Abstract Objective Robot-assisted partial nephrectomy (RAPN) is a widely used technique for treating renal tumors. However, accurate identification of tumor locations and precise surgical planning remain challenging, particularly in cases with complex anatomy or tumors in difficult-to-reach areas. This study evaluated the usefulness of intraoperative real-time 3D reconstruction models for RAPN. Methods We analyzed the data of 57 patients who underwent RAPN using 3D reconstruction models (3D-R group) and 173 patients who underwent RAPN without these models (control group). The models were generated from the preoperative Computed tomography images and displayed on a monitor in the operating room to plan surgical approaches and guide tumor dissection. Propensity score matching was performed to compare the surgical outcomes between the two groups. Results The use of real-time 3D reconstruction models significantly improved surgical outcomes in the propensity score-matched cohort. The ischemia time was shorter in the 3D-R RAPN group than in the control group (p = 0.019). Significantly fewer overall and major complications were observed in the 3D-R RAPN group (p = 0.023 and p = 0.041, respectively). Additionally, the 3D-R RAPN group achieved the trifecta status at a significantly higher rate than the control group (p = 0.005). Conclusions 3D reconstruction models are valuable tools for guiding RAPN, leading to shorter warm ischemia times, fewer complications, and a higher trifecta achievement rate, thereby enhancing the overall quality of care of patients undergoing RAPN.
Miyamoto et al. (Mon,) studied this question.
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