Nephrometry Scores Based on Three-dimensional Virtual Models Improve the Accuracy of Predicting Postoperative Complications After Robotic Partial Nephrectomy: Results from a Collaborative ERUS Validation Study
Background and objective: The aim of our study was to compare assessment of PADUA and RENAL nephrometry scores and risk/complexity categories via two-dimensional (2D) imaging and three-dimensional virtual models (3DVM) in a large multi-institutional cohort of renal masses suitable for robot-assisted...
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Elsevier
2025-04-01
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666168325000606 |
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| author | Daniele Amparore Federico Piramide Paolo Verri Enrico Checcucci Alberto Piana Giuseppe Basile Alessandro Larcher Andrea Gallioli Angelo Territo Josep Maria Gaya Pietro Piazza Stefano Puliatti Antonio Andrea Grosso Andrea Mari Riccardo Campi Laura Zuluaga Ucpinar Burak Badani Ketan Sergio Serni Umberto Capitanio Francesco Montorsi Alexandre Mottrie Cristian Fiori Andrea Minervini Peter Wiklund Alberto Breda Francesco Porpiglia |
| author_facet | Daniele Amparore Federico Piramide Paolo Verri Enrico Checcucci Alberto Piana Giuseppe Basile Alessandro Larcher Andrea Gallioli Angelo Territo Josep Maria Gaya Pietro Piazza Stefano Puliatti Antonio Andrea Grosso Andrea Mari Riccardo Campi Laura Zuluaga Ucpinar Burak Badani Ketan Sergio Serni Umberto Capitanio Francesco Montorsi Alexandre Mottrie Cristian Fiori Andrea Minervini Peter Wiklund Alberto Breda Francesco Porpiglia |
| author_sort | Daniele Amparore |
| collection | DOAJ |
| description | Background and objective: The aim of our study was to compare assessment of PADUA and RENAL nephrometry scores and risk/complexity categories via two-dimensional (2D) imaging and three-dimensional virtual models (3DVM) in a large multi-institutional cohort of renal masses suitable for robot-assisted partial nephrectomy (RAPN), and evaluate the predictive role of these imaging approaches for postoperative complications. Methods: Patients were prospectively enrolled from six international high-volume robotic centers, calculating PADUA and RENAL-nephrometry scores and their relative categories with 2D-imaging and 3DVMs. The concordance of nephrometry scores and categories between the two approaches was evaluated using χ2 tests and Cohen’s κ coefficient. Receiver operating characteristic curves were plotted to assess the sensitivity and specificity of the 3DVM and 2D approaches for predicting the occurrence of postoperative complications. Multivariable logistic analyses were conducted to identify predictors of major postoperative complications. Key findings and limitations: A total of 318 patients were included in the study. There was low concordance for nephrometry scores and categories between the 3DVM and 2D assessment methods, with downgrading of PADUA and RENAL scores on 3DVM assessment in 43% and 49% of cases, and downgrading of the corresponding categories in 25% and 26%, respectively. Moreover, 3DVM assessment showed better accuracy than the 2D approach in predicting overall (p < 0.001) and major (p = 0.001) postoperative complications. In line with these findings, multivariable analyses showed that 3DVM-based nephrometry scores and categories were predictive of major postoperative complications (p < 0.001). Limitations include the risk of interobserver variability in evaluating nephrometry scores and categories, production costs for the 3DVMs, and the experience of the surgeons involved, with potential impacts on diffusion of this technology. Conclusions and clinical implications: In this multi-institutional study, 3DVMs had superior accuracy to 2D images for evaluating the surgical complexity of renal masses and frequently led to downgrading. This could facilitate an increase in recommendations for kidney-sparing surgery and better identification of cases at risk of postoperative complications. Patient summary: Our study shows that the use of three-dimensional models gives lower complexity scores for kidney tumors in comparison to standard two-dimensional scans. This can improve surgical planning and may boost the use of kidney-sparing techniques and better identification of cases that are more likely to have postoperative complications. |
| format | Article |
