Jeih-San Liow

Linearized Reference Tissue Parametric Imaging Methods: Application to [11C]DASB Positron Emission Tomography Studies of the Serotonin Transporter in Human Brain:

The authors developed and applied two new linearized reference tissue models for parametric images of binding potential (BP) and relative delivery (R1) for [11C]DASB positron emission tomography imaging of serotonin transporters in human brain. The original multilinear reference tissue model (MRTMO) was modified (MRTM) and used to estimate a clearance rate (k′2) from the cerebellum (reference). Then, the number of parameters was reduced from three (MRTM) to two (MRTM2) by fixing k′2. The resulting BP and R1 estimates were compared with the corresponding nonlinear reference tissue models, SRTM and SRTM2, and one-tissue kinetic analysis (1TKA), for simulated and actual [11C]DASB data. MRTM gave k′2 estimates with little bias (<1%) and small variability (<6%). MRTM2 was effectively identical to SRTM2 and 1TKA, reducing BP bias markedly over MRTMO from 12–70% to 1–4% at the expense of somewhat increased variability. MRTM2 substantially reduced BP variability by a factor of two or three over MRTM or SRTM. MRTM2, SRTM2, and 1TKA had R1 bias <0.3% and variability at least a factor of two lower than MRTM or SRTM. MRTM2 allowed rapid generation of parametric images with the noise reductions consistent with the simulations. Rapid parametric imaging by MRTM2 should be a useful method for human [11C]DASB positron emission tomography studies.

Qualitative and quantitative evaluation of six algorithms for correcting intensity nonuniformity effects.

The desire to correct intensity nonuniformity in magnetic resonance images has led to the proliferation of nonuniformity-correction (NUC) algorithms with different theoretical underpinnings. In order to provide end users with a rational basis for selecting a given algorithm for a specific neuroscientific application, we evaluated the performance of six NUC algorithms. We used simulated and real MRI data volumes, including six repeat scans of the same subject, in order to rank the accuracy, precision, and stability of the nonuniformity corrections. We also compared algorithms using data volumes from different subjects and different (1.5T and 3.0T) MRI scanners in order to relate differences in algorithmic performance to intersubject variability and/or differences in scanner performance. In phantom studies, the correlation of the extracted with the applied nonuniformity was highest in the transaxial (left-to-right) direction and lowest in the axial (top-to-bottom) direction. Two of the six algorithms demonstrated a high degree of stability, as measured by the iterative application of the algorithm to its corrected output. While none of the algorithms performed ideally under all circumstances, locally adaptive methods generally outperformed nonadaptive methods.

Persistent Dopamine Functions of Neurons Derived from Embryonic Stem Cells in a Rodent Model of Parkinson Disease

The derivation of dopamine neurons is one of the best examples of the clinical potential of embryonic stem (ES) cells, but the long‐term function of the grafted neurons has not been established. Here, we show that, after transplantation into an animal model, neurons derived from mouse ES cells survived for over 32 weeks, maintained midbrain markers, and had sustained behavioral effects. Microdialysis in grafted animals showed that dopamine (DA) release was induced by depolarization and pharmacological stimulants. Positron emission tomography measured the expression of presynaptic dopamine transporters in the graft and also showed that the number of postsynaptic DA D2 receptors was normalized in the host striatum. These data suggest that ES cell‐derived neurons show DA release and reuptake and stimulate appropriate postsynaptic responses for long periods after implantation. This work supports continued interest in ES cells as a source of functional DA neurons.

Design of a motion-compensation OSEM list-mode algorithm for resolution-recovery reconstruction for the HRRT

The HRRT PET system has the potential to produce human brain images with resolution better than 3 mm. To achieve the best possible accuracy and precision, we have designed MOLAR, a motion-compensation OSEM list-mode algorithm for resolution-recovery reconstruction on a computer cluster with the following features: direct use of list mode data with dynamic motion information (Polaris); exact reprojection of each line-of- response (LOR); system matrix computed from voxel-to-LOR distances (radial and axial); spatially varying resolution model implemented for each event by selection from precomputed line spread functions based on factors including detector obliqueness, crystal layer, and block detector position; distribution of events to processors and to subsets based on order of arrival; removal of voxels and events outside a reduced field-of-view defined by the attenuation map; no pre-corrections to Poisson data, i.e., all physical effects are defined in the model; randoms estimation from singles; model-based scatter simulation incorporated into the iterations; and component-based normalization. Preliminary computation estimates suggest that reconstruction of a single frame in one hour is achievable. Careful evaluation of this system will define which factors play an important role in producing high resolution, low-noise images with quantitative accuracy.

