The clinical-MRI nomogram model can effectively predict lymphatic vascular infiltration of cervical cancer

ZOU Mengmeng; ZHOU Xinran; MA Chunyu; LÜ Na; ZHU Lin; GAO Yuanyuan; GUO Fei

Abstract：Objective To evaluate the value of clinically-MRI nomogram model in predicting lymphatic vasculature infiltration of cervical cancer.Methods A retrospective analysis was performed on 168 patients who underwent preoperative MRI examination and were pathologically confirmed as cervical cancer in the First Affiliated Hospital of Bengbu Medical University from January 2019 to November 2023.Clinical and imaging data of patients were collected and randomly divided into two groups,the training set(n=112)and the validation set(n=56),according to a ratio of 7:3.The clinical independent risk factors associated with lymphatic vascular infiltration of cervical cancer were screened by uni-multivariate Logistic regression analysis.The regions of interest were manually delineated in sagittal position of enhanced sequences on T2WI and T1WI respectively,and the intratumoral,peritumoral and intratumoral+peritumoral imaging features were extracted.The imaging model was constructed by dimensionality reduction of the image features and selection of the optimal features.A nomogram model was constructed by combining clinical predictors and imaging omics scores.The area under ROC curve,calibration curve and decision curve were used to analyze and evaluate the prediction efficiency of the model.Results The ratio of neutrophil to lymphocyte count and lymph node metastasis between the two groups were statistically significant(P＜0.05).The graph model had the best prediction performance,and the area under the curve was 0.932(95%CI:0.862-0.984)and 0.896(95%CI:0.803-0.990)respectively,which was significantly higher than that of the tumor.Conclusion The Nomogram model established in this study has high diagnostic performance in predicting lymphatic vascular infiltration of cervical cancer,and can provide important guidance for clinical decision-making before surgery.