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. 2022 Apr 5:13:807145.
doi: 10.3389/fneur.2022.807145. eCollection 2022.

Hyperdense Artery Sign in Patients With Acute Ischemic Stroke-Automated Detection With Artificial Intelligence-Driven Software

Charlotte Sabine Weyland  1 , Panagiotis Papanagiotou  2   3 , Niclas Schmitt  1 , Olivier Joly  4 , Pau Bellot  4 , Yahia Mokli  5 , Peter Arthur Ringleb  5 , A Kastrup  6 , Markus A Möhlenbruch  1 , Martin Bendszus  1 , Simon Nagel  5 , Christian Herweh  1
Affiliations

Hyperdense Artery Sign in Patients With Acute Ischemic Stroke-Automated Detection With Artificial Intelligence-Driven Software

Charlotte Sabine Weyland et al. Front Neurol. .

Abstract

Background: Hyperdense artery sign (HAS) on non-contrast CT (NCCT) can indicate a large vessel occlusion (LVO) in patients with acute ischemic stroke. HAS detection belongs to routine reporting in patients with acute stroke and can help to identify patients in whom LVO is not initially suspected. We sought to evaluate automated HAS detection by commercial software and compared its performance to that of trained physicians against a reference standard.

Methods: Non-contrast CT scans from 154 patients with and without LVO proven by CT angiography (CTA) were independently rated for HAS by two blinded neuroradiologists and an AI-driven algorithm (Brainomix®). Sensitivity and specificity were analyzed for the clinicians and the software. As a secondary analysis, the clot length was automatically calculated by the software and compared with the length manually outlined on CTA images as the reference standard.

Results: Among 154 patients, 84 (54.5%) had CTA-proven LVO. HAS on the correct side was detected with a sensitivity and specificity of 0.77 (CI:0.66-0.85) and 0.87 (0.77-0.94), 0.8 (0.69-0.88) and 0.97 (0.89-0.99), and 0.93 (0.84-0.97) and 0.71 (0.59-0.81) by the software and readers 1 and 2, respectively. The automated estimation of the thrombus length was in moderate agreement with the CTA-based reference standard [intraclass correlation coefficient (ICC) 0.73].

Conclusion: Automated detection of HAS and estimation of thrombus length on NCCT by the tested software is feasible with a sensitivity and specificity comparable to that of trained neuroradiologists.

Keywords: acute ischemic stroke; artificial intelligence; computed tomography; hyperdense artery sign; large vessel occlusion.

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Conflict of interest statement

MB: Unrelated: grants from Siemens, Stryker, Hopp foundation, grants, and personal fees from Novartis and Guerbet, personal fees from Merck, Teva, Grifols, BBraun, Boehringer Ingelheim, Vascular Dynamics, Springer, Bayer, all outside the submitted work. MM: Unrelated: Consultancy: Medtronic, MicroVention, Stryker; Payment for Lectures Including Service on Speakers Bureaus: Medtronic, MicroVention, Stryker. *Money paid to the institution. OJ: Head of the Scientific Research at Brainomix, Oxford, UK. PB: Deep learning researcher at Brainomix, Oxford, UK. PR: Unrelated: Consultancy: Boehringer, Lecture fees from Bayer, Boehringer Ingelheim, BMS, Daichii Sankyo, Pfizer. SN: Unrelated: Consultancy: Brainomix, Boehringer Ingelheim; Payment for Lectures Including Service on Speakers Bureaus: Pfizer, Medtronic, Bayer AG. CH: Related: Consultancy: Brainomix, Oxford, UK. OJ and PB were employed by Brainomix Ltd. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Visualization of the software output—hyperdense artery sign (encircled in light blue) in the M1 segment together with early ischemic changes in the caudate and lentiform nucleus (marked in red) in a patient with acute M1-occlusion on the left side.
Figure 2
Figure 2
Receiver operating curves (ROC) for the software and 2 human readers ROC curves showing the accuracy of detecting hyperdense artery signs by the software (BX) and two human readers (Readers 1 and 2).
See this image and copyright information in PMC

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