J C E M
O N L I N E
B r i e f
R e p o r t — E n d o c r i n e
C a r e
Dynamic PET Imaging Reveals Heterogeneity of
Skeletal Muscle Insulin Resistance
Jason M. Ng, Alessandra Bertoldo, Davneet S. Minhas, Nicole L. Helbling,
Paul M. Coen, Julie C. Price, Claudio Cobelli, David E. Kelley,
and Bret H. Goodpaster
Division of Endocrinology and Metabolism Department of Medicine (J.M.N., N.L.H., B.H.G.) and
Departments of Radiology (D.S.M., J.C.P.) and Health and Physical Activity (P.M.C.), University of
Pittsburgh School of Medicine, Pittsburgh, Pennsylvania 15231; Department of Information Engineering
(A.B., C.C.), University of Padova, Padova, Italy; and Merck, Sharp, and Dohme Corporation (D.E.K.),
Rahway, New Jersey 07065
Purpose: Skeletal muscle insulin resistance (IR) often precedes hyperglycemia and type 2 diabetes.
However, variability exists within different skeletal muscle types and can be influenced by 3 primary
steps of control: glucose delivery, transport, and phosphorylation. We performed dynamic positron
emission tomography imaging studies to determine the extent to which heterogeneity in muscle
type and control of insulin action contribute to IR.
Methods: Thirteen volunteers from normal weight to obese underwent dynamic positron emission
tomography imaging of [15O]H2O, [11C]3-O-methylglucose, and [18F]fluorodeoxyglucose, measuring
delivery, transport, and phosphorylation rates, respectively, in soleus and tibialis anterior muscle during
a hyperinsulinemic-euglycemic clamp. Subjects were classified as insulin-sensitive (IS) or insulin-resistant (IR) based on the median systemic glucose infusion rate needed to maintain euglycemia.
Results: In soleus, transport kinetic rates were significantly higher (P ⬍ .05) in IS (0.126 ⫾ 0.028
min⫺1) vs IR (0.051 ⫾ 0.008 min⫺1) subjects. These differences were not as evident in tibialis
anterior. These differences were paralleled in overall insulin-stimulated tissue activity, higher in IS
(0.017 ⫾ 0.001 mL 䡠 cm3 䡠 min⫺1) vs IR (0.011 ⫾ 0.002 mL 䡠 cm3 䡠 min⫺1) in soleus (P ⬍ .05), without
significant differences in tibialis anterior. No significant differences were observed for either muscle in delivery or phosphorylation. Both muscle types displayed a control shift from an even distribution among the steps in IS to transport exerting greater control of systemic insulin sensitivity
in IR.
Conclusion: Lower glucose transport rates are the major feature underlying IR preceding type 2
diabetes, although substantial heterogeneity in insulin action across muscle types highlight the
complexity of skeletal muscle IR. (J Clin Endocrinol Metab 99: E102–E106, 2014)
S
keletal muscle is the major site for insulin-stimulated
glucose disposal in humans after a meal and is controlled by 3 steps: delivery, transport, and phosphorylation (1, 2). Previous studies have reported glucose transport and impairment of phosphorylation in insulin
resistance (IR) and type 2 diabetes mellitus (T2DM) (3– 6).
It is known that muscle IR can develop in obesity before
T2DM, and IR is not uncommon among normal-weight
persons, termed the lean but metabolically obese phenotype (4, 5, 7).
Understanding skeletal muscle IR is complicated by
skeletal muscle group fiber heterogeneity (oxidative type
1 and glycolytic type 2) and potentially multiple sites for
metabolic control, and this has been challenging to deci-
ISSN Print 0021-972X ISSN Online 1945-7197
Printed in U.S.A.
Copyright © 2014 by The Endocrine Society
Received May 1, 2013. Accepted October 15, 2013.
First Published Online October 29, 2013
Abbreviations: BMI, body mass index; FDG, fluorodeoxyglucose; IR, insulin resistance; IS,
insulin sensitivity; MR, magnetic resonance; OMG, O-methylglucose; PET, positron emission tomography; ROI, region of interest; T2DM, type 2 diabetes mellitus.
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J Clin Endocrinol Metab, January 2014, 99(1):E102–E106
doi: 10.1210/jc.2013-2095
doi: 10.1210/jc.2013-2095
pher in humans (6). Positron emission tomography (PET)
imaging allows for specific muscle group measurements of
insulin sensitivity (IS) and has previously provided valuable information regarding glucose metabolism proximal
control sites and skeletal muscle type heterogeneity in lean
healthy adults (3). However, this methodology has not
specifically been performed to evaluate the effects of IR.
Using PET imaging to distinguish specific muscle groups,
this study provides novel data regarding the IR effect on
specific muscle fiber type heterogeneity in human skeletal
muscle and the control distribution of insulin-stimulated
glucose uptake before hyperglycemia or diabetes.
Materials and Methods
Study design
The study included 13 volunteers ranging from normal weight
(n ⫽ 6; 4 females, 2 males) to overweight and obese (n ⫽ 7; 5
females, 2 males). The study protocol was previously described (3).
Informed, written consent was obtained after the study was described in detail and all questions answered for all participants.
Briefly, after an overnight fast, catheters were placed in an antecubital vein for insulin infusion, glucose infusion, and PET tracer injection and in a radial artery for blood sampling. After insulin initiation (40 mU 䡠 m⫺2 䡠 min⫺1), arterial glucose was measured every
5 minutes with a YSI glucose analyzer. An adjustable 20% dextrose
infusion preserved euglycemia. PET images were acquired using an
ECAT HR⫹ PET scanner (Siemens/CTI) in 3-dimensional imaging
mode. Pliable block molding was used to support the legs, minimize
motion, and maintain leg alignment during imaging. The final reconstructed PET image was 6 mm.
The insulin infusion began 1 hour before any radiotracer injections. Radioactive tracers were injected in the following sequence: [15O]H2O, [11C]3-O-methylglucose (OMG), and
[18F]fluorodeoxyglucose (FDG). The study design is presented in
Supplemental Figure 1 (published on The Endocrine Society’s
Journals Online website at http://jcem.endojournals.org). During the same week, a midcalf T1-weighted magnetic resonance
(MR) imaging of skeletal muscle was conducted. The imaging
methodology for this study is summarized in previous publications (3).
PET imaging data analysis
MR images were used to generate regions of interest (ROI) on
soleus and tibialis anterior muscle avoiding major vessels and bones
of the lower leg. PET images were summed over the initial 15 minutes after the injection scanning period to emphasize and, consequently, avoid the blood component. PET and MR images were
coregistered using previously described methods (8 –10). The ROI
was applied to each frame across each leg omitting the proximal and
distal 5 planes to reduce scatter influence and was applied to the
soleus and tibialis anterior muscle groups in the thigh of each leg.
Tracer activity within the ROI is tissue activity representing the
tracer within the muscle. Tissue activity was converted to radioactivity concentrations (kilobecquerels per milliliter) using an empiric
phantom-based calibration factor (kilobecquerels per milliliter per
PET count per pixel). A representative illustration is shown in Supplemental Figure 2. Compartmental modeling was performed to
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quantify the physiological parameters describing skeletal muscle
glucose delivery, transport, and phosphorylation using previously
described methods (3) with the following significance: k1 is strongly
related to capillary perfusion, k2 is proportional to outward perfusion; k3 is inward transmembrane transport for [11C]3-OMG, k4 is
outward transmembrane transport for [11C]3-OMG, k5 is the
phosphorylation rate constant, and K is overall fractional uptake.
Statistical analysis
Data are expressed as a mean ⫾ SE unless otherwise indicated.
ANOVA was used to examine differences between groups. A P
value ⬍ .05 was considered significant. Spearman’s correlations
were used to calculate correlations between variables.
Results
The mean glucose infusion rate was 5.7 ⫾ 0.4 mg 䡠 min⫺1 䡠
kg⫺1 for all subjects, with a median of 6.4 mg 䡠 min⫺1 䡠
kg⫺1 and a significant difference (P ⬍ .05) between IR
(4.3 ⫾ 0.4) and IS (7.0 ⫾ 0.3). The gender distribution was
4 female and 3 male IS subjects and 5 female and 1 male
IR subject. The IS and IR groups were similar in age, fasting glucose, hemoglobin A1c, total cholesterol, and
plasma triglycerides. Body mass index (BMI) was not significantly different. Clinical characteristics and kinetic estimates representing the steps of skeletal muscle glucose
metabolism with insulin stimulation are shown as mean ⫾
SE with P values in Table 1.
Glucose delivery, either inward (k1) or outward (k2),
was not significantly different between IR and IS in either
muscle group as determined by [15O]H2O (n ⫽ 11). Inward (k3) and outward (k4) transport was significantly
higher in IS (0.126 ⫾ 0.028 minutes⫺1) vs IR (0.051 ⫾
0.008 minutes⫺1) in soleus (P ⬍ .05), but significant differences in glucose transport kinetics were not observed in
tibialis anterior as determined by [11C]3-OMG (IS,
0.071 ⫾ 0.018; IR, 0.057 ⫾ 0.010; P ⫽ .55). The fractional phosphorylation rate (k5) was not significantly different between IR and IS. The overall fractional uptake (K)
was significantly higher in IS (0.017 ⫾ 0.001 mL 䡠 cm3 䡠 min⫺1)
in soleus muscle compared with IR (0.011 ⫾ 0.002) (P ⬍
.05). Tibialis anterior trended toward higher tissue activity
(IR, 0.013 ⫾ 0.001 mL 䡠 cm3 䡠 min⫺1; IS, 0.017 ⫾ 0.001, P ⫽
.13) as determined by [18F]FDG. Kinetic values are shown in
Figure 1.
Control coefficients were determined to assess the influence each step had on skeletal muscle glucose metabolism
under insulin stimulation (Figure 2), with a higher percentage
indicating a higher level of control at that specific step. In
both soleus and tibialis anterior, the control in IS was significantly different from IR, with more evenly distributed control (less control at transport and increased control at deliv-
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Table 1. Clinical Characteristics and PET-Derived Kinetic Measurementsa
Clinical characteristics
Age, y
Fasting glucose, mg/dL
HbA1c. %
Total cholesterol, mg/dL
Triglycerides, mg/dL
BMI
Glucose infusion rate, mg/min 䡠 kg
Kinetic parameters
Soleus
[15O]H2O (n ⫽ 11)
K1, mL 䡠 cm⫺3 䡠 min⫺1
k2, min⫺1
[11C]3-OMG (n ⫽ 13)
K1, mL 䡠 cm⫺3 䡠 min⫺1
k2, min⫺1
k3, min⫺1
k4, min⫺1
18
[ F]FDG (n ⫽ 13)
K1, mL 䡠 cm⫺3 䡠 min⫺1
k2, min⫺1
k3, min⫺1
k4, min⫺1
k5, min⫺1
K, mL 䡠 cm⫺3 䡠 min⫺1
Glucose (n ⫽ 13)
k5, min⫺1
K, mL 䡠 cm⫺3 䡠 min⫺1
Tibialis anterior
[15O]H2O (n ⫽ 11)
K1, mL 䡠 cm⫺3 䡠 min⫺1
k2, min⫺1
[11C]3-OMG (n ⫽ 13)
K1, mL 䡠 cm⫺3 䡠 min⫺1
k2, min⫺1
k3, min⫺1
k4, min⫺1
[18F]FDG (n ⫽ 13)
K1, mL 䡠 cm⫺3 䡠 min⫺1
k2, min⫺1
k3, min⫺1
k4, min⫺1
k5, min⫺1
K, mL 䡠 cm⫺3 䡠 min⫺1
Glucose (n ⫽ 13)
k5, min⫺1
K, mL 䡠 cm⫺3 䡠 min⫺1
a
Data are represented as mean ⫾ SE.
b
P ⬍ .05 represents a significant difference between IS and IR.
