J. Biomedical Science and Engineering, 2013, 6, 201-208 JBiSE
http://dx.doi.org/10.4236/jbise.2013.62024 Published Online February 2013 (http://www.scirp.org/journal/jbise/)
Measurement of lumbar muscle glucose utilization rate can
be as useful in estimating skeletal muscle insulin resistance
as that of thigh muscle*
Ikuo Yokoyama1,2#, Toshiyuki Moritan3, Yusuke Inoue4
1Department of Cardiovascular Medicine, Clinical Research Center, Sanno Medical Center Hospital, International University of
Health and Welfare, Tokyo, Japan
2Department of Cardiovascular Medicine, Clinical Research Center, Sanno Hospital, International University of Health and Welfare,
Tokyo, Japan
3Department of Clinical Engineering, Faculty of Medical Engineering, Suzuka University of Medical Science, Suzuka, Japan
4Department of Radiology, Graduate School of Medicine, Kitasato University, Sagamihara, Japan
Received 2 November 2012; revised 1 December 2012; accepted 7 December 2012
ABSTRACT
Background: Skeletal muscle glucose utilization (SMGU)
can be accessed by positron emission tomography
(PET) and 18F-FDG to characterize insulin resistance.
The quantity of skeletal muscle in the lumbar is suffi-
cient to indicate that SMGU in the lumbar (SMGU-
lumbar) can be measured with 18F-FDG PET of the
chest instead of obtaining thigh muscle SMGU
(SMGU-thigh). This would reduce PET scan time to
avoid thigh muscle PET scan. This study was aimed
to compare SMGU-lumbar and thigh muscle SMGU
under insulin clamping to identify the validity of
measurements of SMGU in the lumbar for studies of
insulin resistance. Methods: Thirty-three patients un-
derwent sequential dynamic 18F-FDG PET of both
the thoracic (37 min) and thigh region (22 min) dur-
ing hyperinsulinemic euglycemic insulin clamping.
Both SMGU-lumbar and SMGU-thigh were calcu-
lated by Patlak graphical analysis. Whole body insu-
lin resistance was assessed by a whole body glucose
disposal rate during hyperinsulinemic euglycemic in-
sulin clamping. Input function was obtained from the
time activity curve of the descending aorta and ve-
nous blood sampling as previously validated. Results:
SMGU-thigh (0.0506 ± 0.0334 µmol/min/g) was com-
parable to SMGU-lumbar (0.0497 ± 0.0255 µmol/min/g).
The Bland-Altman method of difference plot analysis
showed a significant correlationship between SMGU-
thigh and SMGU-lumbar (r = 0.506, p = 0.0028). There
were seen very good significant correlationship be-
tween whole body glucose utilization rate in both
thigh (r = 0.737, p = 0.0001) and lumbar (r = 0.772, p
= 0.0001). Conclusion: These results support the va-
lidity of measuring SMGU-lumbar to estimate insulin
resistance during PET imaging of the chest.
Keywords: 18F-FDG; PET; Skeletal Muscle; Glucose;
Insulin Resistance; Metabolic Syndrome; Type II
Diabetes; Hypertension
1. INTRODUCTION
Insulin resistance, a decreased glucose utilization re-
sponse to the stimulatory effect of insulin, is accepted to
be of critical importance in various metabolic abnormali-
ties leading to atherosclerosis such as essential hyperten-
sion, diabetes mellitus, hypertriglyceridemia, and/or a com-
bination of these diseases, such as in metabolic syndrome,
etc. Positron emission tomography (PET) allows the es-
timation of the glucose utilization rate in vivo using
[18F]-2-fluoro-2-deoxy-D-glucose (18F-FDG) as a tracer
and can provide valuable insights into insulin resistance
in the clinical setting. A major advantage of the PET
technique resides in its quantitative ability to assess an
organ-specific glucose utilization. Skeletal muscle glu-
cose utilization rate (SMGU) is thought to be the most
essential to the whole body insulin resistance, and meas-
urements of SMGU under insulin stimulation with PET
have been reported [1]. Glucose is an essential substrate
as a predominant source of energy for skeletal muscle to
maintain normal skeletal muscle function, and insulin
resistance plays an important role in the development of
coronary artery disease (CAD) [2-4]. An existence of
insulin resistance in the heart has been reported [5-9] but
it is not always pararel to the skeletal muscle and/or
whole body insulin resistance [10-14]. Therefore, simul-
taneous PET measurement of myocardial glucose utilize-
*There are non-financial competing interests with this article.
