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ORIGINAL RESEARCH
Jonathan T. Abele, BSc, MD, FRCPC
Christopher I. Fung, BSc
Purpose:
To evaluate the association between diffuse fatty infiltration of the liver and average fluorine 18 fluorodeoxyglucose (FDG) uptake in the liver.
Materials and
Methods:
Institutional review board approval was obtained for this
study; the requirement for informed patient consent was
waived. Consecutive nonenhanced whole-body hybrid
FDG positron emission tomographic (PET)-computed
tomographic (CT) scans obtained in 142 patients (mean
age, 63.6 years; age range, 19–94 years) from October
1, 2008, to November 28, 2008, were retrospectively reviewed. Mean attenuation (in Hounsfield units) and standardized uptake value (SUV) measurements for the liver
and spleen were obtained, with identical regions of interest used for the CT and PET examinations. The patients
were assigned to three study groups: a control group—119
patients with a mean liver attenuation value greater than
or equal to the mean spleen attenuation value, a diffuse
fatty liver disease group—23 patients in whom the mean
liver attenuation value was less than the mean spleen attenuation value, and a more strictly defined fatty liver disease group—a subset of 10 patients from the diffuse fatty
liver disease group with a mean liver attenuation value
minus mean spleen attenuation value difference of less
than or equal to 210 HU. Mean SUV (SUVm) values were
compared between the groups by using a two-sample t test
for means. The association between mean liver attenuation and average FDG uptake was assessed with linear
regression analysis.
Results:
The average SUVmfor the control group was 2.18 (standard deviation [SD], 0.36; 95% confidence interval [CI]:
2.12, 2.24). No significant difference was identified when
the average SUVmfor the control group was compared
with those for the fatty liver disease (SUVm, 2.03; SD,
0.36; 95% CI: 1.90, 2.16) (P ..05) and more strictly defined fatty liver disease (SUVm, 2.07; SD, 0.24; 95% CI:
1.92, 2.22) groups (P ..05). Linear regression analysis of
liver SUVmas a function of mean liver attenuation revealed
a mean slope of 0.005 (SD, 0.04; 95% CI: 20.005, 0.015)
and a correlation coefficient of 0.02.
Conclusion:
No association between liver attenuation and FDG uptake
measured in terms of SUVmwas observed. On the basis of
these data, it is acceptable to use the liver as a comparator for extrahepatic foci of equivocal increased FDG activity in patients with fatty liver disease.
1
From the Department of Radiology and Diagnostic
Imaging, University of Alberta, 8440-112 St, 2A2.41 WMC,
Edmonton, AB, Canada T6G 2B7. Received May 6, 2009;
revision requested June 3; revision received July 14;
accepted August 26; final version accepted September 9.
Address correspondence to J.T.A. (e-mail: jabele@
ualberta.ca).
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n NUCLEAR MEDICINE
Effect of Hepatic Steatosis on
Liver FDG Uptake Measured in
Mean Standard Uptake Values1
NUCLEAR MEDICINE: Effect of Hepatic Steatosis on Liver FDG Uptake
D
iffuse fatty infiltration of the liver
reflects a spectrum of diseases,
from benign and treatable conditions (simple steatosis) to clinically important abnormalities (steatohepatitis)
to irreversible (fibrosis) disease entities.
Diffuse fatty infiltration of the liver is
generally categorized as alcohol-related
fatty liver disease or non–alcohol-related
fatty liver disease (NAFLD). NAFLD is
the most common chronic liver condition in the Western world, with an estimated prevalence of 20%–35% and
of up to 95% in populations of obese
individuals (1,2).
Liver biopsy is the reference standard for the diagnosis of diffuse fatty
infiltration (2). Imaging studies can also
enable the detection of diffuse fatty infiltration of the liver, with ultrasonography, computed tomography (CT),
and magnetic resonance imaging having been evaluated for this indication
(3–5). CT specifically has been shown
to have 93% sensitivity and a 76% positive predictive value for the detection of
greater than 33% fatty infiltration (3).
In general, at nonenhanced CT, diffuse
fatty infiltration is considered when the
attenuation of the liver (in Hounsfield
units) is less than that of the spleen
(HUL-S , 0) (1,6). This has been more
strictly defined as a mean liver attenuation value minus mean spleen attenuation value difference of less than or
equal to 210 HU (HUL-S ⱕ 210) (7).
