CT-Based Predictors of Spontaneous Ureteral Stone Passage.

Objective: To assess CT-scan based parameters, particularly ureteral wall thickness (UWT), in predicting spontaneous ureteral stone passage.

Study Design: Cross-sectional, analytical study.

Place And Duration Of The Study: Section of Urology, Department of Surgery, The Aga Khan University Hospital, Karachi, Pakistan, from June to November 2023.

Methodology: Patients with symptomatic, single, radio-opaque, unilateral ureteral stones having size ≤10 mm with normal kidney functions, diagnosed by non-contrast CT-scan KUB, and treated by conservative option for four weeks were enrolled. Clinical and radiological predictors for stone passage (SP), including stone size, area, laterality, location, density, degree of hydronephrosis, maximal UWT at the stone site, and ureteral diameter and density above and below the stone, were evaluated. Binary logistic regression analysis was employed to identify predictors of stone passage. Receiver operating characteristic (ROC) curve was used to find the optimal cut-off for UWT.

Results: Among 34 eligible patients, 22 (64.7%) passed their stones spontaneously. Patients who passed had smaller stone size and area and lesser UWT. Stone location, laterality, degree of hydronephrosis, stone density, ureteral wall diameter, and density above and below stones were not associated with SP. Multivariate analysis revealed maximum UWT as the independent predictor of SP, with a cut-off of 1.95 mm and an accuracy of 0.94.

Conclusion: UWT was the single most convincing factor for the spontaneous passage of ureteral stone in this study. By applying UWT's optimal cut-off value, it might be an extremely significant tool when taking decisions in daily practice.

Key Words: Ureteral wall thickness, Medical expulsive therapy, Non-contrast computed tomography.