Robotic Assistance in Percutaneous Liver Ablation Therapies: A Systematic Review and Meta-Analysis.

Euclidean error accuracy minimally invasive liver ablation navigation systems robotic percutaneous liver ablation

Journal

Annals of surgery open : perspectives of surgical history, education, and clinical approaches
ISSN: 2691-3593
Titre abrégé: Ann Surg Open
Pays: United States
ID NLM: 101769928

Informations de publication

Date de publication:
Jun 2024
Historique:
received: 29 09 2023
accepted: 19 02 2024
medline: 24 6 2024
pubmed: 24 6 2024
entrez: 24 6 2024
Statut: epublish

Résumé

The aim of this systematic review and meta-analysis is to identify current robotic assistance systems for percutaneous liver ablations, compare approaches, and determine how to achieve standardization of procedural concepts for optimized ablation outcomes. Image-guided surgical approaches are increasingly common. Assistance by navigation and robotic systems allows to optimize procedural accuracy, with the aim to consistently obtain adequate ablation volumes. Several databases (PubMed/MEDLINE, ProQuest, Science Direct, Research Rabbit, and IEEE Xplore) were systematically searched for robotic preclinical and clinical percutaneous liver ablation studies, and relevant original manuscripts were included according to the Preferred Reporting items for Systematic Reviews and Meta-Analyses guidelines. The endpoints were the type of device, insertion technique (freehand or robotic), planning, execution, and confirmation of the procedure. A meta-analysis was performed, including comparative studies of freehand and robotic techniques in terms of radiation dose, accuracy, and Euclidean error. The inclusion criteria were met by 33/755 studies. There were 24 robotic devices reported for percutaneous liver surgery. The most used were the MAXIO robot (8/33; 24.2%), Zerobot, and AcuBot (each 2/33, 6.1%). The most common tracking system was optical (25/33, 75.8%). In the meta-analysis, the robotic approach was superior to the freehand technique in terms of individual radiation (0.5582, 95% confidence interval [CI] = 0.0167-1.0996, dose-length product range 79-2216 mGy.cm), accuracy (0.6260, 95% CI = 0.1423-1.1097), and Euclidean error (0.8189, 95% CI = -0.1020 to 1.7399). Robotic assistance in percutaneous ablation for liver tumors achieves superior results and reduces errors compared with manual applicator insertion. Standardization of concepts and reporting is necessary and suggested to facilitate the comparison of the different parameters used to measure liver ablation results. The increasing use of image-guided surgery has encouraged robotic assistance for percutaneous liver ablations. This systematic review analyzed 33 studies and identified 24 robotic devices, with optical tracking prevailing. The meta-analysis favored robotic assessment, showing increased accuracy and reduced errors compared with freehand technique, emphasizing the need for conceptual standardization.

Sections du résumé

Objective UNASSIGNED
The aim of this systematic review and meta-analysis is to identify current robotic assistance systems for percutaneous liver ablations, compare approaches, and determine how to achieve standardization of procedural concepts for optimized ablation outcomes.
Background UNASSIGNED
Image-guided surgical approaches are increasingly common. Assistance by navigation and robotic systems allows to optimize procedural accuracy, with the aim to consistently obtain adequate ablation volumes.
Methods UNASSIGNED
Several databases (PubMed/MEDLINE, ProQuest, Science Direct, Research Rabbit, and IEEE Xplore) were systematically searched for robotic preclinical and clinical percutaneous liver ablation studies, and relevant original manuscripts were included according to the Preferred Reporting items for Systematic Reviews and Meta-Analyses guidelines. The endpoints were the type of device, insertion technique (freehand or robotic), planning, execution, and confirmation of the procedure. A meta-analysis was performed, including comparative studies of freehand and robotic techniques in terms of radiation dose, accuracy, and Euclidean error.
Results UNASSIGNED
The inclusion criteria were met by 33/755 studies. There were 24 robotic devices reported for percutaneous liver surgery. The most used were the MAXIO robot (8/33; 24.2%), Zerobot, and AcuBot (each 2/33, 6.1%). The most common tracking system was optical (25/33, 75.8%). In the meta-analysis, the robotic approach was superior to the freehand technique in terms of individual radiation (0.5582, 95% confidence interval [CI] = 0.0167-1.0996, dose-length product range 79-2216 mGy.cm), accuracy (0.6260, 95% CI = 0.1423-1.1097), and Euclidean error (0.8189, 95% CI = -0.1020 to 1.7399).
Conclusions UNASSIGNED
Robotic assistance in percutaneous ablation for liver tumors achieves superior results and reduces errors compared with manual applicator insertion. Standardization of concepts and reporting is necessary and suggested to facilitate the comparison of the different parameters used to measure liver ablation results. The increasing use of image-guided surgery has encouraged robotic assistance for percutaneous liver ablations. This systematic review analyzed 33 studies and identified 24 robotic devices, with optical tracking prevailing. The meta-analysis favored robotic assessment, showing increased accuracy and reduced errors compared with freehand technique, emphasizing the need for conceptual standardization.

Identifiants

pubmed: 38911657
doi: 10.1097/AS9.0000000000000406
pmc: PMC11191991
doi:

Types de publication

Journal Article

Langues

eng

Pagination

e406

Informations de copyright

Copyright © 2024 The Author(s). Published by Wolters Kluwer Health, Inc.

Auteurs

Ana K Uribe Rivera (AK)

From the IHU-Strasbourg, Institute of Image-Guided Surgery, Strasbourg, France.

Barbara Seeliger (B)

From the IHU-Strasbourg, Institute of Image-Guided Surgery, Strasbourg, France.
Department of Visceral and Digestive Surgery, University Hospitals of Strasbourg, Strasbourg, France.
IRCAD, Research Institute Against Digestive Cancer, Strasbourg, France.
ICube, UMR 7357 CNRS, INSERM U1328 RODIN, University of Strasbourg, Strasbourg, France.
Inserm U1110, Institute for Viral and Liver Diseases, Strasbourg. France.
Trustworthy AI Lab, Centre National de la Recherche Scientifique (CNRS), France.

Laurent Goffin (L)

ICube, UMR 7357 CNRS, INSERM U1328 RODIN, University of Strasbourg, Strasbourg, France.
Trustworthy AI Lab, Centre National de la Recherche Scientifique (CNRS), France.
Computational Surgery SAS, Schiltigheim, France.

Alain García-Vázquez (A)

From the IHU-Strasbourg, Institute of Image-Guided Surgery, Strasbourg, France.

Didier Mutter (D)

From the IHU-Strasbourg, Institute of Image-Guided Surgery, Strasbourg, France.
Department of Visceral and Digestive Surgery, University Hospitals of Strasbourg, Strasbourg, France.
IRCAD, Research Institute Against Digestive Cancer, Strasbourg, France.

Mariano E Giménez (ME)

From the IHU-Strasbourg, Institute of Image-Guided Surgery, Strasbourg, France.
IRCAD, Research Institute Against Digestive Cancer, Strasbourg, France.
DAICIM Foundation (Training, Research and Clinical Activity in Minimally Invasive Surgery), Buenos Aires, Argentina.

Classifications MeSH