A generalised spatio-temporal registration framework for dynamic PET data: application to neuroreceptor imaging.

This work presents a novel pharmacokinetic model based registration algorithm for the motion correction of dynamic positron emission tomography (PET) images. The algorithm employs a generalised model that derives the input function from the tomographic data itself to model the PET tracer kinetics and thus eliminates the need of arterial blood sampling. Both the temporal constraint from the tracer kinetic behaviour and spatial constraint from the image similarity are integrated in a joint probabilistic model, in which the subject motion and tracer kinetic parameters are iteratively optimised, leading to a group-wise registration framework of motion corrupted dynamic PET data. The algorithm is evaluated with simulated and measured human dopamine D3 receptor imaging data using [11C]-(+)-PHNO. The simulation-based validation demonstrates that the new algorithm has a subvoxel registration accuracy on average for noisy data with simulated motion artefacts. The algorithm also shows reductions in motion on initial experiments with measured clinical [11C]-(+)-PHNO brain data.

Topography and ultrastructure of the tegument of Lecithochirium musculus (Digenea: Hemiuridae), a parasite of the European eel Anguilla anguilla (Osteichthyes: Anguillidae).

The tegumental ultrastructure of the stomach fluke Lecithochirium musculus was studied using scanning and transmission electron microscopy. The surface of the tegument was smooth and covered by transverse cytoplasmic ridges. Cobblestone-like units of the tegument were observed on the ventral surface. Invagination and evagination of the ecsoma induced variations in the tegumental surface. The ultrastructural study revealed that the tegument of L. musculus had a typical syncytial organization with a distal cytoplasm lying over a basal matrix and cytons. Two types of intra-tegumental sensory structures were observed. Type 1 sensory receptor was a domed-like fusiform structure consisting of a smooth elevation of the tegument. Four receptors of this type were observed on the anterior dorsal surface of the fluke. Three nerve bulbs filled with electron-lucent material and mitochondria composed this receptor. Hemispherical electron-dense collars were observed at the top of the nerve bulbs. Striated rootlets laid just beneath the hemispherical electron-dense collars. Type 2 sensory receptor presented two morphological variations, i.e., a bulb-like monolobed structure, and a bulb-like bilobed structure observed at two different degrees of evagination. For both variations, the nerve bulb enclosed mitochondria, electron-lucent material, and a conical electron-dense collar from which extended a striated rootlet. Numerous sensory receptors of this type were observed around the ventral sucker.

Reproducibility of sensory nerve conduction studies of the sural nerve using ultrasound-guided needle positioning.

INTRODUCTION: In this study we sought to evaluate the reproducibility of sensory nerve conduction studies (NCS) using ultrasound-guided needle positioning (USNP). METHODS: Orthodromic NCS of the sural nerve using needle electrodes with USNP as well as surface electrodes were conducted twice in 20 healthy volunteers. RESULTS: The mean sensory nerve action potential (SNAP) amplitude in the initial examination was 39.5 µV using needle electrodes with USNP, and 12.5 µV using surface electrodes (P < 0.0001). The mean SNAP amplitude in the follow-up examination was 39.2 µV using needle electrodes with USNP, and 12.4 µV using surface electrodes (P < 0.0001). The mean intraindividual change in SNAP amplitude (test-retest) was 21.2% using needle electrodes with USNP, and 24.8% using surface electrodes (P = 0.6). CONCLUSIONS: Sensory NCS of the sural nerve using needle electrodes with USNP have reliable test-retest reproducibility and yield greater SNAP amplitudes than sensory NCS using surface electrodes.

Immunohistological labeling of microtubules in sensory neuron dendrites, tracheae, and muscles in the Drosophila larva body wall.

