Mikhail Paul, Le Michael Gia Duy, Mair Grant
Edinburgh Imaging, University of Edinburgh, United Kingdom; Nepean Blue Mountains LHD, Kingswood, NSW, Australia.
Nepean Blue Mountains LHD, Kingswood, NSW, Australia.
J Stroke Cerebrovasc Dis. 2020 May;29(5):104715. doi: 10.1016/j.jstrokecerebrovasdis.2020.104715. Epub 2020 Mar 4.
Noncontrast enhanced computed tomography (NCCT) remains the most common method for brain imaging patients who present acutely with ischaemic stroke. Computational methods may improve NCCT analysis in this context. We systematically reviewed current research.
We searched 7 medical and computer engineering databases for studies testing computational methods for analysing NCCT in acute ischaemic stroke. Two independent reviewers extracted the following data; computational method, imaging features investigated, test dataset, ground truth comparison, and performance. We critically evaluated studies for risk of bias and applicability using the Quality Assessment of Diagnostic Accuracy Studies tool (QUADAS-2).
From 11,235 nonduplicated articles, we full-text reviewed 200 and selected 68 for inclusion. We identified three dominant study types testing a large range of computational methods for: (1) identifying acute ischaemic stroke (n = 42); (2) ischaemic lesion segmentation (n = 6); and (3) automated Alberta Stroke Program Early CT Score (n = 20). Most articles presented small test datasets, poorly documented patient populations, and did not specify the acuity of the CT scans used in development. There was limited validation or clinical testing of computational methods. Automated Alberta Stroke Program Early CT Score methods were the only software systems presented in multiple publications. Critical evaluation was often limited by lack of data.
Computational techniques for analysing NCCT in patients with acute ischaemic stroke have not been adequately clinically validated. Further research with larger and more relevant datasets, in addition to better collaboration between clinicians and researchers, is needed to aid more widespread clinical adoption and implementation.
对于急性缺血性中风患者，非增强计算机断层扫描（NCCT）仍然是最常用的脑部成像方法。在这种情况下，计算方法可能会改善NCCT分析。我们系统地回顾了当前的研究。
我们在7个医学和计算机工程数据库中搜索了测试用于分析急性缺血性中风NCCT的计算方法的研究。两名独立的评审员提取了以下数据：计算方法、研究的成像特征、测试数据集、与金标准的比较以及性能。我们使用诊断准确性研究质量评估工具（QUADAS-2）对研究的偏倚风险和适用性进行了严格评估。
从11235篇非重复文章中，我们对200篇进行了全文评审，并选择了68篇纳入。我们确定了三种主要的研究类型，测试了一系列用于以下方面的计算方法：（1）识别急性缺血性中风（n = 42）；（2）缺血性病变分割（n = 6）；以及（3）自动阿尔伯塔中风项目早期CT评分（n = 20）。大多数文章展示的测试数据集较小，患者群体记录不完善，并且没有指定开发中使用的CT扫描的急性程度。计算方法的验证或临床测试有限。自动阿尔伯塔中风项目早期CT评分方法是多篇出版物中唯一出现的软件系统。关键评估往往因缺乏数据而受到限制。
用于分析急性缺血性中风患者NCCT的计算技术尚未得到充分的临床验证。需要使用更大且更相关的数据集进行进一步研究，此外临床医生和研究人员之间需要更好地合作，以促进更广泛的临床应用和实施。
