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<p>Stone impaction significantly increases the difficulty of ureteroscopic surgery (URS). While various CT-based parameters have been proposed to predict impaction, direct measurement of ureteral wall thickness (UWT) often lacks accuracy due to imaging artifacts and low conspicuity. This study aimed to identify reliable objective factors, particularly the Ureteral Dilation Coefficient (UDC), to predict ureteral stone impaction. We conducted a retrospective analysis of 189 patients who underwent URS between 2022 and 2025. Patients were divided into Impacted (<i>n</i> = 101) and Non-impacted (<i>n</i> = 88) groups based on intraoperative guidewire passage. Impaction was defined intraoperatively based on the inability to pass a guidewire past the stone.All CT images were evaluated using a bowel window with contrast inversion. We measured standard parameters and calculated the UDC. Inter-observer reliability was assessed using Intraclass Correlation Coefficients (ICC). Multivariate logistic regression was used to identify independent predictors and construct the Prediction Risk Estimation(PRE) model, which was validated using Bootstrap and Propensity Score Matching (PSM). ROC curves and Decision Curve Analysis (DCA) were performed to evaluate performance. UDC demonstrated excellent reproducibility (ICC &gt; 0.85). Multivariate analysis revealed that Laterality, Maximum Stone Length (MSL), Ureteral Outer Area HUD Above stone (UOAHUDA), and UDC were independent predictors of impaction. Notably, UDC exhibited the highest Odds Ratio (OR = 8.156, 95% CI: 3.459–19.233, <i>P</i> &lt; 0.001). The combined prediction model (PRE) achieved an AUC of 0.820, outperforming parameters. Bootstrap validation confirmed the model’s stability, and PSM analysis further validated the robustness of UDC (OR = 3.681, <i>P</i> = 0.041). DCA demonstrated the model’s clinical utility. The UDC is the independent predictor of ureteral stone impaction. The integration of UDC with MSL and CT density metrics into the PRE model suggests the potential of a promising tool for preoperative risk stratification and surgical planning.</p>

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Measuring and analyzing objective factors of impacted ureteral stones on Non-Contrast Computed Tomography (NCCT): a retrospective case-control study

  • 期刊论文

  • 发表日期：

    2026年6月29日

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  • Lu Yu,
  • Jiang He,
  • Yuehua Li,
  • Yirong Chen,
  • Fengjiao Yu

摘要

Stone impaction significantly increases the difficulty of ureteroscopic surgery (URS). While various CT-based parameters have been proposed to predict impaction, direct measurement of ureteral wall thickness (UWT) often lacks accuracy due to imaging artifacts and low conspicuity. This study aimed to identify reliable objective factors, particularly the Ureteral Dilation Coefficient (UDC), to predict ureteral stone impaction. We conducted a retrospective analysis of 189 patients who underwent URS between 2022 and 2025. Patients were divided into Impacted (n = 101) and Non-impacted (n = 88) groups based on intraoperative guidewire passage. Impaction was defined intraoperatively based on the inability to pass a guidewire past the stone.All CT images were evaluated using a bowel window with contrast inversion. We measured standard parameters and calculated the UDC. Inter-observer reliability was assessed using Intraclass Correlation Coefficients (ICC). Multivariate logistic regression was used to identify independent predictors and construct the Prediction Risk Estimation(PRE) model, which was validated using Bootstrap and Propensity Score Matching (PSM). ROC curves and Decision Curve Analysis (DCA) were performed to evaluate performance. UDC demonstrated excellent reproducibility (ICC > 0.85). Multivariate analysis revealed that Laterality, Maximum Stone Length (MSL), Ureteral Outer Area HUD Above stone (UOAHUDA), and UDC were independent predictors of impaction. Notably, UDC exhibited the highest Odds Ratio (OR = 8.156, 95% CI: 3.459–19.233, P < 0.001). The combined prediction model (PRE) achieved an AUC of 0.820, outperforming parameters. Bootstrap validation confirmed the model’s stability, and PSM analysis further validated the robustness of UDC (OR = 3.681, P = 0.041). DCA demonstrated the model’s clinical utility. The UDC is the independent predictor of ureteral stone impaction. The integration of UDC with MSL and CT density metrics into the PRE model suggests the potential of a promising tool for preoperative risk stratification and surgical planning.