@inbook{1d368813afb6493bae1b11c190399379,
title = "Impact of Image Resolution and Resampling on Motion Tracking of the Left Chambers from Cardiac Scans",
abstract = "Cardiac magnetic resonance (CMR) is an important diagnostic imaging modality in cardiovascular medicine. Estimation of myocardium motion derived from CMR scans is routinely used to measure the cardiac mechanics. However, tracking a rapidly moving organ can be compromised by artefacts or impaired image quality. To assess how in-plane image resolution and slice sampling in short and long axis scans impact errors in motion tracking, we utilised retrospective gated cardiac computed tomography (CCT) imaging as a surrogate groundtruth for motion estimation across 10 clinical datasets, since these scans have a higher isotropic resolution than CMR and the ability to capture full 3D motion. In our work, the left atrial (LA) and ventricular (LV) cavities were first delineated, and then reconstructed short and long axis images were used in a non-rigid registration method with optimised hyperparameters to track endocardial motion. Finally, global and regional functions in the form of area, circumferential, and longitudinal strains were computed. Our findings showed that tracking LA was more sensitive than LV to changes in the in-plane resolution and magnitude of strain was robust to resolution changes in short axis images, when correlated with the groundtruth (r: 0.87–0.99, R2 : 0.75–0.98). We also found that 9 short axis slices could capture the motion of LV almost as accurately as 36 slices captured in long axis (r: 0.89 vs. 0.90, R2 : 0.80 vs. 0.80), illustrating that the cardiac mechanics measured by short axis scans are more likely to be robust to image artefacts and reconstruction parameters.",
keywords = "Cardiac magnetic resonance, Image resampling, Motion tracking, Strain calculation",
author = "Orod Razeghi and Marina Strocchi and Cesare Corrado and Henry Chubb and Ronak Rajani and Ennis, {Daniel B.} and Niederer, {Steven A.}",
note = "Funding Information: Acknowledgements. Dr Niederer acknowledges support from the National Institute of Health (NIH R01-HL152256), and by core funding from the Wellcome/EPSRC Centre for Medical Engineering [WT203148/Z/16/Z]. Publisher Copyright: {\textcopyright} 2021, Springer Nature Switzerland AG. Copyright: Copyright 2021 Elsevier B.V., All rights reserved.; 11th International Conference on Functional Imaging and Modeling of the Heart, FIMH 2021 ; Conference date: 21-06-2021 Through 25-06-2021",
year = "2021",
doi = "10.1007/978-3-030-78710-3_2",
language = "English",
isbn = "9783030787097",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "12--21",
editor = "Ennis, {Daniel B.} and Perotti, {Luigi E.} and Wang, {Vicky Y.}",
booktitle = "Functional Imaging and Modeling of the Heart - 11th International Conference, FIMH 2021, Proceedings",
address = "Germany",
}