Preoperative CT-Derived Stone Burden Metrics for Predicting Stone-Free Status and Operative Time After Retrograde Intrarenal Surgery.

Objectives

Non-contrast computed tomography (NCCT) is used before retrograde intrarenal surgery (RIRS) to describe stone size, location, and complexity, but the best way to summarize stone burden remains unsettled. Therefore, we compared multidimensional NCCT-derived burden metrics with cumulative stone diameter (CSD) with respect to their ability to predict stone-free rate (SFR) and operative time after RIRS.

Methods

We reviewed 352 RIRSs performed by one surgical team from April 2024 to May 2026. The primary SFR endpoint was defined as no residual fragments or a maximum residual fragment size of ≤4 mm, with 1-month computed tomography (CT) used as the reference imaging modality. Strict 0 mm CT stone-free status was analyzed as a sensitivity endpoint. The candidate predictors included one-dimensional, two-dimensional, estimated three-dimensional, spatial-distribution, attenuation, and distribution-complexity metrics extracted from preoperative NCCT. The cohort was split into training (n = 247) and validation (n = 105) sets.

Results

The main model retained area-equivalent diameter, staghorn stone, and stone volume distribution entropy, with a validation area under the receiver operating characteristic curve (AUC) of 0.779. A simpler CSD model combining CSD and staghorn stone achieved a validation AUC of 0.761, without a significant AUC difference (p = 0.201). In repeated patient-level full-pipeline validation, the median validation AUC was 0.761. Under the strict 0 mm CT endpoint, the validation AUC was 0.670. Entropy showed lower selection stability in sensitivity analyses. Reclassification favored the main model (validation continuous net reclassification improvement [NRI] 0.460, p = 0.007; integrated discrimination improvement [IDI] 0.038, p = 0.003). Regarding operative time, area-, volume-, and surface-area-based metrics performed better than CSD in regard to both the whole cohort and stone-free episodes.

Conclusions

NCCT-derived burden metrics can refine preoperative assessment before RIRS, but their incremental value over CSD for binary SFR prediction was modest. CSD remains a practical approximation for SFR prediction, whereas multidimensional metrics better reflect operative workload.