Exploring key factors affecting stone retention rates in percutaneous nephrolithotomy from a three-dimensional structural perspective: a retrospective study.

BACKGROUND: Percutaneous nephrolithotomy (PCNL) is a mainstream minimally invasive strategy for renal calculi. Despite widespread use, residual calculi after PCNL remain a key clinical challenge. Precise preoperative evaluation of renal collecting system anatomy and rational planning of the percutaneous access route are critical for improving stone-free rates. This study aimed to explore whether morphological features of the target calyx can predict stone clearance from a non-target puncture calyx and establish a model for assessing residual stone risk. METHODS: A retrospective study was conducted including 105 PCNL cases (67 stone-free, 38 with residual stones) with distinct puncture and target calyces between January 2023 and June 2025. Three-dimensional (3D) models were reconstructed from preoperative computed tomography (CT) urography to measure spatial anatomical parameters. Patient characteristics, stone features, and 3D metrics were entered into binary logistic regression to screen independent predictors and construct a nomogram. Model performance was evaluated using receiver operating characteristic (ROC), calibration curves, decision curve analysis (DCA), and internal validation (n=29). RESULTS: Three independent predictors were identified: punctured calyx length-to-width ratio [odds ratio (OR) =6.89, P=0.020], inter-calyceal axis angle (OR =0.929, P<0.001), and target calyx length-to-width ratio (OR =8.925, P=0.003). The model showed excellent discrimination with an area under the curve (AUC) of 0.905, sensitivity of 86.8%, and specificity of 80.6% at the optimal cutoff of 0.291. The Hosmer-Lemeshow test indicated good calibration (χ2=12.467, P=0.132). Calibration and DCA confirmed favorable accuracy and clinical utility. Internal validation yielded an AUC of 0.829, verifying model stability and reliability. CONCLUSIONS: A predictive model combining calyceal length-to-width ratios and inter-calyceal axis angle can effectively predict stone clearance in the target calyx. This model provides a valuable reference for optimizing calyx selection and improving stone-free outcomes in PCNL.