Assessment of Deep Learning-Based Triage Application for Acute Ischemic Stroke on Brain MRI in the Emergency Room

Backgrounds To improve the outcomes of acute ischemic stroke (AIS) patients, a well-organized triage system is essential in the emergency room (ER). This study aimed to assess the detection performance of a deep learning triage research application for AIS that was newly developed based on brain MRI in the ER. Methods This retrospective study consecutively enrolled 831 brain MRIs including mandatory diffusion-weighted image (DWI) performed in the ER of our institution from April to October 2021. MRIs were analyzed with this triage research application as the index test and results were compared with the gold standard of three neuroradiologists. We evaluated sensitivity, specificity, area under the receiver operating characteristic curve (AUROC), area under the precision-recall curve (AUPRC), and maximum F1 score for this application. We also compared changes in its detection performance with and without the addition of optional sequences, which were T1- and T2-weighted images. Results 831 individuals (mean age, 64 years ± 16; 399 men, 432 women) were enrolled and 201 were positive for AIS. The application showed detection performance as follows; sensitivity, 90%; specificity, 89%; AUROC, 0.95 (95% confidence interval, 0.93-0.96); AUPRC, 0.91 (95% confidence interval, 0.86-0.94); and maximum F1 score, 0.86. The addition of optional sequences led to inferior performance compared to the mandatory sequence alone for detecting AIS. Conclusions The triage research application accurately detected AIS in a real-world ER with no additional benefits to its detection performance with optional sequences. Therefore, the triage research application can potentially help clinicians detect AIS in the ER sufficiently/adequately with only mandatory DWI. ### Competing Interest Statement Heiko Meyer, Stefan Huwer, Gengyan Zhao, and Dongyeob Han are employees of Siemens. However, they had no role in the study design, data collection and analysis, or decision to publish this manuscript. Otherwise, Jimin Kim, Se Won Oh, and Jee Young Kim have nothing to disclose. ### Funding Statement None ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: This study was conducted according to the guidelines of the Declaration of Helsinki and approved by the Institutional review board of Eunpyeong St. Mary's Hospital, The Catholic University of Korea College of Medicine (Protocol number PC22RESI0057, approval date March 30, 2022). The institutional review board waived the requirement for informed consent. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes More information about its development and validation, and the open-source code of the initial version of the triage research application, NeuroTriage, are available at DOI: . The source code of the current version of this application cannot be disclosed due to the copyright policy of Siemens Healthineers. * AIS : Acute ischemic stroke DWI : diffusion-weighted image ADC : apparent diffusion coefficient AUROC : area under the receiver operating characteristic curve AUPRC : area under the precision-recall curve.