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Laboratory of Cardiac Energetics, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland 20892
ABSTRACT
INTRODUCTION
MATERIAL AND METHODS
RESULTS
DISCUSSION
FOOTNOTES
REFERENCES
ABSTRACT 
Fowler, M. D., T. W. Ryschon, R. E. Wysong, C. A. Combs, and
R. S. Balaban. Normalized metabolic stress for
31P-MR spectroscopy studies of
human skeletal muscle: MVC vs. muscle volume. J. Appl.
Physiol. 83(3): 875-883, 1997.
A critical
requirement of submaximal exercise tests is the comparability of
workload and associated metabolic stress between subjects. In this
study, 31P-magnetic resonance
spectroscopy was used to estimate metabolic strain in the soleus muscle
during dynamic, submaximal plantar flexion in which target torque was
10 and 15% of a maximal voluntary contraction (MVC). In 10 healthy,
normally active adults, (PCr + Pi)/PCr, where PCr is
phosphocreatine, was highly correlated with power output normalized to
the volume of muscle in the plantar flexor compartment
(r = 0.89, P < 0.001). The same variable was also correlated, although less strongly
(r = 0.78, P < 0.001), with power normalized to
plantar flexor cross-sectional area. These findings suggest that
comparable levels of metabolic strain can be obtained in subjects of
different size when the power output, or stress, for dynamic plantar
flexion is selected as a function of plantar flexor muscle volume. In
contrast, selecting power output as a function of MVC resulted in a
positive linear relationship between (PCr + Pi)/PCr and the
torque produced, indicating that metabolic strain was increasing rather
than achieving constancy as a function of MVC. These findings provide
new insight into the design of dynamic muscle contraction protocols
aimed at detecting metabolic differences between subjects of different
body size but having similar blood flow capacity and mitochondrial
volume per unit of muscle.
maximal voluntary contraction; soleus; magnetic resonance imaging; 4 tesla; creatine phosphate; adenosine 5 INTRODUCTION SKELETAL MUSCLE ENERGETICS has been extensively studied
by using 31P-magnetic resonance
(31P-MR) spectroscopy coupled with
isometric, eccentric, and concentric muscle actions in subjects who are
physically conditioned (15, 16, 20, 26), have disease (13, 14, 25, 29),
or are sedentary (15, 26, 28). In general, these studies examine metabolic changes (i.e., metabolic strain) with metabolic stress associated with a given workload. Most of these studies have used exercise parameters that increase mechanical load on the muscle group
until exhaustion or fatigue occurs (maximal protocols) (13, 20, 30). An
alternative approach prescribes exercise as a percentage of an assumed
maximal ATP synthesis rate
(Qmax) in an attempt to scale
metabolic stress or demand to the maximal metabolic capacity (3,
4, 14). In these submaximal steady-state exercise protocols, the
ATP synthesis rate matches the rate of ATP hydrolysis needed for muscle
contraction, resulting in a constant ATP level in the muscle.
Advantages of steady-state protocols include a greater specificity to
oxidative ATP synthesis, a reduction in the influence of fatigue
mechanisms associated with maximal contraction protocols, and better
subject compliance. Moreover, submaximal exercise is routinely used in
activities of daily living.
To achieve the same relative work intensity and subsequent metabolic
stress in subjects of different body sizes, the power performed in
steady-state protocols must be normalized between individuals. We
define a normalized metabolic stress as
-triphosphate; phosphorus-31 magnetic resonance spectroscopy
where
Q is the power performed (J/s), E represents mechanochemical
efficiency, Qmax is the maximum
metabolic power (J/s). From Eq. 1, a
measure of the Qmax and E is
required to properly normalize the metabolic stress on a given muscle.
In general, the efficiency for a given muscle action is assumed to be
constant. Thus a measure of Qmax
is all that is required. There have been several approaches to
determine the Qmax to normalize
metabolic stress in studies of human muscle.
(1)
One of the most common strategies for normalizing metabolic stress is the force generated during a maximal voluntary contraction (MVC). The MVC is often used because it is a relatively easy measurement to obtain. MVC as an estimate of Qmax assumes that individuals are highly compliant, that all muscle fibers are activated by voluntary effort, and that no antagonistic muscles contract concurrently to reduce overall force output. These assumptions are controversial for most human subjects (2, 6, 19, 22).
