Quantification of fatty acid uptake with [1-11C]palmitate PET
Palmitate is a physiological substrate of the heart, kidneys, and other organs, and labelling it with 11C does not change its biochemical properties. Palmitate, like the other non-esterified fatty acids (NEFA), are activated in cytosol to acyl-coenzyme A (acyl-CoA) units by acyl-CoA synthetase, which are then transported into the mitochondria for oxidation, or esterified to neutral lipids and phospholipids. [1-11C]palmitate that enters the mitochondria for β-oxidation releases the radionuclide as [11C]CO2. 11C-labelled esterified lipids remain in the tissue during the PET study, except in the liver and intestine, which release the triglycerides (TG) into the circulation.
Whole body [11C]palmitate clearance has been used to calculate fatty acid flux.
Quantification of β-oxidation or lipid synthesis in tissue requires the measurement of proper input function, and consideration of 11C carrying metabolites of 11C-palmitate in arterial plasma and in the tissue.
[11C]CO2 (and [11C]HCO3-) are produced by peripheral and local metabolism of [11C]palmitate. [11C]CO2 readily enters all tissues and approaches a transient equilibrium based on the difference between tissue and plasma pH (Brooks et al., 1984). Concentration of [11C]CO2 in plasma or blood must be measured or estimated and subtracted from the input curve. Also its contribution to tissue radioactivity must be accounted for. In healthy subjects and subjects with type 2 diabetes the plasma fractions are similar, enabling the use of population-based metabolite correction; however, the same correction is not applicable during hyperinsulinemic-euglycemic clamp, because of faster decrease of the fraction of unchanged tracer (Christensen et al., 2017). Venous samples have been used for metabolite analysis (Gormsen et al., 2018).
Liver and intestine synthesize triglycerides, containing the labelled 11C-palmitate, and release these to circulation. The appearance of labeled TG represents an additional source of circulating [11C]palmitate since endothelial lipoprotein lipase is present in most peripheral tissues (Guiducci et al., 2006). Therefore the labeled TG concentration in plasma should be included in the input function with the non-esterified 11C-palmitate.
Also 11C bearing urea, lactate, and glucose can be found in tissues and blood. All these things considered, full quantification of 11C-palmitate uptake is very demanding, and therefore simple semiquantitative methods are usually applied.
Heart muscle normally extracts 40-50% of labelled palmitate in a single transit time. The capillary endothelium is a major barrier to the extraction of FFAs.
Myocardial [11C]palmitate PET studies are commonly analyzed by measuring the clearance of [11C] from myocardial regions assuming bi-exponential washout. The faster component correlates with β-oxidation including formation of [11C]-2-acetyl-CoA and production of [11C]CO2 by the tricarboxylic acid (TCA) cycle in the mitochondrial matrix. The slower washout component correlates with incorporation of [11C]palmitate into triglycerides and phospholipids (Schelbert et al., 1986; Grover-McKay et al., 1986).
Bergmann et al (1996) have developed and validated in dogs a four-compartment model for analysis of myocardial [11C]palmitate PET studies for estimation of myocardial fatty acid utilization (MFAU) and myocardial fatty acid oxidation (FMAO). This method requires that blood TAC is measured, [15O]CO2 appearing in blood is measured and subtracted, and that myocardial blood flow (MBF) is determined from a separate [15O]H2O scan. This method has been used e.g. by Herrero et al (2005). Later, de Jong et al (2009) compared several model settings and concluded that a three-tissue compartment model with three fitted parameters is optimal for analysing 11C-palmitate data. This model setting was used by Bucci et al (2011) and Gormsen et al (2017) to estimate free fatty acid esterification, oxidation and uptake rates.
The four-compartment model with five fitted parameters has also been applied to rat studies (Shoghi et al., 2009); method requires that myocardial blood flow is known, and Shoghi et al estimated MBF from a [11C]acetate study; input function was estimated with hybrid-image and blood sampling algorithm (Shoghi & Welch, 2007).
Angsten et al (2005) analyzed their animal (pig) PET data with a simplified approach: Patlak plot was first used to determine [11C]palmitate net influx rate (KT, or Ki) using arterial curve measured from LV region in the image, and myocardial curve from about half a minute to two minutes after injection. Further, a monoexponential function was fitted to blood curve from about one minute to two minutes after injection and was used to extrapolate the blood curve of parent tracer at later time points. Using this extrapolated blood curve and KT, the total amount of extracted tracer at late times was calculated and compared to the measured tissue concentration at the same time (representing the tracer retained in slow turnover compartment) to calculate the fractional oxidative utilization of palmitate.
Suggested analysis method for myocardium
Calculate the [11C]palmitate uptake index (FUR) by dividing the myocardial concentration at 7.5 min (peak value) with the integral of the metabolite corrected plasma curve (Knuuti et al., 2001). Index should then be further multiplied with the concentration of non-esterified fatty acids in plasma.
To estimate [11C]palmitic acid β-oxidation rate, a two-exponential function is fitted to the steepest descent of the myocardial TAC (11-27.5 min) and the clearance rate (1/min) or half-time (t1/2, min) of the faster component is reported (Knuuti et al., 2001).
Tools for these calculations are available in Carimas™.
If compartmental model analysis is preferred, please consult Marco Bucci.
In the brain, about 50-60% of [11C]palmitate is oxidized to produce [11C]CO2 and other hydrophilic metabolites. The rest enters rapidly the stable brain lipid pool (Miller et al., 1987; Chang et al., 1994). Brain preferentially incorporates fatty acids into phosphoglycerides instead of neutral lipids.
