Measurement of kinetic parameters in skeletal muscle by magnetic resonance imaging with an intravascular agent

Anthony Z. Faranesh, Dara L. Kraitchman, Elliot R. McVeigh

Research output: Contribution to journalArticlepeer-review

Abstract

The purpose of this work was to investigate the use of an intravascular contrast agent to determine perfusion kinetics in skeletal muscle. A two-compartment kinetic model was used to represent the flux of contrast agent between the intravascular space and extravascular extracellular space (EES). The relationship between the image signal-to-noise ratio (SNR) and errors in estimating permeability surface area product (Ktrans), interstitial volume (ve), and plasma volume (vp) for linear and nonlinear curve-fitting methods was estimated from Monte Carlo simulations. Similar results were obtained for both methods. For an image SNR of 60, the estimated errors in these parameters were 10%, 22%, and 17%, respectively. In vivo experiments were conducted in rabbits to examine physiological differences between these parameters in the soleus (SOL) and tibialis anterior (TA) muscles in the hind limb. Values for Ktrans were significantly higher in the SOL (3.2 ± 0.9 vs. 2.0 ± 0.5 × 10-3 min -1), as were values for vp (3.4 ±0.6 vs. 2.1 ± 0.7%). Differences in ve for the two muscles (6.7 ± 2.2 vs. 8.5 ± 1.6%) were not found to be significant. These results demonstrate that relevant physiological metrics can be calculated in skeletal muscle using MRI with an intravascular contrast agent.

Original languageEnglish (US)
Pages (from-to)1114-1123
Number of pages10
JournalMagnetic resonance in medicine
Volume55
Issue number5
DOIs
StatePublished - May 2006

Keywords

  • Blood volume
  • Gadomer
  • Intravascular contrast
  • MRI
  • Permeability

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging

Fingerprint Dive into the research topics of 'Measurement of kinetic parameters in skeletal muscle by magnetic resonance imaging with an intravascular agent'. Together they form a unique fingerprint.

Cite this