Publication:
The contribution of personalized video feedback to robotic partial nephrectomy training in realistic 3D tumor kidney models: design, production and implementation

dc.contributor.departmentSchool of Medicine
dc.contributor.departmentKUTTAM (Koç University Research Center for Translational Medicine)
dc.contributor.departmentRMK AIMES (Koç University RMK Academy of Interventional Medicine, Education, and Simulation)
dc.contributor.kuauthorSarıkaya, Ahmet Furkan
dc.contributor.kuauthorTarım, Kayhan
dc.contributor.kuauthorKöseoğlu, Ersin
dc.contributor.kuauthorÖzkan, Arif
dc.contributor.kuauthorAykanat, İbrahim Can
dc.contributor.kuauthorEsen, Barış
dc.contributor.kuauthorKaraarslan, Umut Can
dc.contributor.kuauthorMüdüroğlu, Mustafa
dc.contributor.kuauthorKiremit, Murat Can
dc.contributor.kuauthorKordan, Yakup
dc.contributor.kuauthorBalbay, Mevlana Derya
dc.contributor.kuauthorEsen, Tarık
dc.contributor.kuauthorAydın, Serdar Onur
dc.contributor.kuauthorCanda, Abdullah Erdem
dc.contributor.kuauthorKanlı, Şevval
dc.contributor.schoolcollegeinstituteSCHOOL OF MEDICINE
dc.contributor.schoolcollegeinstituteResearch Center
dc.date.accessioned2025-09-10T04:55:18Z
dc.date.available2025-09-09
dc.date.issued2025
dc.description.abstractBackground Traditional surgical training relies on a master-apprentice model, but limitations such as restricted working hours and evolving surgical techniques have led to the integration of simulation-based training. Three-dimensional (3D) printing has emerged as a valuable tool for enhancing surgical education, offering patient-specific anatomical models that improve skill acquisition. Additionally, personalized video feedback may further refine training outcomes. This study investigates the impact of 3D-printed renal models and video-based feedback on skill acquisition in robotic partial nephrectomy training.Methods Forty urology residents without prior robotic surgery experience participated in this study. After completing a standardized theoretical and simulation-based training program, they performed partial nephrectomy on 3D-printed kidney models. The participants were randomly assigned to two groups: one received personalized video feedback based on their recorded surgical performances, while the other proceeded without feedback. Their surgical performance was evaluated based on dissection time, renorrhaphy time, total console time, and the amount of healthy renal parenchyma removed. Statistical analysis was conducted to compare improvements between the groups and assess the impact of video feedback on skill development.Results Initial comparisons between junior and senior residents showed no significant differences in their first operations, demonstrating that e-learning and proficiency-based simulation training effectively equalized skill levels before transitioning to realistic 3D model-based training. This suggests that structured preparatory training with objective performance targets can enhance learning outcomes in surgical simulation. Additionally, 3D-printed models provide a significantly more cost-effective alternative to cadaveric and animal-based training, making high-quality surgical education more accessible and scalable. Residents who received video feedback demonstrated a greater percentage improvement in dissection time compared to the control group (46.63% vs. 23.62%, p = 0.043). The amount of healthy renal parenchyma removed significantly decreased in the video feedback group (p = 0.048), indicating improved surgical precision. No significant differences were observed in renorrhaphy times between the two groups, suggesting that video feedback primarily enhanced dissection skills.Conclusion The integration of 3D-printed anatomical models with personalized video feedback enhances skill acquisition in robotic partial nephrectomy training. Video feedback significantly improves surgical precision by reducing unnecessary parenchymal removal and accelerating dissection time. These findings support the use of patient-specific 3D models and targeted feedback as cost-effective and scalable strategies to optimize surgical education and shorten the learning curve for complex procedures.
dc.description.fulltextYes
dc.description.harvestedfromManual
dc.description.indexedbyWOS
dc.description.indexedbyScopus
dc.description.indexedbyPubMed
dc.description.openaccessGold OA
dc.description.publisherscopeInternational
dc.description.readpublishN/A
dc.description.sponsoredbyTubitakEuN/A
dc.description.versionPublished Version
dc.description.volume12
dc.identifier.doi10.3389/fsurg.2025.1615817
dc.identifier.embargoNo
dc.identifier.filenameinventorynoIR06345
dc.identifier.issn2296-875X
dc.identifier.quartileQ2
dc.identifier.scopus2-s2.0-105012269404
dc.identifier.urihttps://doi.org/10.3389/fsurg.2025.1615817
dc.identifier.urihttps://hdl.handle.net/20.500.14288/30058
dc.identifier.wos001540724100001
dc.keywordsRobotic partial nephrectomy
dc.keywords3D-printed kidney models
dc.keywordsVideo feedback
dc.keywordsSurgical simulation training
dc.keywordsUrology resident education
dc.language.isoeng
dc.publisherFrontiers Media Sa
dc.relation.affiliationKoç University
dc.relation.collectionKoç University Institutional Repository
dc.relation.ispartofFrontiers in Surgery
dc.relation.openaccessYes
dc.rightsCC BY (Attribution)
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectSurgery
dc.titleThe contribution of personalized video feedback to robotic partial nephrectomy training in realistic 3D tumor kidney models: design, production and implementation
dc.typeJournal Article
dspace.entity.typePublication
person.familyNameSarıkaya
person.familyNameTarım
person.familyNameKöseoğlu
person.familyNameÖzkan
person.familyNameAykanat
person.familyNameEsen
person.familyNameKaraarslan
person.familyNameMüdüroğlu
person.familyNameKiremit
person.familyNameKordan
person.familyNameBalbay
person.familyNameEsen
person.familyNameAydın
person.familyNameCanda
person.familyNameKanlı
person.givenNameAhmet Furkan
person.givenNameKayhan
person.givenNameErsin
person.givenNameArif
person.givenNameİbrahim Can
person.givenNameBarış
person.givenNameUmut Can
person.givenNameMustafa
person.givenNameMurat Can
person.givenNameYakup
person.givenNameMevlana Derya
person.givenNameTarık
person.givenNameSerdar Onur
person.givenNameAbdullah Erdem
person.givenNameŞevval
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