Neuroimaging and therapeutics in movement disorders

The effect of Parkin gene S/N 167 polymorphism on resting spontaneous brain functional activity in Parkinson's Disease

BACKGROUND

Genetic susceptibility plays a significant role in Parkinson's disease (PD) development. Carriers of the Parkin S/N167 mutation may have an increased risk of PD and altered spontaneous brain activity.

OBJECTIVE

This study aims to investigate the potential pathogenesis of PD through a comparative analysis of the amplitude of low-frequency fluctuations (ALFF) in resting-state functional magnetic resonance imaging (rs-fMRI) of subjects with Parkin gene S/N 167 polymorphisms, and to examine the association between spontaneous brain activity and clinical scale scores of PD.

METHODS

A total of 69 PD patients and 84 healthy controls (HC) were included in the study. Each subject was genotyped for the Parkin gene S/N 167 polymorphism and underwent rs-fMRI scans. ALFF analysis was employed to evaluate the relationship among genotypes, interactive brain regions, and clinical symptoms in PD.

RESULTS

PD patients exhibited decreased ALFF values in the right anterior lobe and vermis of the cerebellum compared to HC. No significant interaction was found between the gene's main effect and the "group × genotype" effect on brain ALFF values. One-factor ANOVA revealed no significant difference in ALFF values between PD subgroups; however, the ALFF values in the right anterior lobe and vermis of the cerebellum were lower in the PD-G and PD-GA groups compared to the HC-G and HC-GA groups. Spearman correlation analysis demonstrated that ALFF values in the PD-GG and PD-GA groups were negatively associated with UPDRS-III scores in the bilateral lingual gyrus (Lingual R/L).

CONCLUSION

Parkin gene S/N 167 polymorphisms may influence brain functional activity in specific brain regions, and ALFF values are associated with motor symptoms in PD patients.

Brain MRI-guided focused ultrasound conceptualised as a tool for brain network intervention

Magnetic resonance imaging guided high intensity focused ultrasound (HIFU) has emerged as a tool offering incisionless intervention on brain tissue. The low risk and rapid recovery from this procedure, in addition to the ability to assess for clinical benefit and adverse events intraprocedurally, makes it an ideal tool for intervention upon brain networks both for clinical and research applications. This review article proposes that conceptualising brain focused ultrasound as a tool for brain network intervention and adoption of methodology to complement this approach may result in better clinical outcomes, fewer adverse events and may unveil or allow treatment opportunities not otherwise possible. A brief introduction to network neuroscience is discussed before a description of pathological brain networks is provided for a number of conditions for which MRI-guided brain HIFU intervention has been implemented. Essential Tremor is discussed as the most advanced example of MRI-guided brain HIFU intervention adoption along with the issues that present with this treatment modality compared to alternatives. The brain network intervention paradigm is proposed to overcome these issues and a number of examples of implementation of this are discussed. The ability of low intensity MRI guided focussed ultrasound to neuromoduate brain tissue without lesioning is introduced. This tool is discussed with regards to its potential clinical application as well as its potential to further our understanding of network neuroscience via its ability to interrogate brain networks without damaging tissue. Finally, a number of current clinical trials utilising brain focused ultrasound are discussed, along with the additional applications available from the utilisation of low intensity focused ultrasound.

Impaired cerebral microcirculation in isolated REM sleep behaviour disorder

During the prodromal period of Parkinson's disease and other α-synucleinopathy-related parkinsonisms, neurodegeneration is thought to progressively affect deep brain nuclei, such as the locus coeruleus, caudal raphe nucleus, substantia nigra, and the forebrain nucleus basalis of Meynert. Besides their involvement in the regulation of mood, sleep, behaviour, and memory functions, these nuclei also innervate parenchymal arterioles and capillaries throughout the cortex, possibly to ensure that oxygen supplies are adjusted according to the needs of neural activity. The aim of this study was to examine whether patients with isolated REM sleep behaviour disorder, a parasomnia considered to be a prodromal phenotype of α-synucleinopathies, reveal microvascular flow disturbances consistent with disrupted central blood flow control. We applied dynamic susceptibility contrast MRI to characterize the microscopic distribution of cerebral blood flow in the cortex of 20 polysomnographic-confirmed patients with isolated REM sleep behaviour disorder (17 males, age range: 54-77 years) and 25 healthy matched controls (25 males, age range: 58-76 years). Patients and controls were cognitively tested by Montreal Cognitive Assessment and Mini Mental State Examination. Results revealed profound hypoperfusion and microvascular flow disturbances throughout the cortex in patients compared to controls. In patients, the microvascular flow disturbances were seen in cortical areas associated with language comprehension, visual processing and recognition and were associated with impaired cognitive performance. We conclude that cortical blood flow abnormalities, possibly related to impaired neurogenic control, are present in patients with isolated REM sleep behaviour disorder and associated with cognitive dysfunction. We hypothesize that pharmacological restoration of perivascular neurotransmitter levels could help maintain cognitive function in patients with this prodromal phenotype of parkinsonism.

