Background
Small-animal positron emission tomography (PET) imaging is being used increasingly in preclinical research. The use of glucose analogue 2-[
18 F]fluoro-2-deoxy-
d-glucose (
18 F-FDG) for the
in vivo measurement of local glucose utilization rate in oncological animal models has been a valuable tool for evaluation of treatment response. Longitudinal imaging allows tracking of the disease progression and provides more sensitive qualitative and quantitative assessments of the effects of an intervention than non-longitudinal measurements [
1,
2]. Reduction in
18 F-FDG uptake from its baseline value is usually used as an indicator of the tumor response to treatment. Standard uptake value (SUV) [
3] is commonly used as a measure of glucose utilization activity, but it can be influenced by a variety of biologic and technical factors, including the plasma time-activity curve and blood glucose level [
4]. The effect of blood glucose level on
18 F-FDG uptake in tumors has been investigated before but with conflicting results. Some found benefit in normalizing SUV by blood glucose level [
5‐
7]; others found no benefit [
8‐
10]. Our previous work also indicated that
18 F-FDG uptake in various tissues is affected by blood glucose level differently [
11]. It is likely that the value of SUV may not necessarily reflect directly the glucose utilization rate in the tissue of concern, and adjustments for glucose level should not be done indiscriminately.
In this work, we addressed the effect of blood glucose level and tumor growth on both the SUV and
18 F-FDG uptake constant (
K
i
) in two different types of tumors. The input function for the calculation of
18 F-FDG
K
i
was derived based on a modeling method that utilizes the early-time dynamic PET images of the heart chamber and a single blood sample taken at the end of the scan [
12]; so, the experimental animal did not need to be sacrificed after each scan, and multiple longitudinal studies could be performed. The use of an input function for quantitation of biological function seeks to reduce many effects due to systemic variations.
Methods
Tumor models and small-animal imaging
Nineteen 6- to 8-week-old severe combined immunodeficiency (SCID) mice were maintained in a strict defined-flora, pathogen-free environment in the AAALAC-accredited animal facilities at UCLA. Human glioblastoma cell line U87 and breast cancer cell line MDA-MB-231(MDA) were used as a SCID-hu tumor model. Tumor cells were injected (with MDA cells in 11 mice and with U87 cells in 8) subcutaneously as single-cell suspensions in phosphate buffer saline (PBS; about 2 × 106 MDA or about 6 × 105 U87 cells in 100 μL PBS). When the diameter of the tumor grew to approximately 2.5 mm, a PET scan was performed once a week on the same animal until the diameter of the tumor exceeded 10 mm. Tumor size was measured weekly with a caliper, and the volume was calculated as 0.5 × length × width2.
Small-animal PET scans were performed either on a microPET Focus 220 scanner running microPET Manager 2.4.1.1 or on an Inveon dedicated PET running IAW 1.5 (Siemens Preclinical Solutions, Knoxville, TN, USA), but the same scanner was used for multiple longitudinal PET scans of each mouse. These scanners provide the same SUV and % ID values for mice imaged sequentially in both systems (unpublished data). List-mode PET data were acquired for 60 min immediately after 18 F-FDG injection via a tail vein catheter (18.28 ± 1.19 MBq, approximately 60 μL) in a bolus. Frame durations of all the PET studies were 4 × 1 s, 15 × 0.5 s, 1 × 2 s, 1 × 4 s, 1 × 6 s, 1 × 15 s, 3 × 30 s, 1 × 60 s, 1 × 120 s, 3 × 180 s, 3 × 900 s, and 1 × 51 s. After the PET scan was completed, a 10-min CT scan was acquired with a small-animal CT scanner (MicroCAT II, Siemens Preclinical Solutions, Knoxville, TN, USA) for attenuation correction of the PET measurements.
Tail vein blood glucose levels (in mmol/L) were measured using a blood glucose meter (Abbott AlphaTRAK, Abbott Laboratories, Abbott Park, IL, USA) at the beginning and the end of each scan. A single blood sample (approximately 10 to 15 μL) was collected with a 1-cc syringe from the heart at the end of the study (approximately 70 to 80 min). The whole blood in the syringe was released to a pre-weighed test tube and weighed, and the radioactivity was counted in a gamma counter (WIZARD 3"; PerkinElmer Life Sciences, Turku, Finland).
All animal experiments were performed in accordance with institutional guidelines and protocols approved by the Animal Research Committee of the University of California, Los Angeles, USA.
