Tc-99m ethylene cysteinate dimer SPECT in the differential diagnosis of parkinsonism

Longitudinal Network Changes and Phenoconversion Risk in Isolated REM Sleep Behavior Disorder

Isolated rapid eye movement sleep behavior disorder (iRBD) is a prodromal syndrome for Parkinson's disease (PD) and related α-synucleinopathies. We conducted a longitudinal imaging study of network changes in iRBD and their relationship to phenoconversion. Expression levels for the PD-related motor and cognitive networks (PDRP and PDCP) were measured at baseline, 2 and 4 years, along with dopamine transporter (DAT) binding. PDRP and PDCP expression increased over time, with higher values in the former network. While abnormal functional connections were identified initially within the PDRP, others bridging the two networks appeared later. A model based on the rates of PDRP progression and putamen dopamine loss predicted phenoconversion within 1.2 years in individuals with iRBD. In aggregate, the data suggest that maladaptive reorganization of brain networks takes place in iRBD years before phenoconversion. Network expression and DAT binding measures can be used together to assess phenoconversion risk in these individuals.

Parkinson's disease cerebrovascular reactivity pattern: A feasibility study

A mounting body of research points to cerebrovascular dysfunction as a fundamental element in the pathophysiology of Parkinson's disease (PD). In the current feasibility study, blood-oxygen-level-dependent (BOLD) MRI was used to measure cerebrovascular reactivity (CVR) in response to hypercapnia in 26 PD patients and 16 healthy controls (HC), and aimed to find a multivariate pattern specific to PD. Whole-brain maps of CVR amplitude (i.e., magnitude of response to CO2) and latency (i.e., time to reach maximum amplitude) were computed, which were further analyzed using scaled sub-profile model principal component analysis (SSM-PCA) with leave-one-out cross-validation. A meaningful pattern based on CVR latency was identified, which was named the PD CVR pattern (PD-CVRP). This pattern was characterized by relatively increased latency in basal ganglia, sensorimotor cortex, supplementary motor area, thalamus and visual cortex, as well as decreased latency in the cerebral white matter, relative to HC. There were no significant associations with clinical measures, though sample size may have limited our ability to detect significant associations. In summary, the PD-CVRP highlights the importance of cerebrovascular dysfunction in PD, and may be a potential biomarker for future clinical research and practice.

Outcome Measures for Disease-Modifying Trials in Parkinson's Disease: Consensus Paper by the EJS ACT-PD Multi-Arm Multi-Stage Trial Initiative

BACKGROUND

Multi-arm, multi-stage (MAMS) platform trials can accelerate the identification of disease-modifying treatments for Parkinson's disease (PD) but there is no current consensus on the optimal outcome measures (OM) for this approach.

OBJECTIVE

To provide an up-to-date inventory of OM for disease-modifying PD trials, and a framework for future selection of OM for such trials.

METHODS

As part of the Edmond J Safra Accelerating Clinical Trials in Parkinson Disease (EJS ACT-PD) initiative, an expert group with Patient and Public Involvement and Engagement (PPIE) representatives' input reviewed and evaluated available evidence on OM for potential use in trials to delay progression of PD. Each OM was ranked based on aspects such as validity, sensitivity to change, participant burden and practicality for a multi-site trial. Review of evidence and expert opinion led to the present inventory.

RESULTS

An extensive inventory of OM was created, divided into: general, motor and non-motor scales, diaries and fluctuation questionnaires, cognitive, disability and health-related quality of life, capability, quantitative motor, wearable and digital, combined, resource use, imaging and wet biomarkers, and milestone-based. A framework for evaluation of OM is presented to update the inventory in the future. PPIE input highlighted the need for OM which reflect their experience of disease progression and are applicable to diverse populations and disease stages.

CONCLUSION

We present a range of OM, classified according to a transparent framework, to aid selection of OM for disease-modifying PD trials, whilst allowing for inclusion or re-classification of relevant OM as new evidence emerges.

Emerging targets signaling for inflammation in Parkinson's disease drug discovery

Parkinson's disease (PD) patients not only show motor features such as bradykinesia, tremor, and rigidity but also non-motor features such as anxiety, depression, psychosis, memory loss, attention deficits, fatigue, sexual dysfunction, gastrointestinal issues, and pain. Many pharmacological treatments are available for PD patients; however, these treatments are partially or transiently effective since they only decrease the symptoms. As these therapies are unable to restore dopaminergic neurons and stop the development of Parkinson's disease, therefore, the need for an effective therapeutic approach is required. The current review summarizes novel targets for PD, that can be utilized to identify disease-modifying treatments.

