Striatal shape in Parkinson's disease

Evaluation of putamen area and cerebral peduncle with surrounding cistern in patients with Parkinson's disease: is there a difference from controls in cranial MRI?

OBJECTIVES

Nigrostriatal dopaminergic neuron loss is essential in pathogenesis of Parkinson's disease (PD). The purpose of this study was to evaluate nigrostriatal structures including the putamen, cerebral peduncle, widths of interpeduncular cistern, and ambient cistern around the midbrain with conventional cranial magnetic resonance images (MRI) in patients with PD.

METHODS

The MRI of 56 subjects was included, which was selected from the radiological data system for this retrospective study. The 29 patients with idiopathic PD were included and their disease duration, Hoehn&Yahr stage, and Levodopa equivalent dose (LED) were recorded. The 27 controls had a normal neurologic examination and cranial MRI. All subjects in the patient and control groups had right-hand dominance. Putamen and cerebral peduncle areas and widths of interpeduncular and ambient cisterns were measured in T2 sequences of MRI. Further statistical analysis was applied to exclude gender and age effect on areas.

RESULTS

The areas of putamen and cerebral peduncles were significantly reduced in patients with PD compared to the control bilaterally (p < 0.001). Enlargement of interpeduncular and ambient cisterns in patients was higher than in controls, and it was significant (p < 0.001). A correlation was not observed between measurement results and clinical characteristics of patients with PD. Only the cerebral peduncle area/ambient cistern width ratio was significantly correlated with disease duration positively (right r = 0.46 p = 0.012, left r = 0.389 p = 0.037).

CONCLUSION

Clinicians should be careful with conventional MRIs of patients with idiopathic PD in practice. It may be different from controls without any neurological disorder, particularly putamen, cerebral peduncles, interpeduncular, and ambient cisterns.

Striatal and thalamic automatic segmentation, morphology, and clinical correlates in Parkinsonism: Parkinson's disease, multiple system atrophy and progressive supranuclear palsy

Parkinson's disease (PD), multisystem atrophy (MSA), and progressive supranuclear palsy (PSP) present similarly with bradykinesia, tremor, rigidity, and cognitive impairments. Neuroimaging studies have found differential changes in the nigrostriatal pathway in these disorders, however whether the volume and shape of specific regions within this pathway can distinguish between atypical Parkinsonian disorders remains to be determined. This paper investigates striatal and thalamic volume and morphology as distinguishing biomarkers, and their relationship to neuropsychiatric symptoms. Automatic segmentation to calculate volume and shape analysis of the caudate nucleus, putamen, and thalamus were performed in 18 PD patients, 12 MSA, 15 PSP, and 20 healthy controls, then correlated with clinical measures. PSP bilateral thalami and right putamen were significantly smaller than controls, but not MSA or PD. The left caudate and putamen significantly correlated with the Neuropsychiatric Inventory total score. Bilateral thalamus, caudate, and left putamen had significantly different morphology between groups, driven by differences between PSP and healthy controls. This study demonstrated that PSP patient striatal and thalamic volume and shape are significantly different when compared with controls. Parkinsonian disorders could not be differentiated on volumetry or morphology, however there are trends for volumetric and morphological changes associated with PD, MSA, and PSP.

Frontostriatal and limbic contributions to cognitive decline in Parkinson's disease

BACKGROUND AND PURPOSE

The circuitry underlying heterogenous cognitive profiles in Parkinson's disease (PD) remains unclear. The purpose of this study is to investigate whether structural changes in frontostriatal and limbic pathways contribute to different cognitive trajectories in PD.

METHODS

We obtained clinical and multimodal MRI data from 120 control and 122 PD subjects without dementia or severe motor disability. T1/T2-weighted images estimated volume, and diffusion imaging evaluated fractional anisotropy (FA) of frontostriatal (striatum and frontostriatal white matter [FSWM]) and limbic (hippocampus and fornix) structures. Montreal Cognitive Assessment (MoCA) gauged total and domain-specific (attention/executive and memory) cognitive function. Linear mixed-effects models were used to compare MRI and cognitive progression over 4.5 years between controls and PD and evaluate associations between baseline MRI and cognitive changes in PD.

RESULTS

At baseline, control and PD groups were comparable, except PD participants had smaller striatal volume (p < 0.001). Longitudinally, PD showed faster decline in hippocampal volume, FSWM FA, and fornix FA (ps < .016), but not striatal volume (p = .218). Total and domain-specific MoCA scores declined faster in PD (ps < .030). In PD, lower baseline hippocampal volume (p = .005) and fornix FA (p = .032), but not striatal volume (p = .662) or FSWM FA (p = .143), were associated with faster total MoCA decline. Baseline frontostriatal metrics of striatal volume and FSWM FA were associated with faster attention/executive decline (p < .038), whereas lower baseline hippocampal volume was associated with faster memory decline (p = .005).

