Integration of Three-Dimensional Liver Models in a Multimodal Image-Guided Robotic Liver Surgery Cockpit
<b>Background:</b> Robotic liver surgery represents the most recent evolution in the field of minimally-invasive liver surgery. For planning and guidance of liver resections, surgeons currently rely on preoperative 2-dimensional (2D) CT and/or MR imaging and intraoperative ultrasonograph...
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MDPI AG
2022-04-01
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author | Okker D. Bijlstra Alexander Broersen Timo T. M. Oosterveer Robin A. Faber Friso B. Achterberg Rob Hurks Mark C. Burgmans Jouke Dijkstra J. Sven D. Mieog Alexander L. Vahrmeijer Rutger-Jan Swijnenburg |
author_facet | Okker D. Bijlstra Alexander Broersen Timo T. M. Oosterveer Robin A. Faber Friso B. Achterberg Rob Hurks Mark C. Burgmans Jouke Dijkstra J. Sven D. Mieog Alexander L. Vahrmeijer Rutger-Jan Swijnenburg |
author_sort | Okker D. Bijlstra |
collection | DOAJ |
description | <b>Background:</b> Robotic liver surgery represents the most recent evolution in the field of minimally-invasive liver surgery. For planning and guidance of liver resections, surgeons currently rely on preoperative 2-dimensional (2D) CT and/or MR imaging and intraoperative ultrasonography. Translating 2D images into digital 3-dimensional (3D) models may improve both preoperative planning and surgical guidance. The da Vinci<sup>®</sup> robotic surgical system is a platform suitable for the integration of multiple imaging modalities into one single view. In this study, we describe multimodal imaging options and introduce the Robotic Liver Surgery Cockpit; <b>Methods:</b> in-house developed software was used and validated for segmentation and registration to create a virtual reality 3D model of the liver based on preoperative imaging. The accuracy of the 3D models in the clinical setting was objectively assessed in 15 patients by measuring tumor diameters and subjectively with a postoperative conducted questionnaire; <b>Results:</b> Implementation and applicability of the 3D model in the surgical cockpit was feasible in all patients and the quality of the 3D reconstructions was high in 14 (93%) of cases. Tumor diameters measured on CT and/or MR imaging were comparable to automated measurements using the segmentation software and 3D models; <b>Conclusions:</b> the 3D model was successfully incorporated in the robotic surgery console as part of a multimodality imaging platform and aided the surgeon in planning and guidance of the resection. Future studies should focus on further automation of 3D rendering and progress into augmented reality. |
first_indexed | 2024-03-10T03:34:00Z |
format | Article |
id | doaj.art-a223f78ff17f4ea5b1a51700b18a469f |
institution | Directory Open Access Journal |
issn | 2075-1729 |
language | English |
last_indexed | 2024-03-10T03:34:00Z |
publishDate | 2022-04-01 |
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series | Life |
spelling | doaj.art-a223f78ff17f4ea5b1a51700b18a469f2023-11-23T11:49:40ZengMDPI AGLife2075-17292022-04-0112566710.3390/life12050667Integration of Three-Dimensional Liver Models in a Multimodal Image-Guided Robotic Liver Surgery CockpitOkker D. Bijlstra0Alexander Broersen1Timo T. M. Oosterveer2Robin A. Faber3Friso B. Achterberg4Rob Hurks5Mark C. Burgmans6Jouke Dijkstra7J. Sven D. Mieog8Alexander L. Vahrmeijer9Rutger-Jan Swijnenburg10Department of Surgery, Leiden University Medical Center, 2333 ZA Leiden, The NetherlandsSection of Image Processing, Department of Radiology, Leiden University Medical Center, 2333 ZA Leiden, The NetherlandsSection of Interventional Radiology, Department of Radiology, Leiden University Medical Center, 2333 ZA Leiden, The NetherlandsDepartment of Surgery, Leiden University Medical Center, 2333 ZA Leiden, The NetherlandsDepartment