CT radiomics model predicts lymphovascular invasion in 252 colorectal cancer patients

ObjectiveThis study aimed to develop and validate a computed tomography (CT)-based radiomics nomogram for the preoperative prediction of lymphovascular invasion (LVI) in colorectal cancer (CRC).MethodsIn this retrospective study, CRC patients were randomly partitioned into training and validation sets at a 7:3 ratio, and were classified as LVI-positive or LVI-negative based on postoperative histopathology. In the training set, univariate analysis, Least Absolute Shrinkage and Selection Operator (LASSO), and multivariate Logistic regression analysis were used to identify the influencing factors of LVI. A combined nomogram integrating the predictors was developed. Model discrimination was evaluated using the area under the receiver operating characteristic curve (AUC). Calibration and clinical utility were assessed with calibration curves and decision curve analysis (DCA), respectively.ResultsAmong the 252 patients in the training set, 70 (27.78%) were LVI-positive. In the validation set of 108 patients, 31 (28.70%) were LVI-positive. Multivariate analysis identified the tumor volume, maximum tumor diameter, depth of tumor invasion, maximum short-axis diameter of regional lymph nodes, Carcinoembryonic Antigen level, Neutrophil-to-Lymphocyte Ratio (NLR), standard deviation of CT value of tumor parenchyma, and Rad-score as independent predictors of LVI (P