Advances in Knowledge
n No clinically important association existed between fluorine 18
fluorodeoxyglucose (FDG) uptake
measured in terms of the mean
standardized uptake value
(SUVm) and mean liver attenuation over a range of Hounsfield
units in diffuse fatty liver disease.
n On the basis of values measured
in a control population of 119
patients by using modern iterative time-of-flight reconstruction
techniques, the liver SUVm was
2.18, with a narrow range of
variability (95% confidence interval: 2.12, 2.24).
918
Abele and Fung
In many reports in the fluorine 18
fluorodeoxyglucose (FDG) positron
emission tomography (PET) literature,
the liver has been described as a comparator for foci of equivocal FDG accumulation, particularly in the abdomen (8–10). With this method, if the
degree of FDG uptake is substantially
increased compared with the degree of
uptake in the liver, the focus should be
considered abnormal. Previous studies
have revealed that the standardized uptake value (SUV) for a normal liver remains stable over time and is essentially
constant between patients with a mean
SUV (SUVm) of 2.17 6 0.33 (standard
deviation [SD]) when iterative reconstruction techniques are used (11,12).
While literature on the evaluation
of the relationship between hepatic
steatosis and maximal SUV (SUVmax)
is limited (13), to our knowledge there
have been no reports on the assessment
of the effect of diffuse fatty infiltration
of the liver on mean FDG accumulation.
While the SUVmax is the most common
clinical parameter used to assess FDG
accumulation in tumors, with respect to
the clinical application of using the liver
as a background comparator for other
abdominal foci, the SUVm is a more robust parameter because there is less
statistical variability and in general,
foci are compared with liver uptake as
a whole rather than as specific voxels.
The SUV is calculated as the tissue concentration of FDG in a structure defined
by a region of interest (ROI), divided by
the activity injected per gram of body
weight (12). Thus, increasing cellular
size due to fat accumulation could conceivably result in less cellular density
and in turn a decrease in the SUVm.
Alternatively, the histologic evidence
of inflammation in a number of these
Implications for Patient Care
n The liver is a stable organ to use
as a visual comparator for equivocal foci of extrahepatic FDG
uptake, including that in patients
with diffuse fatty liver disease.
n The liver had a consistent SUVm
of 2.18, independent of liver
attenuation.
patients suggests possible increased regional metabolic activity related to the
inflammatory response, which could
result in an increase in the SUVm (1).
The purpose of our study was to
evaluate the association between diffuse
fatty infiltration of the liver and average
FDG uptake. Hybrid PET/CT technology represents an ideal method for this
evaluation because each examination is
performed with both PET scanning and
immediate nonenhanced CT scanning,
without the patient being moved. As
such, the association between average
FDG activity in the liver, measured in
SUVm values, and mean liver attenuation, measured in Hounsfield units, can
be directly assessed.
Materials and Methods
Patient Groups
This study was approved by our institutional review board. The requirement for informed patient consent was
waived. The images from 173 consecutive nonenhanced whole-body (base of
skull to mid thigh) FDG PET/CT examinations performed in 173 patients at
our institution from October 1, 2008,
to November 28, 2008, were assessed
retrospectively.
Published online
10.1148/radiol.09090768
Radiology 2010; 254:917–924
Abbreviations:
BMI = body mass index
CI = confidence interval
FDG = fluorine 18 fluorodeoxyglucose
NAFLD = non–alcohol-related fatty liver disease
ROI = region of interest
SD = standard deviation
SUV = standardized uptake value
SUVm = mean SUV
SUVmax = maximal SUV
Author contributions:
Guarantor of integrity of entire study, J.T.A.; study
concepts/study design or data acquisition or data analysis/
interpretation, J.T.A., C.I.F.; manuscript drafting or manuscript revision for important intellectual content, J.T.A.,
C.I.F.; manuscript final version approval, J.T.A., C.I.F.; literature research, J.T.A., C.I.F.; clinical studies, C.I.F.; statistical
analysis, J.T.A., C.I.F.; and manuscript editing, J.T.A., C.I.F.
Authors stated no financial relationship to disclose.
