A Comparison of Techniques for Estimating Training-Induced Changes in Muscle Cross-Sectional Area : The Journal of Strength & Conditioning Research

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A Comparison of Techniques for Estimating Training-Induced Changes in Muscle Cross-Sectional Area

DeFreitas, Jason M; Beck, Travis W; Stock, Matt S; Dillon, Michael A; Sherk, Vanessa D; Stout, Jeffrey R; Cramer, Joel T

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Journal of Strength and Conditioning Research 24(9):p 2383-2389, September 2010. | DOI: 10.1519/JSC.0b013e3181ec86f3
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DeFreitas, JM, Beck, TW, Stock, MS, Dillon, MA, Sherk, VD, Stout, JR, and Cramer, JT. A comparison of techniques for estimating training-induced changes in muscle cross-sectional area. J Strength Cond Res 24(9): 2383-2389, 2010-The ability to accurately estimate changes in muscle cross-sectional area (CSA) could be a useful tool for strength and conditioning practitioners to assess the effectiveness of a resistance training program. The purpose of this study was twofold: (a) to compare the reliability of 2 separate anthropometric-based field estimations of thigh muscle CSA with that of a more accurate, sophisticated imaging technique (peripheral quantitative computed tomography [pQCT] scanner) and (b) to determine if the field methods would be sensitive enough to detect changes in CSA during a resistance training program. Twenty-five healthy, untrained men completed 8 weeks of resistance training. Cross-sectional area testing occurred twice before the start of training, for reliability and again every 2 weeks during the study. Testing consisted of a pQCT scan of the right thigh followed by circumference and skinfold measurements. Two separate equations (Moritani and deVries [M + D] and Housh multiple regression [HMR]) were used to estimate CSA from the anthropometric data. The M + D and HMR methods demonstrated intraclass correlations of 0.983 and 0.961, respectively, but both significantly underestimated thigh muscle CSA when compared to the pQCT. This error was consistent, however, and consequently, the field methods were able to demonstrate increases in muscle CSA with a pattern similar to those from the pQCT. Thus, these equations can be useful tools to evaluate an athlete's progress toward the goal of increasing muscle CSA. It is the authors' hope that the present study will increase awareness among practitioners of these useful field methods for estimating training-induced changes in muscle CSA.


It is well established that strength, which is one of the determinants of performance, has a direct relationship with the mass of skeletal muscle (6,7,9,12). The ability to accurately estimate changes in muscle cross-sectional area (CSA), therefore, could be a useful tool for the strength and conditioning practitioner to assess the effectiveness of their resistance training program. Currently, magnetic resonance imaging (MRI) and computed tomography (CT) are considered to be the gold standards for in vivo estimation of muscle CSA (2-4,8). However, these methods are expensive and typically inaccessible for the coaching community. Anthropometric-based methods may provide the cheapest and most easily accessible alternative for estimating muscle CSA.

The uses of anthropometry for estimating body composition and determination of body build characteristics are fairly well known. However, its use for muscle size estimation is less familiar to the majority of the practitioners. In an early attempt to quantify muscular performance, Martin (10) proposed using height, weight, and chest circumference measurements as an index to predict physical efficiency. Rasch and Morehouse (14) took this concept 1 step further and used upper-arm circumference to track muscle hypertrophy during a 6-week training program. The limitation of girth measurements, however, is that they are unable to distinguish between fat and muscle. To our knowledge, Moritani and deVries (11) were the first to attempt to account for subcutaneous fat with an anthropometric-based estimation of muscle size. They accomplished this by measuring the circumference of the upper arm, calculating its radius, and then adjusting the radius by subtracting the average of 4 skinfolds. Theoretically, the CSA calculated from this fat-adjusted radius includes only the remaining lean tissue (muscle and bone). Housh et al. (8) took a different approach and used MRI to develop an anthropometric-based multiple regression equation to predict thigh muscle CSA.