The Legacy of the TTASAAN Report - Premature Conclusions and Forgotten Promises About SPECT Neuroimaging: A Review of Policy and Practice Part II

Brain perfusion single photon emission computed tomography (SPECT) scans were initially developed in 1970s. A key radiopharmaceutical, hexamethylpropyleneamine oxime (HMPAO), was not stabilized until 1993 and most early SPECT scans were performed on single-head gamma cameras. These early scans were of inferior quality. In 1996, the Therapeutics and Technology Assessment Subcommittee of the American Academy of Neurology (TTASAAN) issued a report regarding the use of SPECT in the evaluation of neurological disorders. This two-part series explores the policies and procedures related to perfusion SPECT functional neuroimaging. In Part I, the comparison between the quality of the SPECT scans and the depth of the data for key neurological and psychiatric indications at the time of the TTASAAN report vs. the intervening 25 years were presented. In Part II, the technical aspects of perfusion SPECT neuroimaging and image processing will be explored. The role of color scales will be reviewed and the process of interpreting a SPECT scan will be presented. Interpretation of a functional brain scans requires not only anatomical knowledge, but also technical understanding on correctly performing a scan, regardless of the scanning modality. Awareness of technical limitations allows the clinician to properly interpret a functional brain scan. With this foundation, four scenarios in which perfusion SPECT neuroimaging, together with other imaging modalities and testing, lead to a narrowing of the differential diagnoses and better treatment. Lastly, recommendations for the revision of current policies and practices are made.

Spatial Covariance of Cholinergic Muscarinic M1 /M4 Receptors in Parkinson's Disease

BACKGROUND

Parkinson's disease (PD) is associated with cholinergic dysfunction, although the role of M1 and M4 receptors remains unclear.

OBJECTIVE

To investigate spatial covariance patterns of cholinergic muscarinic M₁ /M₄ receptors in PD and their relationship with cognition and motor symptoms.

METHODS

Some 19 PD and 24 older adult controls underwent ¹²³ I-iodo-quinuclidinyl-benzilate (QNB) (M₁ /M₄ receptor) and ^99m Tc-exametazime (perfusion) single-photon emission computed tomography (SPECT) scanning. We implemented voxel principal components analysis, producing a series of images representing patterns of intercorrelated voxels across individuals. Linear regression analyses derived specific M₁ /M₄ spatial covariance patterns associated with PD.

RESULTS

A cholinergic M₁ /M₄ pattern that converged onto key hubs of the default, auditory-visual, salience, and sensorimotor networks fully discriminated PD patients from controls (F_1,41  = 135.4, P < 0.001). In PD, we derived M₁ /M₄ patterns that correlated with global cognition (r = -0.62, P = 0.008) and motor severity (r = 0.53, P = 0.02). Both patterns emerged with a shared topography implicating the basal forebrain as well as visual, frontal executive, and salience circuits. Further, we found a M₁ /M₄ pattern that predicted global cognitive decline (r = 0.46, P = 0.04) comprising relative decreased binding within default and frontal executive networks.

CONCLUSIONS

Cholinergic muscarinic M₁ /M₄ modulation within key brain networks were apparent in PD. Cognition and motor severity were associated with a similar topography, inferring both phenotypes possibly rely on related cholinergic mechanisms. Relative decreased M₁ /M₄ binding within default and frontal executive networks could be an indicator of future cognitive decline. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

The Role of Frontal Assessment Battery and Frontal Lobe Single-Photon Emission Computed Tomography in the Differential Diagnosis of Progressive Supranuclear Palsy Variants and Corticobasal Syndrome-A Pilot Study

Progressive supranuclear palsy (PSP) and corticobasal syndrome (CBS) are clinical syndromes classified as atypical parkinsonism. Due to their overlapping symptomatology, recent research shows the necessity of finding new methods of examination of these clinical entities. PSP is a heterogenic disease. PSP Richardson-Steele Syndrome (PSP-RS) and parkinsonism predominant (PSP-P) are the most common clinical variants of progressive supranuclear palsy syndrome. The different clinical course and life expectancy of PSP-RS and PSP-P stress the need of efficient examination in the early stages. The aim of the study was to evaluate the possible feasibility of the combined use of frontal assessment battery (FAB) and single-photon emission computed tomography (SPECT) in the differentiation of PSP-RS, PSP-P, and CBS. The findings show that FAB may be interpreted as a possible supplementary tool in the differential diagnosis of PSP-P and PSP-RS. The differences in SPECT are less pronounced. The study does not show any advantages of performing combined frontal SPECT and FAB in the differential examination of PSP and CBS. Moreover, PSP-RS and CBS, in a detailed evaluation of the frontal lobe, do not show any significant differences. This is a relatively small study which, however, highlights the relevant features of clinical examination of these rare entities.

Parkinson's disease-related network topographies characterized with resting state functional MRI

Spatial covariance mapping can be used to identify and measure the activity of disease-related functional brain networks. While this approach has been widely used in the analysis of cerebral blood flow and metabolic PET scans, it is not clear whether it can be reliably applied to resting state functional MRI (rs-fMRI) data. In this study, we present a novel method based on independent component analysis (ICA) to characterize specific network topographies associated with Parkinson's disease (PD). Using rs-fMRI data from PD and healthy subjects, we used ICA with bootstrap resampling to identify a PD-related pattern that reliably discriminated the two groups. This topography, termed rs-MRI PD-related pattern (fPDRP), was similar to previously characterized disease-related patterns identified using metabolic PET imaging. Following pattern identification, we validated the fPDRP by computing its expression in rs-fMRI testing data on a prospective case basis. Indeed, significant increases in fPDRP expression were found in separate sets of PD and control subjects. In addition to providing a similar degree of group separation as PET, fPDRP values correlated with motor disability and declined toward normal with levodopa administration. Finally, we used this approach in conjunction with neuropsychological performance measures to identify a separate PD cognition-related pattern in the patients. This pattern, termed rs-fMRI PD cognition-related pattern (fPDCP), was topographically similar to its PET-derived counterpart. Subject scores for the fPDCP correlated with executive function in both training and testing data. These findings suggest that ICA can be used in conjunction with bootstrap resampling to identify and validate stable disease-related network topographies in rs-fMRI. Hum Brain Mapp 38:617-630, 2017. © 2016 Wiley Periodicals, Inc.

