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1 From the School of Physical and Health Education (SJL, IJ, and RR), the Department of Community Health and Epidemiology (IJ), and the Division of Endocrinology and Metabolism, Department of Medicine (RR), Queen’s University, Kingston, Canada, and the Obesity Research Center, St Luke’s-Roosevelt Hospital, Columbia University College of Physicians and Surgeons, New York (SBH)
2 Supported by grants from the Canadian Institutes of Health Research (MT 13448) and Mars Corporation (to RR) and by the National Institutes of Health (grants RR-00645 and DK-42618 to SBH). IJ was supported by a Canadian Institutes of Health Research Postdoctoral Fellowship. 3 Address reprint requests to R Ross, School of Physical and Health Education, Queen’s University, Kingston, Ontario, Canada, K7L 3N6. E-mail: rossr{at}post.queensu.ca.
ABSTRACT
Background: It is unknown whether regional measures of skeletal muscle (SM) in the thigh and abdomen accurately reflect whole-body SM mass.
Objective: We aimed to determine whether thigh and abdominal SM measures reflect whole-body SM mass and, if so, which region is a stronger marker.
Design: Whole-body and regional measures of SM were obtained by magnetic resonance imaging in a sample of 387 white men and women.
Results: The regional SM measures, whether obtained by using a single image (midthigh or L4-L5 level) or a series of 7 consecutive images covering 31 cm (thigh or abdomen), were strongly correlated with whole-body SM (P < 0.001). Independent of sex, the thigh SM measures derived from a single image (men: R2 = 0.77, SEE = 6.5%; women: R2 = 0.79, SEE = 7.4%) or a series of 7 consecutive images (men: R2 = 0.84, SEE = 5.4%; women: R2 = 0.90, SEE = 5.1%) were stronger correlates of whole-body SM with smaller SEE values than were the abdominal SM measures (P < 0.01). However, SM in the abdomen was also a strong marker of whole-body SM, whether determined from a single image at the L4-L5 level (men: R2 = 0.63, SEE = 8.2%; women: R2 = 0.58, SEE = 10.4%) or from a series of images across the abdomen (men: R2 = 0.77, SEE = 6.5%; women: R2 = 0.70, SEE = 8.7%).
Conclusion: Although thigh measures of SM are better predictors of whole-body SM, a single image within the abdomen routinely used to estimate abdominal fat may also be a useful marker of whole-body SM.
Key Words: Magnetic resonance imaging • body composition • computed tomography
INTRODUCTION
Accurate measurement of skeletal muscle (SM) is essential in many fields of nutrition, applied physiology, and clinical medicine (1, 2). Computed tomography (CT) and magnetic resonance imaging (MRI) provide accurate measures of SM tissue (3-5), and protocols that use multiple images covering the entire body are the criterion method for measurement of whole-body SM (5). However, cost, accessibility, and ionizing radiation (in the case of CT) limit the use of whole-body imaging. Thus, it is common for investigators and clinicians to use a single image (area, in cm2) for the purpose of estimating whole-body SM. Because >50% of the SM tissue is located in the lower extremity, with much of this muscle located in the thigh region (6), most studies select the midthigh region for SM measurement (5). Although a single image is routinely used to quantify SM, some investigators have hypothesized that the SM volume or mass obtained from a series of multiple images in the thigh would be a stronger predictor of whole-body SM (5, 7, 8). In fact, at present it is unknown whether measures of SM in the thigh region, obtained by using a single image or multiple images, accurately reflect whole-body SM mass.
MRI and CT have also been used extensively in obesity research to examine fat distribution in the abdomen. In most studies, abdominal subcutaneous and visceral fat area are quantified at a level corresponding to the intervertebral disk between the 4th and 5th lumbar vertebrae (L4-L5) (5, 9). Some investigators have used multiple imaging protocols to determine the volume or mass of subcutaneous and visceral fat over the entire abdominal region (5, 9-12). In addition to subcutaneous and visceral fat, SM can be quantified in these abdominal images. To our knowledge, no previous study has examined whether measures of SM in the abdomen relate to whole-body SM mass.
The purpose of the present study was twofold. First, we sought to determine whether regional measures of SM in the thigh and abdomen accurately reflect whole-body SM mass and, if so, which region is a stronger indicator of whole-body SM. Second, we sought to determine whether measures of SM obtained from a single MRI image are as strong a marker of whole-body SM mass as are measures of SM obtained from a series of multiple MRI images. To address these questions, we measured whole-body and regional SM with MRI in a heterogeneous sample of 387 white men and women.