To understand how differences in complex cell shapes are achieved, it is important to accurately follow microtubule organization. The Drosophila larval body wall contains several cell types that are models to study cell and tissue morphogenesis. For example tracheae are used to examine tube morphogenesis(1), and the dendritic arborization (DA) sensory neurons of the Drosophila larva have become a primary system for the elucidation of general and neuron-class-specific mechanisms of dendritic differentiation(2-5) and degeneration(6). The shape of dendrite branches can vary significantly between neuron classes, and even among different branches of a single neuron(7,8). Genetic studies in DA neurons suggest that differential cytoskeletal organization can underlie morphological differences in dendritic branch shape(4,9-11). We provide a robust immunological labeling method to assay in vivo microtubule organization in DA sensory neuron dendrite arbor (Figures 1, 2, Movie 1). This protocol illustrates the dissection and immunostaining of first instar larva, a stage when active sensory neuron dendrite outgrowth and branching organization is occurring (12,13). In addition to staining sensory neurons, this method achieves robust labeling of microtubule organization in muscles (Movies 2, 3), trachea (Figure 3, Movie 3), and other body wall tissues. It is valuable for investigators wishing to analyze microtubule organization in situ in the body wall when investigating mechanisms that control tissue and cell shape.

Restricted maximum likelihood estimation of PET neuroreceptor occupancy in the absence of a reference region.

PURPOSE: Brain positron emission tomography (PET) is a useful technique for estimating the neuroreceptor occupancy of a drug in vivo. In the absence of a reference region, occupancy can be obtained from an "occupancy plot" with ordinary least squares (OLS) regression. However, OLS has been found to return inefficient occupancy estimations. The aim of this study was to improve the accuracy and precision of occupancy estimations. METHODS: Within a simulation framework, the efficiency of several model II regression approaches (accounting for error in the independent variable) and restricted maximum likelihood estimator (REML, specifically modeling the drug occupancy) was compared to the efficiency of OLS. RESULTS: Efficiency of REML was 171%-210% the efficiency of OLS, while model II regressions were found to be substantially less efficient. CONCLUSIONS: In the absence of a reference region, it is recommended to use occupancy REML instead of OLS in order to increase the validity of occupancy estimations and thus decrease the costs of PET research.

The performance of monotonic and new non-monotonic gradient ascent reconstruction algorithms for high-resolution neuroreceptor PET imaging.

Iterative expectation maximization (EM) techniques have been extensively used to solve maximum likelihood (ML) problems in positron emission tomography (PET) image reconstruction. Although EM methods offer a robust approach to solving ML problems, they usually suffer from slow convergence rates. The ordered subsets EM (OSEM) algorithm provides significant improvements in the convergence rate, but it can cycle between estimates converging towards the ML solution of each subset. In contrast, gradient-based methods, such as the recently proposed non-monotonic maximum likelihood (NMML) and the more established preconditioned conjugate gradient (PCG), offer a globally convergent, yet equally fast, alternative to OSEM. Reported results showed that NMML provides faster convergence compared to OSEM; however, it has never been compared to other fast gradient-based methods, like PCG. Therefore, in this work we evaluate the performance of two gradient-based methods (NMML and PCG) and investigate their potential as an alternative to the fast and widely used OSEM. All algorithms were evaluated using 2D simulations, as well as a single [(11)C]DASB clinical brain dataset. Results on simulated 2D data show that both PCG and NMML achieve orders of magnitude faster convergence to the ML solution compared to MLEM and exhibit comparable performance to OSEM. Equally fast performance is observed between OSEM and PCG for clinical 3D data, but NMML seems to perform poorly. However, with the addition of a preconditioner term to the gradient direction, the convergence behaviour of NMML can be substantially improved. Although PCG is a fast convergent algorithm, the use of a (bent) line search increases the complexity of the implementation, as well as the computational time involved per iteration. Contrary to previous reports, NMML offers no clear advantage over OSEM or PCG, for noisy PET data. Therefore, we conclude that there is little evidence to replace OSEM as the algorithm of choice for many applications, especially given that in practice convergence is often not desired for algorithms seeking ML estimates.

