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ArticleClinical neuroradiology2026

Real-Time AI-Generated Guidewire-Out-of-View Notifications in Diagnostic Cerebral Angiography: Higher Observed Rates Among Trainees.

Syun Takano, Yoshikazu Matsuda, Kenichi Kono, Yuya Sakakura, Yuma Miki, Ryo Aiura, Eisuke Hirose, Tohru Mizutani, Yoichi Morofuji

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Article in Clinical neuroradiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

9 authors.

Syun TakanoDepartment of Neurosurgery, Showa Medical University Koto Toyosu Hospital, Tokyo, Japan.
Yoshikazu MatsudaDepartment of Neurosurgery, Showa Medical University Hospital, Tokyo, Japan. ymatsuda0517@yahoo.co.jp.ORCID https://orcid.org/0000-0002-3817-8918
Kenichi KonoiMed Technologies, Tokyo, Japan. vyr01450@gmail.com.ORCID https://orcid.org/0000-0003-0006-076X
Yuya SakakuraDepartment of Neurosurgery, NTT Medical Center Tokyo, Tokyo, Japan.ORCID https://orcid.org/0000-0002-2947-8812
Yuma MikiDepartment of Neurosurgery, Showa Medical University Koto Toyosu Hospital, Tokyo, Japan.
Ryo AiuraDepartment of Neurosurgery, Showa Medical University Hospital, Tokyo, Japan.
Eisuke HiroseDepartment of Neurosurgery, Showa Medical University Koto Toyosu Hospital, Tokyo, Japan.
Tohru MizutaniDepartment of Neurosurgery, Showa Medical University Koto Toyosu Hospital, Tokyo, Japan.
Yoichi MorofujiDepartment of Neurosurgery, Showa Medical University Hospital, Tokyo, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeEvaluation of technical proficiency plays a critical role in ensuring the safety and efficacy of neuroendovascular procedures. However, objective and quantitative assessment methods that are suitable for clinical practice remain scarce or unavailable. To address this limitation, this study examined whether real-time notifications from intraoperative artificial intelligence (AI)-assisted systems can serve as objective indicators of procedural skills.

methodsWe retrospectively analyzed 200 consecutive digital subtraction angiography (DSA) cases performed at our institution using a real-time AI-assisted system called neuro-vascular assist (iMed Technologies, Tokyo, Japan). The procedures were performed by either board-certified neuroendovascular specialists with extensive experience or noncertified trainees. We compared AI notifications and procedural parameters between the groups and evaluated the association between certification status and AI notifications using mixed-effects logistic regression with a random intercept for operator and adjustment for case-mix.

resultsUnivariate analysis revealed that trainees exhibited significantly higher frequency of AI notifications (62.5% vs 41.9%; P = 0.01) and longer fluoroscopy times (P = 0.02) compared to specialists. Furthermore, multivariable mixed-effects logistic regression accounting for case-mix and within-operator clustering showed twofold higher odds of an AI notification in trainees, but the association was not statistically significant (adjusted OR 2.10, 95% CI 0.68-6.49; P = 0.20).

conclusionThis study provides preliminary evidence that intraoperative AI notifications may reflect differences in technical behavior according to operator certification status. Although the adjusted association was not statistically significant, these findings suggest the potential of AI-assisted systems as proof-of-concept tools for evaluating technical proficiency. Further validation involving a larger number of operators is required.

Indexed as

Artificial intelligenceDiagnostic cerebral angiographyNeuroendovascular therapyTechnical skill assessment

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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.