CONCLUSION

In PD, frontostriatal structural metrics are associated with attention/executive tasks, whereas limbic changes correlated with faster global cognitive decline, particularly in memory tasks.

Morphological changes in Parkinson's disease based on magnetic resonance imaging: A mini-review of subcortical structures segmentation and shape analysis

Parkinson's disease (PD) is a neurodegenerative disorder caused by the loss of dopaminergic neurons in the substantia nigra, resulting in clinical symptoms, including bradykinesia, resting tremor, rigidity, and postural instability. The pathophysiological changes in PD are inextricably linked to the subcortical structures. Shape analysis is a method for quantifying the volume or surface morphology of structures using magnetic resonance imaging. In this review, we discuss the recent advances in morphological analysis techniques for studying the subcortical structures in PD in vivo. This approach includes available pipelines for volume and shape analysis, focusing on the morphological features of volume and surface area.

Local striatal volume and motor reserve in drug-naïve Parkinson's disease

Motor reserve (MR) may explain why individuals with similar pathological changes show marked differences in motor deficits in Parkinson's disease (PD). In this study, we investigated whether estimated individual MR was linked to local striatal volume (LSV) in PD. We analyzed data obtained from 333 patients with drug naïve PD who underwent dopamine transporter scans and high-resolution 3-tesla T1-weighted structural magnetic resonance images. Using a residual model, we estimated individual MRs on the basis of initial UPDRS-III score and striatal dopamine depletion. We performed a correlation analysis between MR estimates and LSV. Furthermore, we assessed the effect of LSV, which is correlated with MR estimates, on the longitudinal increase in the levodopa-equivalent dose (LED) during the 4-year follow-up period using a linear mixed model. After controlling for intracranial volume, there was a significant positive correlation between LSV and MR estimates in the bilateral caudate, anterior putamen, and ventro-posterior putamen. The linear mixed model showed that the large local volume of anterior and ventro-posterior putamen was associated with the low requirement of LED initially and accelerated LED increment thereafter. The present study demonstrated that LSV is crucial to MR in early-stage PD, suggesting LSV as a neural correlate of MR in PD.

Mining imaging and clinical data with machine learning approaches for the diagnosis and early detection of Parkinson's disease

Parkinson’s disease (PD) is a common, progressive, and currently incurable neurodegenerative movement disorder. The diagnosis of PD is challenging, especially in the differential diagnosis of parkinsonism and in early PD detection. Due to the advantages of machine learning such as learning complex data patterns and making inferences for individuals, machine-learning techniques have been increasingly applied to the diagnosis of PD, and have shown some promising results. Machine-learning-based imaging applications have made it possible to help differentiate parkinsonism and detect PD at early stages automatically in a number of neuroimaging studies. Comparative studies have shown that machine-learning-based SPECT image analysis applications in PD have outperformed conventional semi-quantitative analysis in detecting PD-associated dopaminergic degeneration, performed comparably well as experts’ visual inspection, and helped improve PD diagnostic accuracy of radiologists. Using combined multi-modal (imaging and clinical) data in these applications may further enhance PD diagnosis and early detection. To integrate machine-learning-based diagnostic applications into clinical systems, further validation and optimization of these applications are needed to make them accurate and reliable. It is anticipated that machine-learning techniques will further help improve differential diagnosis of parkinsonism and early detection of PD, which may reduce the error rate of PD diagnosis and help detect PD at pre-motor stage to make it possible for early treatments (e.g., neuroprotective treatment) to slow down PD progression, prevent severe motor symptoms from emerging, and relieve patients from suffering.

It Is Time to Study Overlapping Molecular and Circuit Pathophysiologies in Alzheimer's and Lewy Body Disease Spectra