An alternative approach for determining Qmax in individuals of different body size is to assume that the activated muscle volume is an approximation of Qmax (5). This assumption requires that the amount of mitochondria per cubic centimeter of muscle and the supporting intermediary metabolism are constant, that the activated muscle can be identified and consistently stimulated, and that blood flow does not limit submaximal metabolic rates. Although volume and Qmax have been estimated by lean body mass and cross-sectional area (CSA), absolute three-dimensional volume measurements should provide a more accurate means of estimating muscle volume and related Qmax.
To compare the use of MVC and muscle volume as measures of Qmax, a measure of metabolic stress independent of muscle mechanics is necessary. In response to a metabolic stress, a change or strain occurs in the energy metabolism of the muscle. Because the major source of energy in the cell is the free energy of ATP hydrolysis, we are defining the metabolic strain as the percent change in ATP free energy or the related (PCr + Pi)/PCr ratio, where PCr is phosphocreatine. It has been shown that this metabolic strain is linearly related to the metabolic stress in several systems over moderate workloads (11, 18).
In this study, metabolic strain or changes in (PCr + Pi)/PCr were used to evaluate different methods of normalizing the metabolic stress in a series of individuals undergoing different levels of submaximal plantar flexion. 31P nuclear magnetic resonance (NMR) was used to continuously monitor the metabolic strain. 1H magnetic resonance imaging (MRI) was used to determine NMR coil placements as well as muscle volume. Muscle mechanics were controlled and monitored by using a specially designed dynamometer (23). Volume, MVC, and CSA were evaluated as methods of normalizing a given workload to Qmax. Identification of a morphometric or functional variable that can be used to normalize metabolic stress is likely to increase the sensitivity and clinical usefulness of 31P-MR for studying metabolic consequences associated with age, pathology, and conditioning.
MATERIAL AND METHODS
Dynamometer. Dynamic concentric plantar flexion was performed by using a custom leg dynamometer incorporating a foot-pedal module mounted on a standard patient-transport bed, as described previously (23). Briefly, the subject was placed on the bed in a supine position with the right leg fully extended. The right foot was secured by using nylon straps attached to the foot pedal with axis of rotation around the ankle. Additional straps were placed 4-5 cm above and below the knee to prevent movement of the thigh and lower leg relative to the dynamometer platform. A broad, contoured foam shelf was positioned below the right calf to support the lower leg. The dynamometer foot pedal is coupled through a low-friction point to a 6.0-kW (peak power) direct-current servomotor (Glentek, El Segundo, CA). The pedal is attached to a crank arm mounted on the motor driveshaft by an aluminum-fiberglass tube. This arrangement allows translation of the rotation of the motor driveshaft to rotation of the foot pedal around the ankle joint. An integrated analog-to-digital converter was used to sample torque and pedal position as a function of time at a rate of 10 Hz. The subject received real-time feedback of torque from a vertical bar graph mounted at eye level in the magnet. Leg exercise. After the position of the surface coil was confirmed, the magnetic field was shimmed. A fully relaxed 31P-MR spectrum was collected at rest. The leg exercise portion of the protocol was then initiated. After the range of motion of an individual was determined, MVC was determined by the peak torque attained during 3-5 maximal effort plantar flexions. Each maximal effort was 3-5 s in duration and was accompanied by vigorous verbal encouragement. Submaximal exercise testing with continuous collection of 31P-MR data was started after 15 min of rest. Each subject performed trials of 10 and 15% MVC concentric plantar flexion separated by 10-15 min of recovery. During the effort portion of each pedal stroke, the pedal rotation was constrained to 30°/s. After the stroke, the pedal was returned to the starting position at 240°/s. In all trials, ankle rotation was limited to 30° (5° dorsiflexion and 25° plantar flexion). All subjects included in the analysis reached a metabolic steady state at each workload. The average tension time integral (TTI) for each stroke was calculated as the sum of sampled torque values during an effort stroke divided by the number of samples in that stroke. Average power per stroke was calculated for the final minute of each period of exercise as the product of pedal velocity (radi/s) and instantaneous torque. Data analysis. All data are reported as means ± SD when normal distributions were determined. All statistics were performed by using SigmaStat (San Rafael, CA). Comparisons between parameter conditions were made via analysis of variance with the Student-Newman-Keuls test for multiple comparisons where necessary. The relationships between morphometric and functional measures and inverse phosphorylation potential, (PCr + Pi)/PCr, were determined from linear regression analysis and the Pearson correlation coefficient. A significance level of P < 0.05 was selected.
