Exploratory Treatment-Selection Model of Intraoperative Cone-Beam Computed Tomography During Percutaneous...

Area of Science:

• Urology
• Medical Imaging
• Nephrolithotomy

Background:

• Intraoperative cone-beam computed tomography (CBCT) can improve stone-free rates after percutaneous nephrolithotomy (PCNL) by detecting residual fragments.
• Limited availability of hybrid operating rooms (ORs) for CBCT necessitates understanding its optimal use.
• Patient and stone characteristics influencing CBCT eligibility and effectiveness require investigation.

Purpose of the Study:

• To explore patient and stone characteristics associated with CBCT eligibility in PCNL.
• To develop an exploratory treatment-selection model estimating stone-free probabilities conditional on CBCT use.
• To assess the model's performance in predicting stone-free status (Grade C and Grade A).

Main Methods:

• Retrospective analysis of a randomized controlled trial on intraoperative CBCT during PCNL.
• Comparison of CBCT-eligible versus ineligible cases and stone-free versus residual fragment cases.
• Development and internal validation (bootstrapping) of a multivariate exploratory treatment-selection model.

Main Results:

• Stone composition was the only significant difference between CBCT-eligible and ineligible cases.
• The final model included intraoperative CBCT, stone size, and composition as predictors of stone-free status.
• Model performance (AUC) was 0.81 for Grade C and 0.75 for Grade A stone-free outcomes, with moderate internal validation optimism.

Conclusions:

• An exploratory model was developed to estimate stone-free probabilities with and without intraoperative CBCT during PCNL.
• The model suggests that the benefit of CBCT may vary depending on stone characteristics.
• The model is hypothesis-generating, not for clinical decision-making, and requires external validation.