IS Group
IR Group
P Value
43.7 ⫾ 2.9
86 ⫾ 2
5.3 ⫾ 0.1
189 ⫾ 13
109 ⫾ 29
24.0 ⫾ 1.8
7.0 ⫾ 0.3b
37.3 ⫾ 1.8
87 ⫾ 2
5.4 ⫾ 0.2
186 ⫾ 19
116 ⫾ 18
29.2 ⫾ 1.9
4.3. ⫾ 0.4
.1314
.9818
.5380
.8849
.8736
.1005
.0002
0.029 ⫾ 0.004
0.128 ⫾ 0.024
0.025 ⫾ 0.004
0.084 ⫾ 0.021
.5925
.2457
0.025 ⫾ 0.002
0.146 ⫾ 0.028
0.126 ⫾ 0.028b
0.041 ⫾ 0.005b
0.026 ⫾ 0.003
0.151 ⫾ 0.024
0.051 ⫾ 0.008
0.021 ⫾ 0.005
.8314
.9038
.0469
.0200
0.031 ⫾ 0.003
0.299 ⫾ 0.079
0.444 ⫾ 0.087b
0.008 ⫾ 0.001
0.025 ⫾ 0.003
0.017 ⫾ 0.001b
0.028 ⫾ 0.004
0.169 ⫾ 0.037
0.153 ⫾ 0.031
0.010 ⫾ 0.003
0.030 ⫾ 0.004
0.011 ⫾ 0.002
.5290
.2239
.0196
.6693
.3714
.0329
0.202 ⫾ 0.037
0.010 ⫾ 0.001b
0.219 ⫾ 0.037
0.006 ⫾ 0.001
.7657
.0236
0.022 ⫾ 0.002
0.108 ⫾ 0.021
0.022 ⫾ 0.003
0.094 ⫾ 0.037
.9945
.7913
0.018 ⫾ 0.001
0.051 ⫾ 0.005
0.071 ⫾ 0.018
0.055 ⫾ 0.012
0.020 ⫾ 0.002
0.097 ⫾ 0.024
0.057 ⫾ 0.010
0.029 ⫾ 0.005
.6378
.0924
.5490
.1166
0.027 ⫾ 0.003
0.134 ⫾ 0.049
0.291 ⫾ 0.058
0.013 ⫾ 0.002
0.025 ⫾ 0.003
0.017 ⫾ 0.001
0.027 ⫾ 0.004
0.211 ⫾ 0.037
0.324 ⫾ 0.064
0.012 ⫾ 0.003
0.028 ⫾ 0.003
0.013 ⫾ 0.001
.9025
.2804
.7334
.8803
.4740
.1291
0.253 ⫾ 0.035
0.009 ⫾ 0.001
0.203 ⫾ 0.029
0.007 ⫾ 0.001
.3512
.1506
ery; both P ⬍ .05) vs IR, which saw the inverse with much
greater control at transport.
Discussion
This PET imaging study revealed that across a range of normal-weight to obese subjects without diabetes, 1) glucose
transport kinetic defects are principally affected with increasing IR, with less or no impairment in either glucose delivery
or phosphorylation; 2) transport defects are significantly
more pronounced in soleus compared with tibialis anterior;
3) and in IS subjects, the control of glucose uptake is more
evenly distributed among delivery and transport. In contrast,
control of glucose transport has a stronger influence on glucose uptake in IR individuals.
Previous studies are not entirely consistent with respect to
which step is rate-limiting in skeletal muscle IR (11–14). Our
novel data indicate that metabolically healthy IS persons disperse control more evenly among the key steps, with roughly
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Figure 2. Control coefficient distribution under insulin stimulation.
Black bars represent delivery, white bars represent transport, and gray
bars represent phosphorylation. *, Significant difference between IS
and IR (P ⬍ .05).
Figure 1. Glucose delivery (top), transport (middle), and
phosphorylation (bottom) kinetics in soleus (left) and tibialis anterior
(right) muscles. The graphs represent kinetic parameters for skeletal
muscle glucose metabolism with insulin stimulation of 40 mU 䡠 m⫺2 䡠
min⫺1. Black bars represent IR, and white bars represent IS. *, P ⬍ .05.
equal control at delivery and transport in both muscle
groups. However, with increasing IR, a dynamic shift occurs
in which delivery control is lessened and transport control
increased. This may explain findings from previous studies in
which maximizing delivery did not improve skeletal muscle
glucose uptake with increasing obesity (15). Our data support this concept, because systemic IS positively correlated
with increasing delivery control (soleus, r ⫽ 0.61, P ⬍ .05;
tibialis anterior, r ⫽ 0.86, P ⬍ .01) and negatively correlated
with transport control (soleus, r ⫽ ⫺0.76, P ⬍ .01; tibialis
anterior, r ⫽ ⫺0.82, P ⬍ .01).
Our data also indicate that glucose transport is particularly impaired in specific skeletal muscle groups; transport in
soleus was strongly associated with IS (r ⫽ 0.83, P ⬍ .01), but
this was not significant in tibialis anterior (r ⫽ 0.16, P ⫽ .60).
