Measured Time-activity Curves Research Articles

A Scintigraphic Method for Quantitation of Lymphatic Function in Arm Lymphedema.

Lymphoscintigraphy is commonly used to assess breast cancer-related lymphedema. However, a reliable quantitative method that clearly distinguishes normal lymphatic function from lymphedema is desired. We propose a quantitative method based upon the physiological mean transit time (MTT) measure of lymph fluid passing through the arm. Eleven patients, aged 34-68 years, with unilateral arm lymphedema following breast cancer treatment underwent simultaneous bilateral lymphoscintigraphy using intradermal injection of 99mTc-labeled human serum albumin (HSA). Imaging was performed at 30-45 minute intervals for 5 hours. Time activity curves from each injection site and each arm region were recorded. The input into the arm region was obtained as the (minus) time derivative of the injection site activity curve. In the proposed model the arm activity curve was considered to arise from the convolution of the retention function and the input function. The retention function was obtained by fitting the calculated arm activity curve to the measured arm activity curve. The MTT of activity passing through the arm was calculated as the time integral of the resulting retention function. All measured time activity curves were well described by the model. The MTT of the lymphedema arm (mean 60.1 minutes, range 22-105 minutes) was markedly different from that of the contralateral normal arm (mean 5.4 minutes, range 1.2-8.7 minutes), p < 0.0001. The proposed model showed great similarity with measured time activity curves and was capable of quantitatively distinguishing lymphatic function of the lymphedema arm from that of the normal arm in terms of calculated MTT.

A hybrid deconvolution approach for estimation of in vivo non-displaceable binding for brain PET targets without a reference region.

Background and aimEstimation of a PET tracer’s non-displaceable distribution volume (VND) is required for quantification of specific binding to its target of interest. VND is generally assumed to be comparable brain-wide and is determined either from a reference region devoid of the target, often not available for many tracers and targets, or by imaging each subject before and after blocking the target with another molecule that has high affinity for the target, which is cumbersome and involves additional radiation exposure. Here we propose, and validate for the tracers [11C]DASB and [11C]CUMI-101, a new data-driven hybrid deconvolution approach (HYDECA) that determines VND at the individual level without requiring either a reference region or a blocking study.MethodsHYDECA requires the tracer metabolite-corrected concentration curve in blood plasma and uses a singular value decomposition to estimate the impulse response function across several brain regions from measured time activity curves. HYDECA decomposes each region’s impulse response function into the sum of a parametric non-displaceable component, which is a function of VND, assumed common across regions, and a nonparametric specific component. These two components differentially contribute to each impulse response function. Different regions show different contributions of the two components, and HYDECA examines data across regions to find a suitable common VND. HYDECA implementation requires determination of two tuning parameters, and we propose two strategies for objectively selecting these parameters for a given tracer: using data from blocking studies, and realistic simulations of the tracer. Using available test-retest data, we compare HYDECA estimates of VND and binding potentials to those obtained based on VND estimated using a purported reference region.ResultsFor [11C]DASB and [11C]CUMI-101, we find that regardless of the strategy used to optimize the tuning parameters, HYDECA provides considerably less biased estimates of VND than those obtained, as is commonly done, using a non-ideal reference region. HYDECA test-retest reproducibility is comparable to that obtained using a VND determined from a non-ideal reference region, when considering the binding potentials BPP and BPND.ConclusionsHYDECA can provide subject-specific estimates of VND without requiring a blocking study for tracers and targets for which a valid reference region does not exist.

Quantitative PET image reconstruction employing nested expectation-maximization deconvolution for motion compensation