| id | doaj-art-fb69498c7e00400986dd7c484bf0e066 |
| institution | DOAJ |
| issn | 2666-1683 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | Elsevier |
| record_format | Article |
| series | European Urology Open Science |
| spelling | doaj-art-fb69498c7e00400986dd7c484bf0e0662025-08-20T03:00:31ZengElsevierEuropean Urology Open Science2666-16832025-04-0174112010.1016/j.euros.2025.02.001Nephrometry Scores Based on Three-dimensional Virtual Models Improve the Accuracy of Predicting Postoperative Complications After Robotic Partial Nephrectomy: Results from a Collaborative ERUS Validation StudyDaniele Amparore0Federico Piramide1Paolo Verri2Enrico Checcucci3Alberto Piana4Giuseppe Basile5Alessandro Larcher6Andrea Gallioli7Angelo Territo8Josep Maria Gaya9Pietro Piazza10Stefano Puliatti11Antonio Andrea Grosso12Andrea Mari13Riccardo Campi14Laura Zuluaga15Ucpinar Burak16Badani Ketan17Sergio Serni18Umberto Capitanio19Francesco Montorsi20Alexandre Mottrie21Cristian Fiori22Andrea Minervini23Peter Wiklund24Alberto Breda25Francesco Porpiglia26Department of Urology AOU San Luigi Gonzaga, University of Turin, Orbassano, Italy; Corresponding author. Department of Urology, San Luigi Gonzaga Hospital, University of Turin, Orbassano, Turin, Italy. Tel. +39 333 3352758; Fax: +39 011 9026244.Department of Urology AOU San Luigi Gonzaga, University of Turin, Orbassano, ItalyDepartment of Urology AOU San Luigi Gonzaga, University of Turin, Orbassano, ItalyDepartment of Surgery, Candiolo Cancer Institute FPO-IRCCS, Candiolo, ItalyDepartment of Urology AOU San Luigi Gonzaga, University of Turin, Orbassano, ItalyDepartment of Urology, Fundaciò Puigvert, Barcelona, SpainDepartment of Urology, Division of Experimental Oncology, IRCCS Ospedale San Raffaele, Milan, ItalyDepartment of Urology, Fundaciò Puigvert, Barcelona, SpainDepartment of Urology, Fundaciò Puigvert, Barcelona, SpainDepartment of Urology, Fundaciò Puigvert, Barcelona, SpainDepartment of Urology, OLV Hospital, Aalst, Belgium; Orsi Academy, Melle, BelgiumDepartment of Urology, OLV Hospital, Aalst, Belgium; Orsi Academy, Melle, BelgiumUnit of Oncologic Minimally Invasive Urology and Andrology, Careggi Hospital, University of Florence, Florence, ItalyUnit of Oncologic Minimally Invasive Urology and Andrology, Careggi Hospital, University of Florence, Florence, ItalyUnit of Urological Robotic Surgery and Renal Transplantation, Careggi Hospital, University of Florence, Florence, ItalyDepartment of Urology, Icahn School of Medicine at Mount Sinai, New York, NY, USADepartment of Urology, Icahn School of Medicine at Mount Sinai, New York, NY, USADepartment of Urology, Icahn School of Medicine at Mount Sinai, New York, NY, USAUnit of Urological Robotic Surgery and Renal Transplantation, Careggi Hospital, University of Florence, Florence, ItalyDepartment of Urology, Division of Experimental Oncology, IRCCS Ospedale San Raffaele, Milan, ItalyDepartment of Urology, Division of Experimental Oncology, IRCCS Ospedale San Raffaele, Milan, ItalyDepartment of Urology, OLV Hospital, Aalst, Belgium; Orsi Academy, Melle, BelgiumDepartment of Urology AOU San Luigi Gonzaga, University of Turin, Orbassano, ItalyUnit of Oncologic Minimally Invasive Urology and Andrology, Careggi Hospital, University of Florence, Florence, ItalyDepartment of Urology, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, SwedenDepartment of Urology, Fundaciò Puigvert, Barcelona, SpainDepartment of Urology AOU San Luigi Gonzaga, University of Turin, Orbassano, ItalyBackground and objective: The aim of our study was to compare assessment of PADUA and RENAL nephrometry scores and risk/complexity categories via two-dimensional (2D) imaging and three-dimensional virtual models (3DVM) in a large multi-institutional cohort of renal masses suitable for robot-assisted partial nephrectomy (RAPN), and evaluate the predictive role of these imaging approaches for postoperative complications. Methods: Patients were prospectively enrolled from six international high-volume robotic centers, calculating PADUA and RENAL-nephrometry scores and their relative categories with 2D-imaging and 3DVMs. The concordance of nephrometry scores and categories between the two approaches was evaluated using χ2 tests and Cohen’s κ coefficient. Receiver operating characteristic curves were plotted to assess the sensitivity and specificity of the 3DVM and 2D approaches for predicting the