Novel cardiovascular magnetic resonance strain heterogeneity phenotypes predict cardiovascular events: A prospective UK Biobank study
Heterogeneity biomarkers are sensitive to early pathological signals by measuring disease regionality. CoV<sub>CS</sub> and CoV<sub>RS</sub> are significant, consistent, additive and sometimes superior predictors of HF, arrhythmia and all-cause death than established risk markers, particularly in cohorts with multiple co-morbidities or LVEF <50%. Expansion of machine learning-guided image analysis makes strain CoV imminently translatable into routine clinical practice.
Authors
- Mohammed Y Khanji (ORCID: https://orcid.org/0000-0002-5903-4454)
- José Miguel Paiva (ORCID: https://orcid.org/0000-0002-9369-6785)
- Kerrick Hesse (ORCID: https://orcid.org/0000-0002-1155-0409)
- Jose D. Vargas (ORCID: https://orcid.org/0000-0002-2005-567X)
- Steffen Erhard Petersen (ORCID: https://orcid.org/0000-0003-4622-5160)
- C. Anwar A. Chahal (ORCID: https://orcid.org/0000-0001-7825-8827)
- Sucharitha Chadalavada Mbbs
- Kenneth Fung Mbbs
- Nay Aung Mbbs
Institutions
- Queen Mary University of London (GB)
- Barts Health NHS Trust (GB)
- Veterans Health Administration (US)
- William Harvey Research Institute (GB)
- Washington DC VA Medical Center (US)
Publication Details
- Journal
- Journal of Cardiovascular Magnetic Resonance
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1016/j.jocmr.2025.101976
- Citations
- 2
- Primary Topic
- Cardiac Imaging and Diagnostics
- Type
- article
- Field-Weighted Citation Impact
- 2.72