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NUCLEAR MEDICINE: Effect of Hepatic Steatosis on Liver FDG Uptake
The medical and imaging data of
31 of the 173 patients were excluded
from analysis owing to the following
exclusion criteria: patient positioning
with both arms down, which results in
an artificial elevation of liver attenuation due to beam-hardening effects (22
patients), the presence of confounding
focal liver findings at PET or CT (five
patients), age younger than 18 years
(one patient), diffuse increased attenuation throughout the liver (mean
attenuation, 87 HU) for unknown reasons (one patient), and technical error
(patient weight accidentally entered as
injected FDG dose) that resulted in inaccurate SUV measurements globally
(two patients).
The remaining 142 patients (mean
age, 63.6 years; age range, 19–94 years)
were included in the study: 78 (54.9%)
men (mean age, 63.8 years; age range,
31–87 years) and 64 (45.1%) women
(mean age, 63.4 years; age range, 19–
94 years). The indications for the imaging examinations included lung cancer
or nodule assessment for 87 (61.3%)
of the 142 patients, esophageal cancer
for 10 (7.0%) patients, colon cancer
for nine (6.3%) patients, head and
neck cancer for nine (6.3%) patients,
lymphoma for seven (4.9%) patients,
genitourinary cancer for four (2.8%)
patients, breast cancer for two (1.4%)
patients, melanoma for one (0.7%)
patient, and “other” for 13 (9.2%)
patients.
Three patient groups were derived
from the study group of 142 patients:
The control group (119 patients)
included all patients with a mean liver
attenuation value greater than or
equal to the mean spleen attenuation
value. The fatty liver disease group (23
patients) included all patients in whom
the mean liver attenuation value was
lower than the mean spleen attenuation
value. Because in some of the literature,
diffuse fatty infiltration is more strictly
defined at nonenhanced CT as the liver
having a mean attenuation value that
is at least 10 HU lower than the mean
spleen attenuation value, the data for a
subset of 10 patients from the fatty liver
disease group who satisfied this more
strict criterion were also analyzed.
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Technical Parameters
All examinations were performed by using a Gemini TF PET/CT scanner (Philips
Medical Systems, Best, the Netherlands).
PET was performed 60 minutes after the
injection of 5.2 MBq of FDG per kilogram
of body weight (maximal dose, 518 MBq).
Emission data were acquired at 1 minute
per bed position for patients weighing
90 kg or less and at 2 minutes per bed
position for patients weighing more than
90 kg. Blood glucose measurements obtained before scanning were lower than 10
mmol/L. PET images were generated by
using standard three-dimensional time-offlight iterative reconstruction algorithms
with CT-based attenuation correction.
Helical CT acquisitions were performed with the following parameters: a
tube current of 100 effective mAs, a tube
voltage of 120 kVp, a collimation of 16 3
1.5 mm, a pitch of 0.813, and a scanning
time of 0.5 second per rotation. For review, the CT images were reconstructed
with a section thickness of 3 mm in 1.5mm increments. All patients were given
oral contrast material. No intravenous
contrast material was administered.
ROI Placement
For each patient, a single circular ROI at
least 3 cm in diameter was drawn over
the right lobe of the liver; any obvious
vessels were avoided. A single circular
ROI measuring a minimum of 3 cm in
diameter was also drawn over the spleen.
Identical ROIs were used for the PET and
CT examinations. The ROIs contained
no perceivable focal lesions on either the
CT or PET image components. SUVm,
SUVmax, and mean attenuation measurements for each ROI were calculated by
using commercially available software
(PET/CT Application Suite V1.2E, Extended Brilliance Workspace; Philips
Medical Systems). The ROIs were placed
by a 3rd-year medical student (C.I.F.)
and were reviewed by a physician with 5
years of experience in diagnostic radiology and nuclear medicine (J.T.A.).
Body Weight, Body Mass Index, Diabetes
History, and Medication History
The data recorded by the clinical nurse
at the time of FDG injection, as well
as the medication lists provided by the
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Abele and Fung
referring physician on the study requisition, were reviewed. Patient body weight
data were available and recorded for all
patients. Patient height data were available for most of the patients and enabled
calculation of the body mass index (BMI,
in kg/m2). Because the imaging protocol
at our institution requires that patients
with diabetes be imaged first, in the
morning, information regarding diabetes
status and insulin use was available and
recorded for all patients. The available
data for all patients were reviewed with
respect to the use of tamoxifen, glucocorticoids, methotrexate, zidovudine,
lamivudine, amiodarone, diltiazem, or
thiazalidinedione therapy at or around
the time of the FDG injection.