#Corresponding author.

I. Yokoyama et al. / J. Biomedical Science and Engineering 6 (2013) 201-208 202
tion rate (MGU) and SMGU has been done [5-15] and
results in such studies might lead to characterize insulin
resistance in various diseases and increase our knowl-
edge of therapies for insulin resistance.
SMGU can be calculated by Patlak graphical analysis
[16], which requires the temporal profile of tissue activ-
ity on PET images as the output function and the tempo-
ral profile of arterial plasma activity as the input function.
To measure glucose utilization in the chest using PET
scan, the input function can be given without arterial
blood sampling using the time-activity curve of the left
ventricle (LV) [17] or descending aorta [18]. Sequential
measurement of both MGU and thigh muscle SMGU
(SMGU (thigh)) following an injection of 18F-FDG has
been used. In the sequential method, the chest PET scan
is commonly performed immediately after tracer injec-
tion, followed by data collection in the thigh region, with
tissue activity only during the late phase used to calculate
SMGU (thigh). The input function can be determined
from chest PET images for the early phase and from ar-
terialized venous blood samples during the late phase
just at the time of the thigh muscle PET scan [10-13,19].
A non-invasive method to measure SMGU (thigh) using
a sequential PET scan of the chest and thigh region that
does not require arterial blood sampling and an early to
mid dynamic PET scan of the thigh region has been re-
ported [20]. Since there exists sufficient amount of skele-
tal muscle in the lumbar region, measurements of SMGU
in the lumbar (SMGU (lumbar)) can be obtained from an
18F-FDG PET scan of the chest using previously vali-
dated non-invasive method [20]. By using that method
[20], MGU, SMGU (lumbar) and SMGU (thigh) can be
calculated with one sequential PET scan with only 3 - 5
times of venous blood sampling leading to avoiding arte-
rial blood sampling. Moreover, if there were no differ-
ence in SMGU value between the lumbar and thigh re-
gion, thigh muscle PET imaging can be avoided leading
to decrease the PET data sampling time to study heart
and skeletal muscle insulin resistance. If there were dif-
ferences in the SMGU value and/or the relationship be-
tween SMGU and the whole body glucose utilization rate
(WBGU) between the lumbar and thigh, measurement of
SMGU in both regions would provide additional infor-
mation to increase our knowledge of several diseases
with insulin resistance. Since PET data acquisition time
with 18F-FDG under insulin clamping might be reduced
as shorter as possible because of too long preparation
time more than 2 hours to obtain steady state condition
of glucose utilization under insulin claming before the
start of 18F-FDG PET scan. Therefore, when considering
simultaneous measurement of MGU and SMGU, SMGU
(lumbar) is preferred because data sampling time can be
decreased to estimate SMGU. Thus, the aim of this study
is to elucidate both differences and similarities in the
SMGU value and its relationships to WBGU between the
thigh and lumbar and demonstrate whether SMGU (lum-
bar) could be used in studies of skeletal muscle insulin
resistance leading to reduce PET data sampling time.