Brain-targeting by optimized 99mTc-olanzapine: in vivo and in silico studies

Purpose: Olanzapine (OLZ) is an atypical antipsychotic agent that is characterized by low brain porousness. The present work aimed to develop radiolabeled olanzapine (OLZ) without colloidal impurities and evaluate its biodistribution following intravenous (I.V.) and intranasal (I.N.) administration as a potential agent for brain diagnosis. Materials and methods: OLZ was radiolabeled with technetium-99m by using sodium dithionite as the reducing agent. Biodistribution of ^99mTc-OLZ complex in mice following I.V. and I.N. administrations was examined. Furthermore, a molecular docking study was performed.Results: Sodium dithionite labeling procedure resulted in highest radiochemical yield (96.30 ± 0.09%) and in vitro stability in serum up to 8 h. Biodistribution study of ^99mTc-OLZ complex showed high brain uptake following I.N. (6.2 ± 0.12% ID/g) and I.V. (5.5 ± 0.09% ID/g) at 0.5 and 1 h post administration (P.I.), respectively. Docking into two brain targets predicts higher affinity of ^99mTc-OLZ than free OLZ. Additionally, docking to P-glycoproteins shows less affinity for the radiolabelled OLZ and hence it is expected to be associated with better brain exposure than free OLZ.Conclusion: These chemical and preliminary biological merits strongly suggest that the ^99mTc-OLZ complex with new reducing agent could be used as a potential diagnostic agent for brain.

Distinguishing patients with Parkinson's disease subtypes from normal controls based on functional network regional efficiencies

Many studies have demonstrated that the pathophysiology and clinical symptoms of Parkinson's disease (PD) are inhomogeneous. However, the symptom-specific intrinsic neural activities underlying the PD subtypes are still not well understood. Here, 15 tremor-dominant PD patients, 10 non-tremor-dominant PD patients, and 20 matched normal controls (NCs) were recruited and underwent resting-state functional magnetic resonance imaging (fMRI). Functional brain networks were constructed based on randomly generated anatomical templates with and without the cerebellum. The regional network efficiencies (i.e., the local and global efficiencies) were further measured and used to distinguish subgroups of PD patients (i.e., with tremor-dominant PD and non-tremor-dominant PD) from the NCs using linear discriminant analysis. The results demonstrate that the subtype-specific functional networks were small-world-organized and that the network regional efficiency could discriminate among the individual PD subgroups and the NCs. Brain regions involved in distinguishing between the study groups included the basal ganglia (i.e., the caudate and putamen), limbic regions (i.e., the hippocampus and thalamus), the cerebellum, and other cerebral regions (e.g., the insula, cingulum, and calcarine sulcus). In particular, the performances of the regional local efficiency in the functional network were better than those of the global efficiency, and the performances of global efficiency were dependent on the inclusion of the cerebellum in the analysis. These findings provide new evidence for the neurological basis of differences between PD subtypes and suggest that the cerebellum may play different roles in the pathologies of different PD subtypes. The present study demonstrated the power of the combination of graph-based network analysis and discrimination analysis in elucidating the neural basis of different PD subtypes.

Cortico-striatal-thalamic network functional connectivity in hemiparkinsonism

Cortico-striatal-thalamic network functional connectivity (FC) and its relationship with levodopa (L-dopa) were investigated in 69 patients with hemiparkinsonism (25 drug-naïve [n-PD] and 44 under stable/optimized dopaminergic treatment [t-PD]) and 27 controls. Relative to controls, n-PD patients showed an increased FC between the left and the right basal ganglia, and a decreased connectivity of the affected caudate nucleus and thalamus with the ipsilateral frontal and insular cortices. Compared with both controls and n-PD patients, t-PD patients showed a decreased FC among the striatal and thalamic regions, and an increased FC between the striatum and temporal cortex, and between the thalamus and several sensorimotor, parietal, temporal, and occipital regions. In both n-PD and t-PD, patients with more severe motor disability had an increased striatal and/or thalamic FC with temporal, parietal, occipital, and cerebellar regions. Cortico-striatal-thalamic functional abnormalities occur in patients with hemiparkinsonism, antecede the onset of the motor symptoms on the opposite body side and are modulated by L-dopa. In patients with hemiparkinsonism, L-dopa is likely to facilitate a compensation of functional abnormalities possibly through an increased thalamic FC.

Effects of hypoxic-ischemic brain injury on striatal dopamine transporter in newborn piglets: evaluation of 11C-CFT PET/CT for DAT quantification

INTRODUCTION

Alterations of dopamine in striatal presynaptic terminals play an important role in the hypoxic-ischemic (HI) brain injury. Quantification of DAT levels in the presynaptic site using (11)C-N-2-carbomethoxy-3-(4-fluorophenyl)-tropane ((11)C-CFT) with positron emission tomography (PET) was applied in studies for Parkinson's disease. The current study investigated the changes in striatal DAT following HI brain injury in newborn piglets using (11)C-CFT PET.

METHODS

Newborn piglets were subjected to occlusion of bilateral common carotid arteries for 30 min and simultaneous peripheral hypoxia. Brain DAT imaging was performed using PET/CT with (11)C-CFT as the probe in each group (including the control group and HI insult groups). Brain tissues were collected for DAT immunohistochemical (IHC) analysis at each time point post the PET/CT procedure. Sham controls had some operation without HI procedure.

RESULTS

A few minutes after intravenous injection of (11)C-CFT, radioactive signals for DAT clearly appeared in the cortical area, striatum and cerebellum of newborn piglets of sham control group and HI insult groups. HI brain insult markedly increased striatal DAT at an early period (P<.05 vs. sham controls) when neuronal pathological changes were mild. Changes in striatal DAT were absent at later period post-HI insult when neuronal injury became more severe. (11)C-CFT PET imaging data and IHC DAT staining data were highly correlated (r=0.844, P<.05).