Bulk body motion may randomly occur during PET acquisitions introducing blurring, attenuation-emission mismatches and, in dynamic PET, discontinuities in the measured time activity curves between consecutive frames. Meanwhile, dynamic PET scans are longer, thus increasing the probability of bulk motion. In this study, we propose a streamlined 3D PET motion-compensated image reconstruction (3D-MCIR) framework, capable of robustly deconvolving intra-frame motion from a static or dynamic 3D sinogram. The presented 3D-MCIR methods need not partition the data into multiple gates, such as 4D MCIR algorithms, or access list-mode (LM) data, such as LM MCIR methods, both associated with increased computation or memory resources. The proposed algorithms can support compensation for any periodic and non-periodic motion, such as cardio-respiratory or bulk motion, the latter including rolling, twisting or drifting. Inspired from the widely adopted point-spread function (PSF) deconvolution 3D PET reconstruction techniques, here we introduce an image-based 3D generalized motion deconvolution method within the standard 3D maximum-likelihood expectation-maximization (ML-EM) reconstruction framework. In particular, we initially integrate a motion blurring kernel, accounting for every tracked motion within a frame, as an additional MLEM modeling component in the image space (integrated 3D-MCIR). Subsequently, we replaced the integrated model component with a nested iterative Richardson-Lucy (RL) image-based deconvolution method to accelerate the MLEM algorithm convergence rate (RL-3D-MCIR). The final method was evaluated with realistic simulations of whole-body dynamic PET data employing the XCAT phantom and real human bulk motion profiles, the latter estimated from volunteer dynamic MRI scans. In addition, metabolic uptake rate Ki parametric images were generated with the standard Patlak method. Our results demonstrate significant improvement in contrast-to-noise ratio (CNR) and noise-bias performance in both dynamic and parametric images. The proposed nested RL-3D-MCIR method is implemented on the Software for Tomographic Image Reconstruction (STIR) open-source platform and is scheduled for public release.

Direct Parametric Reconstruction Using Anatomical Regularization for Simultaneous PET/MRI Data.

Pharmacokinetic analysis of dynamic positron emission tomography (PET) imaging data maps the measured time activity curves to a set of model-specific pharmacokinetic parameters. Voxel-based parameter estimation via curve fitting is conventionally performed indirectly on a sequence of independently reconstructed PET images, leading to high variance and bias in the parametric images. We propose a direct parametric reconstruction algorithm with raw projection data as input that leverages high-resolution anatomical information simultaneously obtained from magnetic resonance (MR) imaging in a PET/MRI scanner for regularization. The reconstruction problem is formulated in a flexible Bayesian framework with Gaussian Markov Random field modeling of activity, parameters, or both simultaneously. MR information is incorporated through a Bowsher-like prior function. Optimization transfer using an expectation-maximization surrogate and a new Bowsher-like penalty surrogate is applied to obtain a voxel-separable algorithm that interleaves a reconstruction with a fitting step. An analytical input function model is used. The algorithm is evaluated on simulated [(18)F]FDG and clinical [(18)F]FET brain data acquired with a Biograph mMR. The results indicate that direct and simultaneously regularized parametric reconstruction increases image quality. Anatomical regularization leads to higher contrast than conventional distance-weighted regularization.

Improved modeling of in vivo kinetics of slowly diffusing radiotracers for tumor imaging.

Large-molecule tracers, such as labeled antibodies, have shown success in immuno-PET for imaging of specific cell surface biomarkers. However, previous work has shown that localization of such tracers shows high levels of heterogeneity in target tissues, due to both the slow diffusion and the high affinity of these compounds. In this work, we investigate the effects of subvoxel spatial heterogeneity on measured time-activity curves in PET imaging and the effects of ignoring diffusion limitation on parameter estimates from kinetic modeling. Partial differential equations (PDE) were built to model a radially symmetric reaction-diffusion equation describing the activity of immuno-PET tracers. The effects of slower diffusion on measured time-activity curves and parameter estimates were measured in silico, and a modified Levenberg-Marquardt algorithm with Bayesian priors was developed to accurately estimate parameters from diffusion-limited data. This algorithm was applied to immuno-PET data of mice implanted with prostate stem cell antigen-overexpressing tumors and injected with (124)I-labeled A11 anti-prostate stem cell antigen minibody. Slow diffusion of tracers in linear binding models resulted in heterogeneous localization in silico but no measurable differences in time-activity curves. For more realistic saturable binding models, measured time-activity curves were strongly dependent on diffusion rates of the tracers. Fitting diffusion-limited data with regular compartmental models led to parameter estimate bias in an excess of 1,000% of true values, while the new model and fitting protocol could accurately measure kinetics in silico. In vivo imaging data were also fit well by the new PDE model, with estimates of the dissociation constant (Kd) and receptor density close to in vitro measurements and with order of magnitude differences from a regular compartmental model ignoring tracer diffusion limitation. Heterogeneous localization of large, high-affinity compounds can lead to large differences in measured time-activity curves in immuno-PET imaging, and ignoring diffusion limitations can lead to large errors in kinetic parameter estimates. Modeling of these systems with PDE models with Bayesian priors is necessary for quantitative in vivo measurements of kinetics of slow-diffusion tracers.

