In the present study, we investigated a multiple diffusion-model-based radiomics model in grading of bowel fibrosis of Crohn's disease (CD) patients. We used histogram features derived from parameters of DWI, IVIM and DKI models and chose SVM as the classifier to construct a prediction model. The results showed that the most accurate prediction was achieved by incorporating the following 6 features into a nomogram, including the DKI-related histogram parameters (mean D, mean K, 10th percentiles of K) and IVIM-related parameters (mean D0-2000, mean D*0-2000, 90th percentiles of f), with AUC and accuracy reached 0.835 and 0.833, respectively.
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