Abstract
Background: Non-invasive imaging methods are still lacking for the evaluation of muscle changes in diabetes.
Purpose: To investigate the feasibility of muscle CT radiomics in evaluating muscle changes in diabetes.
Materials and Methods: 60 diabetics and 60 health controls (HC) were assessed with the method of muscle CT radiomics. 93 CT images of radiomics features of the pectoralis major muscle (PMM) were obtained by using the software 3D Slicer and were then compared between diabetics and HC cases. The least absolute shrinkage and selection operator (LASSO) regression method was used to establish a prediction model. The receiver operating characteristic (ROC) curve was used to determine the performance of the model.
Results: Diabetics and HC cases differed in 19 radiomics features (P<0.05). By using the LASSO method, 6 features were finally selected. The AUC of the model in the discrimination of diabetics and HC were 0.92 and 0.90, respectively, for the training cohort and validation cohort.
Conclusion: Muscle CT radiomics is feasible in evaluating muscle changes in diabetes.
Keywords: Muscle, CT, Radiomics, Diabetes, Regression, Skeletal muscle.
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