SUBJECTS AND METHODS
Study population
The subjects consisted of healthy white men (n = 190) and women (n = 197) who participated in various body-composition studies at Queen’s University (Kingston, Canada) and St Luke’s-Roosevelt Hospital (New York). Although the subjects varied widely in age (18–88 y) and body mass index (BMI, in kg/m2: 16–40), most were middle-aged (65% were aged between 30 and 55 y) and overweight (27% had a BMI of 25–29.9) or obese (46% had a BMI 30). Two hundred ninety-eight subjects from Queen’s University and 89 subjects from Columbia University were recruited from among hospital employees, students at local universities, and the general public through posted flyers and the local media. All participants gave informed consent before participation in accordance with the ethical guidelines of the respective institutional review boards.
Measurement of skeletal muscle by magnetic resonance imaging
The MRI images were obtained with a General Electric 1.5-T scanner (Milwaukee). A T1-weighted, spin-echo sequence with a 210-ms repetition time and a 17-ms echo time was used to obtain the MRI data. The MRI protocol is described in detail elsewhere (10). Briefly, the subjects lay in the magnet in a prone position with their arms placed straight overhead. With use of the L4–L5 as the point of origin, transverse images (10-mm image thickness) were obtained every 40 mm from hand to foot. Three series of 7 images were obtained for the lower body, and 3 series of 7 images were obtained for the upper body. The total time required to acquire all of the MRI data for each subject was 30 min.
Segmentation and calculation of skeletal muscle area, volume, and mass
Once acquired, the MRI data were transferred to a personal computer for analysis with specially designed image analysis software (SLICE-O-MATIC; Tomovision Inc, Montreal), the procedures for which are fully described and illustrated elsewhere (3, 10, 13). Briefly, a multiple-step procedure was used to identify tissue area (cm2) for a given MRI image. In the first step, a filter distinguished between different gray-level regions on the images, and lines were drawn around the different regions by using a watershed algorithm. The observer then labeled the different tissues by assigning them different codes. Each image was reviewed by an interactive slice-editor program that allowed for verification and, where necessary, correction of the segmented results. The original gray-level image was superimposed on the binary segmented image by using a transparency mode to facilitate the corrections. The area (cm2) of adipose tissue–free SM in each image was computed automatically by summing the SM pixels and multiplying by the individual pixel surface area. The volume (cm3) of SM in each image was calculated by multiplying tissue area (cm2) by the image thickness (10 mm). The SM volume for the space between 2 consecutive images (40 mm) was calculated by using a mathematical algorithm given elsewhere (3). Volume units (L) were converted to mass units (kg) by multiplying the volumes by the assumed constant density (1.04 kg/L) for adipose tissue–free SM (14).
Selection and determination of regional skeletal muscle measures
Whole-body SM was calculated by using all 41 images. The regional measures were determined by using the thigh and abdominal regions because they are commonly used in imaging studies that measure regional SM or fat. For both regions, the area (cm2) values of SM obtained from a single image and the mass (kg) values of SM derived from a series of 7 consecutive images were compared with whole-body SM mass (kg). Midthigh SM area (cm2) was measured at a level 20 cm below the femoral head (image 14 in Figure 1). This approach facilitated the use of a common landmark and represents an area in the thigh with a large amount of SM. SM mass in the thigh was calculated by using a series of 7 images beginning at the femoral head and extending to 31 cm below the femoral head (7 x 10 mm thick images + 6 x 40 mm spaces between images = 31 cm; images 12–18 in Figure 1). Abdominal SM area (cm2) was measured at the level of the L4–L5 intervertebral disk (Figure 2; image 21 in Figure 1). SM mass (kg) in the abdomen was calculated by using a series of 7 images extending from 5 cm below L4–L5 to 25 cm above L4–L5 [images 20–26 (31 cm in total) in Figure 1]. This approach facilitated the use of a common landmark (L4–L5) and corresponds with a region that has been used extensively to measure abdominal subcutaneous and visceral fat (5, 9).
FIGURE 1.. Distribution of skeletal muscle as measured by magnetic resonance imaging in 190 men and 197 women. Values are means ± SDs. In general, images 1–16 represent the legs, images 17–19 the pelvic region, images 20–28 the abdomen and torso, and images 30–41 the arms.
FIGURE 2.. Magnetic resonance imaging of the L4-L5 level in a 38-y-old man with a BMI (in kg/m2) of 23.2 and in a 22-y-old woman with a BMI of 23.7. Skeletal muscle and organs appear dark, whereas adipose tissue appears white.