PET and SPECT in cardiovascular molecular imaging.

The current focus of cardiovascular medicine is on early detection and prevention of disease, to control the escalating costs of health care. To achieve this goal, novel imaging approaches that allow for early detection of disease and risk stratification are needed. Traditionally, the diagnosis, monitoring, and prognostication of cardiovascular disease were based on techniques that measured changes in metabolism, blood flow, and biological function. Molecular imaging is emerging as a new tool for the noninvasive detection of biological processes that can differentiate and characterize tissues before manifestation of gross anatomical features or physiological consequences. Leading the way are techniques involving high-sensitivity radiotracers that could revolutionize current diagnostic paradigms. This Review provides an overview of selected molecular-based single photon emission CT (SPECT) and PET imaging strategies for the evaluation of cardiovascular disease-including the evaluation of myocardial metabolism and neurohumoral activity of the heart-and potential future targeted methods of evaluating critical molecular processes, such as atherosclerosis, ventricular remodeling after myocardial infarction, and ischemia-associated angiogenesis.

A new graphic plot analysis for determination of neuroreceptor binding in positron emission tomography studies.

In positron emission tomography (PET) studies with radioligands for neuroreceptors, tracer kinetics have been described by the standard two-tissue compartment model that includes the compartments of nondisplaceable binding and specific binding to receptors. In the present study, we have developed a new graphic plot analysis to determine the total distribution volume (V(T)) and nondisplaceable distribution volume (V(ND)) independently, and therefore the binding potential (BP(ND)). In this plot, Y(t) is the ratio of brain tissue activity to time-integrated arterial input function, and X(t) is the ratio of time-integrated brain tissue activity to time-integrated arterial input function. The x-intercept of linear regression of the plots for early phase represents V(ND), and the x-intercept of linear regression of the plots for delayed phase after the equilibrium time represents V(T). BP(ND) can be calculated by BP(ND)=V(T)/V(ND)-1. Dynamic PET scanning with measurement of arterial input function was performed on six healthy men after intravenous rapid bolus injection of [(11)C]FLB457. The plot yielded a curve in regions with specific binding while it yielded a straight line through all plot data in regions with no specific binding. V(ND), V(T), and BP(ND) values calculated by the present method were in good agreement with those by conventional non-linear least-squares fitting procedure. This method can be used to distinguish graphically whether the radioligand binding includes specific binding or not.

The diagnostic value of ultrasonography in patients with electrophysiologicaly confirmed carpal tunnel syndrome.

OBJECTIVE: To evaluate the diagnostic value of ultrasonography in patients with electrophysiologically confirmed carpal tunnel syndrome. DESIGN: A prospective ultrasonographic study of 70 wrists with electrophysiologically confirmed carpal tunnel syndrome and of 80 normal wrists. Receiver-operating-characteristics curves for the ultrasonographic measurements of median nerve were plotted to identify the most optimal cutoff values. RESULTS: The ultrasonographic measurements of median nerves were found to be increased significantly in patients with carpal tunnel syndrome when compared with controls, particularly in terms of cross-sectional area (P <0.001). According to receiver-operating-characteristics curve results, the most optimal cutoff value for the cross-sectional area of the median nerve was obtained at the level of middle carpal tunnel, which was 9.3 mm2, with a sensitivity of 80% and specificity of 77.5%. CONCLUSION: Ultrasonographic examination of the median nerve seems to be a promising method in the diagnosis of carpal tunnel syndrome, evaluating the morphologic changes of the median nerve in patients with clinical signs and symptoms. Further studies with wider series are needed to confirm our preliminary results.

Relationship between adapted neural population responses in MT and motion adaptation in speed and direction of smooth-pursuit eye movements.

