AUTHOR=Bianchi Lorenzo , Cercenelli Laura , Bortolani Barbara , Piazza Pietro , Droghetti Matteo , Boschi Sara , Gaudiano Caterina , Carpani Giulia , Chessa Francesco , Lodi Simone , Tartarini Lorenzo , Bertaccini Alessandro , Golfieri Rita , Marcelli Emanuela , Schiavina Riccardo , Brunocilla Eugenio TITLE=3D renal model for surgical planning of partial nephrectomy: A way to improve surgical outcomes JOURNAL=Frontiers in Oncology VOLUME=12 YEAR=2022 URL=https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2022.1046505 DOI=10.3389/fonc.2022.1046505 ISSN=2234-943X ABSTRACT=Objective

to evaluate the impact of 3D model for a comprehensive assessment of surgical planning and quality of partial nephrectomy (PN).

Materials and methods

195 patients with cT1-T2 renal mass scheduled for PN were enrolled in two groups: Study Group (n= 100), including patients referred to PN with revision of both 2D computed tomography (CT) imaging and 3D model; Control group (n= 95), including patients referred to PN with revision of 2D CT imaging. Overall, 20 individuals were switched to radical nephrectomy (RN). The primary outcome was the impact of 3D models-based surgical planning on Trifecta achievement (defined as the contemporary absence of positive surgical margin, major complications and ≤30% postoperative eGFR reduction). The secondary outcome was the impact of 3D models on surgical planning of PN. Multivariate logistic regressions were used to identify predictors of selective clamping and Trifecta’s achievement in patients treated with PN (n=175).

Results

Overall, 73 (80.2%) patients in Study group and 53 (63.1%) patients in Control group achieved the Trifecta (p=0.01). The preoperative plan of arterial clamping was recorded as clampless, main artery and selective in 22 (24.2%), 22 (24.2%) and 47 (51.6%) cases in Study group vs. 31 (36.9%), 46 (54.8%) and 7 (8.3%) cases in Control group, respectively (p<0.001). At multivariate logistic regressions, the use of 3D model was found to be independent predictor of both selective or super-selective clamping and Trifecta’s achievement.

Conclusion

3D-guided approach to PN increase the adoption of selective clamping and better predict the achievement of Trifecta.