Robotically assisted augmented reality system for identification of targeted lymph nodes in laparoscopic gynecological surgery: a first step toward the identification of sentinel node : Augmented reality in gynecological surgery

Autor: Lise Lecointre, Juan Verde, Laurent Goffin, Aïna Venkatasamy, Barbara Seeliger, Massimo Lodi, Lee L. Swanström, Chérif Akladios, Benoît Gallix
Přispěvatelé: Laboratoire des sciences de l'ingénieur, de l'informatique et de l'imagerie (ICube), École Nationale du Génie de l'Eau et de l'Environnement de Strasbourg (ENGEES)-Université de Strasbourg (UNISTRA)-Institut National des Sciences Appliquées - Strasbourg (INSA Strasbourg), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Les Hôpitaux Universitaires de Strasbourg (HUS)-Centre National de la Recherche Scientifique (CNRS)-Matériaux et Nanosciences Grand-Est (MNGE), Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)-Réseau nanophotonique et optique, Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA)-Centre National de la Recherche Scientifique (CNRS), Interface de Recherche Fondamentale et Appliquée en Cancérologie (IRFAC - Inserm U1113), Université de Strasbourg (UNISTRA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre Paul Strauss : Centre Régional de Lutte contre le Cancer (CRLCC)-Fédération de Médecine Translationelle de Strasbourg (FMTS), Immuno-Rhumatologie Moléculaire, Université de Strasbourg (UNISTRA)-Institut National de la Santé et de la Recherche Médicale (INSERM)
Rok vydání: 2022
Předmět:
Zdroj: Surgical Endoscopy
Surgical Endoscopy, 2022, ⟨10.1007/s00464-022-09409-1⟩
ISSN: 1432-2218
0930-2794
DOI: 10.1007/s00464-022-09409-1⟩
Popis: To prove feasibility of multimodal and temporal fusion of laparoscopic images with preoperative computed tomography scans for a real-time in vivo-targeted lymph node (TLN) detection during minimally invasive pelvic lymphadenectomy and to validate and enable such guidance for safe and accurate sentinel lymph node dissection, including anatomical landmarks in an experimental model.A measurement campaign determined the most accurate tracking system (UR5-Cobot versus NDI Polaris). The subsequent interventions on two pigs consisted of an identification of artificial TLN and anatomical landmarks without and with augmented reality (AR) assistance. The AR overlay on target structures was quantitatively evaluated. The clinical relevance of our system was assessed via a questionnaire completed by experienced and trainee surgeons.An AR-based robotic assistance system that performed real-time multimodal and temporal fusion of laparoscopic images with preoperative medical images was developed and tested. It enabled the detection of TLN and their surrounding anatomical structures during pelvic lymphadenectomy. Accuracy of the CT overlay was 90%, with overflow rates 6%. When comparing AR to direct vision, we found that scores were significatively higher in AR for all target structures. AR aided both experienced surgeons and trainees, whether it was for TLN, ureter, or vessel identification.This computer-assisted system was reliable, safe, and accurate, and the present achievements represent a first step toward a clinical study.
Databáze: OpenAIRE
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