Predicting shockwave lithotripsy outcome for urolithiasis using clinical and stone computed tomography texture analysis variables.

ABSTRACT: We aimed to develop and evaluate a statistical model, which included known pre-treatment factors and new computed tomography texture analysis (CTTA) variables, for its ability to predict the likelihood of a successful outcome after extracorporeal shockwave lithotripsy (SWL) treatment for renal and ureteric stones. Up to half of patients undergoing SWL may fail treatment. Better prediction of which cases will likely succeed SWL will help patients to make an informed decision on the most effective treatment modality for their stone. 19 pre-treatment factors for SWL success, including 6 CTTA variables, were collected from 459 SWL cases at a single centre. Univariate and multivariable analyses were performed by independent statisticians to predict the probability of a stone free (both with and

SUBMITTER: Cui HW 

PROVIDER: S-EPMC6788981 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature