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The following is a summary of “Application value of surgical navigation system based on deep learning and mixed reality for guiding puncture in percutaneous nephrolithotomy: a retrospective study,” published in the October 2024 issue of Urology by Meng et al.
Researchers conducted a retrospective study to evaluate the clinical value of a deep learning and mixed reality navigation system for patients undergoing percutaneous nephrolithotomy (PNL) for kidney stone treatment.
They analyzed data from 136 patients with kidney stones treated between October 2021 and December 2023. Patients underwent PNL and were divided into a control group (Group 1) using standard ultrasound guidance and a surgical navigation group (Group 2) using a navigation system fused with ultrasound. Preoperative computed tomography (CT) was performed for both groups, and baseline information and procedural characteristics were compared.
The results showed that PNL was successfully performed in both groups, with no significant difference in baseline data. In Group 2, the navigation system accurately matched real-time ultrasound images with CT images. The success rate of single puncture, puncture time, and decrease in hemoglobin were significantly improved in Group 2 compared to Group 1 (P<0.05).
Investigators concluded that a navigation system based on deep learning and mixed reality enhances real-time intraoperative navigation in PNL for kidney stones, demonstrating acceptable accuracy and safety while being easily mastered by novice surgeons.
Source: bmcurol.biomedcentral.com/articles/10.1186/s12894-024-01618-1
