Artificial Intelligence Application Expediates Surgical Team Evaluation as Part of Hemorrhagic Stroke Workflow Metrics

Introduction The mantra “time is brain” has led to significant efforts to expedite tPA administration time and initiation of mechanical thrombectomy for the treatment of ischemic stroke. Evidence supporting surgical intervention for intracerebral hemorrhage (ICH) remains elusive. Numerous clinical trials have had negative overall results and others are still on-going. Most investigators and trial protocols have agreed that intervention should occur rapidly to decrease the risk of hematoma expansion and reduce perihematomal edema, however no trial has directly studied this question. Artificial intelligence applications have been shown to improve ischemic stroke workflow metrics, both decreasing transfer times from outside hospitals and rapidly alerting the interventional teams. We aimed to determine whether the implementation of an ICH detection algorithm that provides immediate active notification to provider cell phones would improve hemorrhagic stroke workflow at our institution. Methods A retrospective review was performed of patients presenting between January 2018 and March 2022 who suffered a spontaneous ICH and for whom the neurosurgical service was consulted for possible surgical intervention. Stroke workflow metrics were compared pre- and post-implementation of the VizAI (Viz.ai, San Francisco, California, USA) smartphone application. Additional demographic, clinical, and radiographic information was all collected. Results 188 adult patients were identified during the study period. Time between identification of ICH to neurosurgical team notification was reduced by 50 minutes after the implementation of VizAI (p<0.002). The number increases to 57 minutes when hemorrhages not identified by the ICH algorithm were excluded. Discussion Active notification of the neurosurgical team by an artificial intelligence application significantly reduces the time from hemorrhage identification to surgical evaluation. Further studies are needed to evaluate whether this results in a clinical benefit. ### Competing Interest Statement John Dalfino is a consultant for MicroVention Terumo. ### Funding Statement All funding for this study was provided by the Department of Neurosurgery at Albany Medical Center. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Not Applicable The details of the IRB/oversight body that provided approval or exemption for the research described are given below: IRB approval for the research was provided by the Albany Medical College IRB. 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. Not Applicable 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). Not Applicable I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Not Applicable The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.