2. MATERIALS AND METHODS
2.1. Study Subjects
Sequential dynamic 18F-FDG PET scans of the chest and
thigh regions were performed in 34 patients. Patient data
obtained for a previous study that had different objec-
tives from the present report were used [20,21]. One pa-
tient moved considerably during the PET scan, making
evaluation of SMGU unreliable, and thus data from this
patient were excluded from analysis. Consequently, data
on 33 patients (1 woman, 32 men; age range 27 - 77
years, mean age 57.5 ± 9.3 years) were analyzed. Thirty-
two patients had type II diabetes, and one had only es-
sential hypertension. Average of HbA1c (%) was 7.2% ±
1.3%. Patients with Type II diabetes or essential hyper-
tension who had been admitted to our hospital or local
health service centers were enrolled in this study. No
other specific inclusion criteria were employed. The in-
vestigative nature of the study was fully explained to
each patient before informed consent was obtained. The
local ethics committee approved the study protocol.
2.2. Imaging Procedures
Dynamic PET scan with 18F-FDG was performed during
hyperinsulinemic euglycemic clamping. 18F was synthe-
sized using the Cypris model 370 cyclotron (Sumitomo
JYUKI Industries, Ltd., Tokyo, Japan), and 18F-FDG was
synthesized with an automated system based on the
method reported by Ehrenkaufer et al. [22]. Radioche-
mical purity was more than 95%. A Headtome IV PET
scanner (Shimadzu Corp., Kyoto, Japan) was used for
PET scans. Transmission data were acquired before the
administration of 18F-FDG to correct for photon attenua-
tion. Two venous catheters were inserted: one in a super-
ficial forearm vein for the infusion of glucose and insulin
and the injection of 18F-FDG, and one in a superficial
vein of the contralateral forearm for venous blood sam-
pling. Prior to the PET scan, a primed-constant insulin
infusion 4 times the final constant rate (1 mlU/min/kg)
for the first 4 min was started after which the insulin in-
fusion was 2 times the final constant infusion rate for an
additional 4 min. The exogenous glucose infusion using
20% glucose solution was started when the insulin infu-
sion was at the constant rate. Plasma glucose concentra-
tion was measured at baseline and then every 5 min dur-
ing insulin clamping. The glucose infusion rate was ad-
justed according to the change in plasma concentration
and targeted at about 5.6 µmol/L. Under near steady-

I. Yokoyama et al. / J. Biomedical Science and Engineering 6 (2013) 201-208 203
state conditions, the exogenous glucose infusion rate
equals the total amount of glucose metabolized by all
tissues. We determined the WBGU as follows: WBGU =
the exogenous glucose infusion rate (mg/min)/body
weight (kg).
When the plasma glucose concentration became con-
stant, 18F-FDG (185 - 370 MBq) was injected intrave-
nously over 60 s.
Sequential PET scanning of the thoracic and thigh re-
gions was performed. Immediately after tracer injection,
dynamic data on the thoracic region, including the heart
in the field of view, were acquired for 37 min (10
s/frame × 9, 30 s/frame × 3, 120 s/frame × 2, 300 s/frame
× 4, and 600 s/frame × 1), followed by the collection of
dynamic data of the mid-thigh region for 22 min (120
s/frame × 1 and 300 s/frame × 4). A venous blood sam-
ple was obtained at the midpoint of each frame for the
last 7 frames of thoracic imaging and for all of the
frames of thigh imaging.
2.3. Data Analysis
PET data were corrected for dead time, decay, and meas-
ured photon attenuation, and transaxial images were re-
constructed. Fifteen circular regions of interest (ROIs) of
5 mm in diameter were placed within the lumbar muscle
and thigh muscles of each side. Orientation of lumbar
muscle was made in relation to specific vertebrae since
lumbar muscle is just behind the vertebral column. We
also defined lumbar muscle 18F-FDG activity by chang-
ing the color scale level for the thoracic region to view
lumbar muscle adequately and to negate the deleterious
influence of cardiac muscle activity. An example of ROI
placement for back muscle is shown in Figure 1. Tissue
activity was determined from the mean counts for the
ROIs. Plasma and tissue time-activity curves were ana-
lyzed by the graphical method described by Patlak et al.
