Real-Time Tract Length During Supine Percutaneous Nephrolithotomy Is Shorter than on Preoperative Imaging: Implications for Surgical Planning

Abstract

Introduction:

Accurate estimation of nephrostomy tract length is crucial for planning percutaneous nephrolithotomy (PCNL) access site and required tools, yet data are limited for supine PCNL. This study compared real-time intraoperative tract lengths with preoperative CT-based estimations using two techniques: a novel CT-anatomical technique and the S.T.O.N.E. nephrolithometry-based technique.

Methods:

In a prospective single-surgeon cohort, patients undergoing supine PCNL between March and June 2025 were included. Preoperative CT-based tract lengths were measured using the CT-anatomical and S.T.O.N.E. techniques and were compared to real-time intraoperative measurements in a blinded manner. Paired comparisons used the Wilcoxon signed-rank test, while mean squared error (MSE) and intraclass correlation coefficients (ICC) assessed accuracy and reliability. Correlation analyses and multivariable regression identified predictive factors and generated a model for improved tract length estimation.

Results:

Of 47 eligible cases, 33 met the inclusion criterion. Both CT-based methods significantly overestimated the real-time intraoperative tract length (mean intraoperative: 9 ± 2.5 cm vs CT-anatomical: 11.2 ± 2.7 cm and S.T.O.N.E.: 11.4 ± 2.2 cm). The CT-anatomical method showed better agreement with intraoperative values (MSE = 10.42, ICC = 0.42) than S.T.O.N.E. (MSE = 11.18, ICC = 0.35). A multivariable linear model incorporating body mass index, access site level, CT positioning, and CT-anatomical length was used to develop an easy-to-use calculator that accurately predicts the actual intraoperative tract length from the preoperative CT measurement (MSE = 3.64, ICC = 0.58; p < 0.001).

Conclusion:

CT-based tract lengths often overestimate actual intraoperative values in supine PCNL, suggesting that true tract lengths in the supine position are shorter than previously believed. Preoperative accuracy can be enhanced using our newly developed predictive formula.