Publication:
Virtual reality tumor navigated robotic radical prostatectomy by using three-dimensional reconstructed multiparametric prostate mri and (68)ga-psma pet/ct images: a useful tool to guide the robotic surgery?

dc.contributor.coauthorAksoy, Sertaç Fatih
dc.contributor.departmentSchool of Medicine
dc.contributor.kuauthorAltınmakas, Emre
dc.contributor.kuauthorBalbay, Mevlana Derya
dc.contributor.kuauthorCanda, Abdullah Erdem
dc.contributor.kuauthorÇil, Barbaros Erhan
dc.contributor.kuauthorEsen, Tarık
dc.contributor.kuauthorFalay, Fikri Okan
dc.contributor.kuauthorKordan, Yakup
dc.contributor.kuauthorKöseoğlu, Ersin
dc.contributor.schoolcollegeinstituteSCHOOL OF MEDICINE
dc.date.accessioned2024-11-09T22:59:25Z
dc.date.issued2020
dc.description.abstractObjectives: to evaluate the use and benefits of tumor navigation during performing robotic assisted radical prostatectomy (RARP). Patients and Methods: borders of the visible tumor(s) was/were and surrounding structures marked on multiparametric prostate magnetic resonance imaging (mpMRI) and 68Ga‐labeled prostate‐specific membrane antigen ligand using positron emission computed tomography (Ga68 PSMA‐PET/CT). Three dimensional (3D) reconstruction of the images were done that were transferred to virtual reality (VR) headsets and Da Vinci surgical robot via TilePro. Images were used as a guide during RARP procedures in five cases. Indocyanine green (ICG) guided pelvic lymph node dissection (n = 2) and Martini Klinik Neurosafe technique (n = 2) were also applied. Results: mean patient age was 60.6 ± 3.7 years (range, 56‐66). All VR models were finalized with the agreement of radiologist, urologist, nuclear physician, and engineer. Surgeon examined images before the surgery. All VR models were found very useful particularly in pT3 diseases. Pathological stages included pT2N0 (n = 1), pT3aN0 (n = 1), pT3aN1 (n = 2), and pT3bN1 (n = 1). Positive surgical margins (SMs) occurred in two patients with extensive disease (pT3aN1 and pT3bN1) and tumor occupied 30% and 50% of the prostate volumes. Mean estimated blood loss was 150 ± 86.6 cc (range, 100‐300). Mean follow‐up was 3.4 ± 1.7 months (range, 2‐6). No complication occurred during perioperative (0‐30 days) and postoperative (30‐90 days) periods in any patient. Conclusions: 3D reconstructed VR models by using mpMRI and Ga68 PSMA‐PET/CT images can be accurately prepared and effectively applied during RARP that might be a useful tool for tumor navigation. Images show prostate tumors and anatomy and might be a guide for the console surgeon. This is promising new technology that needs further study and validation.
dc.description.indexedbyPubMed
dc.description.issue3
dc.description.openaccessYES
dc.description.publisherscopeInternational
dc.description.sponsoredbyTubitakEuN/A
dc.description.volume1
dc.identifier.doi10.1002/bco2.16
dc.identifier.eissn2688-4526
dc.identifier.issn2688-4526
dc.identifier.quartileN/A
dc.identifier.scopus2-s2.0-85144599044
dc.identifier.urihttps://doi.org/10.1002/bco2.16
dc.identifier.urihttps://hdl.handle.net/20.500.14288/7882
dc.identifier.wos1173300300005
dc.keywords3D reconstruction
dc.keywordsAugmented reality
dc.keywordsRadical prostatectomy
dc.keywordsRobotic, training
dc.keywordsVirtual reality
dc.language.isoN/A
dc.publisherWiley
dc.relation.ispartofBJUI Compass
dc.subjectUrogenital diseases
dc.titleVirtual reality tumor navigated robotic radical prostatectomy by using three-dimensional reconstructed multiparametric prostate mri and (68)ga-psma pet/ct images: a useful tool to guide the robotic surgery?
dc.typeJournal Article
dspace.entity.typePublication
local.contributor.kuauthorCanda, Abdullah Erdem
local.contributor.kuauthorAltınmakas, Emre
local.contributor.kuauthorKöseoğlu, Ersin
local.contributor.kuauthorFalay, Fikri Okan
local.contributor.kuauthorKordan, Yakup
local.contributor.kuauthorÇil, Barbaros Erhan
local.contributor.kuauthorBalbay, Mevlana Derya
local.contributor.kuauthorEsen, Tarık
local.publication.orgunit1SCHOOL OF MEDICINE
local.publication.orgunit2School of Medicine
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relation.isOrgUnitOfPublication.latestForDiscoveryd02929e1-2a70-44f0-ae17-7819f587bedd
relation.isParentOrgUnitOfPublication17f2dc8e-6e54-4fa8-b5e0-d6415123a93e
relation.isParentOrgUnitOfPublication.latestForDiscovery17f2dc8e-6e54-4fa8-b5e0-d6415123a93e

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