Image analysis
Image analysis was performed using AMIDE (
http://amide.sourceforge.net/). The 3D isocontour regions of interest (ROIs) were manually defined for the skeletal muscle of the left ventricle (LV), forelegs, liver, and tumor in each mouse on the last 15-min images (about 60 min post
18 F-FDG injection). Only tumors without an apparent necrotic center on the
18 F-FDG PET images were included in the analysis. The time-activity curves (TAC) in each tissue of interest were calculated. Experimental information for all studies is available online at the UCLA Mouse Quantitation Project website (
http://dragon.nuc.ucla.edu/mqp/index.html).
For semi-quantitative analysis, SUV was calculated using the mean voxel value within the ROI of the last 15-min frame (Equation 1). SUVs of each study were recorded and were used for generating the TACs.
(1)
The plasma TAC (TAC
p; the input function) was derived based on the method reported by Ferl et al. [
12]. The method included the use of the early-time LV TAC (
t < 1 min) (with corrections of delay, dispersion, partial volume effects, and red blood cell uptake) and one whole blood sample taken at the end of the study (approximately 70 min). For each study, a time-dependent plasma-to-whole blood
18 F-FDG equilibrium ratio,
R
PB(
t) (Equation 2), was used to convert the whole blood
18 F-FDG concentrations to those in plasma [
11].
(2)
where
t is time in minutes after tracer injection. The input function was assumed to be describable with four exponential components (Equation 3):
(3)
The sum of the first three exponential terms was used to describe the main part of the input function; the fourth exponential term was needed so that TAC
p was equal to 0 at time 0. All parameters were estimated by simultaneously fitting the plasma
18 F-FDG blood curve with Equation
3 and the muscle and liver TACs with two separate 4 K compartmental
18 F-FDG models as described by Ferl et al. [
12]. The kinetic modeling program SAAM II [
13] was used to solve the systems of differential equations and estimate parameters. The Bayesian maximum
a posteriori parameter estimation in SAAM II was used to improve parameter identification and the accuracy of the predicted input function as described by Ferl et al. [
12].
Kinetic analysis
Both the PET image and blood data were converted to absolute radioactivity concentration (Bq/mL) using a cross-calibration factor derived from cylinder phantom experiments. The
18 F-FDG uptake rate constant
K
i
(
K
i
=
K
1
k
3/(
k
2 +
k
3)) was estimated via the Patlak graphical analysis [
14] using the derived plasma input function and tumor TAC data by taking the slope of the linear portion from 15 to 60 min of the plot based on Equation
4:
(4)
(5)
where
C
T(
t) is the total
18 F-FDG concentration in the tissue of interest,
C
1(
t) is the free
18 F-FDG concentration in the tissue,
C
p(
t) is the
18 F-FDG concentration in the plasma,
C
B(
t) is the blood
18 F-FDG concentration in the vasculature, and
V
B is the volume fraction of blood in the tissue. The early-time tissue data (for
t < 15 min) were not used because only after an equilibration time (
t*) will the Patlak plot become linear. The metabolic rate of glucose (MRGlu) was calculated as MRGlu =
K
i
× [Glc]/LC [
15], where [Glc] was the averaged blood glucose level of the two measurements at the beginning and the end of the scan, and LC is the lumped constant. Values of the LC were assumed to be 1.4 for U87 [
16] and 1.0 for MDA. The intercept value (Int) shown in Equation
5 is related to the
V
B and the distribution volume of the tracer in the reversible tissue compartment.
Data analysis and functional relationship determination
K
i
and SUVs were partial volume (PV)-corrected by dividing the values by the recovery coefficient (RC) of the tumor. As a first-order approximation, RC for a tumor was calculated based on a sphere of diameter =
the spatial resolution of the microPET scanner, and an assumed background activity level of 10% of the activity level in the sphere. Four models (Equations 6 to 9) were tested to fit the relationship of glucose concentration and tumor diameter to quantitative PET measures,
Y (SUV/RC or
K
i
/RC).
