Do Traditional Imaging Predictors Still Matter? A Systematic Review on Laser Efficiency and Stone-Free Outcomes in the Era of Advanced Lithotripsy

Abstract

Endoscopic laser lithotripsy has become the standard treatment for urinary stones, yet preoperative imaging parameters that predict laser efficiency and stone-free outcomes remain incompletely characterized. This systematic review synthesizes evidence on current imaging-based predictors of laser efficiency and stone-free outcomes in endoscopic laser lithotripsy, with the goal of informing precision surgical planning and future predictive modeling. A systematic review was conducted following PRISMA guidelines. We screened studies evaluating adult patients (≥18 years) with urinary stones undergoing endoscopic laser lithotripsy with preoperative imaging assessment and reported relationships between imaging parameters and treatment outcomes. Data extraction included patient characteristics, imaging parameters, laser technology, efficiency metrics, stone-free outcomes, and statistical relationships. One hundred ten studies comprising 23,847 patients met inclusion criteria. Stone density >1000 HU predicted significantly lower single-session stone-free rates (40% vs 95%, p=0.01) and longer operative time (75±15 vs 55±13 minutes, p<0.01) for stones >2 cm. Stone size >20 mm reduced stone-free rates to 68% versus 100% for stones ≤20 mm, with first-procedure success of only 25.0% for bilateral total diameter >30 mm. Lower pole location independently predicted reduced stone-free rates (OR 0.523, p<0.001), while stone relocation improved 3-month stone-free rates from 84.4% to 97.8% (p=0.026). Higher BMI unexpectedly predicted improved stone-free rates (OR 1.17, p=0.022). Thulium fiber laser demonstrated shorter lasing time (7.4±1.8 vs 14.8±1.5 minutes, p=0.011) and comparable stone-free rates to Ho: YAG. The SMASH score (HU × size/100) with cut-off of 15 distinguished RIRS success rates (82% vs 61%, p=0.03). Flexible and navigable suction ureteral access sheath (FANS) achieved 94.7-97.5% stone-free rates. Stone imaging characteristics helped predict complex surgical procedures and outcomes of endoscopic lithotripsy․ Imaging methods differed in their ability to predict procedural difficulty‚ with density being most predictive for large stones․ The anatomical location and stone burden helped predict procedural feasibility and stone clearance․ Support is provided for transitioning from descriptive imaging to predictive imaging-based surgical planning and the potential for imaging biomarkers and technology-dependent parameters to individualize surgery and optimize laser parameters․Stone density >1000 HU, size >20 mm, and lower pole location are validated predictors of reduced laser efficiency and stone-free outcomes. Composite scores such as Stone Management According to Size-Hardness (SMASH) score‚ show that radiological factors can be integrated into clinical decision-making for kidney stone management․ These results will allow for the next steps towards the use of artificial intelligence–driven predictive models for personalized endoscopic stone surgery and urinary stone treatment planning․