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Quantitative Assessment and Objective Improvement of the Accuracy of Neurosurgical Planning Through Digital Patient-Specific 3d Models

dc.contributor.author Hanalioglu, Sahin
dc.contributor.author Gurses, Muhammet Enes
dc.contributor.author Baylarov, Baylar
dc.contributor.author Tunc, Osman
dc.contributor.author Isikay, Ilkay
dc.contributor.author Cagiltay, Nergiz Ercil
dc.contributor.author Berker, Mustafa
dc.date.accessioned 2025-05-11T17:04:35Z
dc.date.available 2025-05-11T17:04:35Z
dc.date.issued 2024
dc.description Gurses, Muhammet Enes/0000-0001-7141-0654 en_US
dc.description.abstract Objective Neurosurgical patient-specific 3D models have been shown to facilitate learning, enhance planning skills and improve surgical results. However, there is limited data on the objective validation of these models. Here, we aim to investigate their potential for improving the accuracy of surgical planning process of the neurosurgery residents and their usage as a surgical planning skill assessment tool.Methods A patient-specific 3D digital model of parasagittal meningioma case was constructed. Participants were invited to plan the incision and craniotomy first after the conventional planning session with MRI, and then with 3D model. A feedback survey was performed at the end of the session. Quantitative metrics were used to assess the performance of the participants in a double-blind fashion.Results A total of 38 neurosurgical residents and interns participated in this study. For estimated tumor projection on scalp, percent tumor coverage increased (66.4 +/- 26.2%-77.2 +/- 17.4%, p = 0.026), excess coverage decreased (2,232 +/- 1,322 mm2-1,662 +/- 956 mm2, p = 0.019); and craniotomy margin deviation from acceptable the standard was reduced (57.3 +/- 24.0 mm-47.2 +/- 19.8 mm, p = 0.024) after training with 3D model. For linear skin incision, deviation from tumor epicenter significantly reduced from 16.3 +/- 9.6 mm-8.3 +/- 7.9 mm after training with 3D model only in residents (p = 0.02). The participants scored realism, performance, usefulness, and practicality of the digital 3D models very highly.Conclusion This study provides evidence that patient-specific digital 3D models can be used as educational materials to objectively improve the surgical planning accuracy of neurosurgical residents and to quantitatively assess their surgical planning skills through various surgical scenarios. en_US
dc.description.sponsorship Hacettepe University Scientific Research Projects Coordination Unit en_US
dc.description.sponsorship No Statement Available en_US
dc.identifier.doi 10.3389/fsurg.2024.1386091
dc.identifier.issn 2296-875X
dc.identifier.scopus 2-s2.0-85203008793
dc.identifier.uri https://doi.org/10.3389/fsurg.2024.1386091
dc.identifier.uri https://hdl.handle.net/20.500.12416/9643
dc.language.iso en en_US
dc.publisher Frontiers Media Sa en_US
dc.relation.ispartof Frontiers in Surgery
dc.rights info:eu-repo/semantics/openAccess en_US
dc.subject 3D Model en_US
dc.subject Surgical Planning en_US
dc.subject Simulation en_US
dc.subject Assessment en_US
dc.subject Education en_US
dc.subject Brain Tumor en_US
dc.title Quantitative Assessment and Objective Improvement of the Accuracy of Neurosurgical Planning Through Digital Patient-Specific 3d Models en_US
dc.type Article en_US
dspace.entity.type Publication
gdc.author.id Gurses, Muhammet Enes/0000-0001-7141-0654
gdc.author.scopusid 55801129800
gdc.author.scopusid 57371994800
gdc.author.scopusid 58942884200
gdc.author.scopusid 58934762200
gdc.author.scopusid 25936413500
gdc.author.scopusid 16237826800
gdc.author.scopusid 8297268600
gdc.author.wosid Tunç, Osman/Iyj-4846-2023
gdc.author.wosid Hanalioglu, Sahin/Agh-8775-2022
gdc.author.wosid Cagiltay, Nergiz/O-3082-2019
gdc.author.wosid Gurses, Muhammet Enes/Gwr-4954-2022
gdc.author.wosid Isikay, Ilkay/Htl-5521-2023
gdc.bip.impulseclass C4
gdc.bip.influenceclass C4
gdc.bip.popularityclass C4
gdc.coar.access open access
gdc.coar.type text::journal::journal article
gdc.collaboration.industrial true
gdc.description.department Çankaya University en_US
gdc.description.departmenttemp [Hanalioglu, Sahin; Gurses, Muhammet Enes; Baylarov, Baylar; Isikay, Ilkay; Berker, Mustafa] Hacettepe Univ, Fac Med, Dept Neurosurg, Ankara, Turkiye; [Tunc, Osman] METU Technopark, BTech Innovat, Ankara, Turkiye; [Cagiltay, Nergiz Ercil] Cankaya Univ, Dept Software Engn, Ankara, Turkiye; [Tatar, Ilkan] Hacettepe Univ, Fac Med, Dept Anat, Ankara, Turkiye en_US
gdc.description.publicationcategory Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı en_US
gdc.description.scopusquality Q2
gdc.description.volume 11 en_US
gdc.description.woscitationindex Science Citation Index Expanded
gdc.description.wosquality Q2
gdc.identifier.openalex W4395079158
gdc.identifier.pmid 38721022
gdc.identifier.wos WOS:001215603200001
gdc.index.type WoS
gdc.index.type Scopus
gdc.index.type PubMed
gdc.oaire.accesstype GOLD
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gdc.oaire.impulse 7.0
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gdc.oaire.keywords 3D model
gdc.oaire.keywords surgical planning
gdc.oaire.keywords education
gdc.oaire.keywords RD1-811
gdc.oaire.keywords assessment
gdc.oaire.keywords Surgery
gdc.oaire.keywords simulation
gdc.oaire.keywords brain tumor
gdc.oaire.popularity 7.933576E-9
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gdc.oaire.sciencefields 03 medical and health sciences
gdc.oaire.sciencefields 0302 clinical medicine
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gdc.scopus.citedcount 7
gdc.virtual.author Çağıltay, Nergiz
gdc.wos.citedcount 6
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