This novel finding demonstrates specific muscle group heterogeneity in relation to IS and glucose transport. This could
potentially be due to muscle fiber type differences. Previous
studies have shown that fiber type is associated with IS (6,
16). Soleus and tibialis anterior muscles are composed of
different proportions of type I and II muscle fibers, with soleus having more type I fibers than tibialis anterior. Therefore, a possible mechanism is that oxidative muscle with
higher mitochondrial content (higher proportion of type I
fibers) is more insulin-sensitive, with higher rates of glucose
transport, than muscle groups with a more even distribution
of type I and II muscle fibers (17, 18). Soleus is vital for
plantarflexion (walking, running, and maintaining a standing posture), whereas tibialis anterior is involved in dorsiflexion (ankle stabilization). We postulate that differences in
contractile activity patterns are related to the heterogeneity in
IS and that this difference between IS and IR is magnified
in more highly oxidative muscle. Additional studies are
needed to determine the quantitative contributions of specific muscle types on systemic IS.
Previous studies have shown links between increasing
BMI and increasing IR (4, 7). Generally, our data agree with
these observations with a negative correlation between increasing BMI and IS (r ⫽ ⫺0.57, P ⬍ .05). A novel observation, however, is that the IS group had significantly higher
glucose transport and overall fractional uptake rates despite
having a BMI that was only modestly (and not significantly)
different. This observation confirms that IR is multifactorial
in nature beyond just obesity. For example, potential differences in skeletal muscle IS in individuals of the same weight
may partially explain the lean but metabolically obese phenotype that has been previously reported (5).
Limitations of this study include ROI being estimates of
whole organ/tissue metabolism through extrapolation rely-
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Insulin-Stimulated Muscle Heterogeneity
ing on the lumped constant. However, previous PET studies
have independently verified the validity of using the lumped
constant in modeling of skeletal muscle (19). It is noted that
reliance on any one radioactive tracer relies on mathematical
modeling of that tracer to assess for differences. However,
using multiple tracers allowed us to independently determine
which steps were impaired as, for example, the transport
impairment seen in both [11C]3-OMG and [18F]FDG of soleus muscle. We did not examine T2DM in this study. It is
possible that more severe IR in T2DM could manifest in
different or additional impairments in glucose metabolism and reveal different results in specific skeletal
muscle group impairments. Another limitation to our
study is the relatively small sample size, which precluded more sophisticated statistical analyses of gender
or age, and a more robust linear regression of PETderived kinetic parameters across a broader range of
subject characteristics. Although larger studies should
be performed, these data highlight the heterogeneity in
muscle glucose metabolism that contributed to IR.
In summary, in a range of normal-weight to obese volunteers without diabetes, profound glucose transport defects
were observed with increasing IR more clearly in specific
skeletal muscle groups, eg, soleus muscle, that were not as
evident in tibialis anterior. These transport defects are not
explained by obesity alone. Dynamic shifts occur within the
steps of skeletal muscle glucose metabolism from a fairly even
distribution between delivery and transport to a transportpredominant model with increasing IR. These data suggest
that the heterogeneity in skeletal muscle contributes to the
variability in IR or that different muscle types are more or less
susceptible to factors that cause IR. These dynamic PET imaging studies indicate the complexity of human skeletal muscle IR preceding T2DM.
Acknowledgments
We gratefully acknowledge the efforts and cooperation of the
research volunteers and support from the staffs at the University
of Pittsburgh General Clinical Research Center, PET Center, and
Endocrinology and Metabolism Research Center.
Address all correspondence and requests for reprints to:
Bret H. Goodpaster, PhD, Senior Investigator, Translational
Research Institute for Metabolism and Diabetes, Florida Hospital and Sanford/Burnham Medical Research Institute,
301 East Princeton Street, Orlando, FL 32804. E-mail:
[email protected].
This work was supported by grants from the National Institute of Diabetes and Digestive and Kidney Diseases (DK-6055502), the University of Pittsburgh General Clinical Research Center (5MO1RR00056), and the Obesity and Nutrition Research
Center (NIDDK P30-DK-46204).
J Clin Endocrinol Metab, January 2014, 99(1):E102–E106
Disclosure Summary: J.M.N., A.B., D.S.M., N.L.H., P.M.C.,
J.C.P., C.C., and B.H.G. have nothing to disclose. D.E.K. is currently employed by the Merck, Sharp, and Dohme Corporation.
