Imperial College London, Department of Computing, BioMedIA Group, London, SW7 2AZ, UK.
City, University of London, Department of Computer Science, CitAI Research Centre, London, EC1V 0HB, UK.
Sci Rep. 2020 Feb 12;10(1):2408. doi: 10.1038/s41598-020-58212-2.
In large population studies such as the UK Biobank (UKBB), quality control of the acquired images by visual assessment is unfeasible. In this paper, we apply a recently developed fully-automated quality control pipeline for cardiac MR (CMR) images to the first 19,265 short-axis (SA) cine stacks from the UKBB. We present the results for the three estimated quality metrics (heart coverage, inter-slice motion and image contrast in the cardiac region) as well as their potential associations with factors including acquisition details and subject-related phenotypes. Up to 14.2% of the analysed SA stacks had sub-optimal coverage (i.e. missing basal and/or apical slices), however most of them were limited to the first year of acquisition. Up to 16% of the stacks were affected by noticeable inter-slice motion (i.e. average inter-slice misalignment greater than 3.4 mm). Inter-slice motion was positively correlated with weight and body surface area. Only 2.1% of the stacks had an average end-diastolic cardiac image contrast below 30% of the dynamic range. These findings will be highly valuable for both the scientists involved in UKBB CMR acquisition and for the ones who use the dataset for research purposes.
在 UK Biobank（英国生物银行）等大型人群研究中，通过视觉评估对获得的图像进行质量控制是不可行的。在本文中，我们将最近开发的用于心脏磁共振（CMR）图像的全自动质量控制管道应用于 UKBB 的前 19265 个短轴（SA）电影堆栈。我们展示了三个估计质量指标（心脏覆盖范围、切片间运动和心脏区域的图像对比度）的结果，以及它们与包括采集细节和与受试者相关的表型在内的因素的潜在关联。多达 14.2%的分析 SA 堆栈的覆盖范围不理想（即缺少基底和/或顶端切片），但大多数都仅限于采集的第一年。多达 16%的堆栈受到明显的切片间运动的影响（即平均切片间错位大于 3.4mm）。切片间运动与体重和体表面积呈正相关。只有 2.1%的堆栈的平均舒张末期心脏图像对比度低于动态范围的 30%。这些发现对于参与 UKBB CMR 采集的科学家以及将数据集用于研究目的的科学家都将具有非常重要的价值。