Reliability of magnetic resonance imaging measurements
We determined the reproducibility of the MRI SM measurements by comparing the intra- and interobserver estimates for the measurements (one series of 7 images taken in the legs) obtained in 3 male and 3 female subjects (3). The interobserver difference was 1.8 ± 0.6% and the intraobserver difference was 0.34 ± 1.1% (3). The intraobserver difference was calculated by comparing the analysis of 2 separate MRI acquisitions in a single observer, whereas the interobserver difference was determined by comparing 2 observers’ analyses of the same images. We determined the reproducibility of the MRI SM measurements across the laboratories by comparing the 2 laboratories’ analyses of the same images (whole body) for 5 subjects. The interlaboratory difference was 2.0 ± 1.2% (6).
Statistical analysis
Statistical procedures were performed by using SPSS version 11.0 (SPSS Inc, Chicago). Differences between men and women were tested for significance by using unpaired t tests. Pearson’s correlations were performed to determine the relations between whole-body SM and regional SM measurements. The strength of the correlations was compared by using the Hotelling method (15). The strength of the SEE values was compared by using Pitman’s test (16).
To determine whether there was a nonlinear relation between the various regional SM measures and whole-body SM mass, each of the regional measures was regressed by using a full cubic polynomial (regional SM measure, regional SM measure2, regional SM measure3). Multiple-regression analysis and analysis of variance were used to determine sex differences in the slopes and intercepts of the regression lines.
RESULTS
The subjects’ characteristics are given in Table 1. The men and women did not differ significantly in average age or BMI (P > 0.1). The general distribution of SM across the whole body for men and women is illustrated in Figure 1. In general, men had a higher SM area (cm2) per image across the body. In men, 31% of whole-body SM was located in the thigh region (images 12–18), and 15% of whole-body SM mass was in the abdomen (images 20–26). In women, 33% of whole-body SM mass was in the thigh region, and 15% was in the abdomen.
View this table:
TABLE 1. Subject characteristics1
The variances in whole-body SM mass explained by the regional measures of SM are listed in Table 2. Within both sexes, whether obtained by using a single image (area in cm2, 1-cm thick region) or a series of 7 images (mass in kg, 31-cm thick region), the thigh and abdominal SM measures were all strongly related to whole-body SM mass (P < 0.001). In both men and women, the thigh SM measures were stronger correlates of whole-body SM than were the abdominal SM measures (P < 0.01), and the SEE values were smaller for the thigh measures (P < 0.01). Furthermore, independent of sex, the mass of SM in the thigh region (31-cm thick region) was a stronger correlate of whole-body SM mass than was the area (1-cm thick region) of SM in the single thigh image (P < 0.01), despite the fact that midthigh SM area was highly correlated with thigh SM mass (R2 = 0.72 in men, P < 0.001; R2 = 0.72 in women, P < 0.001). Similarly, abdominal SM mass was a stronger correlate of whole-body SM than was the area of SM in the L4-L5 image (P < 0.01), despite the fact that L4-L5 SM area was highly correlated with abdominal SM mass (R2 = 0.88 in men, P < 0.001; R2 = 0.92 in women, P < 0.001). For both the thigh and abdominal regions, the SEE values were smaller (P < 0.01) for the mass measurements than for the area measurements (Table 2).
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TABLE 2. Relation between regional skeletal muscle (SM) measures and whole-body SM mass1
The relations between each of the thigh (images 12–18 in Figure 1) and abdominal (images 20–26 in Figure 1) images with whole-body SM are provided in Table 3. For the thigh, the highest R2 value with the lowest SEE was obtained at midthigh (image 14) for both men and women. Independent of sex, the SM area values obtained for the 4 images beginning at a point 10 cm below the femoral head (image 16) and extending to 25 cm below the femoral head (image 13) were all strongly related to whole-body SM mass. For the abdomen, the highest R2 value with the lowest SEE was obtained at the image located 5 cm above L4-L5 (image 22). The data in Table 3 also show that the SM values obtained at the L4-L5 level (image 21) and 10 cm above L4-L5 (image 23) were strongly related to whole-body SM mass with low SEE values.
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TABLE 3. Relation between skeletal muscle (SM) measures derived from the individual images obtained in the thigh and abdominal regions and whole-body SM mass1
We used multiple regression analysis to determine whether the combination of thigh and abdominal SM measures explained more of the variance in whole-body SM mass than did the thigh SM measures alone. As shown in Table 4, midthigh SM area explained 77% and 79% of the variance in whole-body SM mass in men and women, respectively. The addition of L4-L5 SM area to the multiple regression models explained an additional 4% and 3% of the variance in whole-body SM mass in men and women, respectively (P < 0.001). Similarly, thigh SM mass explained 84% and 90% of the variance in whole-body SM mass in men and women, respectively. The addition of abdominal SM mass to the multiple regression models explained an additional 8% and 3% of the variance in whole-body SM mass in men and women, respectively (P < 0.001). In women, the SEE values were not significantly different (P > 0.05) when the combination of abdominal and thigh SM measures (area or mass) was used to predict whole-body SM by comparison with when the thigh measures alone were used to predict whole-body SM (Table 4). In men, the SEE values were not significantly different (P > 0.05) when the combination of L4-L5 SM area and midthigh SM area was used to predict whole-body SM. However, in men, the SEE values were smaller (P < 0.01) when the combination of abdominal and thigh SM mass was used to predict whole-body SM than when thigh SM mass alone was used.
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TABLE 4. Multiple regression model for predicting whole-body skeletal muscle (SM) with regional SM measures1
The relation between the 4 regional SM measures and whole-body SM mass is illustrated in Figure 3. There was a nonlinear relation between thigh SM area and whole-body SM mass in men and women (panel A). For SM area at the L4-L5 image, there was a linear relation with whole-body SM mass in men but a nonlinear relation in women (panel B). Independent of sex, there was a linear relation between the mass of SM in the thigh (panel C) and abdomen (panel D) and whole-body SM mass. Without exception, the slopes and intercepts of the regression lines shown in Figure 3 were not significantly different (P > 0.05) in men and women.
FIGURE 3.. Relation between whole-body skeletal muscle (SM) and regional SM measures in men (n = 190) and women (n = 197). A: for men, whole-body SM (kg) = 0.136 (thigh SM area) –0.000085 (thigh SM area2) –3.137 (R2 = 0.78, SEE = 2.12 kg); for women, whole-body SM (kg) = 0.000154 (thigh SM area2) + 12.735 (R2 = 0.79, SEE = 1.55 kg). B: for men, whole-body SM (kg) = 0.134 (L4-L5 SM area) + 8.838 (R2 = 0.63, SEE = 2.73 kg); for women, whole-body SM (kg) = 0.00053 (L4-L5 SM area2) + 13.486 (R2 = 0.60, SEE = 2.15 kg). C: for men, whole-body SM (kg) = 2.912 (thigh SM mass) + 3.399 (R2 = 0.84, SEE = 1.77 kg); for women, whole-body SM (kg) = 2.775 (thigh SM mass) + 1.692 (R2 = 0.90, SEE = 1.09 kg). D: for men, whole-body SM (kg) = 5.679 (abdominal SM mass) + 4.419 (R2 = 0.77, SEE = 2.15 kg); for women, whole-body SM (kg) = 5.495 (abdominal SM mass) + 3.201 (R2 = 0.70, SEE = 1.86 kg).
DISCUSSION
The findings of the present study show that regional measurements of SM in the thigh are stronger correlates of whole-body SM (R2 values 0.07–0.21) with lower SEs (relative SEE values 1.1–3.6% lower) than are corresponding measures of SM in the abdomen. However, measures of SM in the abdomen, whether determined from a single image at the L4-L5 level or from a series of images across the abdomen, were also strong correlates of whole-body SM (R2 values of 0.58–0.77) with reasonable SEs (SEE values of 6.5–10.4%). This is a novel finding and suggests that a single image at the L4-L5 level, which is more routinely used to obtain surrogate measures of total and abdominal fat, may also act as a surrogate measure of whole-body SM.
It is not surprising that the measures of thigh SM were stronger correlates of whole-body SM mass with lower SEs than were the abdominal measures. At least part of the explanation is mathematical: for example, the thigh SM mass measurement derived by using 7 consecutive images represented 31% and 33% of whole-body SM mass in men and women, respectively. By contrast, the corresponding abdominal SM mass measurement represented 15% of whole-body SM mass in both sexes. Interestingly, the addition of abdominal SM to the thigh SM measurements had a minimal effect on the SEEs for predicting whole-body SM that were observed for the thigh SM measures alone (Table 4). This suggests that if the measurement of SM alone is the primary study outcome, measurement of thigh SM would suffice and, accordingly, the added measurement of abdominal SM would be superfluous. On the other hand, if axial images (MRI or CT) of the abdomen were acquired for the purpose of estimating abdominal adiposity, our findings suggest that the measurement of abdominal SM at L4-L5 would explain another 3–8% of the variance in whole-body SM and would reduce the corresponding SEE by 1%.
