First-in-human, real-time artificial intelligence assisted cerebral aneurysm coiling: a preliminary experience.
J Neurointerv Surg
; 2024 Jun 07.
Article
in En
| MEDLINE
| ID: mdl-38849208
ABSTRACT
BACKGROUND:
Neuroendovascular procedures require careful and simultaneous attention to multiple devices on multiple screens. Overlooking unintended device movements can result in complications. Advancements in artificial intelligence (AI) have enabled real-time notifications of device movements during procedures. We report our preliminary experience with real-time AI-assisted cerebral aneurysm coiling in humans.METHODS:
A real-time AI-assistance software (Neuro-Vascular Assist, iMed technologies, Tokyo, Japan) was used during coil embolization procedures in nine patients with an unruptured aneurysm. The AI system provided real-time notifications for 'coil marker approaching', 'guidewire movement', and 'device entry' on biplane fluoroscopic images. The efficacy, accuracy, and safety of the notifications were evaluated using video recordings.RESULTS:
The AI system functioned properly in all cases. The mean number of notifications for coil marker approaching, guidewire movement, and device entry per procedure was 20.0, 3.0, and 18.3, respectively. The overall precision and recall were 92.7% and 97.2%, respectively. Five of 26 true positive guidewire notifications (19%) resulted in adjustment of the guidewire back toward its original position, indicating the potential effectiveness of the AI system. No adverse events occurred.CONCLUSIONS:
The software was sufficiently accurate and safe in this preliminary study, suggesting its potential usefulness. To the best of our knowledge, this is the first reported use of a real-time AI system for assisting cerebral aneurysm coiling in humans. Large scale studies are warranted to validate its effectiveness. Real-time AI assistance has significant potential for future neuroendovascular therapy.
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Language:
En
Journal:
J Neurointerv Surg
Year:
2024
Document type:
Article
Affiliation country:
Japón
Country of publication:
Reino Unido