A three-compartment model for palmitate incorporation into (rat) brain has been presented by Tabata et al (1988). Simplified method for estimating the rate of incorporation of fatty acids into brain phospholipids and other stable compartments (not β-oxidation rate) was further developed in the study of Robinson et al (1992). Model was also used to analyze monkey brain PET studies (45 min), this time accounting for cerebral blood volume and tissue uptake of metabolite [11C]CO2 (Arai et al., 1995): mean net uptake rates were about 0.0027 ml(min g)-1 in cortical regions and 0.0017 ml(min g)-1 in white matter. However, monkeys were anaesthetized, which in rats reduced brain uptake rate by 40%. VB was 3.5 - 4.8% in cortical regions and 2.2% in white matter (Arai et al., 1995). The same model was applied to monkey [11C]arachidonic acid studies (Chang et al., 1997).
Time delay correction, a different correction method for the brain [11C]CO2, and for partial volume effects were introduced by Giovacchini et al (2002 and 2004) for [11C]arachidonic acid human PET studies; these methods would be applicable to [11C]palmitate studies.
Esterified re-circulating palmitate seems not to make any measurable contribution to (rat) brain uptake (Purdon et al., 1997).
Suggested analysis method
Time-delay between plasma and tissue TACs must be corrected before analysis using fitdelay. If blood TAC has been measured for blood volume correction, it can be corrected for time-delay at the same time.
Preparing the blood curve
Because the fatty acid uptake into the brain is very low, the impact of vascular radioactivity is very high and must be considered in analysis. If blood curve has not been measured, it can be calculated from the total plasma curve (not corrected for metabolites) using p2blood.
Correcting tissue data for [11C]CO2
Before this correction, weights for fitting should be added to the regional tissue data files. This is necessary because the early time frames are usually much shorter (and numerous) than the later frames.
The fractions of [11C]CO2 of the total blood radioactivity have been determined using evaporation method from eight subjects in our laboratory, and the population average of fraction curves and individual total plasma TACs can be used to calculate a good estimate of plasma [11C]CO2 concentration during the PET study using metabcor. This curve is then used as input in calculation of the tissue concentration of [11C]CO2, using one-tissue compartment model and assuming that K1=0.3 mL/(min×mL) and K1/k2=0.43, as suggested by Giovacchini et al. (2002) based on the study of Brooks et al. (1984). This tissue [11C]CO2 curve is then subtracted from the measured regional tissue TACs.
Correction for radioactive metabolites in plasma
In the previous phase, as the plasma [11C]CO2 concentration was calculated using metabcor, also the plasma curve corrected for [11C]CO2 was calculated as well.
However, the evaporation method measured only the fraction of [11C]CO2, not the fraction of other labelled metabolites that appear in plasma at later times. In the relatively long brain [11C]palmitate studies also these metabolites (except labelled TG; Guiducci et al., 2006) have to be subtracted from the plasma curve.
One method to correct for these is to fit a single exponential
function to the descending part of plasma curve, previously
corrected for [11C]CO2, before the appearance of other labelled metabolites
(usually about 15 minutes) and extrapolate the plasma curve after this time using the fitted
exponential function; extrapol can be used for this
purpose with option
Estimation of K
One-tissue compartment model with two parameters,
blood volume fraction, VB and a single rate
constant, K, or K1, are estimated from the metabolite corrected plasma
curves, total blood curve, and [11C]CO2 corrected and weighted tissue curves
using fitk2. Specify the following parameter initial values
and constraints in a file with option
K1_lower := 0 K1_upper := 0.01 K1k2_lower := 0 K1k2_upper := 0 Vb_lower := 0 Vb_upper := 0.75
Carimas™ can be (also) used for doing FUR or K calculations.
Insulin has a strong effect on liver metabolism of [11C]palmitate (Guiducci et al., 2006), suggesting that PET studies with [11C]palmitate and palmitate analogues will provide very interesting insight in regulation of lipid metabolism in liver. Compartmental model has been used to analyze hepatic [11C]palmitate data enabling measurement of hepatic fatty acid uptake, oxidation, storage and triglyceride release rates in pigs and human beings (Iozzo et al., 2010). This method has also been used by Gormsen et al (2018).
More simple analysis methods may also be useful: The results of Yamamura et al (1998) obtained with [1-11C]octanoate suggest that the first component of two-exponential function fit could provide useful information on β-oxidation. DeGrado et al (2000) calculated volume of distribution (VT) from liver PET data, not a [11C]palmitate study, but another tracer (15-[18F]fluoro-3-oxa-pentadecanoate, [18F]FOP) with clearly reversible kinetics, and showed that VT (non-linearly) correlated with [3H]palmitate oxidation rate. Therefore, multiple-time graphical analysis for reversible uptake (Logan plot) with metabolite corrected plasma input might be a usable analysis method for quantitation of [11C]palmitate PET data in liver. Rigazio et al (2008) and Rijzewijk et al (2010) used multiple-time graphical analysis for irreversible uptake (Patlak plot) to calculate the influx rate constant Ki; Patlak line fit was confined to 3-10 min after tracer administration (Rijzewijk et al., 2010). Gormsen et al (2018), using metabolite corrected plasma input, used the standard Patlak plot, and also Patlak plot with kloss.
In human studies, BTACs from both hepatic artery and portal vein could be measured from image, and were converted to PTACs and corrected for metabolites, based on fractions measured from venous samples (Gormsen et al., 2018).
- PET imaging of fatty acid metabolism
- Quantification of fatty acid uptake with [18F]FTHA
- Metabolite correction
- Compartmental models
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Updated at: 2018-12-09
Created at: 2007-04-20
Written by: Vesa Oikonen