As expected, our findings showed that for men and women, the relation between the SM mass values derived by multiple images (eg, 31-cm region) in the thigh and abdomen were stronger correlates of whole-body SM with lower SEs than were the respective SM area values derived from a single (eg, 1 cm) image (Table 2). However, further analysis also showed that not all SM values for the images within the thigh and abdominal regions related to whole-body SM in the same way. Indeed, for the thigh region, independent of sex, the relation between thigh and whole-body SM was best for the 4 images that spanned a 16-cm region beginning 10 cm below the femoral head (Table 3). Assuming the purpose of measuring SM in the thigh is to reflect whole-body SM, the implication is that the acquisition of a single MRI or CT image anywhere within this 16-cm region should provide equally strong estimates of whole-body muscle. A similar rationale holds true independent of sex for the region in the abdomen marked by the L4-L5 intervertebral space and 10 cm above (Table 3). These observations have practical implications when using CT, because the acquisition of a single image limits the subject’s exposure to ionizing radiation. For MRI, exposure to radiation is not a problem, nor is the issue of acquisition time, because the time required to obtain 7 images (eg, in this study, 2 min 46 s in the thigh or 26 s in the abdomen) is not different from the time required to obtain a single image (as the result of characteristics inherent to the acquisition of multiple MRI images in a single acquisition sequence). Furthermore, because changes in SM area differ throughout the thigh region in response to various exercise regimens (eg, resistance or aerobic training) (17), it seems reasonable to suggest that a multiple-image protocol be used when using MRI to determine the effects of a given perturbation on SM mass or distribution.
Whereas MRI and CT images in the abdominal regional have been used extensively in obesity research to examine fat distribution (5, 9), little is known about whether the SM measures from these images can be used to estimate SM mass (Figure 2). Accordingly, an important finding of the present study is that SM area for the commonly used L4-L5 image is a strong indicator of whole-body SM, with R2 values of 0.60 and SEE values of 10%. These results indicate that a single image at the L4-L5 level can be used to obtain estimates of whole-body SM, in addition to abdominal subcutaneous and visceral fat.
Because our study sample was relatively homogeneous (eg, all white and predominantly obese), we made no attempt to develop and cross-validate whole-body SM prediction models that could be applied to the general population. Future studies are needed to extend our findings and develop these algorithms. We did observe that there were curvilinear relations between some of the regional measures of SM and whole-body SM mass, particularly in women (Figure 3). The implication of this finding is that a change in abdominal or thigh SM at the lower end of the scale may not reflect the same change in whole-body SM as does a comparable change in abdominal or thigh SM at the upper end of the scale. For example, if 2 women with SM areas of 170 and 250 cm2 in the midthigh were to each lose 20 cm2 of SM in that image over a given period of time, our results suggest that the first women would have lost 1.0 kg of SM (17.2–16.2 kg), whereas the second women would have lost 1.5 kg of SM (22.4–20.9 kg).
In the aforementioned example, there was a loss of SM, which occurs as a natural process of aging, a condition referred to as sarcopenia. We showed previously that sarcopenia progresses at a faster rate in lower-body SM than in upper-body SM (6), which may cause problems when using regional measures of SM to predict whole-body SM mass or changes in SM mass in an aging population. Similar problems may also arise when using regional measures of SM as indicators of whole-body SM in intervention studies, such as strength training, where an increase in SM would be expected. Training programs that focus on muscle groups in one region of the body (eg, thigh) also measure SM in these regions (17, 18), and changes in SM in this region would likely not be an accurate reflection of changes in whole-body SM mass. This notion is confirmed in a preliminary report by Abe et al (19), who observed non-uniform changes in SM hypertrophy across the body in 3 men who performed a 4-mo resistance training program consisting of 3 lower-body and 2 upper-body exercises.
In summary, the findings of the present study suggest that for both men and women, SM values obtained in the thigh are better markers of whole-body SM than are SM values obtained in the abdomen. However, SM values for a single image in a region expanding from L4-L5 to 10 cm above L4-L5 also provide useful estimates of whole-body SM. Because our findings were derived from white men and women, it is unknown whether these findings remain true for other ethnic groups. Future studies should develop and cross-validate prediction models for estimating whole-body SM by the use of single or multiple images in the thigh and abdominal regions.
ACKNOWLEDGMENTS
SJL and IJ performed the data analysis; SJL, IJ, and RR wrote the manuscript; and SBH aided in the interpretation and presentation of the results. None of the authors had a conflict of interest.
REFERENCES