1.Clinical and MRI nomogram model for predicting simultaneous liver metastasis of rectal cancer
Yudie PAN ; Shuxing WANG ; Xiaowen LIU ; Ting XU ; Changsi JIANG ; Xue TANG ; Yan LUO ; Jingshan GONG
Chinese Journal of Medical Imaging Technology 2024;40(9):1361-1365
Objective To explore the value of nomogram model based on clinical data and MRI findings for predicting simultaneous liver metastasis(SLM)of rectal cancer.Methods Clinical and MRI data of 356 patients with rectal cancer were randomly divided into training set(n=249,45 cases of SLM)and validation set(n=107,27 cases of SLM)at a ratio of 7∶3.Logistic regression analysis were used to screen the independent factors for predicting SLM of rectal cancer.The nomogram model was then constructed,and the efficacy of this model was evaluated.Results Tumor N-stage,serum carcinoembryonic antigen,carbohydrate antigen 19-9 and involvement of mesorectal fascia(MRF)or not were all independent factors for predicting SLM of rectal cancer.The area under the curve(AUC)of this nomogram model for predicting rectal cancer SLM in training set and validation set was 0.834(95%CI[0.776,0.893])and 0.769(95%CI[0.662,0.877]),respectively.The calibration curve showed good consistency between the predicted values and the measured values,and the decision curve analysis showed that the nomogram model had good clinical practicality.Conclusion The nomogram model based on clinical data and MRI findings could be used to predict SLM of rectal cancer.