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Evaluation of Artificial Intelligence–Powered Identification of Large-Vessel Occlusions in a Comprehensive Stroke Center
- Source :
- American Journal of Neuroradiology. 42:247-254
- Publication Year :
- 2020
- Publisher :
- American Society of Neuroradiology (ASNR), 2020.
-
Abstract
- BACKGROUND AND PURPOSE: Artificial intelligence algorithms have the potential to become an important diagnostic tool to optimize stroke workflow. Viz LVO is a medical product leveraging a convolutional neural network designed to detect large-vessel occlusions on CTA scans and notify the treatment team within minutes via a dedicated mobile application. We aimed to evaluate the detection accuracy of the Viz LVO in real clinical practice at a comprehensive stroke center. MATERIALS AND METHODS: Viz LVO was installed for this study in a comprehensive stroke center. All consecutive head and neck CTAs performed from January 2018 to March 2019 were scanned by the algorithm for detection of large-vessel occlusions. The system results were compared with the formal reports of senior neuroradiologists used as ground truth for the presence of a large-vessel occlusion. RESULTS: A total of 1167 CTAs were included in the study. Of these, 404 were stroke protocols. Seventy-five (6.4%) patients had a large-vessel occlusion as ground truth; 61 were detected by the system. Sensitivity was 0.81, negative predictive value was 0.99, and accuracy was 0.94. In the stroke protocol subgroup, 72 (17.8%) of 404 patients had a large-vessel occlusion, with 59 identified by the system, showing a sensitivity of 0.82, negative predictive value of 0.96, and accuracy of 0.89. CONCLUSIONS: Our experience evaluating Viz LVO shows that the system has the potential for early identification of patients with stroke with large-vessel occlusions, hopefully improving future management and stroke care.
- Subjects :
- Protocol (science)
Ground truth
business.industry
Retrospective cohort study
medicine.disease
Convolutional neural network
030218 nuclear medicine & medical imaging
03 medical and health sciences
Identification (information)
0302 clinical medicine
Predictive value of tests
Occlusion
Medicine
Radiology, Nuclear Medicine and imaging
Neurology (clinical)
Artificial intelligence
business
Stroke
030217 neurology & neurosurgery
Subjects
Details
- ISSN :
- 1936959X and 01956108
- Volume :
- 42
- Database :
- OpenAIRE
- Journal :
- American Journal of Neuroradiology
- Accession number :
- edsair.doi...........4e95d0a3174001568e2e2479fdd0fc93