[17] to determine the fractional rate of tracer uptake and
phosphorylation Ki·Ki is equal to


13 2 3
kk kk
,
where k1 is the transfer coefficient from intravascular
space into the tissue, k2 is the initial clearance and efflux
Figure 1. A typical example of lumbar muscle static 18F-FDG
uptake positron emission tomography (PET) image (arrow hea-
ded). Regions of interests (ROIs) were placed reffering the
static lumbar muscle 18F-FDG uptake PET images.
coefficient, and k3 is the phosphorylation rate constant.
The dephosphorylation rate constant, k4, is assumed to be
zero with the Patlak method. SMGU was calculated by
substituting Ki in the equation SMGU = Ki × Glp/LC,
where Glp is the mean of the venous plasma glucose
level during imaging and LC is the lumped constant. LC
strands for differences in the transport and phosphoryla-
tion of 18F-FDG and glucose, and was estimated at 1.2
[23,24]. To calculate SMGU, we used an Ultra 30 high-
speed image processing system (Sun Microsystems Ja-
pan, Tokyo, Japan) with Dr. View software (Asahi Kasei
Information System Co., Ltd., Tokyo, Japan).
In the Patlak graphical analysis, the slope of the linear
portion of the plots, which is equal to




13 2 3i
K
kk kk of the 18F-FDG three-compart-
ment tracer kinetic model, is calculated by linear regres-
sion. SMGU (lumbar) was determined based on linear
regression of the last 7 points during the chest PET scan
based on the method by Ohtake et al. [18]. The time ac-
tivity curve of the descending aorta corrected by venous
blood sampling was used as the input function according
to the method by Ohtake et al. [18]. The time-activity
curve for the descending aorta was generated and cor-
rected using venous blood samples. Input function during
the thigh imaging was assessed using venous blood sam-
ples. Thigh muscle SMGU with the estimated input
function was calculated using the combination of the
corrected aorta activity during the chest PET scan and
venous plasma activity during the thigh PET scan as de-
scribed previously [20].
Measurements of whole body insulin resistance were
made by obtaining the glucose disposal rate during hy-
perinsulinemic euglycemic clamping (µmol/min/kg) just
at the time of the PET scan using a previously reported
method [25].
2.4. Statistical Analysis
Data are expressed as means ± standard deviation (SD).
The Bland-Altman method of difference plot analysis
was used to compare the two methods. A p value of less
than 0.05 was considered statistically significant.
3. RESULTS
SMGU (thigh) (0.0506 ± 0.0334 µmol/min/g) was com-
parable with SMGU (lumbar) (0.0497 ± 0.0255 µmol/-
min/g). The ratio of SMGU (thigh) to SMGU (lumbar)
was 0.992 ± 0.322. There was a significant positive rela-
tionship between the SMGU (thigh) and SMGU (lumbar)
(Figure 2).
The Bland-Altman method of difference plot analysis
showed a significant correlation between SMGU (thigh)
and SMGU (lumbar) (r = 0.506, p = 0.0028) (Figure 3).

I. Yokoyama et al. / J. Biomedical Science and Engineering 6 (2013) 201-208 204
(SMGU (thigh)+SMGU(back))/2
0.06
0.05
0.04
0.03
0.02
0.01
0
−0.01
−0.02
−0.03
−0.04
0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16
SMGU (thigh)−SMGU(lumber)
Figure 2. Plots of skeletal muscle glucose utiliza-
tion rate (SMGU [µmol/min/g]) (thigh) and SMGU
([µmol/min/g]) (lumbar). There was a significant
positive relationship between the two.
WBGU of all study subjects was 34.5 ± 21.2 µmol/
min/kg. A significant positive relationship was found
between SMGU thigh and WBGU (r = 0.737, p = 0.0001)
(Figure 4). There was also a significant positive rela-
tionship between SMGU (lumbar) and WBGU (r = 0.772,
p = 0.0001) (Figure 5).
