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Yedavalli V, Heit JJ, Dehkharghani S, Haerian H, Mcmenamy J, Honce J, Timpone VM, Harnain C, Kesselman A, Filly A, Beardsley A, Sakamoto B, Song C, Montuori J, Navot B, Mena FV, Giurgiutiu DV, Kitamura F, Lima FO, Silva H, Mont’Alverne FJ, Albers G. Performance of RAPID noncontrast CT stroke platform in large vessel occlusion and intracranial hemorrhage detection. Front Neurol 2023; 14:1324088. [PMID: 38156093 PMCID: PMC10753184 DOI: 10.3389/fneur.2023.1324088] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2023] [Accepted: 11/08/2023] [Indexed: 12/30/2023] Open
Abstract
Background Noncontrast CT (NCCT) is used to evaluate for intracerebral hemorrhage (ICH) and ischemia in acute ischemic stroke (AIS). Large vessel occlusions (LVOs) are a major cause of AIS, but challenging to detect on NCCT. Aims The purpose of this study is to evaluate an AI software called RAPID NCCT Stroke (RAPID, iSchemaView, Menlo Park, CA) for ICH and LVO detection compared to expert readers. Methods In this IRB approved retrospective, multicenter study, stand-alone performance of the software was assessed based on the consensus of 3 neuroradiologists and sensitivity and specificity were determined. The platform's performance was then compared to interpretation by readers comprised of eight general radiologists (GR) and three neuroradiologists (NR) in detecting ICH and hyperdense vessel sign (HVS) indicating LVO. Results A total of 244 cases were included. Of the 244, 115 were LVOs and 26 were ICHs. One hundred three cases did not have LVO nor ICH. Stand-alone performance of the software demonstrated sensitivities and specificities of 96.2 and 99.5% for ICH and 63.5 and 95.1% for LVO detection. Compared to all 11 readers and eight GR readers only respectively, the software demonstrated superiority, achieving significantly higher sensitivities (63.5% versus 43.6%, p < 0.0001 and 63.5% versus 40.9%, p = 0.001). Conclusion The RAPID NCCT Stroke platform demonstrates superior performance to radiologists for detecting LVO from a NCCT. Use of this software platform could lead to earlier LVO detection and expedited transfer of these patients to a thrombectomy capable center.
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Affiliation(s)
- Vivek Yedavalli
- The Johns Hopkins Hospital, Johns Hopkins Medicine, Baltimore, MD, United States
| | | | - Seena Dehkharghani
- Department of Radiology, New York University, New York, NY, United States
| | | | - John Mcmenamy
- Department of Radiology, New York University, New York, NY, United States
| | - Justin Honce
- Department of Radiology, University of Colorado, Denver, CO, United States
| | | | | | - Andrew Kesselman
- Department of Radiology, Stanford University, Standford, CA, United States
| | | | - Adam Beardsley
- Department of Radiology, University of Virginia Hospital, Charlottesville, VA, United States
| | | | - Chris Song
- Weill Cornell Medicine, Cornell University, New York, NY, United States
| | | | - Benjamin Navot
- Columbia College, Columbia University, New York, NY, United States
| | | | | | - Felipe Kitamura
- Department of Radiology, Universidade Federal de São Paulo, Dasa, Brazil
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