Dynamic positron emission tomography (PET) imaging of the lung using the radiotracer 2-[fluorine-18]-fluoro-2-deoxy-D-glucose ( 18 F-FDG) is an emerging method to assess noninvasively the metabolic activity of pulmonary inflammatory cells. Nevertheless, because of the distinct functional and structural characteristics of inflamed lung tissue standard methods of 18 F-FDG analysis can be substantially limited and there is no consensus about the best method for quantification of the 18 F-FDG signal for acute or chronic inflammatory lung diseases. This article gives an overview on recent advances in quantitative analysis of 18 F-FDG uptake kinetics in non-neoplastic inflamed lung tissue.
Positron emission tomography imaging (PET) with the radiolabeled glucose analog 2-[fluorine-18]-fluoro-2-deoxy-D-glucose ( 18 F-FDG) has been increasingly used to assess pulmonary inflammation . Activated inflammatory cells, particularly neutrophils, increase glucose metabolism to much higher levels than non-neoplastic lung tissue . Therefore, 18 F-FDG accumulates in lung regions with neutrophilic inflammation, which can be identified in PET images. 18 F-FDG enters inflammatory cells via glucose transporter (GLUT) proteins , and is phosphorylated by hexokinase to 18 F-FDG-6-phosphate, which cannot be further metabolized and remains trapped within the cells.
Measurements of 18 F-FDG uptake during acute lung inflammation demonstrated a remarkable specificity for neutrophil activity , and there is strong evidence that neutrophil priming could be the predominant event responsible for increased 18 F-FDG uptake by these cells . Recent studies have demonstrated the potential of this new technology in such diverse conditions as pneumonia and bronchiectasis , cystic fibrosis , endotoxin-induced lung inflammation , segmental allergen challenge , lung transplantation , inflammation in chronic obstructive pulmonary disease and asthma , as well as in acute lung injury (ALI) induced by oleic acid and endotoxin , by mechanical ventilation , and by smoke inhalation ( Table 1 ). However, in contrast to the assessment of 18 FDG uptake by dense tissues such as brain or solid tumors where quantitative analysis is well defined, assessment of 18 F-FDG uptake by the lungs presents a number of challenges, and the best method for quantifying it has yet to be established .
Table 1
Reports on 18 F-FDG Uptake by Non-neoplastic Lung Tissue
Authors Experimental Setting Reference Miyauchi and Wahl, 1995 Normal lung ( n = 15) Taylor et al, 1996 Allergen challenge in atopic asthma ( n = 9) Mamede et al, 2005 Tuberculosis ( n = 10) Zasadny and Wahl, 1993 Normal lung ( n = 28) Jones et al, 2003 Normal subjects ( n = 5) Chronic obstructive pulmonary disease ( n = 6) Asthma ( n = 6) Jones et al, 1997 Lobar pneumonia ( n = 5) Bronchiectasis ( n = 5) Labiris et al, 2003 Cystic fibrosis ( n = 10) Brudin et al, 1994 Sarcoidosis ( n = 7) Chen et al, 2006 Cystic fibrosis ( n = 20) Normal subjects ( n = 7) Chen et al, 2006 Endotoxin instillation in normal subjects ( n = 18) Chen and Schuster, 2004 Acute lung injury in dogs Normal ( n = 5) Oleic acid ( n = 7) Endotoxin ( n = 6) Endotoxin and oleic acid ( n = 7) Holmes et al, 2005 Segmental allergen challenge in rats ( n = 4) Schroeder et al, 2007 Smoke inhalation in sheep ( n = 5) Musch et al, 2007 Ventilator-induced lung injury in sheep Positive end-expiratory pressure ( n = 6) Negative end-expiratory pressure ( n = 6) Costa et al, 2010 Mild endotoxemia in mechanically ventilated sheep ( n = 6)
One challenge comes from the fact that, in the lungs, the volume fraction occupied by blood may be as much as that occupied by parenchyma. Therefore, blood can be a significant source of 18 F-FDG activity unrelated to cellular uptake ( Table 1 ). This is particularly the case during an early phase after intravenous 18 F-FDG injection. Moreover, ALI can be associated with dramatically increased permeability or mechanical disruption of the alveolar-capillary membrane, causing alveolar flooding or pulmonary edema . In this condition, 18 F-FDG could leak into alveolar spaces increasing the apparent rate of 18 F-FDG uptake by the lung. Furthermore, because PET data are expressed in units of “per mL lung,” differences in lung inflation affect tissue density and, thus, 18 F-FDG distribution volume and apparent rate of glucose uptake .