Model-independent plot of dynamic PET data facilitates data interpretation and model selection

When testing new PET radiotracers or new applications of existing tracers, the blood–tissue exchange and the metabolism need to be examined. However, conventional plots of measured time–activity curves from dynamic PET do not reveal the inherent kinetic information. A novel model-independent volume–influx plot (vi-plot) was developed and validated. The new vi-plot shows the time course of the instantaneous distribution volume and the instantaneous influx rate. The vi-plot visualises physiological information that facilitates model selection and it reveals when a quasi-steady state is reached, which is a prerequisite for the use of the graphical analyses by Logan and Gjedde–Patlak. Both axes of the vi-plot have direct physiological interpretation, and the plot shows kinetic parameter in close agreement with estimates obtained by non-linear kinetic modelling. The vi-plot is equally useful for analyses of PET data based on a plasma input function or a reference region input function. The vi-plot is a model-independent and informative plot for data exploration that facilitates the selection of an appropriate method for data analysis.

Lack of association between 11C-PiB and longitudinal brain atrophy in non-demented older individuals

Amyloid-β plaques (Aβ) are a hallmark of Alzheimer's disease (AD), begin deposition decades before the incipient disease, and are thought to be associated with neuronal loss, brain atrophy and cognitive impairment. We examine associations between (11)C-PiB-PET measurement of Aβ burden and brain volume changes in the preceding years in 57 non-demented individuals (age 64-86; M=78.7). Participants were prospectively followed through the Baltimore Longitudinal Study of Aging, with up to 10 consecutive MRI scans (M=8.1) and an (11)C-PiB scan approximately 10 years after the initial MRI. Linear mixed effects models were used to determine whether mean cortical (11)C-PiB distribution volume ratios, estimated by fitting a reference tissue model to the measured time activity curves, were associated with longitudinal regional brain volume changes of the whole brain, ventricular CSF, frontal, temporal, parietal, and occipital white and gray matter, the hippocampus, orbito-frontal cortex, and the precuneus. Despite significant longitudinal declines in the volumes of all investigated regions (p<0.05), no associations were detected between current Aβ burden and regional brain volume decline trajectories in the preceding years, nor did the regional volume trajectories differ between those with highest and lowest Aβ burden. Consistent with a threshold model of disease, our findings suggest that Aβ load does not seem to affect brain volume changes in individuals without dementia.

Longitudinal cognitive decline is associated with fibrillar amyloid-beta measured by [ 11 C]PiB

To investigate whether longitudinal declines in cognition are associated with higher fibrillar amyloid-beta (Abeta) deposition in vivo in individuals without dementia. [(11)C]PiB images were obtained to measure fibrillar Abeta burden in 57 participants without dementia from the Baltimore Longitudinal Study of Aging. Participants (33 men, 24 women) had a mean (SD) age of 78.7 (6.2) years. Six participants (4 men, 2 women) had mild cognitive impairment defined as Clinical Dementia Rating = 0.5. To measure [(11)C]PiB retention, distribution volume ratios (DVR) for 15 regions of interest were estimated by fitting a simplified reference tissue model to the measured time activity curves. Mixed effects regression was used to predict cognitive trajectories over time using data before and including time of PiB (mean follow-up 10.8 years), with mean cortical DVR, age at baseline, sex, and education as independent predictors. Voxel-based analysis identified local associations. [(11)C]PiB retention was higher in older individuals. Greater declines over time in mental status and verbal learning and memory, but not visual memory, were associated significantly with higher PiB retention. Voxel-based analysis showed significant associations in frontal and lateral temporal regions. Higher Abeta deposition is associated with greater longitudinal decline in mental status and verbal memory in the preceding years. The differential association for verbal but not visual memory may reflect the greater reliance of verbal word list learning on prefrontal regions, which show early Abeta deposition. Prospective imaging may help distinguish between individuals with evolving neuropathology who develop accelerated cognitive decline vs those with normal aging.

