TY - JOUR
T1 - Large-scale Quality Control of Cardiac Imaging in Population Studies
T2 - Application to UK Biobank
AU - Tarroni, Giacomo
AU - Bai, Wenjia
AU - Oktay, Ozan
AU - Schuh, Andreas
AU - Suzuki, Hideaki
AU - Glocker, Ben
AU - Matthews, Paul M.
AU - Rueckert, Daniel
N1 - Funding Information:
This research has been conducted using the UK Biobank Resource under Application Number 18545: the authors wish to thank all UK Biobank participants and staff. The authors also acknowledge funding by EPSRC Programme (EP/P001009/1). G.T. benefited from a Marie Skodowska-Curie Fellowship. P.M.M. acknowledges the Edmond J. Safra Foundation and Lily Safra, an NIHR Senior Investigator Award and the UK Dementia Research Institute for personal support. His research is supported also by the Imperial College Healthcare Trust NIHR Biomedical Research Centre.
Publisher Copyright:
© 2020, The Author(s).
PY - 2020/12/1
Y1 - 2020/12/1
N2 - 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.
AB - 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.
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U2 - 10.1038/s41598-020-58212-2
DO - 10.1038/s41598-020-58212-2
M3 - Article
C2 - 32051456
AN - SCOPUS:85079335633
VL - 10
JO - Scientific Reports
JF - Scientific Reports
SN - 2045-2322
IS - 1
M1 - 2408
ER -