Presently, the methods to quantify 18 F-FDG uptake can be grouped in three categories: semiquantitative, graphical analysis, and compartmental modeling. This article gives an overview on recent studies applying these methods in normal and diseased non-neoplastic lungs.
Semiquantitative methods
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SUV=tissueactivity(mCi/mLtissue)injecteddose(mCi)/body weight(kg) SUV
=
tissue
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tissue
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injected
dose
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mCi
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/
body weight
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kg
)
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Graphical analysis
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CPET(t)Cp(t)=Ki∫t=0tCp(t)dtCp(t)+Vdist C
PET
(
t
)
C
p
(
t
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=
K
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∫
t
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0
t
C
p
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dt
C
p
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+
V
dist
to identify the 18 F-FDG net uptake rate (K i ) and an initial distribution volume (V dist ) of the tracer. C P (t) has been traditionally assessed by sequential manual blood sampling. To circumvent invasiveness, radiation exposure, and costs associated with sequential blood sampling, C P (t) has also been estimated from a blood pool region defined over the heart chambers or aorta in the dynamic PET images . However, activity spillover is a concern when C P (t) is estimated from an image region close to tissue with high 18 F-FDG uptake, such as heart muscle or inflamed lung parenchyma. In fact, unless corrected for partial volume effects and activity spillover artifact, the use of a raw image–derived C P (t) can lead to significant bias in Patlak estimates of lung K i . A C P (t) correction technique that has been applied for 18 F-FDG PET imaging of pulmonary inflammation requires only two central venous blood samples for calibration purposes . The authors of that study expect that peripheral rather than central venous calibration blood samples can be used, but refer to further study to validate this assumption.
![Figure 1, Patlak plots generated from dynamic 2-[fluorine-18]-fluoro-2-deoxy-D-glucose ( 18 F-FDG PET) measurements in a control lung ( open symbols ) and a lung with smoke inhalation exposure (closed symbols) in a sheep. Linear regression ( solid lines ) provides lung 18 F-FDG net uptake rate (Ki) and initial volume of distribution (Vdist). For constant plasma levels of 18 F-FDG, the x-axis (normalized time) is identical to true imaging time.](https://storage.googleapis.com/dl.dentistrykey.com/clinical/Analysisof2Fluorine18Fluoro2deoxyDglucoseUptakeKineticsinPETStudiesofPulmonaryInflammation/0_1s20S1076633210006884.jpg)
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Kicorrected=KiVdistnormalVdist K
i
corrected
=
K
i
V
dist
normal
V
dist
where V dist, normal is the V dist found in the lungs of normal subjects (ie, 0.15 mL blood/mL lung). Alternatively, some investigators directly normalized K i by V dist . However, this normalization was found not to contribute to the interpretation of the 18 F-FDG uptake signal during ALI 29 nor to the discrimination between normal subjects and patients with cystic fibrosis . Moreover, there was only a moderate correlation between overall lung density and V dist , and it was argued that differences in V dist were not just dependent on differences in lung inflation . In fact, it is clear that V dist not only reflects extravascular steady-state distribution volume of 18 F-FDG, but also includes the blood volume within the tissue . As an alternative, K i has been normalized by the regional tissue fraction (F tis ) assessed from a PET-acquired transmission scan (ie, by the fraction of the lungs not occupied by air). This approach was found useful to discriminate between normal lungs and those exposed to injurious cyclic hyperinflation . Additionally, in an animal model of smoke inhalation exposure, normalization of K i by F tis did not qualitatively alter the results of increased 18 F-FDG uptake, suggesting that regional metabolic activity increase following smoke inhalation was beyond that expected by a mere change in regional inflation . Normalization by F tis was found to be more relevant during early changes produced by mild endotoxemia and large tidal volume mechanical ventilation .