Off-line motion correction methods for multi-frame PET data

PurposePatient motion during PET acquisition may affect measured time-activity curves, thereby reducing accuracy of tracer kinetic analyses. The aim of the present study was to evaluate different off-line frame-by-frame methods to correct patient motion, which is of particular interest when no optical motion tracking system is available or when older data sets have to be reanalysed.MethodsFour different motion correction methods were evaluated. In the first method attenuation-corrected frames were realigned with the summed image of the first 3 min. The second method was identical, except that non-attenuation-corrected images were used. In the third and fourth methods non-attenuation-corrected images were realigned with standard and cupped transmission images, respectively. Two simulation studies were performed, based on [11C]flumazenil and (R)-[11C]PK11195 data sets, respectively. For both simulation studies different types (rotational, translational) and degrees of motion were added. Simulated PET scans were corrected for motion using all correction methods. The optimal method derived from these simulation studies was used to evaluate two (one with and one without visible movement) clinical data sets of [11C]flumazenil, (R)-[11C]PK11195 and [11C]PIB. For these clinical data sets, the volume of distribution (VT) was derived using Logan analysis and values were compared before and after motion correction.ResultsFor both [11C]flumazenil and (R)-[11C]PK11195 simulation studies, optimal results were obtained when realignment was based on non-attenuation-corrected images. For the clinical data sets motion disappeared visually after motion correction. Regional differences of up to 433% in VT before and after motion correction were found for scans with visible movement. On the other hand, when no visual motion was present in the original data set, overall differences in VT before and after motion correction were <1.5 ± 1.3%.ConclusionFrame-by-frame motion correction using non-attenuation-corrected images improves the accuracy of tracer kinetic analysis compared to non-motion-corrected data.Electronic supplementary materialThe online version of this article (doi:10.1007/s00259-009-1193-y) contains supplementary material, which is available to authorised users.

Longitudinal Cerebral Blood Flow and Amyloid Deposition: An Emerging Pattern?

Although cerebral amyloid deposition may precede cognitive impairment by decades, the relationship between amyloid deposition and longitudinal change in neuronal function has not, to our knowledge, been studied. The aim of this article was to determine whether individuals without dementia with high and low amyloid burden show different patterns of longitudinal regional cerebral blood flow (rCBF) changes in the years preceding measurement of amyloid deposition. Twenty-eight participants without dementia (mean age+/-SD, 82.5+/-4.8 y; 6 mildly impaired) from the Baltimore Longitudinal Study of Aging underwent yearly resting-state (15)O-H(2)O PET scans for up to 8 y. (11)C-PIB images of amyloid deposition were acquired on average 10.8+/-0.8 y after the first CBF scan. (11)C-PIB distribution volume ratios of regions of interest were estimated by fitting a reference-tissue model to the measured time-activity curves. On the basis of mean cortical distribution volume ratios, participants were divided into groups with high or low (11)C-PIB retention. Differences in longitudinal rCBF changes between high- and low-(11)C-PIB groups were investigated by voxel-based analysis. Longitudinal rCBF changes differed significantly between high- (n=10) and low- (n=18) (11)C-PIB groups (P <or= 0.001). Greater longitudinal decreases in rCBF in the high-(11)C-PIB group than in the low-(11)C-PIB group were seen in right anterior to middle cingulate, right supramarginal gyrus, left thalamus, and midbrain bilaterally. Greater increases in rCBF over time in the high-(11)C-PIB group were found in left medial and inferior frontal gyri, right precuneus, left inferior parietal lobule, and left postcentral gyrus. In this group of older adults without dementia, those with high (11)C-PIB show greater longitudinal declines in rCBF in certain areas, representing regions with greater decrements in neuronal function. Greater longitudinal increases in rCBF are also observed in those with higher amyloid load and may represent an attempt to preserve neuronal function in these regions.

Dynamic Small-Animal PET Imaging of Tumor Proliferation with 3′-Deoxy-3′-18F-Fluorothymidine in a Genetically Engineered Mouse Model of High-Grade Gliomas

