Large-scale Quality Control of Cardiac Imaging in Population Studies: Application to UK Biobank

Giacomo Tarroni, Wenjia Bai, Ozan Oktay, Andreas Schuh, Hideaki Suzuki, Ben Glocker, Paul M. Matthews, Daniel Rueckert

Research output: Contribution to journalArticlepeer-review

21 Citations (Scopus)


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.

Original languageEnglish
Article number2408
JournalScientific Reports
Issue number1
Publication statusPublished - 2020 Dec 1


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