Abstract WP129: Artificial Intelligence For Automated Detection Of Intracranial Hemorrhage (RAPID ICH): Initial Clinical Experience
| Autor: | Warren Chang, Laura Eisenmenger, Russell Cerejo, Charles Li, Michael F Goldberg |
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| Rok vydání: | 2022 |
| Předmět: | |
| Zdroj: | Stroke. 53 |
| ISSN: | 1524-4628 0039-2499 |
| Popis: | Purpose: Intracranial hemorrhage (ICH) has high morbidity and mortality, but early intervention has been shown to improve clinical outcomes. Several applications have emerged using artificial intelligence (AI) for automated detection of ICH, including RAPID ICH (RICH, iSchemaView, Menlo Park, CA). We present our initial clinical experience with RICH in a busy Level 1 trauma center. Materials/Methods: The study was supervised by the local IRB. Emergency department (ED) patients and inpatients (IP) receiving head CTs on the ED scanner at a level 1 trauma center were included. RICH output ("no ICH" or "suspected ICH") was recorded for each exam. Initial interpreting emergency radiologists or neuroradiologists had access to RICH output. Radiology reports reporting ICH were positive and those without ICH were negative. A board certified neuroradiologist reviewed each case with access to the initial report, RICH output, and prior exams. In cases with disagreement between readers, a third reader adjudicated the result and their decision was considered final. Expert reads were used as the gold standard and sensitivity, specificity, negative predictive value (NPV) and positive predictive value (PPV) were calculated. Results: 1388 patients were included, 1251 from the ED and 137 IP. For the ED patients, 139 had ICH and 1112 did not, where as in the IP cohort, 100 had ICH and 37 did not. RICH demonstrated overall sensitivity of 79% (73% ED, 88% IP), overall specificity of 95% (96% ED, 84% IP), overall PPV of 76% (65% ED, 94% IP) and overall NPV of 96% (97% ED, 72% IP). Conclusion: RICH had relatively high sensitivity and very high specificity for ICH, with lower sensitivity/higher specificity in the ED, and higher sensitivity/lower specificity in IP. Active worklist reprioritization allows faster triage of potentially positive studies and earlier intervention potentially improving clinical outcomes, especially in IPs with longer average turnaround times for routine studies. |
| Databáze: | OpenAIRE |
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