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Updated: Jun 29, 2025
Estimating Bilateral Atrial Function by Cardiovascular Magnetic Resonance Feature Tracking in Patients with Paroxysmal Atrial Fibrillation
Published on: July 20, 2022
Left Ventricular Trabeculations at Cardiac MRI: Reference Ranges and Association with Cardiovascular Risk Factors in
Nay Aung1, Axel Bartoli1, Elisa Rauseo1
1From the Centre for Advanced Cardiovascular Imaging, William Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, London, England (N.A., E.R., M.M.S., M.Y.K., S.E.P.); Barts Heart Centre, St Bartholomew's Hospital, Barts Health NHS Trust, London, England (N.A., E.R., M.M.S., M.Y.K., S.E.P.); Department of Radiology, Hôpital de la Timone, AP-HM, 264 rue Saint-Pierre, 13385 Marseille CEDEX 05, France (A.B., A.J.); Center for Magnetic Resonance in Biology and Medicine, UMR CNRS 7339, Aix-Marseille University, Marseille, France (A.B., J.F., A.J.); Institut de Recherche pour le Developpement, VITROME, Aix-Marseille University, Marseille, France (S.C.); Aix-Marseille School of Economics, Aix-Marseille University, Marseille, France (B.G.); Newham University Hospital, Barts Health NHS Trust, London, England (M.Y.K.); Health Data Research UK, London, England (S.E.P.); and Alan Turing Institute, London, England (S.E.P.).
Abstract:
Background The extent of left ventricular (LV) trabeculation and its relationship with cardiovascular (CV) risk factors is unclear. Purpose To apply automated segmentation to UK Biobank cardiac MRI scans to (a) assess the association between individual characteristics and CV risk factors and trabeculated LV mass (LVM) and (b) establish normal reference ranges in a selected group of healthy UK Biobank participants. Materials and Methods In this cross-sectional secondary analysis, prospectively collected data from the UK Biobank (2006 to 2010) were retrospectively analyzed. Automated segmentation of trabeculations was performed using a deep learning algorithm. After excluding individuals with known CV diseases, White adults without CV risk factors (reference group) and those with preexisting CV risk factors (hypertension, hyperlipidemia, diabetes mellitus, or smoking) (exposed group) were compared. Multivariable regression models, adjusted for potential confounders (age, sex, and height), were fitted to evaluate the associations between individual characteristics and CV risk factors and trabeculated LVM. Results Of 43 038 participants (mean age, 64 years ± 8 [SD]; 22 360 women), 28 672 individuals (mean age, 66 years ± 7; 14 918 men) were included in the exposed group, and 7384 individuals (mean age, 60 years ± 7; 4729 women) were included in the reference group. Higher body mass index (BMI) (β = 0.66 [95% CI: 0.63, 0.68]; P < .001), hypertension (β = 0.42 [95% CI: 0.36, 0.48]; P < .001), and higher physical activity level (β = 0.15 [95% CI: 0.12, 0.17]; P < .001) were associated with higher trabeculated LVM. In the reference group, the median trabeculated LVM was 6.3 g (IQR, 4.7-8.5 g) for men and 4.6 g (IQR, 3.4-6.0 g) for women. Median trabeculated LVM decreased with age for men from 6.5 g (IQR, 4.8-8.7 g) at age 45-50 years to 5.9 g (IQR, 4.3-7.8 g) at age 71-80 years (P = .03). Conclusion Higher trabeculated LVM was observed with hypertension, higher BMI, and higher physical activity level. Age- and sex-specific reference ranges of trabeculated LVM in a healthy middle-aged White population were established. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Kawel-Boehm in this issue.