RESULTS
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Surface coil. An example of a surface coil localization image series is shown in Fig. 3. The entire sensitive volume of the surface coil is presented in this multislice study. The major muscle observed is the soleus, with some contributions from deeper muscle groups. The gastrocnemius muscle was completely excluded with this coil placement. Similar images were collected for each subject to ensure the anatomy and placement of the coil.
Typical 1-min spectra are shown in Fig. 4. The rest and last-minute exercise spectra at 10 and 15% MVC had a PCr signal-to-noise (peak-to-peak) ratio of 163, 113, and 104, respectively. Table 2 shows the (PCr + Pi)/PCr, [ADP], intracellular pH, and ATP concentration ([ATP]) during the last minute of rest and the last minute of exercise at 10 and 15% MVC, respectively. There was a significant difference in the (PCr + Pi)/PCr and calculated [ADP] between rest and the end of each exercise trial and between the end of the 10 and 15% MVC exercise trials. No significant changes were detected in [ATP] or pH. No significant change in the chemical shift of the ATP
-phosphate was observed throughout the protocol, suggesting no
change in the intracellular free
Mg2+ concentration
([Mg2+]) (24). From
the pH and chemical shift difference between the 
- and -ATP, the
mean intracellular free Mg2+ was
estimated to be ~0.6 mM, similar to previous studies (24).
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Figure 7 shows the positive correlation between mechanical power (in W) and (PCr + Pi)/PCr at both 10 and 15% of MVC. This plot indicates that subjects with larger MVC had larger metabolic strains associated with the given percentage of MVC. If selection of power as a function of MVC had produced comparable metabolic strain, the regression line should have had a slope of zero for each exercise trial. These data suggest that a percentage of MVC did not provide a normalized metabolic stress.
DISCUSSION
In the present study, the relationships between muscle morphometrics, power, and metabolic strain were investigated to find the most appropriate strategy of normalizing submaximal workloads for use in steady-state dynamic muscle ergometry. We sought an approach of assigning load parameters that would achieve metabolic stress and resulting strain in a given muscle group that would be comparable between subjects. In this study, the same percent MVC did not result in comparable metabolic strain between subjects spanning a twofold range in muscle mass. Power output normalized to muscle volume showed the highest correlation, with indexes of metabolic strain compared with MVC or CSA. Muscle volume was better than CSA as an estimate of muscle mass, probably because of the variation in muscle shape and difficulty in finding the maximal CSA slice. These data suggest that muscle volume is a good estimate of Qmax and provides a measure to generate comparable metabolic stress between individuals.
We sought a twofold range in age, weight, MVC, PF CSA, and PF volume to optimize the dynamic range of the absolute values of torque output in a similarly active group of adults. Subjects that were able to achieve a metabolic steady state demonstrated inaccuracy of adhering to the torque target, reaching only 79 and 83% of the target TTI for 10 and 15% MVC, respectively. The difficulty in achieving target torque may reflect limitations in neurological activation of muscle contraction (2), an excessively intense target power output, or noncompliance. We selected mechanical parameters for exercise that were anticipated to be within the ability of all subjects. An effort-stroke contraction speed of 30°/s was selected to replicate the muscle contraction speed of a walking gait of ~3 miles/h (assuming a 3-ft. stride length). A rapid speed of 240°/s was selected to ensure that individuals did not try to "help" the automatically returning foot pedal back to the original position. We had found in previous experiments, using return velocities of 30-60°/s, that individuals fatigue their dorsiflexor muscles before challenging the PF muscle group because of inadvertent attempts to assist the foot pedal in returning to the starting position. These compliance issues demonstrate the importance of measuring work performed during an experiment rather than assuming 100% subject compliance.
