Damon Bruce M, Gore John C
Dept. of Radiology and Radiological Sciences, Vanderbilt University, 1161 21st Ave S., CCC-1121, Nashville, TN 37232-2675, USA.
J Appl Physiol (1985). 2005 Jan;98(1):264-73. doi: 10.1152/japplphysiol.00369.2004. Epub 2004 Aug 27.
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 approximately 45 s) and that effects secondary to glycolysis are the main contributors at later times.
肌肉功能磁共振成像(mfMRI)已被提议作为一种非侵入性测量肌肉激活的代谢和血流动力学反应的工具,但其理论基础仍不清楚。一个挑战是难以单独分离那些影响mfMRI反应幅度和时间模式的变量。因此,本研究的目的是建立一个计算机模型,以了解运动过程中生理因素的变化如何影响mfMRI信号强度随时间的变化过程,然后预测各个因素的作用。定义了一个包含39204条纤维的模型肌肉。纤维类型组成和神经激活策略的设计旨在代表人类胫骨前肌的等长收缩,已有关于该肌肉的mfMRI数据发表。对最大自主收缩的25%和40%时的持续等长收缩进行了建模,同时对血管(毛细血管募集、血液氧提取)和代谢(乳酸积累、磷酸肌酸水解、pH值)反应也进行了建模。估计了对MRI信号横向弛豫的影响,并从模拟图像中测量了mfMRI信号强度随时间的变化过程。模型数据在质量上与已发表的实验数据吻合良好,在长时间运动时定量吻合也很好。然后使用该模型预测,在短时间运动(长达约45秒)时,血容量和氧合变化以及肌酸激酶反应引起的核磁共振弛豫效应主导了mfMRI随时间的变化过程,而在后期糖酵解引起的效应是主要贡献因素。