CONCLUSIONS

HI brain injury resulted in a transient increase in striatal DAT. (11)C-CFT PET/CT imaging data reflected the dynamic changes of DAT in the striatum in vivo.

Functional imaging of cognitive impairment in Parkinson's disease

Parkinson's disease (PD) is known by most persons to be a neurodegenerative disorder that affects one's motor skills. However, the disease is also characterized by the less recognized cognitive symptoms, including deficits in executive functioning, as well as mood and behavioral problems, which are just as disabling and distressing as the motor symptoms. Imaging methods such as positron emission tomography (PET) have recently enhanced our understanding of cognitive disturbances in PD, and are reviewed in the current article. Furthermore, insights gained from the use of specific radiotracers in the dopaminergic and cholinergic neurotransmitter systems are discussed, as well as findings from in vivo detection of amyloid-beta. We will also discuss the potential use of a metabolic covariance network as a biomarker in clinical trials for the objective assessment of cognitive dysfunction in PD.

Metabolic networks for assessment of therapy and diagnosis in Parkinson's disease

Neuroimaging and modern computational techniques like spatial covariance analysis have contributed greatly to the understanding of neural system abnormalities in neurodegenerative disorders such as Parkinson's disease (PD). The application of network analysis to metabolic PET data obtained from patients with PD has led to the identification and validation of two distinct spatial covariance patterns associated with the motor and cognitive manifestations of the disease. Quantifying the activity of these patterns in individual subjects has provided an objective tool for the assessment of treatment efficacy and differential diagnosis. We have found that activity of the PD motor-related network is modulated by antiparkinsonian treatments such as dopaminergic therapy, deep brain stimulation (DBS), and subthalamic nucleus (STN) gene therapy. By contrast, the cognitive-related network is not altered by these interventions for PD motor symptoms. This pattern may however change in response to therapies targeting the cognitive symptoms of this disorder. Recent work has focused on the identification of specific network biomarkers for atypical parkinsonian conditions such as multiple system atrophy (MSA) and progressive supranuclear palsy (PSP). These disease-related patterns can potentially be used in an automated imaging-based algorithm to classify patients with these disorders.

Imaging the nigrostriatal system to monitor disease progression and treatment-induced complications

Radiotracer imaging (RTI) techniques such as positron emission tomography (PET) allow the in vivo assessment of nigrostriatal DA function in Parkinson's disease and have provided valuable insights into the mechanisms of nigrostriatal degeneration and the consequent compensatory changes. Moreover, functional imaging serves as an excellent tool in the assessment of the progression of PD and the evolution of treatment-related complications. However, various studies have shown discordance between clinical progression of PD and nigrostriatal degeneration estimated by PET or SPECT, and no RTI technique can be reliably used as a biomarker for progression of PD. Presynaptic dopaminergic imaging has consistently demonstrated an anterior-posterior gradient of dopaminergic dysfunction predominantly affecting the putamen, with side-to-side asymmetry in tracer binding. Dopaminergic hypofunction in the striatum follows a negative exponential pattern with the fastest rate of decline in early disease. Evaluation of central pharmacokinetics of levodopa action by PET has demonstrated the role of increased synaptic dopamine turnover and downregulation of the dopamine transporter in the pathophysiology of levodopa-induced dyskinesias. In PD with behavioral complications such as impulse control disorders, increased levels of dopamine release have been observed in the ventral striatum during performance of a positive reward task, as well as loss of deactivation in orbitofrontal cortex in response to negative reward prediction errors. This suggests that there is a pathologically heightened "reward" response in the ventral striatum together with loss of the capacity to respond to negative outcomes. Overall, functional imaging with PET is an excellent tool for understanding the disease and its complications; however, caution must be applied in interpretation of the results.

Abnormal regional brain function in Parkinson's disease: truth or fiction?

Normalization of regional measurements by the global mean is commonly employed to minimize inter-subject variability in functional imaging studies. This practice is based on the assumption that global values do not substantially differ between patient and control groups. In this issue of NeuroImage, Borghammer and colleagues challenge the validity of this assumption. They focus on Parkinson's disease (PD) and use computer simulations to show that lower global values can produce spurious increases in subcortical brain regions. The authors speculate that the increased signal observed in these areas in PD is artefactual and unrelated to localized changes in brain function. In this commentary, we summarize what is currently known of the relationship between regional and global metabolic activity in PD and experimental parkinsonism. We found that early stage PD patients exhibit global values that are virtually identical to those of age-matched healthy subjects. SPM analysis revealed increased normalized metabolic activity in a discrete set of biologically relevant subcortical brain regions. Because of their higher variability, the corresponding absolute regional measures did not differ across the two groups. Longitudinal imaging studies in this population showed that the subcortical elevations in normalized metabolism appeared earlier and progressed faster than did focal cortical or global metabolic reductions. The observed increases in subcortical activity, but not the global changes, correlated with independent clinical measures of disease progression. Multivariate analysis with SSM/PCA further confirmed that the abnormal spatial covariance structure of early PD is dominated by these subcortical increases as opposed to network-related reductions in cortical metabolic activity or global changes. Thus, increased subcortical activity in PD cannot be regarded as a simple artefact of global normalization. Moreover, stability of the normalized measurements, particularly at the network level, makes these metabolic indices suitable as imaging biomarkers of PD progression and the treatment response.