Movement disorders

Movement disorders can be hypokinetic (e.g., parkinsonism), hyperkinetic, or dystonic in nature and commonly arise from altered function in nuclei of the basal ganglia or their connections. As obvious structural changes are often limited, standard imaging plays less of a role than in other neurologic disorders. However, structural imaging is indicated where clinical presentation is atypical, particularly if the disorder is abrupt in onset or remains strictly unilateral. More recent advances in magnetic resonance imaging (MRI) may allow for differentiation between Parkinson's disease and atypical forms of parkinsonism. Functional imaging can assess regional cerebral blood flow (functional MRI (fMRI), positron emission tomography (PET), or single-photon emission computed tomography (SPECT)), cerebral glucose metabolism (PET), neurochemical and neuroreceptor status (PET and SPECT), and pathologic processes such as inflammation or abnormal protein deposition (PET) (Table 49.1). Cerebral blood flow can be assessed at rest, during the performance of motor or cognitive tasks, or in response to a variety of stimuli. In appropriate situations, the correct imaging modality and/or combination of modalities can be used to detect early disease or even preclinical disease, and to monitor disease progression and the effects of disease-modifying interventions. Various approaches are reviewed here.

Brain network markers of abnormal cerebral glucose metabolism and blood flow in Parkinson's disease

Neuroimaging of cerebral glucose metabolism and blood flow is ideally suited to assay widely-distributed brain circuits as a result of local molecular events and behavioral modulation in the central nervous system. With the progress in novel analytical methodology, this endeavor has succeeded in unraveling the mechanisms underlying a wide spectrum of neurodegenerative diseases. In particular, statistical brain mapping studies have made significant strides in describing the pathophysiology of Parkinson's disease (PD) and related disorders by providing signature biomarkers to determine the systemic abnormalities in brain function and evaluate disease progression, therapeutic responses, and clinical correlates in patients. In this article, we review the relevant clinical applications in patients in relation to healthy volunteers with a focus on the generation of unique spatial covariance patterns associated with the motor and cognitive symptoms underlying PD. These characteristic biomarkers can be potentially used not only to improve patient recruitment but also to predict outcomes in clinical trials.

Striatal vessels receive phosphorylated tyrosine hydroxylase-rich innervation from midbrain dopaminergic neurons

Nowadays it is assumed that besides its roles in neuronal processing, dopamine (DA) is also involved in the regulation of cerebral blood flow. However, studies on the hemodynamic actions of DA have been mainly focused on the cerebral cortex, but the possibility that vessels in deeper brain structures receive dopaminergic axons and the origin of these axons have not been investigated. Bearing in mind the evidence of changes in the blood flow of basal ganglia in Parkinson's disease (PD), and the pivotal role of the dopaminergic mesostriatal pathway in the pathophysiology of this disease, here we studied whether striatal vessels receive inputs from midbrain dopaminergic neurons. The injection of an anterograde neuronal tracer in combination with immunohistochemistry for dopaminergic, vascular and astroglial markers, and dopaminergic lesions, revealed that midbrain dopaminergic axons are in close apposition to striatal vessels and perivascular astrocytes. These axons form dense perivascular plexuses restricted to striatal regions in rats and monkeys. Interestingly, they are intensely immunoreactive for tyrosine hydroxylase (TH) phosphorylated at Ser19 and Ser40 residues. The presence of phosphorylated TH in vessel terminals indicates they are probably the main source of basal TH activity in the striatum, and that after activation of midbrain dopaminergic neurons, DA release onto vessels precedes that onto neurons. Furthermore, the relative weight of this "vascular component" within the mesostriatal pathway suggests that it plays a relevant role in the pathophysiology of PD.

Abnormal metabolic network activity in REM sleep behavior disorder

OBJECTIVE

To determine whether the Parkinson disease-related covariance pattern (PDRP) expression is abnormally increased in idiopathic REM sleep behavior disorder (RBD) and whether increased baseline activity is associated with greater individual risk of subsequent phenoconversion.

METHODS

For this cohort study, we recruited 2 groups of RBD and control subjects. Cohort 1 comprised 10 subjects with RBD (63.5 ± 9.4 years old) and 10 healthy volunteers (62.7 ± 8.6 years old) who underwent resting-state metabolic brain imaging with (18)F-fluorodeoxyglucose PET. Cohort 2 comprised 17 subjects with RBD (68.9 ± 4.8 years old) and 17 healthy volunteers (66.6 ± 6.0 years old) who underwent resting brain perfusion imaging with ethylcysteinate dimer SPECT. The latter group was followed clinically for 4.6 ± 2.5 years by investigators blinded to the imaging results. PDRP expression was measured in both RBD groups and compared with corresponding control values.