3'-Deoxy-3'-(18)F-fluorothymidine ((18)F-FLT), a partially metabolized thymidine analog, has been used in preclinical and clinical settings for the diagnostic evaluation and therapeutic monitoring of tumor proliferation status. We investigated the use of (18)F-FLT for detecting and characterizing genetically engineered mouse (GEM) high-grade gliomas and evaluating the pharmacokinetics in GEM gliomas and normal brain tissue. Our goal was to develop a robust and reproducible method of kinetic analysis for the quantitative evaluation of tumor proliferation. Dynamic (18)F-FLT PET imaging was performed for 60 min in glioma-bearing mice (n = 10) and in non-tumor-bearing control mice (n = 4) by use of a dedicated small-animal PET scanner. A 3-compartment, 4-parameter model was used to characterize (18)F-FLT kinetics in vivo. For compartmental analysis, the arterial input was measured by placing a region of interest over the left ventricular blood pool and was corrected for partial-volume averaging. The (18)F-FLT "trapping" and tissue flux model parameters were correlated with measured uptake (percentage injected dose per gram [%ID/g]) values at 60 min. (18)F-FLT uptake values (%ID/g) at 1 h in brain tumors were significantly greater than those in control brains (mean +/- SD: 4.33 +/- 0.58 and 0.86 +/- 0.22, respectively; P < 0.0004). Kinetic analyses of the measured time-activity curves yielded independent, robust estimates of tracer transport and metabolism, with compartmental model-derived time-activity data closely fitting the measured data. Except for tracer transport, statistically significant differences were found between the applicable model parameters for tumors and normal brains. The tracer retention rate constant strongly correlated with measured (18)F-FLT uptake values (r = 0.85, P < 0.0025), whereas a more moderate correlation was found between net (18)F-FLT flux and (18)F-FLT uptake values (r = 0.61, P < 0.02). A clinically relevant mouse glioma model was characterized by both static and dynamic small-animal PET imaging of (18)F-FLT uptake. Time-activity curves were kinetically modeled to distinguish early transport from a subsequent tracer retention phase. Estimated (18)F-FLT rate constants correlated positively with %ID/g measurements. Dynamic evaluation of (18)F-FLT uptake offers a promising approach for noninvasively assessing cellular proliferation in vivo and for quantitatively monitoring new antiproliferation therapies.

Cerebral haemodynamics during hypo- and hypercapnia

Transcranial Doppler sonography (TCD) is increasingly used in cerebrovascular disease for monitoring brain perfusion. It allows estimation of cerebral blood flow (CBF) by the measurement of cerebral blood flow velocity (CBFV). The CBFV as well as CBF are intimately associated with the intravascular CO2-concentration. Thus, hyper- or hypocapnia can be used to induce a defined range of blood flows. The aim of our study was the comparison of vasomotor reactivity assessed with simultaneous TCD and quantitative regional CBF-measurements (rCBF) by PET (serving as the reference method for in-vivo quantification of rCBF). Six healthy young volunteers participated in this study. CBF was measured using 15O-butanol PET. A flow and dispersion-model was fitted to the measured time activity curves using arterial input curves. Each subject underwent five scans at five different end-tidal CO2 levels (EtCO2): 25, 32, 40, 48, and 55 mmHg. CBFV was assessed by continuous bilateral TCD of the middle cerebral artery (MCA). Volumes of interest for rCBF determination were placed in grey matter of the prefrontal cortex (PFC) as determined from individual MRIs. Comparisons between the rCBF, EtCO2 and CBFV were carried out with regression and correlation analysis and paired t-tests. Strong positive linear correlations of rCBF and CBFV with the CO2-concentration and linear relationships between rCBF and CBFV were found in each individual. Normalised CO2-reactivities measured by TCD and PET were closely correlated. TCD-measurements of vascular reactivity in healthy volunteers show a high correlation to those acquired with PET that serves as the reference method of quantitative rCBF-measurement. The results of the MCA insonation are a close approximation of the rCBF changes induced by variations of EtCO2.

Comparison of two methods for correction of partial volume effects in PET

The low spatial resolution of PET scanners results in partial volume (PV) effects which limit the accurate quantification in anatomical structures such as the cerebral cortex and subcortical regions. Several correction methods have been proposed to deal with these effects. In a first study 1, using simulated data, we compared the PV correction of some cortical regions, obtained with i) the correction algorithm implemented at the Research Center Juelich (PVC-J) and ii) the one implemented at the Brain Imaging Centre of Montreal (PVC-M). Here, still using simulated data, the impact of mis-registration between the PET and the anatomical data on accuracy of the correction, as well as the correction of real dynamic PET data are presented. The PVC-J algorithm - based on the work of Muller-Gartner - has a fully 3D implementation. The resulting corrected grey matter (GM) activity images are obtained by dividing voxel-wise the uncorrected GM images (without white matter contribution) by the GM probability map, derived from the convolution of the corresponding MR segmented image by a 3D spatially variant gaussian function, which reproduces the actual PET image resolution. The PVC-M algorithm - based on the work of Rousset - accounts for the mutual PV effects between any possible tissue structure. After tissue classification of the high resolution MR data, cerebral structures of interest are chosen. Each structure is convolved with a spatially invariant 3D gaussian kernel yielding a set of 3D probability maps, from which recovery and cross-contamination factors are computed. Measured time-activity curves are finally corrected using the correction factor set. A PET dynamic acquisition of an adenosin receptor study was first corrected by both methods and furthermore used to build simulated dynamic data 1 which were translated and rotated by 1 & 2 mm and 1 & 2 degrees, respectively, with respect to the simulated MR image. In case of real data, the mean recovery factor over the dynamic data (6–90 min) of GM is 1.360.05 for PVC-M and 1.410.01 for PVC-J, while in the thalamus region it is 1.170.03 for PVC-M and 1.220.02 for PVC-J. For the mismatched data, the relative difference between the corrected activity values, obtained with the two correction algorithms, and the references was compared. In all but the rotation about the z-axis case, the results are highly consistent. For the rotations about the z axis, the values given by PVC-M and PVC-J show a difference up to about 2.0%. Furthermore, some curves show an instability in the values during the last 30 minutes of the dynamic series, independent from region, mismatch, and method. In this time period the receptor data are affected by lower statistics and low signal-to-contrast ratio. As in the first comparison study, the presented data show an overall high consistency of the results obtained from the two different methods concerning the adenosine receptor. Some of the observed discrepancies could result from the ways the time activity curves are computed with both correction algorithms.