occurrence of postoperative complications. Multivariable logistic analyses were conducted to identify predictors of major postoperative complications. Key findings and limitations: A total of 318 patients were included in the study. There was low concordance for nephrometry scores and categories between the 3DVM and 2D assessment methods, with downgrading of PADUA and RENAL scores on 3DVM assessment in 43% and 49% of cases, and downgrading of the corresponding categories in 25% and 26%, respectively. Moreover, 3DVM assessment showed better accuracy than the 2D approach in predicting overall (p < 0.001) and major (p = 0.001) postoperative complications. In line with these findings, multivariable analyses showed that 3DVM-based nephrometry scores and categories were predictive of major postoperative complications (p < 0.001). Limitations include the risk of interobserver variability in evaluating nephrometry scores and categories, production costs for the 3DVMs, and the experience of the surgeons involved, with potential impacts on diffusion of this technology. Conclusions and clinical implications: In this multi-institutional study, 3DVMs had superior accuracy to 2D images for evaluating the surgical complexity of renal masses and frequently led to downgrading. This could facilitate an increase in recommendations for kidney-sparing surgery and better identification of cases at risk of postoperative complications. Patient summary: Our study shows that the use of three-dimensional models gives lower complexity scores for kidney tumors in comparison to standard two-dimensional scans. This can improve surgical planning and may boost the use of kidney-sparing techniques and better identification of cases that are more likely to have postoperative complications.http://www.sciencedirect.com/science/article/pii/S2666168325000606Three-dimensional imagingRobotic surgeryRenal cell carcinomaKidney cancerNephron-sparing surgeryNephrometry scores |
| spellingShingle | Daniele Amparore Federico Piramide Paolo Verri Enrico Checcucci Alberto Piana Giuseppe Basile Alessandro Larcher Andrea Gallioli Angelo Territo Josep Maria Gaya Pietro Piazza Stefano Puliatti Antonio Andrea Grosso Andrea Mari Riccardo Campi Laura Zuluaga Ucpinar Burak Badani Ketan Sergio Serni Umberto Capitanio Francesco Montorsi Alexandre Mottrie Cristian Fiori Andrea Minervini Peter Wiklund Alberto Breda Francesco Porpiglia Nephrometry Scores Based on Three-dimensional Virtual Models Improve the Accuracy of Predicting Postoperative Complications After Robotic Partial Nephrectomy: Results from a Collaborative ERUS Validation Study European Urology Open Science Three-dimensional imaging Robotic surgery Renal cell carcinoma Kidney cancer Nephron-sparing surgery Nephrometry scores |
| title | Nephrometry Scores Based on Three-dimensional Virtual Models Improve the Accuracy of Predicting Postoperative Complications After Robotic Partial Nephrectomy: Results from a Collaborative ERUS Validation Study |
| title_full | Nephrometry Scores Based on Three-dimensional Virtual Models Improve the Accuracy of Predicting Postoperative Complications After Robotic Partial Nephrectomy: Results from a Collaborative ERUS Validation Study |
| title_fullStr | Nephrometry Scores Based on Three-dimensional Virtual Models Improve the Accuracy of Predicting Postoperative Complications After Robotic Partial Nephrectomy: Results from a Collaborative ERUS Validation Study |
| title_full_unstemmed | Nephrometry Scores Based on Three-dimensional Virtual Models Improve the Accuracy of Predicting Postoperative Complications After Robotic Partial Nephrectomy: Results from a Collaborative ERUS Validation Study |
| title_short | Nephrometry Scores Based on Three-dimensional Virtual Models Improve the Accuracy of Predicting Postoperative Complications After Robotic Partial Nephrectomy: Results from a Collaborative ERUS Validation Study |
| title_sort | nephrometry scores based on three dimensional virtual models improve the accuracy of predicting postoperative complications after robotic partial nephrectomy results from a collaborative erus validation study |
| topic | Three-dimensional imaging Robotic surgery Renal cell carcinoma Kidney cancer Nephron-sparing surgery Nephrometry scores |
| url | http://www.sciencedirect.com/science/article/pii/S2666168325000606 |
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