Left ventricular shape variation in asymptomatic populations: the multi-ethnic study of atherosclerosis
Open accessAbstract
BACKGROUND: Although left ventricular cardiac geometric indices such as size and sphericity characterize adverse remodeling and have prognostic value in symptomatic patients, little is known of shape distributions in subclinical populations. We sought to quantify shape variation across a large number of asymptomatic volunteers, and examine differences among sub-cohorts. METHODS: An atlas was constructed comprising 1,991 cardiovascular magnetic resonance (CMR) cases contributed from the Multi-Ethnic Study of Atherosclerosis baseline examination. A mathematical model describing regional wall motion and shape was used to establish a coordinate map registered to the cardiac anatomy. The model was automatically customized to left ventricular contours and anatomical landmarks, corrected for breath-hold mis-registration between image slices. Mathematical techniques were used to characterize global shape distributions, after removal of translations, rotations, and scale due to height. Differences were quantified among ethnicity, sex, smoking, hypertension and diabetes sub-cohorts. RESULTS: The atlas construction process yielded accurate representations of global shape (errors between manual and automatic surface points in 244 validation cases were less than the image pixel size). After correction for height, the dominant shape component was associated with heart size, explaining 32% of the total shape variance at end-diastole and 29% at end-systole. After size, the second dominant shape component was sphericity at end-diastole (13%), and concentricity at end-systole (10%). The resulting shape components distinguished differences due to ethnicity and risk factors with greater statistical power than traditional mass and volume indices. CONCLUSIONS: We have quantified the dominant components of global shape variation in the adult asymptomatic population. The data and results are available at cardiacatlas.org. Shape distributions were principally explained by size, sphericity and concentricity, which are known correlates of adverse outcomes. Atlas-based global shape analysis provides a powerful method for quantifying left ventricular shape differences in asymptomatic populations. TRIAL REGISTRATION: ClinicalTrials.gov NCT00005487.
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In the Multi-Ethnic Study of Atherosclerosis, heart shape variations derived from MRI examinations were associated with known cardiovascular risk factors.
“In the Multi-Ethnic Study of Atherosclerosis, heart shape variations derived from MRI examinations were associated with known cardiovascular risk factors [143].”
From AI in Medical Imaging Informatics: Current Challenges and Future Directions (2020) · cites this paper as [143]
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Vasan, R. S., Larson, M. G., Benjamin, E. J., Evans, J. C., & Levy, D. (1997) · New England Journal of Medicine · doi:10.1056/nejm199705083361903 · Cited by 402 · see citing works
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AI in Medical Imaging Informatics: Current Challenges and Future Directions
Panayides, A. S., Amini, A., Filipovic, N. D., Sharma, A., Tsaftaris, S. A., Young, A., Foran, D., Do, N., Golemati, S., Kurc, T., et al. (2020) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2020.2991043 · Cited by 713 · see citing works
Self-citationBai, W., Shi, W., de Marvao, A., Dawes, T. J. W., O’Regan, D. P., Cook, S. A., & Rueckert, D. (2015) · Medical Image Analysis · doi:10.1016/j.media.2015.08.009 · Cited by 171 · see citing works
Strocchi, M., Augustin, C. M., Gsell, M. A. F., Karabelas, E., Neic, A., Gillette, K., Razeghi, O., Prassl, A. J., Vigmond, E. J., Behar, J. M., et al. (2020) · PLoS ONE · doi:10.1371/journal.pone.0235145 · Cited by 112 · see citing works
Statistical Shape Modeling of the Left Ventricle: Myocardial Infarct Classification Challenge
Suinesiaputra, A., Dhooge, J., Duchateau, N., Ehrhardt, J., Frangi, A. F., Gooya, A., Grau, V., Lekadir, K., Lu, A., Mukhopadhyay, A., et al. (2018) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2017.2652449 · Cited by 95 · see citing works
Self-citationBig Heart Data: Advancing Health Informatics Through Data Sharing in Cardiovascular Imaging
Suinesiaputra, A., Medrano-Gracia, P., Cowan, B. R., & Young, A. A. (2015) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2014.2370952 · Cited by 45 · see citing works
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- Authors
- Medrano-Gracia, P., Cowan, B. R., Ambale-Venkatesh, B., Bluemke, D. A., Eng, J., Finn, J. P., Fonseca, C. G., Lima, J. A., Suinesiaputra, A., & Young, A. A.
- Affiliations
- University of Auckland (NZ)
- National Institute of Biomedical Imaging and Bioengineering (US)
- Johns Hopkins University (US)
- University of California, Los Angeles (US)
- Corresponding author
- Young, Alistair A
- Venue
- Journal of Cardiovascular Magnetic Resonance
- Publisher
- Elsevier BV
- Published
- 2014-12
- Volume
- 16
- Issue
- 1
- Pages
- 56
- ISSN
- 1097-6647 (ISSN-L)
- PMC
- PMC4145340
- OpenAlex
- W2114855512
- Cited by
- 98
- References
- 1
- Citations by year
- 2026: 6 · 2025: 9 · 2024: 4 · 2023: 4 · 2022: 10 · 2021: 5 · 2020: 14 · 2019: 8 · 2018: 8 · 2017: 9 · 2016: 9 · 2015: 11 · 2014: 1
- FWCI
- 7.82
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Journal of Cardiovascular Magnetic Resonance (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Research Portal (King's College London) (publishedVersion, cc-by)
- eScholarship (California Digital Library) (submittedVersion, cc-by)
- ResearchSpace (University of Auckland) (submittedVersion, public-domain)
- Funders
- National Institutes of Health (n01hc95164-17-0-1, n01hc95165-34-0-1, n01hc95161-24-0-1, n01hc095169-003, n01hc95166-21-0-1, n01hc95162-31-0-1, n01hc95168-27-0-1, n01hc95160-18-0-1, n01hc095167-000, N01-HC- 95159, n01hc95163-22-0-1, n01hc95159-40-0-1, N01‐HC‐95169)
- National Heart, Lung, and Blood Institute (N01 HC-95159, N01-HC-95160, N01 HC-95168, N01 HC95167, (N01-HC-95163, N01 HC-95161, N01 HC95165, N01HC95164, RR-024156, N01‐HC‐95166, N01 HC-95162, R01HL087773, N01 HC95169)
- National Center for Research Resources (N01 HC 95169, UL1RR024156, UL1RR025005, RR024156, N01-HC-95159, UL1-RR-024156 and UL1-RR-025005)
- Topics
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Cardiac Imaging and Diagnostics
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Cardiovascular Function and Risk Factors
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Medical Image Segmentation Techniques
- Keywords
- left ventricular shape, left ventricular remodeling, left ventricular sphericity, left ventricular dimensions, asymptomatic population, ethnic differences, cardiovascular risk factors, heart size, regional wall motion, Multi-Ethnic Study of Atherosclerosis
- MeSH terms
- Aged, Aged, 80 and over, Atlases as Topic, Computer Simulation, Female, Heart Ventricles, Humans, Magnetic Resonance Imaging, Male, Middle Aged, Models, Anatomic, Models, Cardiovascular, Predictive Value of Tests, Risk Factors, United States, Ventricular Function, Left, Ventricular Remodeling, Principal Component Analysis, Atherosclerosis, Fiducial Markers, Asymptomatic Diseases, Anatomic Landmarks
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