Management of complex renal stones in horseshoe kidney using real-time intrarenal pressure monitoring with artificial intelligence in retrograde intrarenal surgery: A case report

TL;DR

This case report shows how AI-assisted pressure monitoring helped safely perform kidney stone surgery in a patient with a rare horseshoe kidney anatomy.

Contribution

First documented use of AI-assisted intrarenal pressure monitoring in RIRS for horseshoe kidneys.

Findings

AI system maintained stable intrarenal pressure at ~30 mmHg during surgery.

Improved intraoperative visibility and procedural control without complications.

Demonstrated feasibility of AI-assisted IRP monitoring in complex kidney anatomy.

Abstract

Retrograde intrarenal surgery (RIRS) in horseshoe kidneys is technically challenging due to altered anatomy and unstable intrarenal pressure (IRP). We report a case of a 45-year-old male with complex renal stones in a horseshoe kidney managed using artificial intelligence (AI)-assisted real-time IRP monitoring during RIRS. The AI system dynamically regulated irrigation and suction to maintain IRP within a safe range (∼30 mmHg), improving intraoperative visibility and procedural control. Stone clearance was achieved without complications. This case highlights the feasibility and potential safety benefits of AI-assisted IRP monitoring in anatomically complex kidneys.

•First documented case applying AI-assisted intrarenal pressure (IRP) monitoring in retrograde intrarenal surgery (RIRS) for a horseshoe kidney.•The AI-driven system maintained stable intrarenal pressure (∼30 mmHg) and improved intraoperative visibility throughout the procedure.•This case demonstrates the potential of AI-assisted IRP monitoring to enhance procedural safety in anatomically complex kidneys.

First documented case applying AI-assisted intrarenal pressure (IRP) monitoring in retrograde intrarenal surgery (RIRS) for a horseshoe kidney.

The AI-driven system maintained stable intrarenal pressure (∼30 mmHg) and improved intraoperative visibility throughout the procedure.

This case demonstrates the potential of AI-assisted IRP monitoring to enhance procedural safety in anatomically complex kidneys.

Figures