Three-Dimensional Virtual Model for Robot-Assisted Partial Nephrectomy (RAPN): Development of Study Protocol for Evaluation of the Learning Curve to Optimize the Precision and Accuracy of the 3D Imaging

Paolo Traverso,1,2,* Guglielmo Mantica,1,2,* Veronica Giasotto,2 Carlo Terrone1,2 1Department of Surgical and Diagnostic Integrated Sciences (DISC), University of Genova, Genova, Italy; 2IRCCS Policlinico San Martino, Genova, Italy*These authors contributed equally to this wo...

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Main Authors: Traverso P, Mantica G, Giasotto V, Terrone C
Format: Article
Language:English
Published: Dove Medical Press 2025-02-01
Series:Research and Reports in Urology
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Online Access:https://www.dovepress.com/three-dimensional-virtual-model-for-robot-assisted-partial-nephrectomy-peer-reviewed-fulltext-article-RRU
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Summary:Paolo Traverso,1,2,* Guglielmo Mantica,1,2,* Veronica Giasotto,2 Carlo Terrone1,2 1Department of Surgical and Diagnostic Integrated Sciences (DISC), University of Genova, Genova, Italy; 2IRCCS Policlinico San Martino, Genova, Italy*These authors contributed equally to this workCorrespondence: Guglielmo Mantica, Department of Surgical and Diagnostic Integrated Sciences (DISC), University of Genova, Largo Rosanna Benzi 20, Genova, 16132, Italy, Tel +39010555964, Email guglielmo.mantica@gmail.comAbstract: 3D models have been introduced as tools to improve surgeon’s precision during Robotic-Assisted Partial Nephrectomy (RAPN). They showed to provide accurate anatomical details, improve operative time and patient safety by reducing complications. Over the last years, several useful models have been developed and proposed. However, literature is still scant regarding if and how the experience of the operator, and the learning curve, may impact the accuracy and precision of the model. In this light, the aim of the study is to evaluate the accuracy, the interpersonal variability of the precision and the learning curve for the segmentation of RAPN 3D preoperative models starting from CT images. This study will identify the influence of operator experience and learning curves on the accuracy of 3D preoperative models in RAPN, optimizing workflows for broader clinical adoption.Keywords: 3D surgery, RAPN, three-dimensional, virtual model, nephrectomy
ISSN:2253-2447