Evidence map›Paper›PMID 39961616›Full record

ArticleAJNR. American journal of neuroradiology2025

World's First Real-Time Artificial Intelligence-Assisted Mechanical Thrombectomy for Acute Ischemic Stroke.

Eisuke Hirose, Yoshikazu Matsuda, Syun Takano, Ryo Aiura, Kenichi Kono, Tohru Mizutani

Abstract read
In one paragraph

Article in AJNR. American journal of neuroradiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Eisuke HiroseFrom the Department of Neurosurgery (E.H., Y.M., S.T., R.A., T.M.), Showa Medical University Hospital, Tokyo, Japan.
Yoshikazu MatsudaFrom the Department of Neurosurgery (E.H., Y.M., S.T., R.A., T.M.), Showa Medical University Hospital, Tokyo, Japan ymatsuda0517@yahoo.co.jp.ORCID https://orcid.org/0000-0002-3817-8918
Syun TakanoFrom the Department of Neurosurgery (E.H., Y.M., S.T., R.A., T.M.), Showa Medical University Hospital, Tokyo, Japan.
Ryo AiuraFrom the Department of Neurosurgery (E.H., Y.M., S.T., R.A., T.M.), Showa Medical University Hospital, Tokyo, Japan.
Kenichi KonoDepartment of Neurosurgery (K.K.), Showa Medical University Fujigaoka Hospital, Yokohama, Kanagawa, Japan.ORCID https://orcid.org/0000-0003-0006-076X
Tohru MizutaniFrom the Department of Neurosurgery (E.H., Y.M., S.T., R.A., T.M.), Showa Medical University Hospital, Tokyo, Japan.ORCID https://orcid.org/0000-0003-4762-8332

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Several recent reports have discussed real-time artificial intelligence (AI) assistance in elective neuroendovascular procedures such as carotid artery stent placement, coil embolization for cerebral aneurysms, and liquid embolization. We present our preliminary experience with real-time AI-assisted mechanical thrombectomy (MT) for acute ischemic stroke (AIS) under local anesthesia. A real-time deep learning-based AI software (Neuro-Vascular Assist, iMed Technologies) was used during MT for 16 consecutive patients with AIS. The AI system provided real-time notifications when the guiding catheter (GC) moved out of the fluoroscopic image. The efficacy, accuracy, and safety of the notifications were evaluated by using video recordings. The AI system functioned properly in all cases. The mean number of notifications per case for the GC moving out of view was 8.1. The overall precision and recall of AI notifications were 97% and 99%, respectively. Of the 126 true-positive AI notifications, 25 (20%) prompted operators to reposition the GC within 10 seconds when it became unobservable in both frontal and lateral imaging planes. This response indicates the potential effectiveness of the AI system. No adverse events or delays in procedures due to the AI system occurred. In this preliminary study, the software was sufficiently accurate and safe for MT procedures, suggesting its usefulness. To the best of our knowledge, this is one of the first studies to report using a real-time AI system for MT in patients with AIS as an emergent procedure. Large-scale studies are warranted to validate its impact on procedural workflow and clinical outcomes.

Indexed as

Artificial IntelligenceIschemic StrokeMechanical ThrombolysisSurgery, Computer-AssistedThrombectomyAgedAged, 80 and overComputer SystemsDeep LearningFemaleHumansMaleMiddle Aged

Identifiers

PMID39961616
PMCPMC12453512

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.