Statistical Analyses
Office Excel 2007 software (Microsoft,
Redmond, Wash) was used to enter the
data onto a spreadsheet and perform
statistical analyses. Liver SUVm and
SUVmax values for the control group
were compared with those for the fatty
liver disease and strict fatty liver disease
groups by using a two-sample t test for
means. The two-sample t test was also
used to compare the groups with respect
to weight and BMI. A cutoff P value of
less than .05 indicated statistical significance. The minimal expected detectable
difference between the fatty liver group
and control group as well as between
the strict fatty liver group and control
group was calculated by using a significance criterion of P , .05 and a power
of 0.90.
To graphically assess the relationship between liver SUVm as a function
of mean liver attenuation (in Hounsfield
units), we performed least-squares linear
regression analysis of these two variables
by using liver attenuation as the independent variable. The correlation coefficient for the correlation between these
two variables was also calculated.
Results
With the criterion of a mean liver attenuation value lower than the mean
spleen attenuation value (HUL-S , 0)
used to indicate diffuse fatty infiltration
of the liver, 23 patients had diffuse fatty
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NUCLEAR MEDICINE: Effect of Hepatic Steatosis on Liver FDG Uptake
infiltration and 119 patients were control subjects—that is, their mean liver
attenuation value was greater than or
equal to their mean spleen attenuation
value (HUL-S ⱖ 0). These data indicate a
prevalence of diffuse fatty infiltration of
16.2% (23 of 142 patients).
The average liver SUVm for the
control group was 2.18 (standard deviation [SD], 0.36; 95% confidence
interval [CI]: 2.12, 2.24), which is not
significantly different from previously
published data (SUVm, 2.17; SD, 0.33;
95% CI: 2.03, 2.31) (P = .91) (12). The
average liver SUVm for the diffuse fatty
infiltration group was 2.03 (SD, 0.31;
95% CI: 1.90, 2.16), which was not
significantly different from that for the
control group (P = .07). The average liver
SUVm for the strict fatty liver disease
group—those with a mean liver attenuation value minus mean spleen attenuation value difference of less than or
equal to 210 HU (HUL-S ⱕ 210)—was
2.07 (SD, 0.24; 95% CI: 1.92, 2.22)
and did not differ significantly from
the average liver SUVm for the control
group (P = .35) (Table 1).
The mean liver SUVmax was also
measured. There was no significant difference in mean liver SUVmax between
the control (mean SUVmax, 2.76; SD,
0.47; 95% CI: 2.68, 2.84) and fatty
liver disease (mean SUVmax, 2.63; SD,
0.42; 95% CI: 2.46, 2.80) groups (P =
.22) or between the control and strict
fatty liver disease (mean SUVmax, 2.54;
SD, 0.3; 95% CI: 2.54, 2.92) groups
(P = .23). The control group demonstrated a mean spleen attenuation value
of 42.3 HU (SD, 3.4; range, 35–54 HU).
The mean spleen attenuation value for
the fatty liver disease group was 43.9 HU
(SD, 2.8; range, 41–50 HU). The mean
spleen attenuation value for the strict
fatty liver disease group was 43.4 HU
(SD, 2.8; range, 41–49 HU).
The fatty liver disease group demonstrated a significantly higher mean body
weight (89.0 kg; SD, 25.6) compared
with the control group (77.1 kg; SD,
18.2) (P = .009). The strict fatty liver
disease subgroup also demonstrated a
significantly higher mean body weight
(99.8 kg; SD, 19.4) compared with the
control group (P , .001). There was
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Abele and Fung
Table 1
Liver SUVm Values for Control and Fatty Liver Disease Groups
Patient Group
Control
Fatty liver disease
Strict fatty liver disease§
HUL-S*
No. of Patients
Average Liver SUVm†
P Value
ⱖ0
,0
ⱕ–10
119
23
10
2.18 (2.12, 2.24)
2.03 (1.90, 2.16)
2.07 (1.92, 2.22)
…
.07‡
.35‡
* HUL-S = mean liver attenuation value, in Hounsfield units, minus mean spleen attenuation value.
†
Mean values, with 95% CIs in parentheses.
‡
P values for comparisons with control group values.
§
The strict fatty liver disease group is a subset of the fatty liver disease group.