RESULTS

PDRP expression was elevated in both groups of subjects with RBD (cohort 1: p < 0.04; cohort 2: p < 0.005). Of the 17 subjects with long-term follow-up, 8 were diagnosed with Parkinson disease or dementia with Lewy bodies; the others did not phenoconvert. For individual subjects with RBD, final phenoconversion status was predicted using a logistical regression model based on PDRP expression and subject age at the time of imaging (r(2) = 0.64, p < 0.0001).

CONCLUSIONS

Latent network abnormalities in subjects with idiopathic RBD are associated with a greater likelihood of subsequent phenoconversion to a progressive neurodegenerative syndrome.

Functional reorganization of motor and limbic circuits after exercise training in a rat model of bilateral parkinsonism

Exercise training is widely used for neurorehabilitation of Parkinson's disease (PD). However, little is known about the functional reorganization of the injured brain after long-term aerobic exercise. We examined the effects of 4 weeks of forced running wheel exercise in a rat model of dopaminergic deafferentation (bilateral, dorsal striatal 6-hydroxydopamine lesions). One week after training, cerebral perfusion was mapped during treadmill walking or at rest using [(14)C]-iodoantipyrine autoradiography. Regional cerebral blood flow-related tissue radioactivity (rCBF) was analyzed in three-dimensionally reconstructed brains by statistical parametric mapping. In non-exercised rats, lesions resulted in persistent motor deficits. Compared to sham-lesioned rats, lesioned rats showed altered functional brain activation during walking, including: 1. hypoactivation of the striatum and motor cortex; 2. hyperactivation of non-lesioned areas in the basal ganglia-thalamocortical circuit; 3. functional recruitment of the red nucleus, superior colliculus and somatosensory cortex; 4. hyperactivation of the ventrolateral thalamus, cerebellar vermis and deep nuclei, suggesting recruitment of the cerebellar-thalamocortical circuit; 5. hyperactivation of limbic areas (amygdala, hippocampus, ventral striatum, septum, raphe, insula). These findings show remarkable similarities to imaging findings reported in PD patients. Exercise progressively improved motor deficits in lesioned rats, while increasing activation in dorsal striatum and rostral secondary motor cortex, attenuating a hyperemia of the zona incerta and eliciting a functional reorganization of regions participating in the cerebellar-thalamocortical circuit. Both lesions and exercise increased activation in mesolimbic areas (amygdala, hippocampus, ventral striatum, laterodorsal tegmental n., ventral pallidum), as well as in related paralimbic regions (septum, raphe, insula). Exercise, but not lesioning, resulted in decreases in rCBF in the medial prefrontal cortex (cingulate, prelimbic, infralimbic). Our results in this PD rat model uniquely highlight the breadth of functional reorganizations in motor and limbic circuits following lesion and long-term, aerobic exercise, and provide a framework for understanding the neural substrates underlying exercise-based neurorehabilitation.

Identification of disease-related spatial covariance patterns using neuroimaging data

The scaled subprofile model (SSM)(1-4) is a multivariate PCA-based algorithm that identifies major sources of variation in patient and control group brain image data while rejecting lesser components (Figure 1). Applied directly to voxel-by-voxel covariance data of steady-state multimodality images, an entire group image set can be reduced to a few significant linearly independent covariance patterns and corresponding subject scores. Each pattern, termed a group invariant subprofile (GIS), is an orthogonal principal component that represents a spatially distributed network of functionally interrelated brain regions. Large global mean scalar effects that can obscure smaller network-specific contributions are removed by the inherent logarithmic conversion and mean centering of the data(2,5,6). Subjects express each of these patterns to a variable degree represented by a simple scalar score that can correlate with independent clinical or psychometric descriptors(7,8). Using logistic regression analysis of subject scores (i.e. pattern expression values), linear coefficients can be derived to combine multiple principal components into single disease-related spatial covariance patterns, i.e. composite networks with improved discrimination of patients from healthy control subjects(5,6). Cross-validation within the derivation set can be performed using bootstrap resampling techniques(9). Forward validation is easily confirmed by direct score evaluation of the derived patterns in prospective datasets(10). Once validated, disease-related patterns can be used to score individual patients with respect to a fixed reference sample, often the set of healthy subjects that was used (with the disease group) in the original pattern derivation(11). These standardized values can in turn be used to assist in differential diagnosis(12,13) and to assess disease progression and treatment effects at the network level(7,14-16). We present an example of the application of this methodology to FDG PET data of Parkinson's Disease patients and normal controls using our in-house software to derive a characteristic covariance pattern biomarker of disease.

Functional neuroimaging in Parkinson's disease

The use of functional imaging in neurodegenerative diseases has increased in recent years, with applications in research into the underlying pathophysiology, aiding in diagnosis, or evaluating new treatments. In Parkinson's disease (PD), these imaging methods have expanded our understanding of the disease beyond dopaminergic deficits. Moreover, functional imaging methods have described alterations in functional networks relating not only to the motor symptoms, but also to many nonmotor features of PD, such as cognitive dysfunction. From a clinical viewpoint, functional imaging methods can assist in monitoring disease progression, such as in the context of clinical trials, and holds the potential to aid in early diagnosis of PD and differentiation from other parkinsonian disorders.

