Objective: The aim of the study was to evaluate three-dimensional virtual models (3DVMs) usefulness in the intraoperative assistance of minimally-invasive partial nephrectomy in highly complex renal tumors. Methods: At our institution cT1-2N0M0 all renal masses with Preoperative Aspects and Dimensions Used for an Anatomical classification score ≥10 treated with minimally-invasive partial nephrectomy were considered for the present study. For inclusion a baseline contrast-enhanced computed tomography in order to obtain 3DVMs, the baseline and postoperative serum creatinine as well as estimated glomerular filtration rate values were needed. These patients, in which 3DVMs were used to assist the surgeon in the planning and intraoperative guidance, were then compared with a control group of patients who underwent minimally-invasive partial nephrectomy with the same renal function assessments, but without 3DVMs. Multivariable logistic regression models were used to predict the margin, ischemia, and complication score achievement. Results: Overall, 79 patients met the inclusion criteria and were compared with 143 complex renal masses without 3DVM assistance. The 3DVM group showed better postoperative outcomes in terms of baseline-weighted differential estimated glomerular filtration rate (−17.7% vs. −22.2%, p=0.03), postoperative complications (16.5% vs. 23.1%, p=0.03), and major complications (Clavien Dindo >III, 2.5% vs. 5.6%, p=0.03). At multivariable logistic regression 3DVM assistance independently predicted higher rates of successful partial nephrectomy (odds ratio: 1.42, p=0.03). Conclusion: 3DVMs represent a useful tool to plan a tailored surgical approach in case of surgically complex masses. They can be used in different ways, matching the surgeon's needs from the planning phase to the demolitive and reconstructive phase, leading towards maximum safety and efficacy outcomes.

Three-dimensional imaging reconstruction of the kidney's anatomy for a tailored minimally invasive partial nephrectomy: A pilot study

Di Dio, Michele;
2022-01-01

Abstract

Objective: The aim of the study was to evaluate three-dimensional virtual models (3DVMs) usefulness in the intraoperative assistance of minimally-invasive partial nephrectomy in highly complex renal tumors. Methods: At our institution cT1-2N0M0 all renal masses with Preoperative Aspects and Dimensions Used for an Anatomical classification score ≥10 treated with minimally-invasive partial nephrectomy were considered for the present study. For inclusion a baseline contrast-enhanced computed tomography in order to obtain 3DVMs, the baseline and postoperative serum creatinine as well as estimated glomerular filtration rate values were needed. These patients, in which 3DVMs were used to assist the surgeon in the planning and intraoperative guidance, were then compared with a control group of patients who underwent minimally-invasive partial nephrectomy with the same renal function assessments, but without 3DVMs. Multivariable logistic regression models were used to predict the margin, ischemia, and complication score achievement. Results: Overall, 79 patients met the inclusion criteria and were compared with 143 complex renal masses without 3DVM assistance. The 3DVM group showed better postoperative outcomes in terms of baseline-weighted differential estimated glomerular filtration rate (−17.7% vs. −22.2%, p=0.03), postoperative complications (16.5% vs. 23.1%, p=0.03), and major complications (Clavien Dindo >III, 2.5% vs. 5.6%, p=0.03). At multivariable logistic regression 3DVM assistance independently predicted higher rates of successful partial nephrectomy (odds ratio: 1.42, p=0.03). Conclusion: 3DVMs represent a useful tool to plan a tailored surgical approach in case of surgically complex masses. They can be used in different ways, matching the surgeon's needs from the planning phase to the demolitive and reconstructive phase, leading towards maximum safety and efficacy outcomes.
2022
Complex renal mass
Kidney cancer
Laparoscopic
Nephron-sparing surgery
Renal cell carcinoma
Robotic
Three-dimensional
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11770/398946
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