Afreen Ryan, Ezzat Bahie, Kalagara Roshini, Dangayach Neha S, Kellner Christopher P
Neurosurgery, Icahn School of Medicine at Mount Sinai, New York, USA.
Cureus. 2025 Mar 18;17(3):e80790. doi: 10.7759/cureus.80790. eCollection 2025 Mar.
This case study explores the integration of Viz ICH Plus, an AI-powered intracerebral hemorrhage (ICH) detection system, into a centralized program called the Neuroemergencies Management and Transfer (NEMAT) program of a large urban healthcare system. The study highlights how Viz ICH Plus promptly identified a right parieto-occipital hematoma in a patient presenting with a headache, resulting in a marked reduction in interhospital transfer (IHT) time. The patient underwent a successful supratentorial craniotomy for hematoma evacuation and demonstrated significant cognitive and physical improvement over the following year. Viz ICH Plus reduced IHT time from approximately 200 to 101 minutes, expediting access to definitive care and improving patient outcomes. Standard of care radiology review of the scan and communication of results could have added to additional delays in transferring this patient to receive definitive care. This case study illustrates a substantial reduction in transfer time and highlights the potential of AI to transform stroke care by optimizing response times and facilitating timely interventions.
本案例研究探讨了Viz ICH Plus(一种人工智能驱动的脑出血检测系统)如何融入一个大型城市医疗系统的名为神经急症管理与转运(NEMAT)的集中项目。该研究强调了Viz ICH Plus如何迅速在一名头痛患者中识别出右侧顶枕部血肿,从而显著缩短了院间转运(IHT)时间。该患者接受了成功的幕上开颅血肿清除术,并在接下来的一年中显示出显著的认知和身体改善。Viz ICH Plus将IHT时间从约200分钟缩短至101分钟,加快了获得确定性治疗的速度并改善了患者预后。对扫描结果进行的标准护理放射学审查及结果传达可能会进一步延迟该患者接受确定性治疗的时间。本案例研究表明转运时间大幅缩短,并突出了人工智能通过优化响应时间和促进及时干预来改变中风护理的潜力。