EFNS/MDS-ES/ENS [corrected] recommendations for the diagnosis of Parkinson's disease

BACKGROUND

A Task Force was convened by the EFNS/MDS-ES Scientist Panel on Parkinson's disease (PD) and other movement disorders to systemically review relevant publications on the diagnosis of PD.

METHODS

Following the EFNS instruction for the preparation of neurological diagnostic guidelines, recommendation levels have been generated for diagnostic criteria and investigations.

RESULTS

For the clinical diagnosis, we recommend the use of the Queen Square Brain Bank criteria (Level B). Genetic testing for specific mutations is recommended on an individual basis (Level B), taking into account specific features (i.e. family history and age of onset). We recommend olfactory testing to differentiate PD from other parkinsonian disorders including recessive forms (Level A). Screening for pre-motor PD with olfactory testing requires additional tests due to limited specificity. Drug challenge tests are not recommended for the diagnosis in de novo parkinsonian patients. There is an insufficient evidence to support their role in the differential diagnosis between PD and other parkinsonian syndromes. We recommend an assessment of cognition and a screening for REM sleep behaviour disorder, psychotic manifestations and severe depression in the initial evaluation of suspected PD cases (Level A). Transcranial sonography is recommended for the differentiation of PD from atypical and secondary parkinsonian disorders (Level A), for the early diagnosis of PD and in the detection of subjects at risk for PD (Level A), although the technique is so far not universally used and requires some expertise. Because specificity of TCS for the development of PD is limited, TCS should be used in conjunction with other screening tests. Conventional magnetic resonance imaging and diffusion-weighted imaging at 1.5 T are recommended as neuroimaging tools that can support a diagnosis of multiple system atrophy (MSA) or progressive supranuclear palsy versus PD on the basis of regional atrophy and signal change as well as diffusivity patterns (Level A). DaTscan SPECT is registered in Europe and the United States for the differential diagnosis between degenerative parkinsonisms and essential tremor (Level A). More specifically, DaTscan is indicated in the presence of significant diagnostic uncertainty such as parkinsonism associated with neuroleptic exposure and atypical tremor manifestations such as isolated unilateral postural tremor. Studies of [(123) I]MIBG/SPECT cardiac uptake may be used to identify patients with PD versus controls and MSA patients (Level A). All other SPECT imaging studies do not fulfil registration standards and cannot be recommended for routine clinical use. At the moment, no conclusion can be drawn as to diagnostic efficacy of autonomic function tests, neurophysiological tests and positron emission tomography imaging in PD.

CONCLUSIONS

The diagnosis of PD is still largely based on the correct identification of its clinical features. Selected investigations (genetic, olfactory, and neuroimaging studies) have an ancillary role in confirming the diagnosis, and some of them could be possibly used in the near future to identify subjects in a pre-symptomatic phase of the disease.

Characterization of disease-related covariance topographies with SSMPCA toolbox: effects of spatial normalization and PET scanners

To generate imaging biomarkers from disease-specific brain networks, we have implemented a general toolbox to rapidly perform scaled subprofile modeling (SSM) based on principal component analysis (PCA) on brain images of patients and normals. This SSMPCA toolbox can define spatial covariance patterns whose expression in individual subjects can discriminate patients from controls or predict behavioral measures. The technique may depend on differences in spatial normalization algorithms and brain imaging systems. We have evaluated the reproducibility of characteristic metabolic patterns generated by SSMPCA in patients with Parkinson's disease (PD). We used [(18) F]fluorodeoxyglucose PET scans from patients with PD and normal controls. Motor-related (PDRP) and cognition-related (PDCP) metabolic patterns were derived from images spatially normalized using four versions of SPM software (spm99, spm2, spm5, and spm8). Differences between these patterns and subject scores were compared across multiple independent groups of patients and control subjects. These patterns and subject scores were highly reproducible with different normalization programs in terms of disease discrimination and cognitive correlation. Subject scores were also comparable in patients with PD imaged across multiple PET scanners. Our findings confirm a very high degree of consistency among brain networks and their clinical correlates in PD using images normalized in four different SPM platforms. SSMPCA toolbox can be used reliably for generating disease-specific imaging biomarkers despite the continued evolution of image preprocessing software in the neuroimaging community. Network expressions can be quantified in individual patients independent of different physical characteristics of PET cameras.

Movement disorders in systemic lupus erythematosus and the antiphospholipid syndrome

Movement disorders (MDs), particularly chorea, may be the presenting neurological complication of systemic lupus erythematosus (SLE) and the antiphospholipid syndrome (APS), but the association is not often initially recognized. Current evidence suggests an autoimmune mechanism related to antiphospholipid antibodies in these two conditions, although the antigenic target within the central nervous system has not yet been identified. Based on a comprehensive review of the literature, this article summarizes the current knowledge on MDs in SLE and APS. A high index of suspicion is required to make an early diagnosis and initiate appropriate treatment to provide symptomatic relief and to prevent other systemic complications related to the autoimmune process.