STN-stimulation in Parkinson's disease restores striatal inhibition of thalamocortical projection

To test the hypothesis that deep brain stimulation of the subthalamic nucleus (STN) restores the inhibitory output to the striatothalamocortical loop in Parkinson's disease, we obtained functional brain images of blood flow in 10 STN-stimulated patients with Parkinson's disease. Patients were immobile and off antiparkinsonian medication for 12 h. They were scanned with and without bilateral STN-stimulation with a 4-h interval between the two conditions. The order of DBS stimulation (ON or OFF) was randomized. Stimulation significantly raised regional cerebral blood flow (rCBF) bilaterally in the STN and in the left nucleus lentiformis. Conversely, flow declined in the left supplementary motor area (BA 6), ventrolateral nucleus of the left thalamus, and right cerebellum. Activation of the basal ganglia and deactivation of supplementary motor area and thalamus were both correlated with the improvement of motor function. The result is consistent with the explanation that stimulation in resting patients raises output from the STN with activation of the inhibitory basal ganglia output nuclei and subsequent deactivation of the thalamic anteroventral and ventrolateral nuclei and the supplementary motor area.

Differential diagnosis of parkinsonian syndromes using PCA-based functional imaging features

In the current paper, we describe methodologies for single subject differential diagnosis of degenerative brain disorders using multivariate principal component analysis (PCA) of functional imaging scans. An automated routine utilizing these methods is applied to positron emission tomography (PET) brain data to distinguish several discrete parkinsonian movement disorders with similar clinical manifestations. Disease specific expressions of voxel-based spatial covariance patterns are predetermined using the Scaled Subprofile Model (SSM/PCA) and a scalar measure of the manifestation of each pattern in prospective subject images is subsequently derived. Scores are automatically compared to reference values generated for each pathological condition in a corresponding set of patient and control scans. Diagnostic outcome is optimized using strategies such as the derivation of patterns in a voxel subspace that reflects contrasting image characteristics between conditions, or by using an independent patient population as controls. The prediction models for two, three and four way classification problems using direct scalar comparison as well as classical discriminant analysis are assessed in a composite training population comprised of three different patient classes and normal controls, and validated in a similar independent test population. Results illustrate that highly accurate diagnosis can often be achieved by simple comparison of scores utilizing optimized patterns.

Positron emission tomography for neurologists

This short review focuses on practical, present day, clinical application of FDG PET, a technology available to practicing neurologists for managing their patients. Indications in the disease states of dementia, neuro-oncology, epilepsy, parkinsonism, and other less common settings are reviewed. Many third-party payers currently make reimbursements based on these indications. By measuring an aspect of brain function, PET provides information that often is unobtainable from other sources, thus facilitating more rationale and cost-effective management, which can only benefit the patient, the referring physician, and the health care system as a whole.

Neuroimaging and transcranial ultrasonography in Parkinson's disease

Parkinson's disease is a progressive, widespread, neurodegenerative disease in which the involvement of the dopaminergic neurons of the substantia nigra results in significant dopamine depletion in the striatum. Newer imaging modalities reviewed here, using various radioligands, positron emission tomography, and single-photon emission computed tomography, have made it possible to assess the in vivo presynaptic and postsynaptic dopaminergic function. This is not only important from a diagnostic standpoint; these tests are being increasingly studied as surrogate markers to assess disease progression and responses to various interventions, including drugs. A brief comment on their role as a putative biomarker of the disease is also included. Because Parkinson's disease involves multiple neurotransmitter systems, neuroimaging of neurotransmitter systems other than dopamine is also discussed. Lastly, the evidence supporting the use of transcranial ultrasonography and substantia nigra hyperechogenicity in the diagnosis of Parkinson's disease is presented, along with some controversies that surround this technique.

Motor sequence learning and movement disorders

PURPOSE OF REVIEW

New insights into the psychophysiological determinants of performance changes and brain plasticity associated with motor sequence learning have recently been gained through behavioral and imaging studies in healthy individuals. In addition, using a variety of motor sequential paradigms in groups of patients affected by a movement disorder, major advances have been achieved in our understanding of the pathophysiological mechanisms underlying Parkinson's and Huntington's diseases, as well as primary forms of dystonia.

RECENT FINDINGS

This review begins by describing the latest findings in normal participants with regards to the dynamic alterations in neural networks observed across the different phases of motor sequence learning. It then focuses on the hotly debated issue of motor memory consolidation, highlighting the results of novel studies that investigated the role of both day and night sleep, the neural substrates and the developmental evolution mediating this process. Finally, this paper addresses current work looking at motor sequence learning in movement disorders that helps to better comprehend the functional contribution of basal ganglia structures to this type of memory, to assess the impact of such diseases on related patterns of brain activation, as well as to identify the neuronal compensatory mechanisms educed by these basal ganglia disorders.

SUMMARY

Such advances have major implications, not only for optimizing ways to learn new skilled behaviors in real-life situations, but also for guiding therapeutic approaches in patients with movement disorders.