References
1. Kelley DE, Reilly JP, Veneman T, Mandarino LJ. Effects of insulin
on skeletal muscle glucose storage, oxidation, and glycolysis in humans. Am J Physiol. 1990;258:E923–E929.
2. Bonadonna RC, Saccomani MP, Seely L, et al. Glucose transport in
human skeletal muscle. The in vivo response to insulin. Diabetes.
1993;42:191–198.
3. Bertoldo A, Pencek RR, Azuma K, et al. Interactions between delivery, transport, and phosphorylation of glucose in governing uptake into human skeletal muscle. Diabetes. 2006;55:3028 –3037.
4. Kahn SE, Hull RL, Utzschneider KM. Mechanisms linking obesity to insulin resistance and type 2 diabetes. Nature. 2006;444:840–846.
5. Romero-Corral A, Somers VK, Sierra-Johnson J, et al. Normal
weight obesity: a risk factor for cardiometabolic dysregulation and
cardiovascular mortality. Eur Heart J. 2010;31:737–746.
6. James DE, Jenkins AB, Kraegen EW. Heterogeneity of insulin action
in individual muscles in vivo: euglycemic clamp studies in rats. Am J
Physiol. 1985;248:E567–E574.
7. Bogardus C, Lillioja S, Mott D, Reaven GR, Kashiwagi A, Foley JE.
Relationship between obesity and maximal insulin-stimulated glucose uptake in vivo and in vitro in Pima Indians. J Clin Invest. 1984;
73:800 – 805.
8. Minoshima S, Berger KL, Lee KS, Mintun MA. An automated
method for rotational correction and centering of three-dimensional
functional brain images. J Nucl Med. 1992;33:1579 –1585.
9. Woods RP, Mazziotta JC, Cherry SR. MRI-PET registration with
automated algorithm. J comput Assist Tomogr. 1993;17:536 –546.
10. Bertoldo A, Price J, Mathis C, et al. Quantitative assessment of
glucose transport in human skeletal muscle: dynamic positron emission tomography imaging of [O-methyl-11C]3-O-methyl-D-glucose. J Clin Endocrinol Metab. 2005;90:1752–1759.
11. Bonadonna RC, Del Prato S, Bonora E, et al. Roles of glucose transport and glucose phosphorylation in muscle insulin resistance of
NIDDM. Diabetes. 1996;45:915–925.
12. Cline GW, Petersen KF, Krssak M, et al. Impaired glucose transport
as a cause of decreased insulin-stimulated muscle glycogen synthesis
in type 2 diabetes. N Engl J Med. 1999;341:240 –246.
13. Bonadonna RC, Del Prato S, Saccomani MP, et al. Transmembrane
glucose transport in skeletal muscle of patients with non-insulindependent diabetes. J Clin Invest. 1993;92:486 – 494.
14. Kelley DE, Mintun MA, Watkins SC, et al. The effect of non-insulin-dependent diabetes mellitus and obesity on glucose transport and phosphorylation in skeletal muscle. J Clin Invest. 1996;97:2705–2713.
15. Laine H, Yki-Jarvinen H, Kirvela O, et al. Insulin resistance of glucose uptake in skeletal muscle cannot be ameliorated by enhancing
endothelium-dependent blood flow in obesity. J Clin Invest. 1998;
101:1156 –1162.
16. Coen PM, Dubé JJ, Amati F, et al. Insulin resistance is associated
with higher intramyocellular triglycerides in type I but not type II
myocytes concomitant with higher ceramide content. Diabetes.
2010;59:80 – 88.
17. Gollnick PD, Sjödin B, Karlsson J, Jansson E, Saltin B. Human soleus
muscle: a comparison of fiber composition and enzyme activities
with other leg muscles. Pflugers Arch. 1974;348:247–255.
18. Henriksson-Larsén KB, Lexell J, Sjöström M. Distribution of different fibre types in human skeletal muscles. I. Method for the preparation and analysis of cross-sections of whole tibialis anterior. Histochem J. 1983;15:167–178.
19. Kelley DE, Williams KV, Price JC, Goodpaster B. Determination of
the lumped constant for [18F] fluorodeoxyglucose in human skeletal
muscle. J Nucl Med. 1999;40:1798 –1804.