HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS		QUICK SEARCH:   [advanced] Author: Keyword(s): Year:  Vol:  Page:

This Article Full Text Free Full Text (PDF) Free All Versions of this Article: 98/1/264    most recent 00369.2004v1 Submit a response Alert me when this article is cited Alert me when eLetters are posted Alert me if a correction is posted Citation Map Services Email this article to a friend Similar articles in this journal Similar articles in ISI Web of Science Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via HighWire Citing Articles via ISI Web of Science (4) Citing Articles via Google Scholar Google Scholar Articles by Damon, B. M. Articles by Gore, J. C. Search for Related Content PubMed PubMed Citation Articles by Damon, B. M. Articles by Gore, J. C.

Physiological basis of muscle functional MRI: predictions using a computer model

Department of Radiology and Radiological Sciences and Vanderbilt University Institute of Imaging Science, Vanderbilt University, Nashville, Tennessee

Submitted 8 April 2004 ; accepted in final form 20 August 2004

Muscle functional MRI (mfMRI) has been proposed as a tool for noninvasively measuring the metabolic and hemodynamic responses to muscle activation, but its theoretical basis remains unclear. One challenge is that it is difficult to isolate individually those variables affecting the magnitude and temporal pattern of the mfMRI response. Therefore, the purpose of this study was to develop a computer model of how physiological factors altered during exercise affect the mfMRI signal intensity time course and then predict the contributions made by individual factors. A model muscle containing 39,204 fibers was defined. The fiber-type composition and neural activation strategies were designed to represent isometric contractions of the human anterior tibialis muscle, for which published mfMRI data exist. Sustained isometric contractions at 25 and 40% maximum voluntary contraction were modeled, as were the vascular (capillary recruitment, blood oxygen extraction) and metabolic (lactate accumulation, phosphocreatine hydrolysis, pH) responses. The effects on the transverse relaxation of MRI signal were estimated, and the mfMRI signal intensity time course was measured from simulated images. The model data agreed well qualitatively with published experimental data, and at long exercise durations the quantitative agreement was also good. The model was then used to predict that NMR relaxation effects secondary to blood volume and oxygenation changes, plus the creatine kinase reaction, dominate the mfMRI time course at short exercise durations (up to 45 s) and that effects secondary to glycolysis are the main contributors at later times.

transverse relaxation time; time series; skeletal muscle; modeling

This article has been cited by other articles:

				R. L Segal Use of Imaging to Assess Normal and Adaptive Muscle Function Physical Therapy, June 1, 2007; 87(6): 704 - 718. [Abstract] [Full Text] [PDF]