of Surgery, Leiden University Medical Center, 2333 ZA Leiden, The NetherlandsDepartment of Radiology, Amsterdam University Medical Center, 1081 HV Amsterdam, The NetherlandsSection of Interventional Radiology, Department of Radiology, Leiden University Medical Center, 2333 ZA Leiden, The NetherlandsSection of Image Processing, Department of Radiology, Leiden University Medical Center, 2333 ZA Leiden, The NetherlandsDepartment of Surgery, Leiden University Medical Center, 2333 ZA Leiden, The NetherlandsDepartment of Surgery, Leiden University Medical Center, 2333 ZA Leiden, The NetherlandsDepartment of Surgery, Amsterdam University Medical Center, Cancer Center Amsterdam, University of Amsterdam, 1081 HV Amsterdam, The Netherlands<b>Background:</b> Robotic liver surgery represents the most recent evolution in the field of minimally-invasive liver surgery. For planning and guidance of liver resections, surgeons currently rely on preoperative 2-dimensional (2D) CT and/or MR imaging and intraoperative ultrasonography. Translating 2D images into digital 3-dimensional (3D) models may improve both preoperative planning and surgical guidance. The da Vinci<sup>®</sup> robotic surgical system is a platform suitable for the integration of multiple imaging modalities into one single view. In this study, we describe multimodal imaging options and introduce the Robotic Liver Surgery Cockpit; <b>Methods:</b> in-house developed software was used and validated for segmentation and registration to create a virtual reality 3D model of the liver based on preoperative imaging. The accuracy of the 3D models in the clinical setting was objectively assessed in 15 patients by measuring tumor diameters and subjectively with a postoperative conducted questionnaire; <b>Results:</b> Implementation and applicability of the 3D model in the surgical cockpit was feasible in all patients and the quality of the 3D reconstructions was high in 14 (93%) of cases. Tumor diameters measured on CT and/or MR imaging were comparable to automated measurements using the segmentation software and 3D models; <b>Conclusions:</b> the 3D model was successfully incorporated in the robotic surgery console as part of a multimodality imaging platform and aided the surgeon in planning and guidance of the resection. Future studies should focus on further automation of 3D rendering and progress into augmented reality.https://www.mdpi.com/2075-1729/12/5/667robotic surgeryliver surgerymultimodal imagingimage-guided surgeryvirtual reality3D |
spellingShingle | Okker D. Bijlstra Alexander Broersen Timo T. M. Oosterveer Robin A. Faber Friso B. Achterberg Rob Hurks Mark C. Burgmans Jouke Dijkstra J. Sven D. Mieog Alexander L. Vahrmeijer Rutger-Jan Swijnenburg Integration of Three-Dimensional Liver Models in a Multimodal Image-Guided Robotic Liver Surgery Cockpit Life robotic surgery liver surgery multimodal imaging image-guided surgery virtual reality 3D |
title | Integration of Three-Dimensional Liver Models in a Multimodal Image-Guided Robotic Liver Surgery Cockpit |
title_full | Integration of Three-Dimensional Liver Models in a Multimodal Image-Guided Robotic Liver Surgery Cockpit |
title_fullStr | Integration of Three-Dimensional Liver Models in a Multimodal Image-Guided Robotic Liver Surgery Cockpit |
title_full_unstemmed | Integration of Three-Dimensional Liver Models in a Multimodal Image-Guided Robotic Liver Surgery Cockpit |
title_short | Integration of Three-Dimensional Liver Models in a Multimodal Image-Guided Robotic Liver Surgery Cockpit |
title_sort | integration of three dimensional liver models in a multimodal image guided robotic liver surgery cockpit |
topic | robotic surgery liver surgery multimodal imaging image-guided surgery virtual reality 3D |
url | https://www.mdpi.com/2075-1729/12/5/667 |
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