Preoperative Prediction of Lymphovascular Invasion of Colorectal Cancer by Artificial Neural Network

Abstract Background: Lymphovascular invasion (LVI) is considered to be important for metastasis of colorectal cancer (CRC). However, there is still no effective method to predict LVI before operation. Our research aimed to construct an artificial neural network (ANN) for the pre-operative prediction of LVI.Methods: We obtained blood indexes and conditions of LVI (confirmed by pathological examination) of 288 cases of CRC patients from a tertiary hospital in China. ANN and logistic regression model were constructed based on randomly chosen 185 cases CRC patients (training group). The remaining 103 cases of CRC patients received tests of ANN and logistic model (validation group). Receiver operating characteristics curve (ROC) and decision curve analysis (DCA) was performed to assess the accuracy of constructed model respectively.Results: In the training group, the area under curve (AUC) of ANN was higher than that of logistic model (0.832 vs 0.692). The ANN correctly predicted 92% cases of LVI, whereas logistic model only predicted 56% cases. Similar results were also tested in the validation model.Conclusions: Our constructed ANN showed higher accuracy compared with a conventional linear model. The ANN based on blood indexes may provide value for pre-operative prediction of LVI.