Quantitative comparisons of image registration techniques based on high-resolution MRI of the brain.

Objective A variety of methods for matching intrasubject MRI-MRI, PET-PET, or MRI-PET image pairs have been proposed. Based on the rigid body transformations needed to align pairs of high-resolution MRI scans and/or simulated PET scans (derived from these MRI scans), we obtained general comparisons of four intrasubject image registration techniques: Talairach coordinates, head and hat, equivalent internal points, and ratio image uniformity. In addition, we obtained a comparison of stereotaxic Z frames with a customized head mold for MRI-MRI image pairs. Materials and Methods and Results Each technique was quantitatively evaluated using the mean and maximum voxel registration errors for matched voxel pairs within the brain volumes being registered. Conclusion We conclude that fiducial markers such as stereotaxic Z frames that are not rigidly fixed to a patients skull are inaccurate compared with other registration techniques, Talairach coordinate transformations provide surprisingly good registration, and minimizing the variance of MRI-MRI, PET-PET, or MRI-PET ratio images provides significantly better registration than all other techniques tested. Registration optimization based on measurement of the similarity of spatial distributions of voxel values is superior to techniques that do not use such information.

Imaging Neuroinflammation in Alzheimer's Disease with Radiolabeled Arachidonic Acid and PET

Incorporation coefficients (K*) of arachidonic acid (AA) in the brain are increased in a rat model of neuroinflammation, as are other markers of AA metabolism. Data also indicate that neuroinflammation contributes to Alzheimers disease (AD). On the basis of these observations, K* for AA was hypothesized to be elevated in patients with AD. Methods: A total of 8 patients with AD with an average (±SD) Mini-Mental State Examination score of 14.7 ± 8.4 (mean age, 71.7 ± 11.2 y) and 9 controls with a normal Mini-Mental State Examination score (mean age, 68.7 ± 5.6 y) were studied. Each subject received a 15O-water PET scan of regional cerebral blood flow, followed after 15 min by a 1-11C-AA scan of regional K* for AA. Results: In the patients with AD, compared with control subjects, global gray matter K* for AA (corrected or uncorrected for the partial-volume error [PVE]) was significantly elevated, whereas only PVE-uncorrected global cerebral blood flow was reduced significantly (P < 0.05). A false-discovery-rate procedure indicated that PVE-corrected K* for AA was increased in 78 of 90 identified hemispheric gray matter regions. PVE-corrected regional cerebral blood flow, although decreased in 12 regions at P < 0.01 by an unpaired t test, did not survive the false-discovery-rate procedure. The surviving K* increments were widespread in the neocortex but were absent in caudate, pallidum, and thalamic regions. Conclusion: These preliminary results show that K* for AA is widely elevated in the AD brain, particularly in regions reported to have high densities of senile (neuritic) plaques with activated microglia. To the extent that the elevations represent upregulated AA metabolism associated with neuroinflammation, PET with 1-11C-AA could be used to examine neuroinflammation in patients with AD and other brain diseases.

Evaluation of anesthesia effects on [18F]FDG uptake in mouse brain and heart using small animal PET

This study evaluates effects of anesthesia on (18)F-FDG (FDG) uptake in mouse brain and heart to establish the basic conditions of small animal PET imaging. Prior to FDG injection, 12 mice were anesthetized with isoflurane gas; 11 mice were anesthetized with an intraperitoneal injection of a ketamine/xylazine mixture; and 11 mice were awake. In isoflurane and ketamine/xylazine conditions, FDG brain uptake (%ID/g) was significantly lower than in controls. Conversely, in the isoflurane condition, %ID/g in heart was significantly higher than in controls, whereas heart uptake in ketamine/xylazine mice was significantly lower. Results suggest that anesthesia impedes FDG uptake in mouse brain and affects FDG uptake in heart; however, the effects in the brain and heart differ depending on the type of anesthesia used.

