Abstract
Background: Artificial intelligence-based software may automatically detect ischaemic stroke lesions and provide an Alberta Stroke Program Early CT score (ASPECTS) on CT, and identify arterial occlusion and provide a collateral score on CTA. Large-scale independent testing will inform clinical use, but is lacking. We aim to test e-ASPECTS and e-CTA (Brainomix, Oxford UK) using CT scans obtained from a range of clinical studies. Methods: Using prospectively collected baseline CT and CTA scans from 10 national/international clinical stroke trials or registries (total >6600 patients), we will select a large clinically representative sample for testing e-ASPECTS and e-CTA compared to previously acquired independent expert human interpretation (reference standard). Our primary aims are to test agreement between software-derived and masked human expert ASPECTS, and the diagnostic accuracy of e-ASPECTS for identifying all causes of stroke symptoms using follow-up imaging and final clinical opinion as diagnostic ground truth. Our secondary aims are to test when and why e-ASPECTS is more or less accurate, or succeeds/fails to produce results, agreement between e-CTA and human expert CTA interpretation, and repeatability of e-ASPECTS/e-CTA results. All testing will be conducted on an intention-to-analyse basis. We will assess agreement between software and expert-human ratings and test the diagnostic accuracy of software. Conclusions: RITeS will provide comprehensive, robust and representative testing of e-ASPECTS and e-CTA against the current gold-standard, expert-human interpretation.
Highlights
Accurate and rapid identification and quantification of CT imaging features indicative of early ischaemic and haemorrhagic stroke is required to correctly triage patients for urgent treatment
A CT angiogram (CTA) may be required immediately after non-enhanced CT (NECT) to identify patients with arterial obstruction who are suitable for thrombectomy
Perform new human-ratings for a subgroup of the previously collected scans to compare the time needed for human versus e-Alberta Stroke Program Early CT score (ASPECTS) assessment of CT and to assess the clinical impact of e-ASPECTS software on acute stroke care, i.e. whether it influences diagnostic confidence or alters treatment decisions
Summary
Accurate and rapid identification and quantification of CT imaging features indicative of early ischaemic and haemorrhagic stroke is required to correctly triage patients for urgent treatment. Artificial intelligence-based software may automatically detect ischaemic stroke lesions and provide an Alberta Stroke Program Early CT score (ASPECTS) on CT, and identify arterial occlusion and provide a collateral score on CTA. Methods: Using prospectively collected baseline CT and CTA scans from 10 national/international clinical stroke trials or registries (total >6600 patients), we will select a large clinically representative sample for testing e-ASPECTS and e-CTA compared to previously acquired independent expert human interpretation (reference standard). Our primary aims are to test agreement between software-derived and masked human expert ASPECTS, and the diagnostic accuracy of eASPECTS for identifying all causes of stroke symptoms using follow-up imaging and final clinical opinion as diagnostic ground truth. Our secondary aims are to test when and why e-ASPECTS is more or less accurate, or succeeds/fails to produce results, agreement between eCTA and human expert CTA interpretation, and repeatability of eASPECTS/e-CTA results. Conclusions: RITeS will provide comprehensive, robust and representative testing of e-ASPECTS and e-CTA against the current
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