Despite these advancements in anthropometric-based methodology, CSA is still an inaccessible measurement for most practitioners. The purpose of this study was twofold: (a) to compare the reliability of 2 separate anthropometric-based field estimations of thigh muscle CSA with that of a more accurate, sophisticated imaging technique (peripheral quantitative computed tomography [pQCT] scanner) and (b) to determine if the field methods would be sensitive enough to detect changes in CSA during a resistance training program.


Experimental Approach to the Problem

To investigate the test-retest reliability of the anthropometric and pQCT measurements, each subject performed 2 sessions of pretesting before the resistance training, separated by at least 48 hours. To observe the patterns of response for the different CSA measurement techniques, the subjects performed an 8-week resistance training program designed to stimulate hypertrophy in the leg extensor muscles. The training was 3 d·wk−1, and the sessions were always 48 hours apart. After training began, the subjects were tested again every 2 weeks throughout the study. During the third visit of each testing week, the subjects were tested for CSA, and they then performed their training. With a few minor exceptions, all of the testing was performed at the same time of the day for each subject. A summary of the study design can be seen in Table 1.

Table 1:
A summary of the study design.


Twenty-five healthy men (mean ± SD age = 21.5 ± 3.6 years; stature = 1.81 ± 0.01 m; and mass = 76.5 ± 13.2 kg) volunteered to participate in this investigation. Each participant completed an informed consent and a pre-exercise health and exercise status questionnaire. The questionnaire had to indicate no current or recent (within the past 6 months) neuromuscular or musculoskeletal problems to the knees, hips, or lower back for the subject to be considered eligible for the study. In addition, each subject had to be untrained in resistance exercise (i.e., no participation in an organized weight training program for at least the last 6 months before the study). The study was approved by the University Institutional Review Board for Human Subjects before testing and took place during both the Fall and Spring semesters on the University of Oklahoma campus.


Resistance Training and Testing

The training program consisted of the bilateral incline leg-press, leg extension and bench-press exercises performed 3 d·wk−1 for 8 weeks. For each exercise, 3 sets to failure were performed, with approximately 2 minutes of rest between each set. The training load continually increased as the subjects became stronger to follow the principles of progressive overload. Therefore, the weight was constantly adjusted to assure that the subject was failing between 8 and 12 repetitions (i.e., if the subject performed 16 repetitions, the weight was increased accordingly before the next set). This set-by-set adjustment system is shown in Table 2. During the first pretesting session (PRE1), the subjects were familiarized with the leg press and bench press exercises. This allowed the inexperienced participants to become accustomed to proper lifting technique and also allowed the investigator to find an approximate estimate of the 1-repetition maximums (1RMs) for each participant. During the second pretesting session (PRE2), the subjects performed the 1RM test. Before the 1RM test, each subject performed 3 warm-up sets with loads of 60% (6-8 repetitions), 70% (3-5 repetitions), and 80% (1-2 repetitions) of their estimated 1RM. The weight was then increased after each successful lift until the participant failed. The 1RM was usually established within 5 attempts to the nearest 5-lb increment. Approximately 80% of each subject's 1RM (to the nearest 5-lb. increment) was used as their starting weight for the first training session. The same 1RM testing procedures were used for the posttesting, except that the warm-ups were based on pretesting values, rather than on estimations.

Table 2:
An example of a subject's first workout. *†

Muscle Cross-Sectional Area

The CSA of the right thigh muscles was measured using a pQCT (XCT 3000, Stratec Medizintechnik GmbH, Pforzheim, Germany) scanner. Cramer et al. showed that when compared to the gold standard MRI, the pQCT was a valid and reliable measurement of muscle CSA (3). The authors tested the pQCT's validity using 2 separate investigators and calculated a correlation between MRI and pQCT. Their R2 values were 0.979 and 0.983. For the present study, the subject sat upright with their leg fully extended (180°), and the scan was taken at the midpoint of the thigh (i.e., 50% of the distance between the greater trochanter and lateral epicondyle of the femur). The voxel resolution for each scan was 0.4 mm. Muscle CSA was calculated using the software provided by the manufacturer. This procedure can be seen in Figure 1.

