当前位置： SCI文献检索 > COMPUTER METHODS IN BIOMECHANICS AND BIOMEDICAL ENGINEERING期刊下所有文献 > Fractal network model for simulating abdominal and lower extremity blood flow during resting and exercise conditions.

Fractal network model for simulating abdominal and lower extremity blood flow during resting and exercise conditions.

Abstract：

:We present a one-dimensional (1D) fluid dynamic model that can predict blood flow and blood pressure during exercise using data collected at rest. To facilitate accurate prediction of blood flow, we developed an impedance boundary condition using morphologically derived structured trees. Our model was validated by computing blood flow through a model of large arteries extending from the thoracic aorta to the profunda arteries. The computed flow was compared against measured flow in the infrarenal (IR) aorta at rest and during exercise. Phase contrast-magnetic resonance imaging (PC-MRI) data was collected from 11 healthy volunteers at rest and during steady exercise. For each subject, an allometrically-scaled geometry of the large vessels was created. This geometry extends from the thoracic aorta to the femoral arteries and includes the celiac, superior mesenteric, renal, inferior mesenteric, internal iliac and profunda arteries. During rest, flow was simulated using measured supraceliac (SC) flow at the inlet and a uniform set of impedance boundary conditions at the 11 outlets. To simulate exercise, boundary conditions were modified. Inflow data collected during steady exercise was specified at the inlet and the outlet boundaries were adjusted as follows. The geometry of the structured trees used to compute impedance was scaled to simulate the effective change in the cross-sectional area of resistance vessels and capillaries due to exercise. The resulting computed flow through the IR aorta was compared to measured flow. This method produces good results with a mean difference between paired data to be 1.1 +/- 7 cm(3) s(- 1) at rest and 4.0 +/- 15 cm(3) s(- 1) at exercise. While future work will improve on these results, this method provides groundwork with which to predict the flow distributions in a network due to physiologic regulation.

journal_name

Comput Methods Biomech Biomed Engin

journal_title

Computer methods in biomechanics and biomedical engineering

authors

Steele BN,Olufsen MS,Taylor CA

doi

10.1080/10255840601068638

subject

Has Abstract

pub_date

2007-02-01 00:00:00

pages

39-51

issue

eissn

1025-5842

issn

1476-8259

pii

770213688

journal_volume

pub_type

杂志文章

在线工具

Fractal network model for simulating abdominal and lower extremity blood flow during resting and exercise conditions.