Table 2
Mean Body Weight and BMI Values for Control and Fatty Liver Disease Groups
Patient Group
Control
Fatty liver disease
Strict fatty liver disease§
HUL-S*
Body Weight (kg)†
BMI†
ⱖ0
,0
ⱕ–10
77.1 (73.9, 80.4)
88.9 (78.5, 99.4)‡
99.8 (87.8, 111.8)‡
26.7 (25.7, 27.7)
29.5 (26.3, 32.6)‡
30.9 (27.5, 34.2)‡
* HUL-S = mean liver attenuation value, in Hounsfield units, minus mean spleen attenuation value.
†
Mean values, with 95% CIs in parentheses.
‡
P , .05 for comparison with control group values.
§
The strict fatty liver disease group is a subset of the fatty liver disease group.
no statistically significant difference in
mean body weight between the fatty
liver disease and strict fatty liver disease groups (P = .24).
Patient height data were available
for most patients and enabled calculations of the BMI. Patient height data
were not recorded for nine patients in
the control group, one patient in the
fatty liver disease group, and one patient in the strict fatty liver disease subgroup. Because the data were analyzed
retrospectively, patient height data for
these patients could not be obtained.
Allowing for this, the fatty liver disease
group had a significantly higher mean
BMI (29.5; SD, 7.5) compared with the
control group (26.7; SD, 5.3) (P = .04).
The strict fatty liver disease group also
demonstrated a significantly higher BMI
(30.8; SD, 5.2) compared with the control group (P = .03). There was no significant difference in BMI between the
fatty liver disease and strict fatty liver
disease groups (P = .62) (Table 2).
The control group of 119 subjects
included 19 patients with diabetes
mellitus, seven of whom were taking
insulin. The fatty liver disease group
of 23 subjects included four patients
with diabetes mellitus, none of whom
was taking insulin. The strict fatty
liver disease subgroup of 10 subjects
included one patient with diabetes
mellitus, who was not taking insulin.
Oral antidiabetic medication histories
were less reliable owing to the retrospective nature of this study; however,
we noted that two patients in the fatty
liver disease group, but no patients in
the control group or strict fatty liver
disease subgroup, were receiving thiazalidinedione therapy.
The medication lists provided by
the referring physicians at study requisition and the medication history taken
by the clinical nurse immediately before the FDG injection revealed that at
the time of FDG PET/CT examination,
16 of the 142 study patients (12 from
control group, four from fatty liver disease group, one from strict fatty liver
disease subgroup) were taking glucocorticoids, two patients (two from fatty
liver disease group, one from strict
fatty liver disease subgroup) were taking
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Abele and Fung
Figure 1
Figure 1: Graph illustrates FDG uptake in the liver, measured in SUVm values, as a function of mean liver attenuation, in Hounsfield
units. Graph data indicate no significant association between these parameters (r = 0.02). The measured slope at linear regression
analysis is 0.005.
methotrexate, one patient from the
control group was receiving lamivudine
therapy, and one patient from the control group was taking tamoxifen. No
patients were identified as having a history of amiodarone, zidovudine, or diltiazem therapy.
Linear regression analysis to assess
the relationship between liver SUVm as
a function of mean liver attenuation
revealed a slope of 0.005, with a correlation coefficient of 0.02. This relationship is plotted graphically in Figure 1.
In Figure 2, the same data are plotted
on the x (liver attenuation minus spleen
attenuation) axis with a more clear depiction of the control and fatty liver disease groups. Representative images obtained in a control patient and a patient
with fatty liver disease are shown in
Figure 3. With use of a pooled SD for
the study group of 0.358, the minimal
expected detectable difference between
the fatty liver group and the control
group was calculated to be 0.26. The
Radiology: Volume 254: Number 3—March 2010
n
minimal expected detectable difference
between the strict fatty liver group and
the control group was calculated to
be 0.38.
Discussion
The data in our study demonstrated
no clinically important correlation
between liver attenuation at CT and
SUVm. In addition, the average liver
SUVm and mean liver SUVmax measurements in the patients with evidence of diffuse fatty infiltration of
the liver were not significantly different from those in the healthy control
subjects.
