Mair Grant, Chappell Francesca, Martin Chloe, Dye David, Bath Philip M, Muir Keith W, von Kummer Rüdiger, Al-Shahi Salman Rustam, Sandercock Peter A G, Macleod Malcolm, Sprigg Nikola, White Philip, Wardlaw Joanna M
Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, EH16 4SB, UK.
Stroke Trials Unit, University of Nottingham, Nottingham, NG5 1PB, UK.
AMRC Open Res. 2020 Apr 28;2:20. doi: 10.12688/amrcopenres.12904.1.
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. 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. RITeS will provide comprehensive, robust and representative testing of e-ASPECTS and e-CTA against the current gold-standard, expert-human interpretation.
基于人工智能的软件可自动检测缺血性中风病灶，并在CT上提供阿尔伯塔中风项目早期CT评分（ASPECTS），还能识别动脉闭塞并在CT血管造影（CTA）上提供侧支循环评分。大规模的独立测试将为临床应用提供依据，但目前尚缺此类测试。我们旨在使用从一系列临床研究中获取的CT扫描图像来测试电子ASPECTS和电子CTA（Brainomix公司，英国牛津）。我们将从10项国家/国际临床中风试验或登记研究中（总计超过6600名患者）前瞻性收集基线CT和CTA扫描图像，与之前获得的独立专家人工解读结果（参考标准）相比，我们将选取一个具有广泛临床代表性的大样本用于测试电子ASPECTS和电子CTA。我们的主要目的是测试软件得出的ASPECTS与经过盲法处理的专家人工ASPECTS之间的一致性，以及使用后续成像和最终临床诊断作为诊断金标准时，电子ASPECTS识别中风症状所有病因的诊断准确性。我们的次要目的是测试电子ASPECTS何时以及为何更准确或不太准确，或者成功/未能得出结果，测试电子CTA与专家人工CTA解读之间的一致性，以及电子ASPECTS/电子CTA结果的可重复性。所有测试将基于意向性分析进行。我们将评估软件与专家人工评分之间的一致性，并测试软件的诊断准确性。RITeS将针对当前的金标准——专家人工解读，对电子ASPECTS和电子CTA进行全面、可靠且具有代表性的测试。
