PurposeTo explore the potential of texture analysis based on apparent diffusion coefficient (ADC) maps, as a predictor of local invasion depth (stage pT1-2 versus pT3-4) and nodal status (pN0 versus pN1-2) of rectal cancer. Materials and MethodsSixty-eight patients with rectal cancer underwent preoperative magnetic resonance (MR) imaging including diffusion weighted imaging (DWI) at a 3.0 Tesla system. Routine ADC variables (ADC(mean), ADC(min), ADC(max)), histogram features (skewness, kurtosis) and gray level co-occurrence matrix features (entropy, contrast, correlation) were compared between pT1-2 and pT3-4 stages, between pN0 and pN1-2 stages. ResultsSkewness, entropy, and contrast were significantly lower in patients with pT1-2 as compared to those with pT3-4 tumors (0.166 versus 0.476, P=0.015; 3.212 versus 3.441 P=0.004; 10.773 versus 13.596, P=0.017). Furthermore, skewness and entropy were identified as independent predictors for extramural invasion of tumors (stage pT3-4). Significant differences were observed between pN0 and pN1-2 tumors with respect to ADC(mean) (1.152 versus 1.044, P=0.029), ADC(max) (1.692 versus 1.460, P=0.006) and entropy (3.299 versus 3.486, P=0.015). ADC(max.) and entropy were independent predictors of positive nodal status. ConclusionTexture analysis on ADC maps could provide valuable information in identifying locally advanced rectal cancer.