We have asked how sensory adaptation is represented in the response of a population of visual motion neurons and whether the neural adaptation could drive behavioral adaptation. Our approach was to evaluate the effects of about 10 s of motion adaptation on both smooth-pursuit eye movements and the responses of neuron populations in extrastriate middle temporal visual area (MT) in awake monkeys. Stimuli for neural recordings consisted of patches of 100% correlated dot textures. There was a wide range of effects across neurons, but on average adaptation reduced the amplitude and width of the direction tuning curves of MT neurons, without large changes in the preferred direction. The effects were greatest when the direction of the adapting stimulus corresponded to the preferred direction of the MT neuron under study. Adaptation also reduced the amplitude of speed-tuning curves, again with the greatest effect when the adapting speed was equal to the preferred speed. The adapted tuning curves were shifted toward lower preferred speeds as the adapting speed increased. We constructed populations of model MT neurons based on our experimental sample and showed that the effects of adaptation on the direction and speed of pursuit eye movements were predicted when a variant of vector averaging decoded the responses of a subset of the neural population. We conclude that the effects of motion adaptation on the responses of MT neurons can support behavioral adaptation in pursuit eye movements.

Improvement of likelihood estimation in Logan graphical analysis using maximum a posteriori for neuroreceptor PET imaging.

OBJECTIVE: To reduce variance of the total volume of distribution (V (T)) image, we improved likelihood estimation in graphical analysis (LEGA) for dynamic positron emission tomography (PET) images using maximum a posteriori (MAP). METHODS: In our proposed MAP estimation in graphical analysis (MEGA), a set of time-activity curves (TACs) was formed with V (T) varying in physiological range as a template, and then the most similar TAC was sought out for a given measured TAC in a feature space. In simulation, MEGA was compared with other three methods, Logan graphical analysis (GA), multilinear analysis (MA1), and LEGA using 500 noisy TACs, under each of seven physiological conditions (from 9.9 to 61.5 of V (T)). PET studies of [(11)C]SA4503 were performed in three healthy volunteers. In clinical studies, the V (T) images estimated from MEGA were compared with region of interest (ROI) estimates from a nonlinear least square (NLS) fitting over four brain regions. RESULTS: In the simulation study, the estimated V (T) by GA had a large underestimation (y = 0.27x + 8.72, r (2) = 0.87). Applying the other methods (MA1, LEGA, and MEGA), these noise-induced biases were improved (y = 0.80x + 4.04, r (2) = 0.98; y = 0.85x + 3.05, r (2) = 0.99; y = 0.96x + 1.21, r (2) = 0.99, respectively). MA1 and LEGA produced increased variance of the estimated V (T) in clinical studies. However, MEGA improved signal-to-noise ratio (SNR) in V (T) images with linear correlations between ROI estimates with NLS (y = 0.87x + 5.1, r (2) = 0.96). CONCLUSIONS: MEGA was validated as an alternative strategy of LEGA to improve estimates of V (T) in clinical PET imaging.

Robust fitting for neuroreceptor mapping.

Among many other uses, positron emission tomography (PET) can be used in studies to estimate the density of a neuroreceptor at each location throughout the brain by measuring the concentration of a radiotracer over time and modeling its kinetics. There are a variety of kinetic models in common usage and these typically rely on nonlinear least-squares (LS) algorithms for parameter estimation. However, PET data often contain artifacts (such as uncorrected head motion) and so the assumptions on which the LS methods are based may be violated. Quantile regression (QR) provides a robust alternative to LS methods and has been used successfully in many applications. We consider fitting various kinetic models to PET data using QR and study the relative performance of the methods via simulation. A data adaptive method for choosing between LS and QR is proposed and the performance of this method is also studied.

Robust estimation of the arterial input function for Logan plots using an intersectional searching algorithm and clustering in positron emission tomography for neuroreceptor imaging.