Figure 1:
Analyzing each subject's whole muscle cross-sectional area (CSA, cm2) was a 3-part process. A) A sample scan of a subject's dominant thigh. B) A filter was used to distinguish between the density of fatty tissue and the density of lean tissue (which includes both muscle and bone). C) A separate filter was then used to distinguish between the density of bone tissue and the densities of fat and lean tissue. The CSA of the bone tissue was then subtracted from the CSA of the lean tissue (B-C) to provide the CSA of the thigh muscles.

In addition to using the pQCT to directly measure changes in the muscle CSA, 2 separate techniques of estimating CSA from anthropometric measurements were used. The scan location of the pQCT was marked on the thigh to ensure that the anthropometric measurements were taken at the same position. The measurements included thigh circumference and 4 skinfolds (anterior, posterior, medial, and lateral). The first technique estimated CSA with the following equation as provided by Moritani and deVries (M + D) (11):

where Circumference was the circumference of the thigh, and skf were the thigh skinfold thicknesses at each of the 4 sites. The second technique used the following multiple regression equation as provided by Housh et al (Housh multiple regression [HMR]) (8):

where skfA was the anterior thigh skinfold.

Statistical Analyses

A 2-way repeated measures (method × time) analysis of variance (ANOVA) was used to compare the 3 different muscle CSA measurements across the training program. When appropriate, follow-up analyses included 1-way repeated measures ANOVAs and Bonferroni post hoc comparisons. An alpha level of 0.05 was used for all comparisons. Test-retest reliability between the 2 pretesting sessions was calculated using Pearson correlations, 3 separate paired samples t-tests and 2-way, fixed-effect intraclass correlations (ICCs; model 3,1), and standard error of measurement (SEM), and the minimal difference needed for a change to be considered real (15).


Muscle Cross-Sectional Area

The mean ± SD thigh muscle CSAs for the 3 measurement methods can be seen in Figure 2. The 2-way repeated measures ANOVA revealed a significant method × time interaction. Three separate 1-way repeated-measures ANOVAs established that for each of the 3 methods, there was a significant increase in CSA over time. Six additional 1-way repeated-measures ANOVAs showed that there were significant differences among the CSAs from the 3 methods at each time point. Bonferroni pairwise comparisons for all 1-way ANOVAs are shown in Figure 2. Correlations among the 3 methods are demonstrated in Figures 3-5. The test-retest reliability results for each method are shown in Table 3. The pretesting (PRE 2) to posttesting (Week 8) percent changes in CSA for the pQCT, M + D, and HMR methods were 9.1, 16.6, and 9.9%, respectively.

Table 3:
Test-retest reliability for the 3 methods of estimating muscle cross-sectional area.*
Figure 2:
Mean ± SD muscle cross-sectional area (CSA; cm2) across the training program for the peripheral quantitative computed tomography (pQCT), Moritani and deVries (M + D) (11), and Housh multiple regression (HMR) (8) methods.
Figure 3:
Relationship between the pQCT and Moritani and deVries (M + D) (11) methods for estimating cross-sectional area (CSA; cm2).
Figure 4:
Relationship between the pQCT and Housh multiple regression (HMR) (8) methods for estimating cross-sectional area (CSA; cm2).
Figure 5:
Relationship between the Moritani and deVries (M + D) (11) and Housh multiple regression (HMR) (8) methods for estimating cross-sectional area (CSA; cm2).


Previous investigations have shown that the pQCT can accurately determine muscle CSA (3,4). However, the technique is expensive and requires extensive training by the investigator. Therefore, it is also impractical and prohibitive for strength and conditioning practitioners and some researchers. The results from this study indicated that anthropometric field methods can not only be used to estimate thigh muscle CSA before a training program, as previously investigated (3) but can also estimate the changes in CSA that occur during a resistance training program.