Alzheimer's disease (AD) is the leading cause of dementia due to neurodegeneration and is characterized by extracellular senile plaques composed of amyloid β1 - 42 (Aβ) as well as intracellular neurofibrillary tangles consisting of phosphorylated tau (p-tau). Dementia with Lewy bodies constitutes a continuous spectrum with Parkinson's disease, collectively termed Lewy body disease (LBD). LBD is characterized by intracellular Lewy bodies containing α-synuclein (α-syn). The core clinical features of AD and LBD spectra are distinct, but the two spectra share common cognitive and behavioral symptoms. The accumulation of pathological proteins, which acquire pathogenicity through conformational changes, has long been investigated on a protein-by-protein basis. However, recent evidence suggests that interactions among these molecules may be critical to pathogenesis. For example, Aβ/tau promotes α-syn pathology, and α-syn modulates p-tau pathology. Furthermore, clinical evidence suggests that these interactions may explain the overlapping pathology between AD and LBD in molecular imaging and post-mortem studies. Additionally, a recent hypothesis points to a common mechanism of prion-like progression of these pathological proteins, via neural circuits, in both AD and LBD. This suggests a need for understanding connectomics and their alterations in AD and LBD from both pathological and functional perspectives. In AD, reduced connectivity in the default mode network is considered a hallmark of the disease. In LBD, previous studies have emphasized abnormalities in the basal ganglia and sensorimotor networks; however, these account for movement disorders only. Knowledge about network abnormalities common to AD and LBD is scarce because few previous neuroimaging studies investigated AD and LBD as a comprehensive cohort. In this paper, we review research on the distribution and interactions of pathological proteins in the brain in AD and LBD, after briefly summarizing their clinical and neuropsychological manifestations. We also describe the brain functional and connectivity changes following abnormal protein accumulation in AD and LBD. Finally, we argue for the necessity of neuroimaging studies that examine AD and LBD cases as a continuous spectrum especially from the proteinopathy and neurocircuitopathy viewpoints. The findings from such a unified AD and Parkinson's disease (PD) cohort study should provide a new comprehensive perspective and key data for guiding disease modification therapies targeting the pathological proteins in AD and LBD.

Statistical shape analysis of putamen in early-onset Parkinson's disease

OBJECTIVE

To investigate the shape differences in the putamen of early-onset Parkinson's patients compared with healthy controls and to assess and to assess sub-regional brain abnormalities.

METHODS

This study was conducted using the 3-T MRI scans of 23 early-onset Parkinson's patients and age and gender matched control subjects. Landmark coordinate data obtained and Procrustes analysis was used to compare mean shapes. The relationships between the centroid sizes of the left and right putamen, and the durations of disease examined using growth curve models.

RESULTS

While there was a significant difference between the right putamen shape of control and patient groups, there was not found a significant difference in terms of left putamen. Sub-regional analyses showed that for the right putamen, the most prominent deformations were localized in the middle-posterior putamen and minimal deformations were seen in the anterior putamen.

CONCLUSION

Although they were not as pronounced as those in the right putamen, the deformations in the left putamen mimic the deformations in the right putamen which are found mainly in the middle-posterior putamen and at a lesser extend in the anterior putamen.

Structural and functional neuroimaging changes associated with cognitive impairment and dementia in Parkinson's disease

This study seeks a better understanding of possible pathophysiological mechanisms associated with cognitive impairment and dementia in Parkinson's disease using structural and functional MRI. We investigated resting-state functional connectivity of important subdivisions of the caudate nucleus, putamen and thalamus, and also how the morphology of these structures are impacted in the disorder. We found cognitively unimpaired Parkinson's disease subjects (n = 33), compared to controls (n = 26), display increased functional connectivity of the dorsal caudate, anterior putamen and mediodorsal thalamic subdivisions with areas across the frontal lobe, as well as reduced functional connectivity of the dorsal caudate with posterior cortical and cerebellar regions. Compared to cognitively unimpaired subjects, those with mild cognitive impairment (n = 22) demonstrated reduced functional connectivity of the mediodorsal thalamus with the paracingulate cortex, while also demonstrating increased functional connectivity of the mediodorsal thalamus with the posterior cingulate cortex, compared to subjects with dementia (n = 17). Extensive volumetric and surface-based deflation was found in subjects with dementia compared to cognitively unimpaired Parkinson's disease participants and controls. Our research suggests that structures within basal ganglia-thalamocortical circuits are implicated in cognitive impairment and dementia in Parkinson's disease, with cognitive impairment and dementia associated with a breakdown in functional connectivity of the mediodorsal thalamus with para- and posterior cingulate regions of the brain respectively.

Cortical complexity and gyrification patterns in Parkinson's disease

This study aimed to investigate the cortical complexity and gyrification patterns in Parkinson's disease (PD) using local fractional dimension (LFD) and local gyrification index (LGI), respectively. In a cross-sectional study, LFD and LGI in 60 PD patients without dementia and 56 healthy controls (HC) were investigated using brain structural MRI data. LFD and LGI were estimated using the Computational Anatomy Toolbox (CAT12) and statistically analyzed between groups on a vertex level using statistical parametric mapping 12 (SPM12). Additionally, correlations between structural changes and clinical indices were further examined. PD patients showed widespread LFD reductions mainly in the left pre- and postcentral cortex, the left superior frontal cortex, the left caudal middle frontal cortex, the bilaterally superior parietal cortex and the right superior temporal cortex compared to HC. For LGI, there was no significant difference between PD and HC. In PD patients group, a significant negative correlation was found between LFD of the left postcentral cortex and duration of illness (DOI). Our results of widespread LFD reductions, but not LGI, indicate that LFD may provide a more sensitive diagnostic biomarker and encode specific information of PD. The significant negative correlation between LFD of the left postcentral cortex and DOI suggests that LFD may be a biomarker to monitor disease progression in PD.