(7)
(9)
The parameters
a and
c were to account for the effect due to tumor growth in size;
b was equivalent to the half saturation glucose concentration of
18 F-FDG uptake [
11]. Models were tested separately for U87 and MDA. To account for possible effects introduced through repeated measures, models were fit using standard least-squares method as well as mixed-effects method [
17]. For models 3 and 4 (Equations 8 and 9), if fitted values for parameter
b were not found to be significant, the model was rebuilt, setting
b equal to 0. Mixed-effects models were built assuming no within-group covariance of random effects. For models with more than one fitted parameter, all possible combinations of random effects were tested. If more than one mixed-effect model showed significant improvement over the standard fixed-effect model, the optimal mixed-effect model was chosen by the likelihood ratio test if models were nested or by the corrected Akaike's information criterion (AIC
c), otherwise. After a fitting method for each model was chosen, the optimal model for each cell line and response variable was chosen based on AIC
c. Fittings and model comparison were done using the nlme package of the statistical software R [
18].
Discussion
In this work, a set of longitudinal quantitative
18 F-FDG PET studies was performed on tumor-bearing mice, and a method to account simultaneously for the blood glucose level and tumor growth has been tested. While the impact of medium/blood glucose levels on
18 F-FDG uptake in tumors has previously been investigated in both
in vitro and
in vivo studies [
20,
21], no longitudinal studies have been reported to elucidate the associations of both blood glucose level and tumor size with
18 F-FDG
K
i
in tumors. Our quantitative analysis based on
18 F-FDG uptake, kinetics analysis, and model selection addresses the effect of blood glucose level and tumor size (for tumors without necrotic cores) in two different types of tumors. The results suggested that the need to account for the confounding effects of glucose in the fitting of measured data is tumor cell line dependent and that appropriately taking this into account would lead to improvement in the measurement sensitivity of the true biological signals in the tumors.
Results of the growth rate and Patlak analysis showed that human breast cancer MDA cells have an adequate proliferation rate in SCID mice for longitudinal
18 F-FDG PET studies, as do human glioma U87 cells. In this work, tumor growth was monitored longitudinally, and it was found that MDA and U87 had a similar growth rate for about 30 days after the baseline imaging time point (Figure
2). However, MDA developed necrotic cores much earlier than U87 (Figure
1), probably due to different angiogenesis rates between the two tumor types (U87 > MDA). The larger Int value derived from the U87 tumor
18 F-FDG kinetics is consistent with having more angiogenesis in U87. Although a larger proportion of tumor cells in tissue would increase the FDG uptake rate constant and thus the slope of the Patlak plot, it is not expected to affect the value of Int by a large amount. The larger value of Int also supports the reasoning that the higher angiogenesis rate is the cause of the observed slower development of necrotic core in the U87 tumors as compared to the MDA tumors.
In PET tumor imaging, SUV is the most frequently used index for characterizing tumor
18 F-FDG uptake. However, the value of its use for interpreting
18 F-FDG PET scans was found to be limited because of the considerable overlap between SUV measurements in malignant and benign lesions and subtle changes at early response to therapy [
22]. Therefore, large variability in SUV measurements could affect the clinical interpretation. Generally speaking, these variability sources can be categorized into two types. One comes from biological factors (e.g., tumor's size/configuration changes, plasma substrate level, insulin level, and input function variations). Another type is associated with technical factors (e.g., reconstruction parameter changes). Our study was designed to examine the effect of blood glucose level and tumor growth on
18 F-FDG uptake.
Results of MDA showed that SUV,
K
i
, and MRGlu were relatively constant when the tumor grew bigger (Figure
3); no correlation was found between SUV or
K
i
, and blood glucose levels, but MRGlu increased with increasing blood glucose levels (Figure
4). Unlike that in MDA, SUV and
K
i
in the U87 tumor correlate significantly with tumor size and blood glucose levels, indicating that correction for both blood glucose level and tumor size is needed in the calculation of SUV and
K
i
to reflect tumor glucose utilization rate. These results also suggested that the glucose uptake regulation could be different in different tumor types, and correcting for blood glucose level or not in the SUV formula should be done selectively. Reported results in the literature on the effect of blood glucose levels on a few other types of tumors were somewhat controversial. Most studies have demonstrated that
18 F-FDG uptake into human cancer cells is inhibited by increasing blood glucose levels because of saturation of glucose uptake in tumors [
6,
7]. Our results from U87 data were consistent with these findings. However, animal studies performed by Torizuka et al. [
10] indicated that the uptake of
18 F-FDG in mammary carcinoma was reduced for insulin-induced hypoglycemia. In our present study,
18 F-FDG SUV in the mammary cancer MDA has a slightly negative slope but with an insignificant correlation, with respect to blood glucose levels (Figure
4).
