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arXiv · 2505.23984

Improved Accuracy in Pelvic Tumor Resections Using a Real-Time Vision-Guided Surgical System

Vahid Danesh·Paul Arauz·Maede Boroji·Andrew Zhu·Mia Cottone·Elaine Gould·Fazel A. Khan·Imin Kao
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Abstract

Pelvic bone tumor resections remain significantly challenging due to complex three-dimensional anatomy and limited surgical visualization. Current navigation systems and patient-specific instruments, while accurate, present limitations including high costs, radiation exposure, workflow disruption, long production time, and lack of reusability. This study evaluates a real-time vision-guided surgical system combined with modular jigs to improve accuracy in pelvic bone tumor resections. A vision-guided surgical system combined with modular cutting jigs and real-time optical tracking was developed and validated. Five female pelvis sawbones were used, with each hemipelvis randomly assigned to either the vision-guided and modular jig system or traditional freehand method. A total of twenty resection planes were analyzed for each method. Accuracy was assessed by measuring distance and angular deviations from the planned resection planes. The vision-guided and modular jig system significantly improved resection accuracy compared to the freehand method, reducing the mean distance deviation from 2.07 $\pm$ 1.71 mm to 1.01 $\pm$ 0.78 mm (p=0.0193). In particular, all specimens resected using the vision-guided system exhibited errors of less than 3 mm. Angular deviations also showed significant improvements with roll angle deviation reduced from 15.36 $\pm$ 17.57$^\circ$ to 4.21 $\pm$ 3.46$^\circ$ (p=0.0275), and pitch angle deviation decreased from 6.17 $\pm$ 4.58$^\circ$ to 1.84 $\pm$ 1.48$^\circ$ (p<0.001). The proposed vision-guided and modular jig system significantly improves the accuracy of pelvic bone tumor resections while maintaining workflow efficiency. This cost-effective solution provides real-time guidance without the need for referencing external monitors, potentially improving surgical outcomes in complex pelvic bone tumor cases.

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Vahid Danesh, Paul Arauz, Maede Boroji, Andrew Zhu, Mia Cottone, Elaine Gould, Fazel A. Khan, Imin Kao. 2025-05-29. Improved Accuracy in Pelvic Tumor Resections Using a Real-Time Vision-Guided Surgical System. https://doi.org/10.1002/jor.26111

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