The Logan plot is a powerful algorithm used to generate binding-potential images from dynamic positron emission tomography (PET) images in neuroreceptor studies. However, it requires arterial blood sampling and metabolite correction to provide an input function, and clinically it is preferable that this need for arterial blood sampling be obviated. Estimation of the input function with metabolite correction using an intersectional searching algorithm (ISA) has been proposed. The ISA seeks the input function from the intersection between the planes spanned by measured radioactivity curves in tissue and their cumulative integrals in data space. However, the ISA is sensitive to noise included in measured curves, and it often fails to estimate the input function. In this paper, we propose a robust estimation of the cumulative integral of the plasma time-activity curve (pTAC) using ISA (robust EPISA) to overcome noise issues. The EPISA reduces noise in the measured PET data using averaging and clustering that gathers radioactivity curves with similar kinetic parameters. We confirmed that a little noise made the estimation of the input function extremely difficult in the simulation. The robust EPISA was validated by application to eight real dynamic [(11)C]TMSX PET data sets used to visualize adenosine A(2A) receptors and four real dynamic [(11)C]PIB PET data sets used to visualize amyloid-beta plaque. Peripherally, the latter showed faster metabolism than the former. The clustering operation improved the signal-to-noise ratio for the PET data sufficiently to estimate the input function, and the calculated neuroreceptor images had a quality equivalent to that using measured pTACs after metabolite correction. Our proposed method noninvasively yields an alternative input function for Logan plots, allowing the Logan plot to be more useful in neuroreceptor studies.

[Study on neuroreceptor imaging with radionuclide tracing in vivo].

Neuroreceptor imaging with radionuclide tracing in vivo has been greatly developed recently. Distribution, density, and activity of receptors in the brain can be visualized by the radioligands labeled for emission computed tomography (ECT), including PET (positron emission tomography) and SPECT (single photon emission computed tomography). The functional and quantitative imaging for several receptors, such as dopamine receptors, serotonin receptors, cholinergic receptors, benzodiazepine receptors, and opioid receptors, has clinical importance. The preparation of receptor imaging agents, foundation of the physio-mathematical model, and the development of nuclear medicine instruments are the main points. In the present review, we will concentrate on introducing the development of brain receptor imaging.

In vivo neuroreceptor imaging in attention-deficit/hyperactivity disorder: a focus on the dopamine transporter.

There is converging evidence of the role of catecholamine dysregulation in the underlying pathophysiology of attention-deficit/hyperactivity disorder (ADHD). The dopamine transporter (DAT) is known to be a key regulator of dopamine, and recent genetic, treatment, and imaging studies have highlighted the role of DAT in ADHD. There is an emerging literature on in vivo neuroreceptor imaging of DAT in ADHD and control subjects reported by a number of groups internationally. A comprehensive review of existing imaging studies of DAT binding in ADHD shows that six of eight independent studies by six different groups have reported increased DAT binding in (mostly) treatment-naïve children and adults with ADHD. Although there is fair agreement regarding the presence and direction of abnormal DAT binding, there remains disagreement as to the magnitude of the finding and the importance of many potentially confounding variables, including clinical characteristics and imaging methodology. Three studies by three different groups have reported decreased DAT binding after methylphenidate treatment. Interpretation of the latter finding awaits clarification of the issue of timing of drug administration and imaging to disentangle receptor occupancy from downregulation.

Research applications of selected 123I-labeled neuroreceptor SPECT imaging ligands.

Neuroreceptor imaging is a promising area of brain imaging used to investigate various neurodegenerative and neuropsychiatric disorders. In the research setting, radiopharmaceuticals targeted to specific areas of the brain are used along with SPECT to assess and analyze functional mechanisms within brain structures. Utilization of the data that are collected from these studies may aid in the development of drug therapies that can be used to relieve symptoms or delay progression of certain disease states. After reading this article, the nuclear medicine technologist should be able to identify and describe the role of structures in the brain, identify various radiopharmaceuticals used and the disease states they demonstrate, and become familiar with the drugs used in treatment of these disorders.