Dissociation of metabolic and neurovascular responses to levodopa in the treatment of Parkinson's disease

We compared the metabolic and neurovascular effects of levodopa (LD) therapy for Parkinson's disease (PD). Eleven PD patients were scanned with both [15O]-H2O and [18F]-fluorodeoxyglucose positron emission tomography in the unmedicated state and during intravenous LD infusion. Images were used to quantify LD-mediated changes in the expression of motor- and cognition-related PD covariance patterns in scans of cerebral blood flow (CBF) and cerebral metabolic rate for glucose (CMR). These changes in network activity were compared with those occurring during subthalamic nucleus (STN) deep brain stimulation (DBS), and those observed in a test-retest PD control group. Separate voxel-based searches were conducted to identify individual regions with dissociated treatment-mediated changes in local cerebral blood flow and metabolism. We found a significant dissociation between CBF and CMR in the modulation of the PD motor-related network by LD treatment (p < 0.001). This dissociation was characterized by reductions in network activity in the CMR scans (p < 0.003) occurring concurrently with increases in the CBF scans (p < 0.01). Flow-metabolism dissociation was also evident at the regional level, with LD-mediated reductions in CMR and increases in CBF in the putamen/globus pallidus, dorsal midbrain/pons, STN, and ventral thalamus. CBF responses to LD in the putamen and pons were relatively greater in patients exhibiting drug-induced dyskinesia. In contrast, flow-metabolism dissociation was not present in the STN DBS treatment group or in the PD control group. These findings suggest that flow-metabolism dissociation is a distinctive feature of LD treatment. This phenomenon may be especially pronounced in patients with LD-induced dyskinesia.

Cutting-edge brain imaging with positron emission tomography

A review of recent advances in brain imaging using positron emission tomography (PET) is presented in this article. Some properties of the high-resolution research tomograph are described as examples of state-of-the-art PET instrumentation. A summary of current research topics in image reconstruction and quantification is given, with emphasis on the requirements of brain dynamic imaging. A brief overview of image analysis methods is presented, together with some examples of the contributions of quantitative PET imaging to the current understanding of brain function and disease. PET findings must be evaluated in the context of clinical observations and complemented by other imaging modalities whenever possible to ensure a proper interpretation of the data.

Modulation of metabolic brain networks after subthalamic gene therapy for Parkinson's disease

Parkinson's disease (PD) is characterized by elevated expression of an abnormal metabolic brain network that is reduced by clinically effective treatment. We used fluorodeoxyglucose (FDG) positron emission tomography (PET) to determine the basis for motor improvement in 12 PD patients receiving unilateral subthalamic nucleus (STN) infusion of an adenoassociated virus vector expressing glutamic acid decarboxylase (AAV-GAD). After gene therapy, we observed significant reductions in thalamic metabolism on the operated side as well as concurrent metabolic increases in ipsilateral motor and premotor cortical regions. Abnormal elevations in the activity of metabolic networks associated with motor and cognitive functioning in PD patients were evident at baseline. The activity of the motor-related network declined after surgery and persisted at 1 year. These network changes correlated with improved clinical disability ratings. By contrast, the activity of the cognition-related network did not change after gene transfer. This suggests that modulation of abnormal network activity underlies the clinical outcome observed after unilateral STN AAV-GAD gene therapy. Network biomarkers may be used as physiological assays in early-phase trials of experimental therapies for PD and other neurodegenerative disease.

Brain imaging research: does the science serve clinical practice?

Brain imaging represents a potent tool to characterize biomarkers, biological traits that are pathognomonic for specific neurological and neuropsychiatric disorders. Positron emission tomography (PET) and single photon emission computed tomography (SPECT) are imaging techniques used to identify alterations in the density and distribution of neurotransmitters, neuroreceptors, and transporters in specific regions of the brains of people with these disorders. Brain imaging research currently facilitates the elucidation of dysfunction of dopamine, serotonin, acetylcholine, and other substances in people with Alzheimer's and Parkinson's diseases, schizophrenia, alcoholism and other substance abuse disorders, attention deficit/hyperactivity disorder, and the syndromes of restless legs, Lesch-Nyhan, Rett, and Tourette. Thus, brain imaging research offers great potential for the diagnosis, treatment, prevention, and cure of neurological and neuropsychiatric disorders. Brain imaging research also facilitates new drug development and helps establish therapeutic doses of novel drugs. In particular, studies of specific receptors, such as the dopamine D2 receptor, before and after the administration of doses of drugs that occupy these D2 receptors, provide the means to determine receptor occupancy. For example, an optimal dose of D2 antagonist antipsychotics produces occupancy of 65% to 80% of D2 receptors, while a greater dose carries a risk of extrapyramidal side effects.

Assessment of the progression of Parkinson's disease: a metabolic network approach

BACKGROUND

Clinical research into Parkinson's disease has focused increasingly on the development of interventions that slow the neurodegeneration underlying this disorder. These investigations have stimulated interest in finding objective biomarkers that show changes in the rate of disease progression with treatment. Through radiotracer-based imaging of nigrostriatal dopaminergic function, a specific class of biomarkers to monitor the progression of Parkinson's disease has been identified, and these biomarkers were used in the clinical trials of drugs with the potential to modify the course of the disease. However, in some of these studies there was discordance between the imaging outcome measures and blinded clinical ratings of disease severity. Research is underway to identify and validate alternative ways to image brain metabolism, through which the efficacy of new therapies for Parkinson's disease and related disorders can be assessed.

