Robot assisted Fetoscopic Laser Coagulation: Improvements in navigation, re-location and coagulation.


Por: Hernansanz A, Parra-Hernandez JA, Sayols N, Eixarch E, Gratacós E and Casals-Gelpi A

Publicada: 1 ene 2024 Ahead of Print: 25 nov 2023
Resumen:
Fetoscopic Laser Coagulation (FLC) for Twin to Twin Transfusion Syndrome is a challenging intervention due to the working conditions: low quality images acquired from a 3 mm fetoscope inside a turbid liquid environment, local view of the placental surface, unstable surgical field and delicate tissue layers. FLC is based on locating, coagulating and reviewing anastomoses over the placenta's surface. The procedure demands the surgeons to generate a mental map of the placenta with the distribution of the anastomoses, maintaining, at the same time, precision in coagulation and protecting the placenta and amniotic sac from potential damages. This paper describes a teleoperated platform with a cognitive-based control that provides assistance to improve patient safety and surgery performance during fetoscope navigation, target re-location and coagulation processes. A comparative study between manual and teleoperated operation, executed in dry laboratory conditions, analyzes basic fetoscopic skills: fetoscope navigation and laser coagulation. Two exercises are proposed: first, fetoscope guidance and precise coagulation. Second, a resolved placenta (all anastomoses are indicated) to evaluate navigation, re-location and coagulation. The results are analyzed in terms of economy of movement, execution time, coagulation accuracy, amount of coagulated placental surface and risk of placenta puncture. In addition, new metrics, based on navigation and coagulation maps evaluate robotic performance. The results validate the developed platform, showing noticeable improvements in all the metrics.

Filiaciones:
Hernansanz A:
 Research Centre for Biomedical Engineering, Technical University of Catalonia, CREB-UPC, 08034 Barcelona, Spain

 Simulation, Imaging and Modelling for Biomedical Systems (SIMBIOsys-UPF), Barcelona, Spain

Parra-Hernandez JA:
 BCNatal Fetal Medicine Research Center (Hospital Clinic and Hospital Sant Joan de Deu), 08950 Esplugues de Llobregat, Spain

Sayols N:
 Research Centre for Biomedical Engineering, Technical University of Catalonia, CREB-UPC, 08034 Barcelona, Spain

 Simulation, Imaging and Modelling for Biomedical Systems (SIMBIOsys-UPF), Barcelona, Spain

Eixarch E:
 BCNatal Fetal Medicine Research Center (Hospital Clinic and Hospital Sant Joan de Deu), 08950 Esplugues de Llobregat, Spain

 Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain

 Centre for Biomedical Research on Rare Diseases (CIBER-ER), Barcelona, Spain

Gratacós E:
 BCNatal Fetal Medicine Research Center (Hospital Clinic and Hospital Sant Joan de Deu), 08950 Esplugues de Llobregat, Spain

 Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain

 Centre for Biomedical Research on Rare Diseases (CIBER-ER), Barcelona, Spain

Casals-Gelpi A:
 Research Centre for Biomedical Engineering, Technical University of Catalonia, CREB-UPC, 08034 Barcelona, Spain
ISSN: 09333657





Artificial Intelligence in Medicine
Editorial
ELSEVIER, RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS, Países Bajos
Tipo de documento: Article
Volumen: 147 Número:
Páginas: 102725-102725
WOS Id: 001166220100001
ID de PubMed: 38184348
imagen hybrid, Green Published

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