Teaching and evolution in surgical planning of robotic partial nephrectomy with 3D printing models

This study aims to analyze the contribution of 3D printing to the teaching and development of robotic partial nephrectomy (RNP) for renal tumors. Evaluation of results in planning the technique, which may vary depending on the professional performing it. A prospective study involving 32 patients who were susceptible to undergoing RPN for renal tumor. Surgical planning (SP) by senior, junior, and resident surgeons was analyzed based on three variables: (1) Tomography (2D), (2) Three-dimensional (3D) tomography, and (3) With a 3D printed model. Three consecutive pre-surgery SP questionnaires were administered. A usability test was completed after surgery. The cohort has a high R.E.N.A.L. score (41% intermediate and 21% high). The use of the 3D printed model changes the SP relative to the CT image by 25.60% and 20.11% with the 3D CT image. The SP factor that varies the most with 3D printing is that related to vascular anatomy (43.84% - 56.82%), followed by assessment of tumor depth (37.67% - 43.18%). Senior urologists modified the vascular hilum passage by up to 63.16%, compared to less than 12.5% by junior urologists. Feelings of security (55.3%), stress (4%), assessment of vascular anatomy (58.9%), tumor depth (36.45%), and surgical time (30.4%) improved. 3D printing influences planning regardless of the professional level, improves safety, and decreases surgical time. Senior surgeons significantly modify the SP more when assessing vascular anatomy by proposing more advanced surgeries.

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Publication Details

Journal
Journal of Robotic Surgery
Published
2025-12-10
DOI
https://doi.org/10.1007/s11701-025-03007-8
Primary Topic
Anatomy and Medical Technology
Type
article
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article

Teaching and evolution in surgical planning of robotic partial nephrectomy with 3D printing models

Maite Urizar Gorosarri, Rubén I. García, D Lopez, Cristina Del Amo et al.
Journal of Robotic Surgery
Anatomy and Medical Technology
article

Teaching and evolution in surgical planning of robotic partial nephrectomy with 3D printing models

Maite Urizar Gorosarri, Rubén I. García, D Lopez, Cristina Del Amo, María Victoria Bárcena Robredo, Marcos García M, Ainara Rábade Ferreiro, C. Zubiaur Líbano, Isabel Lacasa Viscasillas, Ignacio Sanchez, Ana Loizaga Iriarte, Iñigo Alzaga Manso, Jorge González Tampán
article en

Abstract

This study aims to analyze the contribution of 3D printing to the teaching and development of robotic partial nephrectomy (RNP) for renal tumors. Evaluation of results in planning the technique, which may vary depending on the professional performing it. A prospective study involving 32 patients who were susceptible to undergoing RPN for renal tumor. Surgical planning (SP) by senior, junior, and resident surgeons was analyzed based on three variables: (1) Tomography (2D), (2) Three-dimensional (3D) tomography, and (3) With a 3D printed model. Three consecutive pre-surgery SP questionnaires were administered. A usability test was completed after surgery. The cohort has a high R.E.N.A.L. score (41% intermediate and 21% high). The use of the 3D printed model changes the SP relative to the CT image by 25.60% and 20.11% with the 3D CT image. The SP factor that varies the most with 3D printing is that related to vascular anatomy (43.84% - 56.82%), followed by assessment of tumor depth (37.67% - 43.18%). Senior urologists modified the vascular hilum passage by up to 63.16%, compared to less than 12.5% by junior urologists. Feelings of security (55.3%), stress (4%), assessment of vascular anatomy (58.9%), tumor depth (36.45%), and surgical time (30.4%) improved. 3D printing influences planning regardless of the professional level, improves safety, and decreases surgical time. Senior surgeons significantly modify the SP more when assessing vascular anatomy by proposing more advanced surgeries.

Journal of Robotic SurgeryVol. 20(1)
University of the Basque Country (ES), Instituto de Salud Carlos III (ES), BioCruces Health research Institute (ES), Hospital de Basurto (ES)
Openalex Percentile: Top 61%
Anatomy and Medical Technology
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