RECENT DEVELOPMENTS

During recent years, spatial covariance analysis has been used with (18)F-fluorodeoxyglucose PET to detect abnormal patterns of brain metabolism in patients with neurodegenerative disorders. Rapid, automated, voxel-based algorithms have been used with metabolic imaging to quantify the activity of disease-specific networks. This approach has helped to characterise the unique metabolic patterns associated with the motor and cognitive features of Parkinson's disease. The results of several studies have shown correction of abnormal motor, but not cognitive, network activity by treatment with dopaminergic therapy and deep brain stimulation. The authors of a longitudinal imaging study of early-stage Parkinson's disease reported substantial differences in the development of these metabolic networks over a follow-up of 4 years. WHERE NEXT?: Developments in network imaging have provided the basis for several new applications of metabolic imaging in the study of Parkinson's disease. A washout study is currently underway to determine the long-duration effects of dopaminergic therapy on the network activity related to Parkinson's disease, which will be useful to plan future trials of disease-modifying drugs. Network approaches are also being applied to the study of atypical parkinsonian syndromes. The characterisation of specific patterns associated with atypical parkinsonian syndromes and classic Parkinson's disease will be the basis for a fully automated imaging-based procedure for early differential diagnosis. Efforts are underway to quantify the networks related to Parkinson's disease with less invasive imaging methods. Assessments of network activity with perfusion-weighted MRI show excellent concordance with measurements done with established radiotracer techniques. This approach will ultimately enable the assessment of abnormal network activity in people who are genetically at risk of Parkinson's disease.

Molecular Neuroimaging: From Conventional to Emerging Techniques

The use of molecular imaging techniques in the central nervous system (CNS) has a rich history. Most of the important developments in imaging-such as computed tomography, magnetic resonance imaging, single photon emission computed tomography, and positron emission tomography-began with neuropsychiatric applications. These techniques and modalities were then found to be useful for imaging other organs involved with various disease processes. Molecular imaging of the CNS has enabled scientists and researchers to understand better the basic biology of brain function and the way in which various disease processes affect the brain. Unlike other organs, the brain is not easily accessible, and it has a highly selective barrier at the endothelial cell level known as the blood-brain barrier. Furthermore, the brain is the most complex cellular network known to exist. Various neurotransmitters act in either an excitatory or an inhibitory fashion on adjacent neurons through a multitude of mechanisms. The various neuronal systems and the myriad of neurotransmitter systems become altered in many diseases. Some of the most devastating diseases, including Alzheimer disease, Parkinson disease, brain tumors, psychiatric disease, and numerous degenerative neurologic diseases, affect only the brain. Molecular neuroimaging will be critical to the future understanding and treatment of these diseases. Molecular neuroimaging of the brain shows tremendous promise for clinical application. In this article, the current state and clinical applications of molecular neuroimaging will be reviewed.

The assessment of neurological systems with functional imaging

In recent years a number of multivariate approaches have been introduced to map neural systems in health and disease. In this review, we focus on spatial covariance methods applied to functional imaging data to identify patterns of regional activity associated with behavior. In the rest state, this form of network analysis can be used to detect abnormal topographies reflecting regional changes in distributed neural systems. In activation experiments, this approach can be used to quantify network-performance relationships in normal and disease cohorts. Functional changes in the relevant neural systems are likely to underlie the behavioral abnormalities observed in a variety of disease and treatment conditions.

Changes in network activity with the progression of Parkinson's disease

Parkinson's disease (PD) is associated with abnormal activity in spatially distributed neural systems mediating the motor and cognitive manifestations of this disorder. Metabolic PET studies have demonstrated that this illness is characterized by a set of reproducible functional brain networks that correlate with these clinical features. The time at which these abnormalities appear is unknown, as is their relationship to concurrent clinical and dopaminergic indices of disease progression. In this longitudinal study, 15 early stage PD patients (age 58.0 +/- 10.2 years; Hoehn and Yahr Stage 1.2 +/- 0.3) were enrolled within 2 years of diagnosis. The subjects underwent multitracer PET imaging at baseline, 24 and 48 months. At each timepoint they were scanned with [18F]-fluorodeoxyglucose (FDG) to assess longitudinal changes in regional glucose utilization and in the expression of the PD-related motor (PDRP) and cognitive metabolic covariance patterns (PDCP). At each timepoint the subjects also underwent PET imaging with [18F]-fluoropropyl betaCIT (FP-CIT) to quantify longitudinal changes in caudate and putamen dopamine transporter (DAT) binding. Regional metabolic changes across the three timepoints were localized using statistical parametric mapping (SPM). Longitudinal changes in regional metabolism and network activity, caudate/putamen DAT binding, and Unified Parkinson's Disease Rating Scale (UPDRS) motor ratings were assessed using repeated measures analysis of variance (RMANOVA). Relationships between these measures of disease progression were assessed by computing within-subject correlation coefficients. We found that disease progression was associated with increasing metabolism in the subthalamic nucleus (STN) and internal globus pallidus (GPi) (P < 0.001), as well as in the dorsal pons and primary motor cortex (P < 0.0001). Advancing disease was also associated with declining metabolism in the prefrontal and inferior parietal regions (P < 0.001). PDRP expression was elevated at baseline relative to healthy control subjects (P < 0.04), and increased progressively over time (P < 0.0001). PDCP activity also increased with time (P < 0.0001). However, these changes in network activity were slower than for the PDRP (P < 0.04), reaching abnormal levels only at the final timepoint. Changes in PDRP activity, but not PDCP activity, correlated with concurrent declines in striatal DAT binding (P < 0.01) and increases in motor ratings (P < 0.005). Significant within-subject correlations (P < 0.01) were also evident between the latter two progression indices. The early stages of PD are associated with progressive increases and decreases in regional metabolism at key nodes of the motor and cognitive networks that characterize the illness. Potential disease-modifying therapies may alter the time course of one or both of these abnormal networks.