On the basis of phantom calibrations and repeated measures on a human leg, MRI muscle volume measurements were apparently accurate and precise. However, some limitations of this method should be pointed out. Beginning the calculation of PF volume at the tibial tuberosity gave a reproducible starting point in all individuals. An end point was more difficult, because a precise anatomic end point for the PF compartment could not be determined. Errors related to the failure to identify this terminus of the muscle would be small, because the contribution of each slice in this region of the PF compartment to the overall PF volume was typically <1%/slice. The accuracy of this method for measuring muscle volume could be increased by increasing the spatial resolution with reduced slice thickness and slice separation. However, this approach would dramatically increase the number of images to be processed (from the current average of 25), a scenario more tenable once automated multislice image segmentation is available.
The most accurate and precise measurements of muscle metabolic strain associated with work and morphometry are likely to come from single-muscle models composed of one fiber type. The complex architecture and enervation of coactive muscles around joints in the human body precludes mechanical isolation of most muscles. In addition, the phenotypic and metabolic heterogeneity of human skeletal muscle has been well described (12). Nonetheless, the soleus muscle is more uniform in fiber type (type I) than any of the other large, accessible muscles of the human body (12). The type I fiber composition of the soleus also improved the chances of maintaining a metabolic steady required for this study. For these reasons, the measurement of metabolic strain was made principally from the soleus in this complex muscle action.
In the PF compartment, all muscles are capable of participating in plantar flexion; thus the entire PF compartment was used to estimate Qmax. Estimating the fraction of observed plantar flexion power attributable to any single muscle in this compartment has proven difficult. Furthermore, the stability of a contribution during a sustained bout of submaximal dynamic activity is unclear. Although electromyogram methods and T2-weighted MRI have been used to estimate mechanical activation (1, 7, 8, 21), these methods have limitations in sensitivity and specificity. This is especially true for the water T2 measures, where a complete biophysical description of the exercise-induced water proton-relaxation changes has not been established. Using a nonfatiguing, steady-state paradigm, we have assumed that the soleus muscle contributes a constant fraction of the power. Support for this contention comes from several observations. First, a linear relation between volume-normalized power and soleus metabolic strain was observed among different individuals. This suggests that the contribution of the soleus muscle was similar among individuals. In addition, glycogen depletion is primarily confined to type I fibers during isometric plantar flexion action of <20% MVC (9). Because the soleus is predominantly type I, it is unlikely that very active recruitment of type II fibers (both within the soleus and in other muscles of the PF compartment) would occur in submaximal exercise. Finally, time-dependent activation or recruitment of other muscle groups or fibers was eliminated in this study, because only those individuals who maintained a metabolic steady state were included. A metabolic steady state implies that activation was constant in these individuals. It should be stressed that the metabolic strain measured in this study was only for the soleus muscle group and did not represent the total metabolic strain of the lower leg muscle groups.
There are several critical assumptions in using muscle volume as an estimate of Qmax. First, the blood flow capacity per liter of muscle does not become rate limiting for metabolism. No evidence of demand ischemia was observed in these studies. That is, pH was unchanged and a metabolic steady state was achieved at these submaximal workloads. The use of moderate workloads minimizes the possibility of blood flow limitations as well as improved subject compliance. Second, the mitochondrial volume per liter of muscle and the supporting intermediary metabolism must be the same between index and control groups. This may be a serious limitation in muscle myopathies, some drug treatments, or genetically linked conditions. Third, the degree of muscle activation, for any given muscle group analyzed, must be the same in the exercise protocol. In the present study, a linear correlation was observed between muscle workload and soleus metabolic strain, suggesting that consistent soleus activation was achieved. This may not be the case in other exercise protocols or patient populations. If these assumptions do not hold, then the use of muscle volume as an estimate of Qmax in these protocols may be inappropriate.
Conclusions
These data suggest that normalizing power to muscle volume will result in a similar metabolic stress and strain between different individuals performing submaximal dynamic work. This approach was superior to the use of percentage of MVC or CSA as normalizing parameters. This strategy of power normalization can be used to study populations with either enhanced or impaired muscle performance, provided that the assumptions discussed are adequately addressed when selecting a control group. Normalizing metabolic stress by using muscle volume may improve the sensitivity of clinical studies using 31P-MR spectroscopy to detect alterations in the relationship between work and metabolism.FOOTNOTES
Address for reprint requests: R. S. Balaban, Laboratory of Cardiac Energetics, National Heart, Lung, and Blood Institute, National Institutes of Health, Bldg. 10, Rm. B1D-162, Bethesda, MD 20892.
Received 16 July 1996; accepted in final form 6 June 1997.
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