4. DISCUSSION
In this study, we made sequential 18F-FDG PET scans of
the chest and thigh regions without arterial blood sam-
pling and calculated both lumbar muscle and thigh mus-
cle SMGU to validate a method to quantify SMGU
(lumbar). Nearly the similar good agreement between
SMGU (thigh) and SMGU (lumbar) and that between
SMGU (lumbar) and WBGU shows that PET imaging of
SMGU (lumbar) can be used in evaluating skeletal mus-
cle insulin resistance nearly the same accuracy as that of
thigh. In addition, PET imaging of SMGU (lumbar)
could decrease data sampling time for the study of heart
and skeletal muscle insulin resistance. SMGU (lumbar)
can be estimated with only venous blood sampling start-
ing at the time of the 18F-FDG injection and during the
dynamic chest PET scan. One of the principal assump-
tions in applying Patlak graphical analysis to estimate the
muscle glucose utilization is that the dephosphorylation
of 18F-FDG-6-phosphate is negligible in the target tissue.
Calculation using tissue 18F-FDG activity obtained at the
early to late-mid phase of a PET scan appears to negate
the negative influence of dephosphorylation of 18F-FDG-
6-phosphate, which increases during the late phase after
18F-FDG injection. That is one of the advantages of the
dynamic PET scan using 18F-FDG. The extremely low
activity of dephosphorylation in skeletal muscle [25] can
be an important factor in producing a good agreement
between SMGU (lumbar) and SMGU (thigh).
(SMGU (thigh)+SMGU(back))/2
0.06
0.05
0.04
0.03
0.02
0.01
0
−0.01
−0.02
−0.03
−0.04
0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16
SMGU (thigh)−SMGU(lumber)
Figure 3. The bland-Altman method of difference
plot analysis between skeletal muscle glucose utili-
zation rate (SMGU [µmol/min/g]) (thigh) and SMGU
[µmol/min/g]) (lumbar) showed a significant posi-
tive relationship between SMGU thigh and SMGU
back = lumbar, r = 0.868, p = 0.0001.
WBGU
SMGU (thigh)
0 10 20 30 40 50 60 70 80 90
0.16
0.14
0.12
0.1
0.08
0.06
0.04
0.02
0
Figure 4. Plots of skeletal muscle glucose utiliza-
tion rate (SMGU [(µmol/min/g)]) (thigh) and whole
body glucose utilization rate (WBGU [µmol/min/kg]).
A significant positive relationship was found be-
tween SMGU thigh and WBGU (r = 0.737, p =
0.0001).
The validity of shortening the PET data sampling time
is convenient for both the patients and the PET labora-
tory. In addition, reducing the total PET data sampling
time has merit in estimating the effects of certain drugs
such as insulin sensitizers on the heart and skeletal mus-
cle insulin resistance because PET should be done more
than two times for the same patients. Several reports
have cited an existence of myocardial perfusion abnor-
malities in subjects with angiographically normal coro-
nary arteries who are at high risk for CAD [27,28] or
who have no evidence of CAD [25,29]. Reversal effects
of certain medicines to improve such myocardial perfu-

I. Yokoyama et al. / J. Biomedical Science and Engineering 6 (2013) 201-208 205
SMGU (Lumbar)
0.11
0.1
0.09
0.08
0.07
0.06
0.05
0.04
0.03
0.02
0.01
0 10 20 30 40 50 60 70 80 90
WBGU
Figure 5. Plots of skeletal muscle glucose
utilization rate (SMGU [µmol/min/g]) (lum-
bar) and whole body glucose utilization rate
(WBGU [µmol/min/kg]). There was also a
significant positive relationship between SMGU
(lumbar) and WBGU (r = 0.772, p = 0.0001).