Functional imaging of cerebral blood flow and glucose metabolism in Parkinson's disease and Huntington's disease

Brain imaging of cerebral blood flow and glucose metabolism has been playing key roles in describing pathophysiology of Parkinson's disease (PD) and Huntington's disease (HD), respectively. Many biomarkers have been developed in recent years to investigate the abnormality in molecular substrate, track the time course of disease progression, and evaluate the efficacy of novel experimental therapeutics. A growing body of literature has emerged on neurobiology of these two movement disorders in resting states and in response to brain activation tasks. In this paper, we review the latest applications of these approaches in patients and normal volunteers at rest conditions. The discussions focus on brain mapping studies with univariate and multivariate statistical analyses on a voxel basis. In particular, we present data to validate the reproducibility and reliability of unique spatial covariance patterns related with PD and HD.

Subthalamic glutamic acid decarboxylase gene therapy: changes in motor function and cortical metabolism

Parkinson's disease (PD) is associated with increased excitatory activity within the subthalamic nucleus (STN). We sought to inhibit STN output in hemiparkinsonian macaques by transfection with adeno-associated virus (AAV) containing the gene for glutamic acid decarboxylase (GAD). In total, 13 macaques were rendered hemiparkinsonian by right intracarotid 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine injection. Seven animals were injected with AAV-GAD into the right STN, and six received an AAV gene for green fluorescent protein (GFP). Videotaped motor ratings were performed in a masked fashion on a weekly basis over a 55-week period. At 56 weeks, the animals were scanned with (18)F-fluorodeoxyglucose (FDG) positron emission tomography (PET). Histological examination was performed at the end of the study. No adverse events were observed after STN gene therapy. We found that the clinical rating scores for the two treatment groups had different patterns of change over time (group x time interaction, P<0.001). On FDG PET, the GAD animals exhibited an increase in glucose utilization in the right motor cortex relative to GFP controls (P<0.001). Metabolism in this region correlated with clinical ratings at end point (P<0.01). Histology confirmed GAD expression in treated animals. These findings suggest that STN AAV-GAD is well tolerated and potentially effective in a primate model of PD. The changes in motor cortical glucose utilization observed after gene therapy are consistent with the modulation of metabolic brain networks associated with this disorder.

Abnormal metabolic network activity in Parkinson's disease: test-retest reproducibility

Parkinson's disease (PD) is associated with an abnormal pattern of regional brain function. The expression of this PD-related covariance pattern (PDRP) has been used to assess disease progression and the response to treatment. In this study, we validated the PDRP network as a measure of parkinsonism by prospectively computing its expression (PDRP scores) in (15)O-water (H(2)(15)O) and (18)F-fluorodeoxyglucose (FDG) positron emission tomography (PET) scans from PD patients and healthy volunteers. The reliability of this measure was also assessed within subjects using a test-retest design in mildly affected and advanced PD patients scanned at baseline and during treatment with levodopa or deep brain stimulation (DBS). We found that PDRP expression was significantly elevated in PD patients (P<0.001) relative to controls in a prospective analysis of brain scans obtained with either H(2)(15)O or FDG PET. A significant correlation (R(2)=0.61; P<0.001) was evident between PDRP scores computed from H(2)(15)O and FDG images in PD subjects scanned with both tracers. Test-retest reproducibility was very high (intraclass correlation coefficient (ICC)>0.92) for PDRP scores measured both within PET session and between sessions separated by up to 2 months. This high reproducibility was observed in both early stage and advanced PD patients scanned at baseline and during treatment. The within-subject variability of this measure was less than 10% for both unmedicated and treated conditions. These findings suggest that the PDRP network is a reproducible and stable descriptor of regional functional abnormalities in parkinsonism. The quantification of PDRP expression in PD patients can serve as a potential biomarker in PET intervention studies for this disorder.

Prodromal non-motor symptoms of Parkinson's disease

The motor symptoms of Parkinson's disease (PD), bradykinesia, muscular rigidity, and tremor depend upon degeneration of the dopaminergic neurons in the substantia nigra pars compacta. Recent neuropathological studies show that the Lewy bodies, the intraneuronal landmark of PD, accumulate in several neuronal cell types in the brain. An ascending gradient of pathological involvement, from the medulla oblongata to neocortical areas has been reported. Thus the original view of PD as a disease characterized by selective damage of the dopaminergic neurons in the mesencephalon should be updated into the concept of a severe multisystemic neurodegenerative disorder. Additionally, the neuropathological alterations outside the substantia nigra are soundly correlated with the non-motor symptoms of PD. As a result of these findings, interest is growing in the identification of prodromal non-motor symptoms of PD. Indeed, data from the literature suggest that autonomic disturbances, olfactory dysfunctions, depression and sleep disorders (in particular REM-sleep behavior disorder) may represent prodromal non-motor symptoms of PD. Several tests are available to detect most of these symptoms. Thus, the identification of prodromal non-motor symptoms may contribute to the precocious diagnosis of PD, and might be useful in the future to test the efficacy of neuroprotective agents.