Metabolic brain networks in translational neurology: concepts and applications

Over the past 2 decades, functional imaging techniques have become commonplace in the study of brain disease. Nevertheless, very few validated analytical methods have been developed specifically to identify and measure systems-level abnormalities in living patients. Network approaches are particularly relevant for translational research in the neurodegenerative disorders, which often involve stereotyped abnormalities in brain organization. In recent years, spatial covariance mapping, a multivariate analytical tool applied mainly to metabolic images acquired in the resting state, has provided a useful means of objectively assessing brain disorders at the network level. By quantifying network activity in individual subjects on a scan-by-scan basis, this technique makes it possible to objectively assess disease progression and the response to treatment on a system-wide basis. To illustrate the utility of network imaging in neurological research, we review recent applications of this approach in the study of Parkinson disease and related movement disorders. Novel uses of the technique are discussed, including the prediction of cognitive responses to dopaminergic therapy, evaluation of the effects of placebo treatment on network activity, assessment of preclinical disease progression, and the use of automated pattern-based algorithms to enhance diagnostic accuracy.

Functional brain networks and abnormal connectivity in the movement disorders

Clinical manifestations of movement disorders, such as Parkinson's disease (PD) and dystonia, arise from neurophysiological changes within the cortico-striato-pallidothalamocortical (CSPTC) and cerebello-thalamo-cortical (CbTC) circuits. Neuroimaging techniques that probe connectivity within these circuits can be used to understand how these disorders develop as well as identify potential targets for medical and surgical therapies. Indeed, network analysis of (18)F-fluorodeoxyglucose (FDG) positron emission tomography (PET) has identified abnormal metabolic networks associated with the cardinal motor symptoms of PD, such as akinesia and tremor, as well as PD-related cognitive dysfunction. More recent task-based and resting state functional magnetic resonance imaging studies have reproduced several of the altered connectivity patterns identified in these abnormal PD-related networks. A similar network analysis approach in dystonia revealed abnormal disease related metabolic patterns in both manifesting and non-manifesting carriers of dystonia mutations. Other multimodal imaging approaches using magnetic resonance diffusion tensor imaging in patients with primary genetic dystonia suggest abnormal connectivity within the CbTC circuits mediate the clinical manifestations of this inherited neurodevelopmental disorder. Ongoing developments in functional imaging and future studies in early patients are likely to enhance our understanding of these movement disorders and guide novel targets for future therapies.

Milestones in neuroimaging

In the last 25 years there have been enormous advances in brain imaging. In addition to utility in diagnosis, these have led to novel insights into the pathogenesis of basal ganglia disease and the role of dopamine and the basal ganglia in normal health. The authors review highlights of this work, with a focus on advances in Parkinson's disease, the dystonias, Huntington's disease, and the role of dopamine in cognition and reward signaling. Emerging areas for future development include studies of functional connectivity, the analysis of default mode networks, studies of novel neurochemical pathways, methods to study disease pathogenesis, and the application of imaging techniques to investigate animal models of disease.

Brain perfusion and markers of neurodegeneration in rapid eye movement sleep behavior disorder

Potential early markers of neurodegeneration such as subtle motor signs, reduced color discrimination, olfactory impairment, and brain perfusion abnormalities have been reported in idiopathic rapid eye movement sleep behavior disorder, a risk factor for Parkinson's disease and Lewy body dementia. The aim of this study was to reproduce observations of regional cerebral blood flow abnormalities in a larger independent sample of patients and to explore correlations between regional cerebral blood flow and markers of neurodegeneration. Twenty patients with idiopathic rapid eye movement sleep behavior disorder and 20 healthy controls were studied by single-photon emission computerized tomography. Motor examination, color discrimination, and olfactory identification were examined. Patients with rapid eye movement sleep behavior disorder showed decreased regional cerebral blood flow in the frontal cortex and in medial parietal areas and increased regional cerebral blood flow in subcortical regions including the bilateral pons, putamen, and hippocampus. In rapid eye movement sleep behavior disorder, brain perfusion in the frontal cortex and occipital areas was associated with poorer performance in the color discrimination test. Moreover, a relationship between loss of olfactory discrimination and regional cerebral blood flow reduction in the bilateral anterior parahippocampal gyrus, a region known to be involved in olfactory functions, was found. This study provides further evidence of regional cerebral blood flow abnormalities in rapid eye movement sleep behavior disorder that are similar to those seen in Parkinson's disease and Lewy body dementia. Moreover, regional cerebral blood flow anomalies were associated with markers of neurodegeneration.

Abnormal metabolic brain networks in Parkinson's disease from blackboard to bedside

Metabolic imaging in the rest state has provided valuable information concerning the abnormalities of regional brain function that underlie idiopathic Parkinson's disease (PD). Moreover, network modeling procedures, such as spatial covariance analysis, have further allowed for the quantification of these changes at the systems level. In recent years, we have utilized this strategy to identify and validate three discrete metabolic networks in PD associated with the motor and cognitive manifestations of the disease. In this chapter, we will review and compare the specific functional topographies underlying parkinsonian akinesia/rigidity, tremor, and cognitive disturbance. While network activity progressed over time, the rate of change for each pattern was distinctive and paralleled the development of the corresponding clinical symptoms in early-stage patients. This approach is already showing great promise in identifying individuals with prodromal manifestations of PD and in assessing the rate of progression before clinical onset. Network modulation was found to correlate with the clinical effects of dopaminergic treatment and surgical interventions, such as subthalamic nucleus (STN) deep brain stimulation (DBS) and gene therapy. Abnormal metabolic networks have also been identified for atypical parkinsonian syndromes, such as multiple system atrophy (MSA) and progressive supranuclear palsy (PSP). Using multiple disease-related networks for PD, MSA, and PSP, we have developed a novel, fully automated algorithm for accurate classification at the single-patient level, even at early disease stages.