Principal Component Analysis and the Scaled Subprofile Model Compared to Intersubject Averaging and Statistical Parametric Mapping: I. “Functional Connectivity” of the Human Motor System Studied with [15O]Water PET

Using [15O]water PET and a previously well studied motor activation task, repetitive finger-to-thumb opposition, we compared the spatial activation patterns produced by (1) global normalization and intersubject averaging of paired-image subtractions, (2) the mean differences of ANCOVA-adjusted voxels in Statistical Parametric Mapping, (3) ANCOVA-adjusted voxels followed by principal component analysis (PCA), (4) ANCOVA-adjustment of mean image volumes (mean over subjects at each time point) followed by F-masking and PCA, and (5) PCA with Scaled Subprofile Model pre- and postprocessing. All data analysis techniques identified large positive focal activations in the contralateral sensorimotor cortex and ipsilateral cerebellar cortex, with varying levels of activation in other parts of the motor system, e.g., supplementary motor area, thalamus, putamen; techniques 1–4 also produced extensive negative areas. The activation signal of interest constitutes a very small fraction of the total nonrandom signal in the original dataset, and the exact choice of data preprocessing steps together with a particular analysis procedure have a significant impact on the identification and relative levels of activated regions. The challenge for the future is to identify those preprocessing algorithms and data analysis models that reproducibly optimize the identification and quantification of higher-order sensorimotor and cognitive responses.

The convergence of object dependent resolution in maximum likelihood based tomographic image reconstruction

Study of the maximum likelihood by EM algorithm (ML) with a reconstruction kernel equal to the intrinsic detector resolution and sieve regularization has demonstrated that any image improvements over filtered backprojection (FBP) are a function of image resolution. Comparing different reconstruction algorithms potentially requires measuring and matching the image resolution. Since there are no standard methods for describing the resolution of images from a nonlinear algorithm such as ML, we have defined measures of effective local Gaussian resolution (ELGR) and effective global Gaussian resolution (EGGR) and examined their behaviour in FBP images and in ML images using two different measurement techniques. For FBP these two resolution measures are equal and exhibit the standard convolution behaviour of linear systems. For ML, the FWHM of the ELGR monotonically increased with decreasing Gaussian object size due to slower convergence rates for smaller objects. For the simple simulated phantom used, this resolution dependence is independent of object position. With increasing object size, number of iterations and sieve size the object size dependence of the ELGR decreased. The FWHM of the EGGR converged after approximately 200 iterations, masking the fact that the ELGR for small objects was far from convergence. When FBP is compared to a nonlinear algorithm such as ML, it is recommended that at least the EGGR be matched; for ML this requires more than the number of iterations (e.g., < 100) that are typically run to minimize the mean square error or to satisfy a feasibility or similar stopping criterion. For many tasks, matching the EGGR of ML to FBP images may be insufficient and >> 200 iterations may be needed, particularly for small objects in the ML image because their ELGR has not yet converged.

P-Glycoprotein Function at the Blood–Brain Barrier in Humans Can Be Quantified with the Substrate Radiotracer 11C-N-Desmethyl-Loperamide

Permeability-glycoprotein (P-gp), an efflux transporter in several organs, acts at the blood–brain barrier to protect the brain from exogenous toxins. P-gp almost completely blocks brain entry of the PET radiotracer 11C-N-desmethyl-loperamide (11C-dLop). We examined the ability of 11C-dLop to quantify P-gp function in humans after increasing doses of tariquidar, an inhibitor of P-gp. Methods: Seventeen healthy volunteers had a total of 23 PET scans with 11C-dLop at baseline and after increasing doses of tariquidar (2, 4, and 6 mg/kg intravenously). A subset of subjects received PET with 15O-H2O to measure cerebral blood flow. Brain uptake of 11C-dLop was quantified in 2 ways. Without blood data, uptake was measured as area under the time–activity curve in the brain from 10 to 30 min (AUC10–30). With arterial blood data, brain uptake was quantified with compartmental modeling to estimate the rates of entry into (K1) and efflux from (k2) the brain. Results: Brain uptake of radioactivity was negligible at baseline and increased only slightly (∼30%) after 2 mg of tariquidar per kilogram. In contrast, 4 and 6 mg of tariquidar per kilogram increased brain uptake 2- and 4-fold, respectively. Greater brain uptake reflected greater brain entry (K1), because efflux (k2) and cerebral blood flow did not differ between tariquidar-treated and untreated subjects. In the subjects who received the highest dose of tariquidar (and had the highest brain uptake), regional values of K1 correlated linearly with absolute cerebral blood flow, consistent with high single-pass extraction of 11C-dLop. AUC10–30 correlated linearly with K1. Conclusion: P-gp function at the blood–brain barrier in humans can be quantified using PET and 11C-dLop. A simple measure of brain uptake (AUC10–30) may be used as a surrogate of the fully quantified rate constant for brain entry (K1) and thereby avoid arterial sampling. However, to dissect the function of P-gp itself, both brain uptake and the influx rate constant must be corrected for radiotracer delivery (blood flow).