Abstract
BackgroundAccurate lymph node metastasis (LNM) prediction in colorectal cancer (CRC) patients is of great significance for treatment decision making and prognostic evaluation. We aimed to develop and validate a clinical-radiomics nomogram for the individual preoperative prediction of LNM in CRC patients.MethodsWe enrolled 766 patients (458 in the training set and 308 in the validation set) with clinicopathologically confirmed CRC. We included nine significant clinical risk factors (age, sex, preoperative carbohydrate antigen 19-9 (CA19-9) level, preoperative carcinoembryonic antigen (CEA) level, tumor size, tumor location, histotype, differentiation and M stage) to build the clinical model. We used analysis of variance (ANOVA), relief and recursive feature elimination (RFE) for feature selection (including clinical risk factors and the imaging features of primary lesions and peripheral lymph nodes), established classification models with logistic regression analysis and selected the respective candidate models by fivefold cross-validation. Then, we combined the clinical risk factors, primary lesion radiomics features and peripheral lymph node radiomics features of the candidate models to establish combined predictive models. Model performance was assessed by the area under the receiver operating characteristic (ROC) curve (AUC). Finally, decision curve analysis (DCA) and a nomogram were used to evaluate the clinical usefulness of the model.ResultsThe clinical-primary lesion radiomics-peripheral lymph node radiomics model, with the highest AUC value (0.7606), was regarded as the candidate model and had good discrimination and calibration in both the training and validation sets. DCA demonstrated that the clinical-radiomics nomogram was useful for preoperative prediction in the clinical environment.ConclusionThe present study proposed a clinical-radiomics nomogram with a combination of clinical risk factors and radiomics features that can potentially be applied in the individualized preoperative prediction of LNM in CRC patients.
Highlights
Accurate lymph node metastasis (LNM) prediction in colorectal cancer (CRC) patients is of great significance for treatment decision making and prognostic evaluation
To evaluate the added value of radiomics features to clinical features in individually predicting LNM in CRC patients, we developed six decision curves based on the clinical parameters, primary lesion radiomics features, LN radiomics features and the combined clinical-radiomics models
Feature extraction and model construction A total of 222 radiomics features were extracted from computed tomography (CT) images (111 lesion radiomics features and 111 peripheral LN radiomics features)
Summary
Accurate lymph node metastasis (LNM) prediction in colorectal cancer (CRC) patients is of great significance for treatment decision making and prognostic evaluation. Lymph node metastasis (LNM) is the main metastatic mode of CRC and an important cause of postoperative recurrence and death [2]. The metastasis of lymph nodes (LNs) determines the surgical range of CRC, the formulation of adjuvant treatment plans, and the postoperative survival rate of. For early colorectal cancer (ECC), local treatment such as endoscopic local resection is considered feasible management for patients without LNM because of its low risk of metastasis (3.6–16.2%) [7, 8].
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