Automated radiomic analysis of CT images to predict likelihood of spontaneous passage of symptomatic renal stones.

ABSTRACT:

Purpose

To evaluate the ability of a semi-automated radiomic analysis software in predicting the likelihood of spontaneous passage of urinary stones compared with manual measurements.

Methods

Symptomatic patients visiting the emergency department with suspected stones in either kidney or ureters who underwent a CT scan were included. Patients were followed for up to 6 months for the outcome of a trial of passage. Maximum stone diameters in axial and coronal images were measured manually. Stone length, width, height, max diameter, volume, the mean and standard deviation of the Hounsfield units, and morphologic features were also measured using automated radiomic analysis software. Multivariate models were developed using these data to predict subsequent spontaneous stone pass

SUBMITTER: Mohammadinejad P 

PROVIDER: S-EPMC8477419 | biostudies-literature | 2021 Aug

REPOSITORIES: biostudies-literature