{
  "abstract": "Introduction If patients of suspected ELVO can be quickly screened and notified to clinicians in step of the NCCT test, it has the advantage of improving the prognosis by reducing the time required for treatment.Aim of Study The purpose of this study is to evaluate the time reduction from hospital door to endovascular treatment (EVT) when using a non-contrast CT (NCCT) basis AI solution to classify and notify patients with anterior large vessel occlusion (LVO).Method Post-AI cases were collected prospectively after applying the AI solution, and Pre-AI cases were retrospectively collected. The main comparison point was time difference from ER door to endovascular treatment between Pre-AI and Post-AI groups. Additionally, time from ER door to CT scan, CT scan to Stroke team treatment (STT), and STT to EVT were also compared between groups.Abstract A183 Figure 1Results A total of 25 EVT cases were enrolled prospectively, and 70 cases were retrospectively selected after 1:3 propensity score matching with age, gender and NIHSS. Time from ER door to EVT was significantly different between Pre-AI (174.7±75.0 min.) and Post-AI (147.7±31.6 min) [p=0.0155]. As other time metrics, the time from CT scan to Stroke team treatment (20.2±7.9 min. vs. 35.4±41.3 min., p=0.0043) and the time from CT scan to EVT (127.7±29.2 min. vs. 153.9±71.1 min., p=0.0127) were significantly reduced in Post-AI group.Abstract A183 Figure 2Conclusion It has been confirmed that quickly screening LVO patients and notifying clinicians by an AI solution at the clinical process can significantly reduce the time from ER admission to EVT, and it will influence to prognosis outcome.Conflict of Interest Yes This study was researched using Heuron StroCare Suite as an AI-based product, and Dr. Shin, Dr. Kim, and Dr. Lee are employees of Heuron Co., Ltd.",
  "authors": [
    {
      "affiliations": [
        "Heuron Co., Ltd., Seoul, South Korea"
      ],
      "name": "Dong Hoon Shin"
    },
    {
      "affiliations": [
        "Heuron Co., Ltd., Seoul, South Korea"
      ],
      "name": "Dohyun Kim"
    },
    {
      "affiliations": [
        "Soon Chun Hyang University Hospital Bucheon, Bucheon, South Korea"
      ],
      "name": "Aleum Lee"
    },
    {
      "affiliations": [
        "Gil Medical Center, Gachon University College of Medicine, Incheon, South Korea"
      ],
      "name": "Woo Sung Choi"
    },
    {
      "affiliations": [
        "Gil Medical Center, Gachon University College of Medicine, Incheon, South Korea"
      ],
      "name": "Yong Su Lim"
    }
  ],
  "title": "A183 The usability study of non-contrast ct based ai to reduce the time from hospital door to reperfusion in anterior large vessel occlusion",
  "uid": "a65ffc2b-9369-59f6-9bf2-aca203e17103"
}