Neurofunctional imaging of the pancreas utilizing the cholinergic PET radioligand [18F]4-fluorobenzyltrozamicol.

The pancreas is one of the most heavily innervated peripheral organs in the body. Parasympathetic and sympathetic neurons terminate in the pancreas and provide tight control of endocrine and exocrine functions. The aim of this study was to determine whether the pancreas can be imaged with a radioligand that binds to specific neuroreceptors. Using fluorine-18 4-fluorobenzyltrozamicol (FBT), which binds to the presynaptic vesicular acetylcholine transporter, positron emission tomography scans were performed in four adult mice, two adult rhesus monkeys, and one adult human. In these mammals, the pancreas is intensely FBT avid, with uptake greater than in any other organ at 30, 60, and 90 min. The maximum standardized uptake value (SUV) ratios of pancreas to liver, for example, ranged from 1.4 to 1.7 in rhesus monkeys (mean 1.6; median 1.7) and from 1.9 to 4.7 (mean 3.24; median 3.02) in mice. The maximum SUV ratio of pancreas to liver in the human was 1.8. These data suggest that neuroreceptor imaging of the pancreas in vivo is feasible in animal models and humans. This imaging could allow researchers to interrogate functions under control of the autonomic nervous system in the pancreas, with applications possible in transplanted and native pancreata. Also, as beta cell function is intimately related to parasympathetic cholinergic input, FBT activity in the pancreas may correlate with insulin-producing beta cell mass. This could ultimately provide a method of in vivo imaging in animal models and humans for diabetes research.

Development of an inexpensive, low attenuation styrofoam primate chair for use in a PET scanner.

Pharmacokinetic modelling of radiotracers for positron emission tomography (PET) imaging of neuroreceptors can be performed with time-activity data for brain and blood. We aimed to develop an alternative to withdrawal of arterial blood samples for acquisition of a blood curve. A supportive primate chair was constructed out of styrofoam and fixed to the head portion of the bed of a PET scanner. A lightly anaesthetised rhesus monkey was positioned in the chair in a sitting position and injected with the radiotracer. The styrofoam chair provided sufficient support for the monkey. The presence of the chair in the PET scanner caused negligible attenuation of radiation, allowing simultaneous acquisition of dynamic data from the subject's brain and heart. We conclude that a styrofoam primate chair is an ideal tool to measure blood and brain data from a rhesus monkey with PET. Invasiveness to the animal is reduced, as well as experimenter time.

Predicting the success of a radiopharmaceutical for in vivo imaging of central nervous system neuroreceptor systems.

In vivo imaging of the central nervous system (CNS) neuroreceptors in humans began was used in the early 1980s. Now, some twenty years later, the success of radiopharmaceutical imaging is still often one based on empiricism and serendipity. Nevertheless, a number of factors can be identified based on the robot experience in developing these radiotracers. This article will describe some of the issues that may be useful in choosing approaches to radiolabel ligands as future imaging agents of neuroreceptors, transporters and intrasynaptic measures of neurotransmitters. A description of the current process from hypothesis to radiochemical preclinical development, non-human primate imaging development of quantitative procedures finally leading to toxicology, dosimetry and eventually human applications are provided. The role of important factors including metabolism and lipophilicity, affinity and other factors for optimizing radiolabeling strategies is dealt with. Furthermore, issues involving decision making of how far to extend efforts in developing a radiotracer and when might be an appropriate stopping place are discussed. Finally some typical examples of the use of these radiotracers, especially with emphasis on stable drug design and development, are provided. These include occupancy studies and mechanism of action studies. In summary, the prediction of tracer success includes: first, identification of appropriate targets and precursors, then systematic optimization of ligands with continuous feedback from pharmacokinetics and iterative improvement based on unsuccessful tracers. This article is intended to present a pragmatic overview of the radiopharmaceutical development process with emphasis on the CNS.