Metabolic brain networks associated with cognitive function in Parkinson's disease

The motor manifestations of Parkinson's disease (PD) have been linked to an abnormal spatial covariance pattern involving basal ganglia thalamocortical pathways. By contrast, little is known about the functional networks that underlie cognitive dysfunction in this disorder. To identify such patterns, we studied 15 non-demented PD patients using FDG PET and a voxel-based network modeling approach. We detected a significant covariance pattern that correlated (p<0.01) with performance on tests of memory and executive functioning. This PD-related cognitive pattern (PDCP) was characterized by metabolic reductions in frontal and parietal association areas and relative increases in the cerebellar vermis and dentate nuclei. To validate this pattern, we analyzed data from 32 subsequent PD patients of similar age, disease duration and severity. Prospective measurements of PDCP activity predicted memory performance (p<0.005), visuospatial function (p<0.01), and perceptual motor speed (p<0.005) in this validation sample. PDCP scores additionally exhibited an excellent degree of test-retest reliability (intraclass correlation coefficient, ICC=0.89) in patients undergoing repeat FDG PET at an 8-week interval. Unlike the PD-related motor pattern, PDCP expression was not significantly altered by antiparkinsonian treatment with either intravenous levodopa or deep brain stimulation (DBS). These findings substantiate the PDCP as a reproducible imaging marker of cognitive function in PD. Because PDCP expression is not altered by routine antiparkinsonian treatment, this measure of network activity may prove useful in clinical trials targeting the progression of non-motor manifestations of this disorder.

Regional metabolic changes in Parkinsonian patients with normal dopaminergic imaging

Dopaminergic imaging has been found to be normal in approximately 15% of parkinsonian patients enrolled in neuroprotective trials. We used (18)F-fluorodeoxyglucose positron emission tomography (FDG PET) to determine the metabolic basis for this finding. We reviewed scans from 185 patients with clinical signs of Parkinson's disease (PD) who underwent (18)F-fluorodopa PET imaging for diagnostic confirmation. Of this group, 27 patients (14.6%) had quantitatively normal scans; 8 of these patients were additionally scanned with FDG PET. Pattern analysis was performed on an individual scan basis to determine whether the metabolic changes were consistent with classic PD. Computer-assisted single-case assessments of the FDG PET scans of these 8 patients did not disclose patterns of regional metabolic change compatible with classical PD or an atypical parkinsonian variant. Similarly, network quantification revealed that PD-related pattern expression was not elevated in these patients as it was in an age- and duration-matched cohort with classical PD (P < 0.0001). None of these patients developed clinical signs of classical PD or of an atypical parkinsonian syndrome at a follow-up visit conducted 3 years after imaging. The results suggest that parkinsonian subjects with normal dopaminergic imaging do not have evidence of classical PD or an atypical parkinsonian syndrome.

Quantification of Parkinson's disease-related network expression with ECD SPECT

PURPOSE

Spatial covariance analysis has been used with FDG PET to identify a specific metabolic network associated with Parkinson's disease (PD). In the current study, we utilized a new, fully automated voxel-based method to quantify network expression in ECD SPECT images from patients with classical PD, patients with multiple system atrophy (MSA), and healthy control subjects.

METHODS

We applied a previously validated voxel-based PD-related covariance pattern (PDRP) to quantify network expression in the ECD SPECT scans of 35 PD patients, 15 age- and disease severity-matched MSA patients, and 35 age-matched healthy control subjects. PDRP scores were compared across groups using analysis of variance. The sensitivity and specificity of the prospectively computed PDRP scores in the differential diagnosis of individual subjects were assessed by receiver operating characteristic (ROC) analysis.

RESULTS

PDRP scores were significantly increased (p < 0.001) in the PD group relative to the MSA and control groups. ROC analysis indicated that the overall diagnostic accuracy of the PDRP measures was 0.91 (AUC). The optimal cutoff value was consistent with a sensitivity of 0.97 and a specificity of 0.80 and 0.71 for discriminating PD patients from MSA and normal controls, respectively.

CONCLUSION

Our findings suggest that fully automated voxel-based network assessment techniques can be used to quantify network expression in the ECD SPECT scans of parkinsonian patients.

Applications of Clinical Dopamine Imaging

Recent technologic advances make it increasingly possible to image neurotransmitter systems in living human brain, The dopamine system has been most intensively studied owing to its involvement in several brain disorders such as Parkinson's disease and Huntington's disease, as well as psychiatric disorders such as schizophrenia, depression, and compulsive behavioral disorders of multiple types. A variety of aspects of dopamine receptor density, function, and dopaminergic terminal status can now be assessed using the minimally invasive neuroimaging techniques of positron emission tomography and single-photon emission computed tomography. Although these techniques are currently used most often in the context of research, clinical applications are rapidly emerging.

Network modulation by the subthalamic nucleus in the treatment of Parkinson's disease

Deep brain stimulation of the subthalamic nucleus (STN DBS) has become an accepted tool for the treatment of Parkinson's disease (PD). Although the precise mechanism of action of this intervention is unknown, its effectiveness has been attributed to the modulation of pathological network activity. We examined this notion using positron emission tomography (PET) to quantify stimulation-induced changes in the expression of a PD-related covariance pattern (PDRP) of regional metabolism. These metabolic changes were also compared with those observed in a similar cohort of patients undergoing STN lesioning. We found that PDRP activity declined significantly (P < 0.02) with STN stimulation. The degree of network modulation with DBS did not differ from that measured following lesioning (P = 0.58). Statistical parametric mapping (SPM) revealed that metabolic reductions in the internal globus pallidus (GPi) and caudal midbrain were common to both STN interventions (P < 0.01), although declines in GPi were more pronounced with lesion. By contrast, elevations in posterior parietal metabolism were common to the two procedures, albeit more pronounced with stimulation. These findings indicate that suppression of abnormal network activity is a feature of both STN stimulation and lesioning. Nonetheless, these two interventions may differ metabolically at a regional level.