Publication Date
2-7-2023
Journal
Journal of the American Heart Association
DOI
10.1161/JAHA.122.027649
PMID
36688362
PMCID
PMC9973623
PubMedCentral® Posted Date
1-23-2023
PubMedCentral® Full Text Version
Post-print
Published Open-Access
yes
Keywords
Humans, Peripheral Arterial Disease, Magnetic Resonance Imaging, Intermittent Claudication, Leg, Muscle, Skeletal, Perfusion, computational microvascular model, magnetic resonance imaging, microvascular perfusion, peripheral artery disease
Abstract
Background
Computational fluid dynamics has shown good agreement with contrast‐enhanced magnetic resonance imaging measurements in cardiovascular disease applications. We have developed a biomechanical model of microvascular perfusion using contrast‐enhanced magnetic resonance imaging signal intensities derived from skeletal calf muscles to study peripheral artery disease (PAD).
Methods and Results
The computational microvascular model was used to study skeletal calf muscle perfusion in 56 individuals (36 patients with PAD, 20 matched controls). The recruited participants underwent contrast‐enhanced magnetic resonance imaging and ankle‐brachial index testing at rest and after 6‐minute treadmill walking. We have determined associations of microvascular model parameters including the transfer rate constant, a measure of vascular leakiness; the interstitial permeability to fluid flow which reflects the permeability of the microvasculature; porosity, a measure of the fraction of the extracellular space; the outflow filtration coefficient; and the microvascular pressure with known markers of patients with PAD. Transfer rate constant, interstitial permeability to fluid flow, and microvascular pressure were higher, whereas porosity and outflow filtration coefficient were lower in patients with PAD than those in matched controls (all P values ≤0.014). In pooled analyses of all participants, the model parameters (transfer rate constant, interstitial permeability to fluid flow, porosity, outflow filtration coefficient, microvascular pressure) were significantly associated with the resting and exercise ankle‐brachial indexes, claudication onset time, and peak walking time (all P values ≤0.013). Among patients with PAD, interstitial permeability to fluid flow, and microvascular pressure were higher, while porosity and outflow filtration coefficient were lower in treadmill noncompleters compared with treadmill completers (all P values ≤0.001).
Conclusions
Computational microvascular model parameters differed significantly between patients with PAD and matched controls. Thus, computational microvascular modeling could be of interest in studying lower extremity ischemia.
Comments
Associated Data