From a clinical perspective, these
data are important, given the high
prevalence of diffuse fatty infiltration
in the Western population (20%–35%)
and the continuously increasing problem of obesity, which is strongly associated with NAFLD (1,2). Also, the
increased use of hybrid PET/CT rather
radiology.rsna.org
than PET alone has led to increased recognition of background hepatic steatosis
in the population of patients who undergo clinical PET owing to the added
information gained from the CT component of the hybrid examination. Given
that the average FDG uptake in the liver
is often used as a background comparator to determine the clinical importance
of focal FDG uptake elsewhere in the
abdomen (ie, adrenal glands, pancreas,
lymph nodes), it is important to validate
this approach in patients with diffuse
liver disease. On the basis of the data in
our study, it is acceptable to use average
liver FDG uptake as a comparator in patients with obvious hepatic steatosis.
The results of this study contradict
trends recently reported in the limited literature. Qazi et al (13) described a small
study with 33 patients in which liver
SUVmax–to–spleen SUVmax ratios and liver
SUVmax–to–mediastinum SUVmax ratios
were compared between a healthy volunteer group and a fatty liver neoplasm
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Abele and Fung
Figure 2
Figure 2: Graph illustrates liver FDG uptake, measured in SUVm values, as a function of mean liver attenuation value minus mean
spleen attenuation value difference. Circles indicate control group, and triangles indicate fatty liver disease group. The measured slope
at linear regression analysis is 0.005.
patient group. Although the liver-spleen
SUVmax ratio for the fatty liver disease group
was noted to be significantly lower than
that for the healthy group (1.1 versus 1.4,
P = .002), there was no significant difference in liver-mediastinum SUVmax ratio
between these groups (P = .1). Concerns
with this report include uncertainty in the
abstract regarding how the diagnosis of
fatty liver disease was made, uncertainty
regarding how the ROIs were applied,
and the use of SUVmax as the measured
parameter. SUVmax is commonly used
as a marker of FDG uptake in tumors
because it is less susceptible to volumeaveraging effects. In contrast, for large
anatomic structures such as the liver,
where ROIs can be reliably applied, the
SUVm is a more robust measure of FDG
uptake statistically, because few or no
unwanted voxels are included. From the
clinical point of view of using the liver
as a comparator for foci of FDG uptake
in the abdomen and pelvis, the SUVm
can be applied more directly because
these foci generally are compared with
922
liver activity as a whole rather than as
specific voxels.
A case report by Purandare et al
(14) describes a case of focal increased
FDG uptake in a region of focal fatty
sparing in the liver. The measured SUV
in this focus was 4.0. This value is greater
than that expected for a normal liver
and indicates increased FDG uptake in
the focus as opposed to decreased FDG
uptake in the background regional fatty
change. Assuming the correct site was
sampled at biopsy, this finding may have
been a reflection of increased focal FDG
delivery related to vascular flow differences rather than of a true difference in
metabolic activity.
In a recent report, Borra and colleagues (15) describe an inverse association between liver fat content and
hepatic glucose uptake in patients with
type 2 diabetes mellitus. In that study,
FDG was injected in the presence of
a euglycemic hyperinsulinemic clamp.
It is likely that the diminished glucose
uptake in the examined population was
related to increased insulin resistance
in the liver rather than a direct effect of
increased liver fat content. In any event,
the results of the Borra et al study do
not apply to the general population of
patients with neoplasms examined with
PET in our study. In particular, oncology
patients generally are prohibited from
oral caloric intake and insulin injection
for a period before the FDG injection.
As a result, insulin levels are generally
low and the effects of insulin resistance
are likely to be reduced.
It should be noted that a number of
medications used in oncologic and cardiology applications are known to be secondary causes of NAFLD. These medications include tamoxifen, glucocorticoids,
methotrexate, zidovudine, amiodarone,
and diltiazem (1,2). Because FDG PET is
commonly used for oncologic and cardiology applications at both initial presentation and follow-up, secondary NAFLD
may develop over a period of clinical
imaging examinations. For example, the
limited available medication data on the
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Figure 3
Figure 3: Transverse (a, c) CT and (b, d) PET images acquired from hybrid FDG PET/CT examinations
performed in two patients: one from fatty liver disease group (a, b) and the other from control group (c and d).
CT scanning was performed without intravenous contrast material administration. While a clearly depicts
diffuse fatty liver disease, there is no significant qualitative difference in average FDG uptake between the
two patients.
patients in our study indicated that 19
patients were taking at least one of these
medications. The results of this study
help to validate the use of background
liver activity as a comparator when there
has been an interval development of hepatic steatosis in these patients.