We hypothesized that the pQCT would be more sensitive to changes in muscle CSA than the other 2 methods that are based on anthropometric measurements. For example, small changes in muscle CSA at the beginning of the training program might be detected with the pQCT but not with the other 2 methods. To our surprise, not only did the anthropometric measurement-based methods show high degrees of precision with ICCs of 0.983 and 0.961, compared to 0.995 for the pQCT, but they also showed similar sensitivity to change. All 3 methods showed a significant increase in muscle CSA after only 2 weeks of training. It should be noted that although the anthropometric-based methods provided a similar pattern of response for CSA over time as the pQCT, they consistently underestimated the absolute value of muscle CSA. The overall percentage change in CSA because of training from the HMR method (9.9%) was very similar to that of the pQCT (9.1%), but less than that from the M + D method (16.6%). The absolute CSA values for the HMR method were also more highly correlated with those of the pQCT (r = 0.95) than those from the M + D method (r = 0.91). However, as shown in Figure 2, the values estimated by the M + D method did not underestimate the CSA as much as the HMR method. At each time point, the M + D CSA values were significantly closer to those from the pQCT than were those from the HMR. Therefore, each anthropometric-based method has advantages and disadvantages, but both provide reliable and reasonably valid estimates of CSA.

Moritani and deVries (11) did not report any hypertrophic changes (based on the Efficiency of Electrical Activity [EEA] technique) until roughly 4-6 weeks into their training program. The authors (11) did not, however, have access to the peripheral imaging techniques that are available today. This led to the expectation of less sensitivity to change for the M + D method when compared to the pQCT technique in this study. The disparity in the time course of hypertrophic changes between Moritani and deVries (11) and the present investigation could be because of a number of reasons. First, Moritani and deVries (11) investigated the biceps brachii, whereas the present study examined the quadriceps femoris. It is possible that the difference in the architecture between the 2 muscle groups (fusiform vs. pennate) may have influenced the disparity in the rate that the CSAs increased. Second, the volume of training used was significantly different in the 2 studies. Moritani and deVries's (11) subjects performed unilateral training of the forearm flexors using 2 sets of 10 repetitions at approximately 67% of their maximum. The subjects of the present study followed a program in which the variables matched recommendations by the National Strength and Conditioning Association (NSCA) with the goal of stimulating hypertrophy (1). Therefore, they performed bilateral training of the leg extensors using 3 sets of 8-12 repetitions at approximately 80% of their maximum while following the principles of progressive overload. Additionally, because they also performed the bench press exercise, they recruited more muscle mass than the Moritani and deVries (11) study and incorporated both the upper- and lower-body. This may be noteworthy because Hansen et al. (5) have shown there is a significantly greater growth hormone response when a combination of upper- and lower-body exercises is performed, and Mulligan et al. (13) reported that exercise routines with greater training volumes elicit greater hormonal and metabolic responses than those with lower volumes. Third, Moritani and deVries's (11) subjects only trained the agonist muscle. Because the leg press exercise used in the present study involves thigh extension, the antagonist (hamstrings) muscles were also trained. Although the thigh extensors did not undergo the same volume of training as the leg extensors, it is possible that they did influence the muscle CSA changes. However, they would have influenced the CSA measurements of the pQCT and anthropometric-based methods equally.

Practical Applications

For a coach aiming to increase the muscle mass of his or her athletes, the anthropometric equations that were used in the present study can be useful tools to evaluate their progress toward that goal. These equations are simple, inexpensive, and reliable methods for estimating training-induced changes in muscle CSA. It is the authors' hope that the present study not only increases the awareness among practitioners of these potentially useful field methods for assessing muscle CSA but also justifies their use to assess progress and track training-induced changes in muscle CSA.


The funding for this study was received by the NSCA Foundation through their Master's Student Research Grant.


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anthropometry; pQCT; hypertrophy

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