sion abnormalities have also been reported [30,31]. Since
most diseases presenting a risk for CAD such as essential
hypertension, type-II diabetes hypertriglyceridemia and
abdominal obesity can usually be associated with insulin
resistance, it is better to shorten the PET data aquisition
time to estimate effects of certain therapies on both the
myocardial perfusion abnormalities and heart and skele-
tal muscle insulin resistance. To achieve such an aim, our
method enables measurement of MGU and SMGU
(lumbar) simultaneously, while SMGU (thigh) and MGU
cannot be measured simultaneously. Measuring both
MGU and SMGU and myocardial perfusion abnormali-
ties in a specific subject may aid in evaluating the rela-
tion between metabolic abnormalities such as insulin
resistance in the heart and skeletal muscle and certain
heart diseases. Measurement of SMGU (lumbar) allows
for an easier investigation in a much shorter data acquisi-
tion period compared with a PET study that includes a
heart and thigh muscle 18F-FDG PET scan and a myo-
cardial perfusion study. PET scan of the chest can visu-
alize both the myocardium and skeletal muscle in the
lumbar, and skeletal muscle in the arm also can be in-
cluded in the field of view if the patient’s arm is at his or
her side. MGU and SMGU in the arm [5] may be simul-
taneously assessed; however, the volume of skeletal
muscles in the arm is small, especially in lean patients,
which may cause difficulty in placing ROIs and cause
underestimation of SMGU due to the partial volume ef-
fect. In addition, high activity in the myocardium may
interfere with an accurate estimation of SMGU of arm
muscle due to star artifacts. Whereas in the present study,
apparently obvious 18F-FDG uptake was seen in the
lumbar muscle associated with high myocardial 18F-FDG
uptake and no obvious artifact, which exist at lower part
of human body than that of heart. Moreover, lumbar
muscle has an adequate amount of skeletal muscle to
negate partial volume effect. Therefore, such star arti-
facts could be negated in the measurement of SMGU
(lumbar). The thigh region contains a large amount of
skeletal muscle and no other structures with high 18F-
FDG uptake, and has been thought to be suitable for es-
timating SMGU. In the present study, individual vari-
ability among patients was found in the SMGU value
between the lumbar and the thigh. This may be caused by
movement of thigh muscle due to long data sampling
time (chest PET scan time plus thigh muscle PET scan
time), a difference in daily physical activities (lack of
exercise, difference in type of job and/or exercise, etc.)
and a difference in function between lumbar muscle,
which is mainly used to maintain body structure and
posture and to breathe, and thigh muscle, which is used
to walk and to stand. The much wider range in SMGU
values for the thigh than in SMGU values for the lumbar
could imply that there are differences in the essential
nature of skeletal muscle glucose handling between the
two. Moreover, when the SMGU (thigh) value was ap-
proximately more than 0.12 µmol/min/g, the difference
in the SMGU value between the lumbar and the thigh
seemed to be increased. In addition, the range of SMGU
(thigh) value was much wider than that in SMGU (lum-
bar) in spite of the significant positive relationship be-
tween the SMGU (thigh) and SMGU (lumbar). The rea-
son for such a discrepancy is speculative. A difference in
the timing of PET data sampling between SMGU (lum-
bar—early to mid phase) and SMGU (thigh—late phase)
could be related to such differences. That is one of the
limitations of this study. However, the quite excellent
agreement in SMGU values between lumbar and thigh
muscle in our present study indicated that measurement
of SMGU (lumbar) could provide accuracy similar to
that of SMGU (thigh) in an absolute estimation of the
SMGU value. Moreover, the good relationship between
SMGU and WBGU in lumbar muscle was observed to be
similar to that between thigh muscle SMGU and WBGU.
Therefore, chest PET imaging using the lumbar muscle
can offer reasonable estimates of SMGU and skeletal
muscle insulin resistance. Since skeletal muscle insulin
resistance is a predominant parameter for the whole body
insulin resistance, our results might contribute to the
study of certain diseases associated with insulin resis-
tance. However, another factors contribute to approxi-
mately 20% of total whole body insulin resistance, so
both SMGU, whole body insulin resistance and MGU
should be measured simultaneously for the much more
accurate understanding of insulin resistance of certain
diseases.
