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Navigating the Future of 3D Laparoscopic Liver Surgeries: Visualization of Internal Anatomy on Laparoscopic Images With Augmented Reality.
Oh, Moon Young; Yoon, Kyung Chul; Hyeon, Seulgi; Jang, Taesoo; Choi, Yeonjin; Kim, Junki; Kong, Hyoun-Joong; Chai, Young Jun.
Afiliación
  • Oh MY; Department of Surgery, Seoul National University College of Medicine, Seoul National University Boramae Medical Center.
  • Yoon KC; Department of Surgery, Seoul National University College of Medicine, Seoul National University Boramae Medical Center.
  • Hyeon S; Department of Surgery, Seoul National University College of Medicine, Seoul National University Boramae Medical Center.
  • Jang T; Department of Transdisciplinary Medicine, Seoul National University Hospital, Seoul, Korea.
  • Choi Y; Department of Transdisciplinary Medicine, Seoul National University Hospital, Seoul, Korea.
  • Kim J; Department of Transdisciplinary Medicine, Seoul National University Hospital, Seoul, Korea.
  • Kong HJ; Department of Transdisciplinary Medicine, Seoul National University Hospital, Seoul, Korea.
  • Chai YJ; Department of Surgery, Seoul National University College of Medicine, Seoul National University Boramae Medical Center.
Surg Laparosc Endosc Percutan Tech ; 2024 Jul 05.
Article en En | MEDLINE | ID: mdl-38965779
ABSTRACT

INTRODUCTION:

Liver tumor resection requires precise localization of tumors and blood vessels. Despite advancements in 3-dimensional (3D) visualization for laparoscopic surgeries, challenges persist. We developed and evaluated an augmented reality (AR) system that overlays preoperative 3D models onto laparoscopic images, offering crucial support for 3D visualization during laparoscopic liver surgeries.

METHODS:

Anatomic liver structures from preoperative computed tomography scans were segmented using open-source software including 3D Slicer and Maya 2022 for 3D model editing. A registration system was created with 3D visualization software utilizing a stereo registration input system to overlay the virtual liver onto laparoscopic images during surgical procedures. A controller was customized using a modified keyboard to facilitate manual alignment of the virtual liver with the laparoscopic image. The AR system was evaluated by 3 experienced surgeons who performed manual registration for a total of 27 images from 7 clinical cases. The evaluation criteria included registration time; measured in minutes, and accuracy; measured using the Dice similarity coefficient.

RESULTS:

The overall mean registration time was 2.4±1.7 minutes (range 0.3 to 9.5 min), and the overall mean registration accuracy was 93.8%±4.9% (range 80.9% to 99.7%).

CONCLUSION:

Our validated AR system has the potential to effectively enable the prediction of internal hepatic anatomic structures during 3D laparoscopic liver resection, and may enhance 3D visualization for select laparoscopic liver surgeries.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Surg Laparosc Endosc Percutan Tech Asunto de la revista: DIAGNOSTICO POR IMAGEM / GASTROENTEROLOGIA Año: 2024 Tipo del documento: Article Pais de publicación: Estados Unidos
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Surg Laparosc Endosc Percutan Tech Asunto de la revista: DIAGNOSTICO POR IMAGEM / GASTROENTEROLOGIA Año: 2024 Tipo del documento: Article Pais de publicación: Estados Unidos