Evidence for reduced arterial plasma input, prolonged lung retention and reduced lung monoamine oxidase in smokers

We have previously found that smokers have reduced brain monoamine oxidase (MAO) A and B using positron emission tomography (PET) and the irreversible mechanism-based radiotracers [ 11C]-labeled clorgyline (CLG) and deprenyl (DEP) and their deuterated analogs (D CLG, D DEP). More recently, we have estimated MAO A and B activity in other organs using the deuterium isotope effect to determine binding specificity for MAO and a three-compartment model to estimate k 3, the model term proportional to MAO A activity. Here, we have investigated the robustness of the model term k 3 for estimating lung MAO A and B in light of our unexpected finding that lung MAO activity ( k 3) was reduced for smokers relative to nonsmokers, although radiotracer uptake in the lungs was similar at peak and plateau for the two groups. Methods Time–activity data from lung and arterial plasma were used from seven nonsmokers and seven smokers scanned previously with CLG and D CLG, and five nonsmokers and nine smokers scanned previously with DEP and D DEP. The measured time–activity curves for lung and plasma and the integrals for the arterial plasma time–activity curves were compared at an early time point (2.5 min) and at the end of the study (55 min). A three-compartment irreversible model was used to estimate the differences between smokers and nonsmokers, and the stability of the parameter ( k 3) while varying model assumptions for the relative fractions of lung tissue, blood and air in the PET voxel. Results The peak in the arterial plasma input function and the integral of the arterial plasma time–activity curve over the first 2.5 min after radiotracer injection were significantly lower for smokers relative to nonsmokers for all four tracers. However, although the peak and plateau of the lung time–activity curves were similar for smokers and nonsmokers, the decline in radioactivity from peak to plateau was slower for smokers for all tracers. Using a three-compartment irreversible model, we estimated the ratio of MAO subtypes A and B in normal lung tissue to be on the order of 3 to 1 (MAO A to B) and that smokers have reduced MAO levels for both subtypes as measured by the model parameter, k 3. The values of k 3 are insensitive to model assumptions of variations in air and tissue fraction in the PET voxel. Most of the effects of changes in these fractions are absorbed into the parameter K 1, which governs the plasma-to-tissue transfer of tracer and is a function of blood flow. K 1 was found to be larger in smokers, although the values depend upon model assumptions of air and tissue fractions. k 3 was found to be significantly lower in smokers; for CLG, a 50% reduction in MAO A for both CLG and D CLG was observed. For DEP, k 3 was also significantly lower in smokers with a reduction of ∼80% in lung MAO B, although there was a very large coefficient of variation in the smoker's k 3. We also found larger values of λ ( K 1/ k 2) for smokers relative to nonsmokers for all tracers consistent with a longer lung retention of the nonenzyme-bound tracer, which explains the slower decline in uptake from peak radioactivity for smokers. Conclusions The measured arterial input function values for smokers and nonsmokers are significantly different for these two tracer pairs for nonsmokers and smokers particularly for the first few minutes after radiotracer injection. Model estimates of k 3 that indicate that smokers have lower lung MAO A and B activity than nonsmokers are robust and insensitive to variations in model assumptions for relative fractions of lung tissue, blood and air in the PET voxel. Although we have only investigated the behavior of [ 11C]clorgyline and [ 11C] l-deprenyl and their deuterium-substituted analogs in this report, the extent to which reduced arterial input and longer lung retention also hold for other tracers for subjects who smoke merits investigation.