Regional cerebral blood flow changes in patients with idiopathic REM sleep behavior disorder

BACKGROUND

Recent studies have shown an association between rapid eye movement sleep behavior disorder (RBD) and neurodegenerative disorders, especially alpha-synucleinopathies.

OBJECTIVE

We investigated regional cerebral blood flow (rCBF) changes using single photon emission computed tomography (SPECT) in patients with idiopathic RBD (iRBD), to determine functional brain alterations associated with the disorder.

METHODS

The SPECT data of 24 patients with iRBD were compared with those of 18 age-matched normal controls using statistical parametric mapping 2.

RESULTS

We found decreased rCBF in the parietooccipital lobe (precuneus), limbic lobe, and cerebellar hemispheres in patients with iRBD, which is commonly seen in patients with Lewy body disease (Parkinson's disease and dementia with Lewy bodies) or multiple system atrophy.

CONCLUSION

Our SPECT study suggests that iRBD can be a presymptomatic stage of alpha-synucleinopathies.

Scaled subprofile modeling of resting state imaging data in Parkinson's disease: methodological issues

Consistent functional brain abnormalities in Parkinson's disease (PD) are difficult to pinpoint because differences from the normal state are often subtle. In this regard, the application of multivariate methods of analysis has been successful but not devoid of misinterpretation and controversy. The Scaled Subprofile Model (SSM), a principal components analysis (PCA)-based spatial covariance method, has yielded critical information regarding the characteristic abnormalities of functional brain organization that underlie PD and other neurodegenerative disorders. However, the relevance of disease-related spatial covariance patterns (metabolic brain networks) and the most effective methods for their derivation has been a subject of debate. We address these issues here and discuss the inherent advantages of proper application as well as the effects of the misapplication of this methodology. We show that ratio pre-normalization using the mean global metabolic rate (GMR) or regional values from a "reference" brain region (e.g. cerebellum) that may be required in univariate analytical approaches is obviated in SSM. We discuss deviations of the methodology that may yield erroneous or confounding factors.

Cortical hypometabolism and hypoperfusion in Parkinson's disease is extensive: probably even at early disease stages

Recent cerebral blood flow (CBF) and glucose consumption (CMRglc) studies of Parkinson's disease (PD) revealed conflicting results. Using simulated data, we previously demonstrated that the often-reported subcortical hypermetabolism in PD could be explained as an artifact of biased global mean (GM) normalization, and that low-magnitude, extensive cortical hypometabolism is best detected by alternative data-driven normalization methods. Thus, we hypothesized that PD is characterized by extensive cortical hypometabolism but no concurrent widespread subcortical hypermetabolism and tested it on three independent samples of PD patients. We compared SPECT CBF images of 32 early-stage and 33 late-stage PD patients with that of 60 matched controls. We also compared PET FDG images from 23 late-stage PD patients with that of 13 controls. Three different normalization methods were compared: (1) GM normalization, (2) cerebellum normalization, (3) reference cluster normalization (Yakushev et al.). We employed standard voxel-based statistics (fMRIstat) and principal component analysis (SSM). Additionally, we performed a meta-analysis of all quantitative CBF and CMRglc studies in the literature to investigate whether the global mean (GM) values in PD are decreased. Voxel-based analysis with GM normalization and the SSM method performed similarly, i.e., both detected decreases in small cortical clusters and concomitant increases in extensive subcortical regions. Cerebellum normalization revealed more widespread cortical decreases but no subcortical increase. In all comparisons, the Yakushev method detected nearly identical patterns of very extensive cortical hypometabolism. Lastly, the meta-analyses demonstrated that global CBF and CMRglc values are decreased in PD. Based on the results, we conclude that PD most likely has widespread cortical hypometabolism, even at early disease stages. In contrast, extensive subcortical hypermetabolism is probably not a feature of 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.

Metabolic brain networks in neurodegenerative disorders: a functional imaging approach

Network analysis of functional brain imaging data is an innovative approach to study circuit abnormalities in neurodegenerative diseases. In Parkinson's disease, spatial covariance analysis of resting-state metabolic images has identified specific regional patterns associated with motor and cognitive symptoms. With functional imaging, these metabolic networks have recently been used to measure system-related progression and to evaluate novel treatment strategies. Network analysis is also being used to characterize specific functional biomarkers for Huntington's disease and Alzheimer's disease. These networks have been particularly helpful in uncovering compensatory mechanisms in genetically at-risk individuals. Ongoing developments in network applications are likely to enhance the role of functional imaging in the investigation of neurodegenerative disorders.