Furthermore, our study results confirm previously published values for
liver SUVm. The control group in our
study was much larger (119 patients)
than control groups in previously published studies (11,12), and the control
group results validated the use of the
liver as a stable comparator, with an
SUVm of 2.18 (95% CI: 2.12, 2.24). The
liver not only demonstrates stable FDG
uptake over time (11) and between patients (12) but also is stable regardless
of diffusely decreased CT attenuation.
These factors are key to the use of the
liver as a baseline organ for comparison
in the abdomen and pelvis.
It is interesting that the fatty liver
disease groups demonstrated a signifiRadiology: Volume 254: Number 3—March 2010
n
cantly greater mean body weight and
mean BMI compared with the control
group. This finding correlates with the
known association between obesity and
hepatic steatosis (1). It is also interesting that in this study, even the control
group demonstrated a mean BMI higher
than 25 (26.7). A BMI higher than 25 is
categorized as overweight according to
the World Health Organization classification (16), and an increased BMI has
been linked to numerous cancers, including lung cancer (17), the most prevalent
malignancy in our study population.
One potential problem with our study
was type II error—that is, the possibility that the power of the study was not
high enough for the detection of a true
difference between the groups. This issue
in particular is raised owing to the relatively low but non–significance-indicating
P value of .07 for the difference in average SUVm between the fatty liver disease and control groups. The minimal
expected detectable difference between
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Abele and Fung
these groups was calculated to be 0.26.
The minimal expected detectable difference between the strict fatty liver disease and the control groups was calculated to be 0.38. Because most clinically
important changes in SUVm are greater
than 0.50 (18,19), these values suggest
that our study had an adequate number
of subjects for the detection of a clinically importance difference in average
liver SUVm.
One limitation of this study was
the potential for confounding lesions in
the ROI that were not identifiable with
use of the nonaugmented CT or PET
component of the hybrid examination.
While those patients with identifiable
focal abnormalities in the liver were excluded from analysis, it is possible that
lesions such as hemangiomata, small
cysts, vascular anomalies, or even isoattenuating isometabolic metastases were
included, particularly given the absence
of intravenous contrast material. The
importance of this potential confounder
was mitigated by the relative rarity of
this scenario combined with the relatively large ROIs (.3 cm) applied.
Because fatty liver disease was defined as a mean liver attenuation value
lower than the mean spleen attenuation
value in this study, abnormally increased
spleen attenuation could have had a
confounding effect. The spleen attenuation measurements were reviewed and
noted to have relatively narrow ranges,
with no obvious outliers. Given these results, there is no evidence to suggest that
the group stratification was confounded
by spleen abnormalities. We also noted
that no patient had a reported history of
amiodarone therapy or thorium dioxide
exposure.
The prevalence of hepatic steatosis
in this study was 16.2%. This is similar to but slightly lower than published
prevalences of 20%–35%. While a component of this result may be related to
the study population, this prevalence
is also probably a reflection of the limited sensitivity of CT for detecting mild
fatty liver disease (3). However, the fact
that this study revealed no relationship
between SUV and either moderate or
severe fatty liver disease perceivable at
CT makes it reasonable to assume that
923
NUCLEAR MEDICINE: Effect of Hepatic Steatosis on Liver FDG Uptake
this relationship absence also applies to
mild nonperceivable steatosis.
Finally, the results from this study
apply to a broad cross section of patients in a typical oncologic PET practice at a single point in time. The effect of transition from no steatosis to
steatosis on liver SUV in individual patients was not directly assessed. Given
that the use of some chemotherapeutic
agents can result in secondary hepatic
steatosis, it would be useful to evaluate specifically this group over time in
future studies.
In conclusion, we observed no significant association between liver attenuation and SUVm. Specifically, hepatic
steatosis does not appear to have any
significant effect on FDG uptake by the
liver as determined by using SUVm values. The data presented in this study
further validate the use of background
liver activity as a stable comparator
when determining the clinical importance of equivocal focal FDG uptake
elsewhere in the abdomen. Specifically, the liver is acceptable to use as a
comparator in patients with fatty liver
disese.
Acknowledgment: The authors thank Michael
Grace, PhD, for his help in preparing this
manuscript.
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Radiology: Volume 254: Number 3—March 2010