Related Experiment Video
Updated: May 14, 2026

In Vivo Quantitative Assessment of Myocardial Structure, Function, Perfusion and Viability Using Cardiac Micro-computed Tomography
Published on: February 16, 2016
Myocardial blood flow at rest and stress measured with dynamic contrast-enhanced MRI: comparison of a distributed
David A Broadbent1, John D Biglands, Abdulghani Larghat
1Division of Medical Physics, Leeds Institute of Genetics Health and Therapeutics, Faculty of Medicine and Health, University of Leeds, Leeds, UK; Department of Medical Physics and Engineering, Leeds Teaching Hospitals NHS Trust, Leeds, UK; Multidisciplinary Cardiovascular Research Centre, University of Leeds, Leeds, UK.
Purpose:
To assess the feasibility of simultaneously measuring blood flow (Fb ), Gd-DTPA extraction fraction (E), and distribution volume (vd ) in healthy myocardium at rest and under adenosine stress using dynamic contrast-enhanced MRI.
Methods:
Sixteen volunteers were examined at 1.5 T and 11 returned for a repeat study. The data were analyzed using a distributed parameter (DP) 2-region model to arrive at estimates of Fb , E, blood volume, and interstitial volume. For comparison, estimates of Fb were also obtained using a Fermi function model.
Results:
DP model fits were successful in 49 of the 54 data sets. Estimates obtained using DP and Fermi models did not differ for either rest Fb or myocardial perfusion reserve though DP estimates of stress Fb were lower than Fermi estimates. The repeatability of the DP parameters Fb , E, and vd was better than or equal to the repeatability of Fermi-Fb . E at rest and under stress was estimated to be 66% and 57%, respectively.
Conclusion:
The results suggest that characteristics of the microvasculature of healthy myocardium can be reliably determined using dynamic contrast-enhanced MRI at rest and under stress and that delivery of Gd-DTPA to the myocardium is not flow-limited.
Related Concept Videos
Magnetic Resonance Imaging
Physiological Pharmacokinetic Models: Blood Flow-Limited Versus Diffusion-Limited Models
