Staghorn Morphometry: A New Tool for Clinical Classification and Prediction Model for Percutaneous Nephrolithotomy Monotherapy

Background and Purpose: Staghorn stone volume and its distribution within the collecting system, staghorn morphometry, predicts the requirement of tract and stage for percutaneous nephrolithotomy (PCNL) monotherapy. The purpose of the study was to develop a CT urography staghorn morphometry-based prediction algorithm to predict tract(s) and stage(s) for PCNL monotherapy and classify staghorn accordingly. Material and Methods: A retrospective case-control design of 94 units was used. CT software calculated the total stone volume (TSV) with absolute volume and percentile volume in the pelvis, planned entry calix, favorable and unfavorable calix. Entry calix was the optimum calix chosen, keeping the relations of the ribs and adjoining viscera that could clear maximum stone volume. Unfavorable calix was defined as having an acute angle from the entry calix and infundibular width of <= 8 mm. A prediction model with odds ratio (OR) (95% confidence interval) was constructed on univariate and multivariate regression factors. Results: On univariate analysis, TSV (P = 0.013), unfavorable calix stone volume (0.007), and percentile distribution of stone in pelvis (0.026), pelvis and entry calix (<0.001), and unfavorable calix (0.001) predicted tracts while total stone (<0.001), pelvic stone (0.0046), and unfavorable calix stone (<0.001) volume and percentile volume in pelvis (0.04), pelvis and entry calix (0.005) and unfavorable calix (P < 0.001) predicted stage. Multivariate analysis showed that unfavorable calix stone percentile volume predicted tract (area under the curve [AUC] - 0.91) while TSV and unfavorable calix stone percentile volume (AUC - 0.846) predicted stage. The OR-based prediction model suggested a need for single tract and stage PCNL vs multiple tract and stage PCNL for TSV and unfavorable calix percentile stone volume of (<5,000 mm(3) and 5%) and (>20,000 mm(3) and 10%), respectively. Conclusion: The model predicts the tract and stage for PCNL monotherapy. Staghorn morphometry differentiates staghorn into type 1 (single tract and stage); type 2 (single tract-single/multiple stage, or multiple tract-single stage), and type 3 (multiple tract and stage).