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![Figure 2, Maps of 2-[fluorine-18]-fluoro-2-deoxy-D-glucose ( 18 F-FDG) net uptake rate (Ki) and of Ki normalized by regional tissue fraction (Ki/Ftis) in a sheep with unilateral exposure to smoke inhalation (9) . The smoke exposed left lung appears on the right side of each panel.](https://storage.googleapis.com/dl.dentistrykey.com/clinical/Analysisof2Fluorine18Fluoro2deoxyDglucoseUptakeKineticsinPETStudiesofPulmonaryInflammation/1_1s20S1076633210006884.jpg)
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Compartmental modeling
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CPET(t)=k1k2k2+k3e−(k2+k3)t⊗CP(t)+k1k3k2+k3∫CP(t)dt+VBCP(t) C
PET
(
t
)
=
k
1
k
2
k
2
+
k
3
e
−
(
k
2
+
k
3
)
t
⊗
C
P
(
t
)
+
k
1
k
3
k
2
+
k
3
∫
C
P
(
t
)
dt
+
V
B
C
P
(
t
)
where ⊗ is the convolution operator; V B is pulmonary blood volume in units of “mL blood/mL lung;” the rate constant k 1 describes blood-to-tissue transfer of 18 F-FDG in units of “mL blood/mL lung/minute;” k 2 is the rate of 18 F-FDG diffusion back from tissue into the blood in units of “1/minute;” and k 3 describes the rate of 18 F-FDG phosphorylation by hexokinase in units of “1/minute.” These parameters are estimated by fitting C PET (t) and C P (t) to Equation 4 (eg, with iterative, nonlinear curve fitting algorithms) . Basic assumptions of Sokoloff’s model are that 1) the entire unbound tracer is present in a single compartment acting as precursor pool for the hexokinase reaction, 2) regional glucose metabolism is in a steady state, and that 3) after its phosphorylation the tracer is effectively trapped in the tissue .
![Figure 3, Compartmental models of 2-[fluorine-18]-fluoro-2-deoxy-D-glucose ( 18 F-FDG) tissue kinetics. (a) Sokoloff’s three-compartment model (34) , accounting for 18 F-FDG in blood plasma (CP(t)), for the extravascular 18 F-FDG precursor pool for phosphorylation (CE(t)), and for concentration of 18 F-FDG-6-phosphate (CM(t)), which is irreversibly trapped in the tissue. (b) Four-compartment model of pulmonary 18 F-FDG kinetics during acute lung injury (36) , comprising an extravascular/noncellular (“edema”) compartment for 18 F-FDG that is not an immediate precursor for hexokinase (CEE(t)). k1 = blood-to-tissue 18 F-FDG transfer rate; k2 = tissue-to-blood transfer rate of 18 F-FDG; k3 = rate of 18 F-FDG phosphorylation; k5 and k6 = forward and backward transfer rates of 18 F-FDG between precursor pool and extravascular/noncellular compartment.](https://storage.googleapis.com/dl.dentistrykey.com/clinical/Analysisof2Fluorine18Fluoro2deoxyDglucoseUptakeKineticsinPETStudiesofPulmonaryInflammation/2_1s20S1076633210006884.jpg)
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![Figure 4, Compartmental model curve fits of pulmonary 2-[fluorine-18]-fluoro-2-deoxy-D-glucose ( 18 F-FDG) kinetics in the smoke exposed lung depicted in Figure 2 . At t = 0, a bolus of 10 mCi of 18 F-FDG was injected. (a) Curve fit achieved with the traditional Sokoloff model according to Figure 3 a, showing a poor model fit during the early phase following tracer bolus injection. (b) Curfe fit achieved with the lung-specific model according to Figure 3 b. CPET(t) = positron emission tomography-acquired tissue time-activity curve ( heavy line ); Cmodel(t) = model-generated curfe fit; VB = blood volume (mL blood/mL lung).](https://storage.googleapis.com/dl.dentistrykey.com/clinical/Analysisof2Fluorine18Fluoro2deoxyDglucoseUptakeKineticsinPETStudiesofPulmonaryInflammation/3_1s20S1076633210006884.jpg)
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Conclusions
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