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Updated: Mar 7, 2026

In Vivo Quantitative Assessment of Myocardial Structure, Function, Perfusion and Viability Using Cardiac Micro-computed Tomography
Published on: February 16, 2016
Mid-diastolic left ventricular volume and mass: Normal values for coronary computed tomography angiography
Daniel Juneau1, Fernanda Erthal2, Owen Clarkin2
1Department of Medicine (Cardiology), University of Ottawa Heart Institute, Ontario, Canada; Centre Hospitalier de l'Université de Montréal (CHUM), Montréal, Québec, Canada.
Background:
The adoption of prospectively ECG-triggered acquisition coronary computed tomography angiography (CTA) has resulted in the inability to measure left ventricle (LV) end-diastolic volume and LV ejection fraction. However other prognostic measures such as LV mass and LV mid-diastolic volume (LVMDV) can still be assessed. The objective of this study is to establish normal reference values for LVMDV and LV mass.
Methods:
Left ventricular mid-diastolic volumes and LV mass were prospectively measured in 2647 consecutive 'normal' patients undergoing prospectively ECG-triggered coronary CTA. Patients with known coronary artery disease (prior myocardial infarction or prior revascularization), heart failure, congenital heart disease, heart transplant or prior cardiac surgery were excluded. Commercially available software was used to calculate the LVMDV and LV mass.
Results:
Among the 2647 patient cohort (mean age = 58 years, 54% men), the mean LVMDV indexed for body surface area was 57.5 ± 15.3 mL/m2 and 64.5 ± 20.2 mL/m2 for women and men, respectively. The mean indexed LV mass was 52.2 ± 10.9 g/m2 for women and 63.6 ± 13.7 g/m2 for men. Indexed LVMDV decreased with increasing age. The presence of hypertension, diabetes and obstructive coronary artery disease did not have a clinically relevant impact on these values. Age and sex specific upper limits of normal were defined.
Conclusion:
We establish normal reference ranges for LVMDV and LV mass using prospectively ECG-triggered coronary CTA. These benchmarks may identify patients at increased risk of adverse events, supporting the potential for clinical reporting of these metrics.
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