Recent developments in multiple system atrophy

Multiple system atrophy (MSA) is a rare late onset neurodegenerative disorder which presents with autonomic failure and a complicated motor syndrome including atypical parkinsonism, ataxia and pyramidal signs. MSA is a glial alpha-synucleinopathy with rapid progression and currently poor therapeutic management. This paper reviews the clinical features, natural history and novel diagnostic criteria for MSA as well as contemporary knowledge on pathogenesis based on evidence from neuropathological studies and experimental models. An outline of the rationale for managing symptomatic deterioration in MSA is provided together with a summary of novel experimental therapeutic approaches to decrease disease progression.

Clinical and cerebral activity changes induced by subthalamic nucleus stimulation in advanced Parkinson's disease: a prospective case-control study

BACKGROUND

High-frequency stimulation of the subthalamic nucleus (STN-DBS) improves motor symptoms in advanced Parkinson's disease (PD), but the mechanisms are still unclear. Functional imaging evidenced pathological overactivity in motor cortical areas in advanced PD that can be normalized by effective therapies.

PATIENTS AND METHODS

We studied resting state cerebral blood flow pre-operatively and 12 months after surgery in 40 patients with advanced PD using ECD-SPECT. SPECT scans were also acquired 1 year apart in 21 matched PD controls who did not undergo surgery. Statistical analysis was performed using statistical parametric mapping (SPM2) software. In addition, we correlated brain perfusion changes after surgery with clinical improvement, assessed using the unified PD rating scale motor score (UPDRS-III).

RESULTS

Patients showed marked motor improvement and medication reduction after surgery. Stimulated PD patients revealed bilateral rCBF decrements in motor cortical areas and prefrontal cortex bilaterally compared to pre-surgical condition as well as versus PD controls (p<.01 FDR corrected). Perfusion increases were found in cerebellum, temporal and occipital lobes. Clinical improvement was associated with perfusion decrements in primary motor and premotor cortices.

CONCLUSIONS

Effective STN-DBS is associated with neuronal activity changes in brain regions implicated in movement programming and performance. We hypothesize that clinical benefit might be associated with stimulation-induced normalization of the abnormal overactivity within the cortico-basal ganglia-thalamo-cortical motor loop in advanced PD.

New strategies for automated differential diagnosis of degenerative brain disorders

New strategies are considered for automated, single-subject differential diagnosis of independent degenerative brain disorders characterized by similar clinical symptoms using functional imaging. The methodology of these strategies is described and its application in parkinsonian movement disorders is illustrated for PET data. Using an automated diagnostic Topographic Profile Rating (TPR) technique based on the Scaled Subprofile Model (SSM-PCA), single-subject score values for different conditions are compared with reference values to predict diagnosis. The discriminatory parameters of reference score sets associated with significant SSM principal components referred to as group invariant subprofiles (GIS networks) are examined. It is shown that the extraction of exclusive sub-networks that stem from contrasting image features between conditions can be an effective tool for optimization that does not require expert knowledge.

Cerebral activity modulation by extradural motor cortex stimulation in Parkinson's disease: a perfusion SPECT study

Extradural motor cortex stimulation (EMCS) has been proposed as alternative to deep brain stimulation (DBS) in the treatment of Parkinson's disease (PD). Its mechanisms of action are still unclear. Neuroimaging evidenced motor cortical dysfunction in PD that can be reversed by therapy. We performed left hemisphere EMCS surgery in six advanced PD patients fulfilling CAPSIT criteria for DBS with the exception of age >70 years. After 6 months, we measured regional cerebral blood flow (rCBF) at rest with SPECT and Tc-99m cysteinate dimer bicisate off-medication with stimulator off and on. Clinical assessment included Unified Parkinson's Disease Rating Scale part II and III, Abnormal Involuntary Movement Scale and mean dopaminergic medication dosage. We used statistical parametric mapping for imaging data analysis. Clinically we observed no mean changes in motor scales, although blinded evaluation revealed some benefit in individual patients. We found significant rCBF decrements in the pre-central gyrus, pre-motor cortex and caudate nucleus bilaterally, left prefrontal areas and right thalamus. Perfusion increments were found in cerebellum bilaterally. EMCS determined significant modulation of neuronal activity within the cortico-basal ganglia-thalamo-cortical motor loop in our cohort of advanced PD patients. However, these effects were paralleled by mild and variable clinical efficacy.

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.

Deep gray matter hyperperfusion with occipital hypoperfusion in dementia with Lewy bodies

Although decreased occipital perfusion is a characteristic feature of dementia with Lewy bodies (DLB), not all patients with DLB show a significant decreased perfusion in the occipital lobe. We explored characteristics of perfusion changes to improve the identification of DLB, in addition to occipital hypoperfusion. Statistical image analysis of single photon emission computed tomography data was performed on 22 patients with DLB and 25 patients with Alzheimer's disease (AD). A significant decreased perfusion in the occipital lobe was found in 16 patients with DLB (72%) and three patients with AD (12%), while a significant increased perfusion in the deep gray matter (striatum and/or thalamus) was found in 18 patients with DLB (81%) and eight patients with AD (31%), respectively. Either occipital hypoperfusion or deep gray matter hyperperfusion was found in 21 patients with DLB (95%), while in nine patients with AD (35%), indicating a sensitivity of 95% and a specificity of 65% in discriminating DLB from AD. Our results suggest that the addition of deep gray matter hyperperfusion to occipital hypoperfusion may be useful in the clinical differentiation of DLB and AD.

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.

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.