Chest PET imaging yields a time-activity curve that
represents temporal changes in blood activity, and the
input function during thoracic imaging can be deter-

I. Yokoyama et al. / J. Biomedical Science and Engineering 6 (2013) 201-208 206
mined by venous blood sampling alone [17,18]. Al-
though venous plasma activity underestimates peak arte-
rial activity [32], venous blood sampling could suffice
for the estimation of the input function during the late
phase. Elimination of the need for frequent arterial sam-
pling is a definite convenience. Even without the need
for MGU measurement, chest PET imaging provides an
assessment of the input function for glucose metabolism
in thoracic region and/or SMGU (thigh) with only ve-
nous blood sampling instead of arterial blood sampling
[20].
The present study aimed to investigate the validity of
the methodology for PET measurement of SMGU (lum-
bar). The results reported here support future investiga-
tion of heart and skeletal muscle insulin resistance
through methods that are relatively easy with decreased
sampling time. Our results also support the avoidance of
thigh imaging and the validity of omission of arterial
blood sampling in assessing SMGU (lumbar) during hy-
perinsulinemic euglycemic clamping using the input
function derived from the time activity curve of the de-
scending aorta corrected by venous blood sampling [18].
Full compartment model analysis could provide rate
constants for the 18F-FDG tracer kinetic model leading to
obtaining individual quantitative values for the transfer
from the intravascular space to tissue (k1), the efflux co-
efficient (k2), the phosphorylation rate (k3) and eventu-
ally the phosphatase activity (k4). These analyses would
clarify differences and similarities in skeletal muscle
glucose utilization between thigh and lumbar muscle
under insulin clamping. Because the first aim of this
study was to clarify whether SMGU (lumbar) could be
estimated similar to the SMGU (thigh), full compartment
model analysis (three or more compartment model) was
not done. To achieve such an aim as accurately as possi-
ble, a simultaneous 18F-FDG PET scan for both the lum-
bar and thigh muscles might be required with Dual PET
to obtain full dynamic PET data, which can estimate tis-
sue metabolism, blood flow, etc. simultaneously in two
separate portions of the human body [33] and has been
used in human heart and brain studies [34-36]. Further
investigations would be warranted on this methodology
for this purpose.
The influence of the Lumped Constant on the quanti-
tative results in patients with type II diabetes may be one
problem in the estimation of SMGU with 18F-FDG PET.
Although such an issue is important in the estimation of
SMGU, because we compared individual differences in
SMGU between thigh and lumbar muscle in the same
study subjects, such a problem can be negated.
5. CONCLUSION
SMGU (lumbar) could be estimated only by chest PET
imaging with accuracy similar to that of thigh muscle
SMGU. The results of this study support the validity of
simultaneous measurements of MGU and SMGU with
only a chest PET scan using 18F-FDG and venous blood
sampling to estimate insulin resistance syndrome.
6. AUTHORS’ CONTRIBUTIONS
Dr. Yokoyama made the study design of this study and
recruited study subjects. Drs. Yokoyama, Inoue, Moritan
made PET data sampling and data analysis. Drs. Inoue,
Moritan gave appropriate discussion and advises in mak-
ing this manuscript.
7. ACKNOWLEDGEMENTS
We thank Mr. Tohru Inoue for his technical support in preparing
18F-FDG and Dr. Katsunori Yonekura for his kind cooperation.
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ABBREVIATIONS
SMGU: Skeletal muscle glucose utilization;
PET: Positron emission tomography;
18F-FDG: 18Fluorine-fluoro-2-deoxy-D-glucose;
CAD: Coronary artery disease;
WBGR: Whole body glucose disposal rate;
MGU: Myocardial glucose utilization;
ROIs: Regions of interest;
FWHM: Full width at half maximum;
LC: Lumped constant;
Glp: Mean of the venous plasma glucose level during
imaging;
RC: Recovery coefficients.