%0 Journal Article
%T CT-based radiomics for predicting success of shock wave lithotripsy in ureteral stones larger than 1 cm.
%A Xu H
%A Liu B
%A Tang L
%J World J Urol
%V 42
%N 1
%D 2024 Jul 10
%M 38985166
%F 3.661
%R 10.1007/s00345-024-05111-0
%X <B>OBJECTIVE: </B>This study aims to investigate the predictive value of CT-based radiomics in determining the success of extracorporeal shock wave lithotripsy (SWL) treatment for ureteral stones larger than 10mm in adult patients.<BR><B>METHODS: </B>A total of 301 eligible patients (165/136 successful/unsuccessful) who underwent SWL were retrospectively evaluated and divided into a training cohort (n = 241) and a test cohort (n = 60) following an 8:2 ratio. Univariate analysis was performed to assess clinical characteristics for constructing a nomogram. Radiomics and conventional radiological characteristics of stones were evaluated. Following feature selection, radiomics and radiological models were constructed using logistic regression (LR), support vector machine (SVM), random forest (RF), K nearest neighbor (KNN), and XGBoost. The models' performance was compared using metrics such as the area under the receiver operating characteristic curve (AUC), precision, recall, accuracy, and F1 score. Finally, a nomogram was created incorporating the best image model signature and clinical predictors.<BR><B>RESULTS: </B>The SVM-based radiomics model showed superior predictive performance in both training and test cohorts (AUC: 0.956, 0.891, respectively). The nomogram, which combined SVM-based radiomics signature with proximal ureter diameter (PUD), demonstrated further improved predictive performance in the test cohort (AUC: 0.891 vs. 0.939, P = 0.166).<BR><B>CONCLUSIONS: </B>Integration of CT-derived radiomics and PUD showed excellent ability to predict SWL treatment success in patients with ureteral stones larger than 10mm, providing a promising approach for clinical decision-making.