Computational Network Model Prediction of Hemodynamic Alterations Due to Arteriolar Rarefaction and Estimation of Skeletal Muscle Perfusion in Peripheral Arterial Disease.

ABSTRACT:

Objective

To estimate the relative influence of input pressure and arteriole rarefaction on gastrocnemius muscle perfusion in patients with PAD after exercise and/or percutaneous interventions.

Methods

A computational network model of the gastrocnemius muscle microcirculation was adapted to reflect rarefaction based on arteriolar density measurements from PAD patients, with and without exercise. A normalized input pressure was applied at the feeder artery to simulate both reduced and restored ABI in the PAD condition.

Results

In simulations of arteriolar rarefaction, resistance increased non-linearly with rarefaction, leading to a disproportionally large drop in perfusion. In addition, perfusion was less sensitive to changes in input pressure as the degree of rarefact

SUBMITTER: Heuslein JL 

PROVIDER: S-EPMC4506703 | biostudies-literature | 2015 Jul

REPOSITORIES: biostudies-literature