analysis based on DWI images and ADC maps. METHODS: tests were used for statistical analysis. Multivariate logistic regression analysis was conducted to establish the models. The predictive performance was validated by receiver operating characteristic curve analysis. . RESULTS: and information correlation from ADC maps were identified as independent predictors of nodal involvement. The area under the operating characteristic curve of the model reached 0.802 with a sensitivity of 80.77% and a specificity of 68.25%. CONCLUSION: Texture features extracted from DWI images and ADC maps are useful clues for predicting pathological T and N stages in rectal cancer.