Predictive value of enhanced CT radiomics nomogram in muscular invasion of bladder urothelial carcinoma
ZHANG Zhiya
MENG Ying
LIU Xinxin
YUE Fenghui
ZHOU Xinran
ZHANG Yuwen
ZHU Guanghui
Abstract：Objective To investigate the value of enhanced CT imaging nomogram in preoperative prediction of muscular infiltration in urinary tract carcinoma of bladder.Methods A retrospective analysis was performed on 175 patients diagnosed with bladder urothelial carcinoma from August 2018 to April 2023 in the First Affiliated Hospital of Bengbu Medical College.All cases were randomly divided into training group(n=122)and verification group(n=53)according to 7:3.The region of interest was manually defined and the image omics features were extracted from the multi-phase enhanced CT images.The dimensionality was reduced by minimum absolute contraction and selection operator,and machine learning was performed on the extracted features using support vector machine classifier to screen out the optimal image omics features and construct the image omics scoring model.The independent predictors of muscular infiltration of bladder urothelial carcinoma were screened by univariate analysis and multivariate binary logistic regression analysis,and the clinical-CT signs model was constructed.Combining the imaging omics model with the clinical-CT sign model,the combined model was constructed.The ROC curve is plotted,the area under the curve(AUC),sensitivity,and specificity were calculated to evaluate the predictive efficacy of different models,and then the best model was visualized to construct a nomogram.Results The diagnostic efficacy of the combined model was the highest(AUC=0.891),which was higher than that of the imaging model(AUC=0.777)and the clinical-CT sign model(AUC=0.829).Decision curve analysis and correction curve confirm that the nomogram has high predictive performance.Conclusion Enhanced CT image nomogram has a high value in predicting myoinfiltration of bladder urothelial carcinoma before operation.
Keywords：bladder cancermuscular invasionradiomicscontrast-enhanced computed tomography
Publication Date：2023-12-28
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：7( 1028-1034 )