In vitro comparison of manual and robotic endovascular thrombectomy for acute ischemic stroke.

Abstract

BACKGROUND:

Robotic endovascular systems have the potential to reduce radiation exposure to physicians and expand timely neurointerventional access to patients in remote areas. The goal of the study was to determine the feasibility of robotic endovascular thrombectomy (EVT) in an in vitro model.

METHODS:

In vitro procedures were conducted manually and robotically using the Corpath GRX robotic system in a human vascular simulator with an elastic ovine clot in the M1 segment of the left middle cerebral artery. Due to the limited device compatibility of the CorPath GRX, a simple technique with a stent retriever and guiding catheter without a balloon was used in the study. Seven robotic EVT and manual EVT were carried out in each group. Metrics including procedural time, success rate, and radiation dose were compared between the two groups.

RESULTS:

In robotic EVT, the mean total preparation and procedural time was 892 s, which was significantly longer than manual operation at 357 (p = 0.0001). There was no significant difference in the success rate between the two approaches (robotic: 28.6% vs. manual 42.9%, p = 0.577). The mean radiation exposure to operating physicians was significantly lower during robotic operation compared to manual operation (0.02 μSv vs. 0.22 μSv, p < 0.0001).

CONCLUSIONS:

Robotic EVT was feasible in our human vascular simulator with significantly reduced radiation exposure to the operating physicians, despite an increased length of procedure when compared to manual procedures. Future technological advancement is warranted for reducing procedural length using endovascular robotic techniques.

• Authors: Naoki Kaneko, Charles Beaman, Taichiro Imahori, Ariel Takayanagi, Hamidreza Saber, Satoshi Tateshima
• Journal: Interventional neuroradiology : journal of peritherapeutic neuroradiology, surgical procedures and related neurosciences (Interv Neuroradiol) Pg. 15910199231206315 (Oct 08 2023) ISSN: 2385-2011 [Electronic] United States
• PMID: 37807666 (Publication Type: Journal Article)