When tracer uptake in small tumors was measured, large biases could be introduced by the PVE [
23]. We used the calculated RC to reduce the errors attributable to PVE. Four models (Equations 6 to 9) with one to three independent parameters were used to account for glucose level and to evaluate if the PV-corrected
18 F-FDG SUV and
K
i
changed as the tumors grew in size. Likelihood ratio tests (Tables
1 and
2) showed that mixed-effects modeling is not necessary for the U87 data but is necessary for the MDA cell line, suggesting that the U87 has more homogenous development than the MDA among different mice. This is consistent with the larger data scatter of
18 F-FDG uptake obtained for the MDA cell line than for U87 in
in vitro experiments using multiwell plates [
24]. The best model (Equation 8) for U87 indicates that U87
K
i
was inversely correlated to the blood glucose levels. That is similar to our previous findings on
18 F-FDG
K
i
in the brain [
11] that showed a significant inverse relationship between cerebral
18 F-FDG
K
i
and the blood glucose level. The best model (Equation 1) for MDA is consistent with the results of our
in vitro studies, which showed that the
18 F-FDG uptake in MDA was affected little by medium glucose level over the normal physiological glucose range [
24]. Since U87 is a human cancer cell line originating from the brain, the finding that U87 behaves like the brain tissue in glucose metabolism is interesting, but not unexpected. The
18 F-FDG SUV and
K
i
, after accounting for the PVE and blood glucose levels (Figures
5 and
6), did not show any significant correlation with tumor size, further confirming that tumor glucose utilization rate was rather stable when the tumor (of either MDA or U87) grew bigger in size (but before necrotic core development). The relationship indicates that without treatment intervention, tumor cells/tissues do not change their metabolic aggressiveness as tumors grow (at least before necrosis appears).
The current results showed that the use of either SUV or
K
i
gave the same conclusion regarding the effects of blood glucose level and tumor growth on glucose utilization rates for MDA and U87. The use of
K
i
, however, was supposed to better account for the systemic variations in
18 F-FDG delivery between studies or animals. In the present study, these variations were small because the animals were obtained from the same source, had the same diet and similar age, and were treated similarly. When the variations in the systemic condition are large, as in a patient population, the use of SUV as an indicator of tumor glucose utilization rate is expected to give a larger variability than that of
K
i
and may not be as sensitive to reveal the same effects. Similar advantages of
K
i
over SUV were also observed in one of our previous studies on the effects of blood glucose level on the brain
18 F-FDG uptake [
11]. The main desirable feature of SUV is that it does not need dynamic PET imaging and is thus more practical for human studies.
The present results indicate that
18 F-FDG
K
i
in MDA and U87 differs considerably in response to altered blood glucose level, suggesting that regulation of
18 F-FDG uptake and glucose metabolism are tumor-type dependent. However, more work needs to be done to account for effects due to other possible factors, including blood insulin level and tumor heterogeneity (when a necrotic core appears), to further improve the reliability of the quantitative measurements and to examine the metabolic stability/change after a necrotic core develops. Insulin is known to induce a host of effects on traditional metabolic actions such as glucose transport and utilization [
25]. Insulin also has vascular-specific actions that are particular to vascular tissues [
26]. Although the effects of insulin on tumor
18 F-FDG uptake have been studied by others before [
10,
27], the prior studies all involved insulin injections into the animal or patient that yielded a non-steady state circulating insulin level and also a variable blood glucose level at the same time. As a result,
18 F-FDG uptake could be affected by either or both factors and is more difficult to interpret. Only after the known confounding factors are properly accounted for can one begin to critically assess the temporal changes in
18 F-FDG uptake kinetics during normal growth or due to intervention or treatment.
A frequently asked question about 18 F-FDG uptake in tumors is whether it reflects more tumor biology versus inflammatory response associated with the xenograft. Our present study would not be able to provide a definitive answer. Although inflammatory response is usually considered to be transient, it could be compensated by tumor biology changes. A longitudinal PET study with coordinated tissue autopsy examination could be performed in the future to address this question.
Competing interests
The authors declare that they have no competing interests.
Authors' contributions
WS participated in conceiving the study, performed the animal experiments and data analysis, and drafted the manuscript. HY participated in performing the animal studies, and KSI participated in the tumor implant and design of experiments. KPW participated in the animal studies and data analysis. MQW performed the statistical analysis. DS participated in performing the animal imaging studies, and WM participated in conceiving the study and in its design. SCH conceived the study, participated in its design, guided the data analysis, and helped draft the manuscript. All authors read and approved the final manuscript.