To predictthe canceration of rectal adenoma based on multi-parameter MRI imaging omics model.

A total of 46 patients with rectal adenoma (n=25) and cancerous rectal adenoma (n=21) confirmed by pathology from November 2016 to December 2018 in Shandong Provincial Qianfoshan Hospital were retrospectively analyzed. All patients underwent pelvic MRI examination 2 weeks before surgery, including high-resolution T2WI and diffusion-weighted imaging (DWI). A total of 1396 image omics features were extracted from the high-resolutionT2WI and DWI sequences respectively by RadCloud v2.2 platform. The least absolute shrinkageand selection operator (LASSO) wasused toscreen cancer-related features ofrectal adenomafrom 1396 T2WI features, 1396 DWI features and 2792 combined features (T2WI sequence and DWI sequence). Logistic regression (LR) algorithm and5-fold cross-validation were used to construct three imaging omics predictionmodels: Model 1(T2WI), Model 2(DWI) and Model 3(T2WI+ DWI). The diagnostic performance of the imaging omics modelwas evaluated by accuracy, sensitivity, specificity and area under the curve (AUC).

The AUC of Model 1, Model 2 and Model 3was0.80, 0.84, 0.92 respectively. Model 3 showed the best predictive performance. The accuracy, sensitivity and specificity of Model 3were0.85, 0.81, 0.88 respectively.

Maging omics model based on multi-parameterMRI hasthe potential to predict canceration of rectal adenoma, and combination of high resolutionT2WI and DWI sequence is more effective than single sequence in predicting canceration.