Convergent patterns of structural brain changes in rapid eye movement sleep behavior disorder and Parkinson's disease on behalf of the German rapid eye movement sleep behavior disorder study group

STUDY OBJECTIVES

Rapid eye movement sleep behavior disorder (RBD) is considered a prodromal state of Parkinson's disease (PD). We aimed to characterize patterns of structural brain changes in RBD and PD patients using multimodal MRI.

METHODS

A total of 30 patients with isolated RBD, 29 patients with PD, and 56 age-matched healthy controls (HC) underwent MRI at 3T, including tensor-based morphometry, diffusion tensor imaging, and assessment of cortical thickness.

RESULTS

RBD individuals showed increased volume of the right caudate nucleus compared with HC, and higher cerebellar volume compared with both PD subjects and HC. Similar to PD subjects, RBD patients displayed increased fractional anisotropy (FA) in the corticospinal tracts, several tracts mainly related to non-motor function, and reduced FA of the corpus callosum compared with HC. Further, RBD subjects showed higher FA in the cerebellar peduncles and brainstem compared with both, PD patients and HC. PD individuals exhibited lower than normal volume in the basal ganglia, midbrain, pedunculopontine nuclei, and cerebellum. In contrast, volume in PD subjects was increased in the thalamus compared with both HC and RBD subjects.

CONCLUSIONS

We found convergent patterns of structural brain alterations in RBD and PD patients compared with HC. The changes observed suggest a co-occurrence of neurodegeneration and compensatory mechanisms that fail with emerging PD pathology. Our findings strengthen the hypothesis of RBD and PD constituting a continuous disease spectrum.

The role of the dorsal striatum in the recognition of emotions expressed by voice in Parkinson's disease

BACKGROUND AND PURPOSE

Non-motor impairment such as emotion recognition deficit in both facial and vocal expressions has been previously reported in Parkinson's disease (PD). We investigated whether the decoding of emotional prosody is impaired in PD and whether this deficit is related to striatal damage.

METHODS

Fifteen PD patients and 15 healthy controls (HCs) were requested to listen to six audio tracks and to recognize the emotions expressed by a professional actor while reading a meaning-neutral sentence. All subjects also received a structural MRI examination. Volumetric measurements were extracted for the striatum, a key region involved in emotional processing and typically impaired in PD.

RESULTS

Decoding sadness conveyed by voice was impaired in PD compared with HC and was related to the volume of the dorsal striatum bilaterally.

CONCLUSIONS

The dorsal striatum is involved in the decoding of vocal negative emotions in PD.

A Review of Publicly Available Automatic Brain Segmentation Methodologies, Machine Learning Models, Recent Advancements, and Their Comparison

BACKGROUND

The noninvasive study of the structure and functions of the brain using neuroimaging techniques is increasingly being used for its clinical and research perspective. The morphological and volumetric changes in several regions and structures of brains are associated with the prognosis of neurological disorders such as Alzheimer's disease, epilepsy, schizophrenia, etc. and the early identification of such changes can have huge clinical significance. The accurate segmentation of three-dimensional brain magnetic resonance images into tissue types (i.e., grey matter, white matter, cerebrospinal fluid) and brain structures, thus, has huge importance as they can act as early biomarkers. The manual segmentation though considered the "gold standard" is time-consuming, subjective, and not suitable for bigger neuroimaging studies. Several automatic segmentation tools and algorithms have been developed over the years; the machine learning models particularly those using deep convolutional neural network (CNN) architecture are increasingly being applied to improve the accuracy of automatic methods.

PURPOSE

The purpose of the study is to understand the current and emerging state of automatic segmentation tools, their comparison, machine learning models, their reliability, and shortcomings with an intent to focus on the development of improved methods and algorithms.

METHODS

The study focuses on the review of publicly available neuroimaging tools, their comparison, and emerging machine learning models particularly those based on CNN architecture developed and published during the last five years.

CONCLUSION

Several software tools developed by various research groups and made publicly available for automatic segmentation of the brain show variability in their results in several comparison studies and have not attained the level of reliability required for clinical studies. The machine learning models particularly three dimensional fully convolutional network models can provide a robust and efficient alternative with relation to publicly available tools but perform poorly on unseen datasets. The challenges related to training, computation cost, reproducibility, and validation across distinct scanning modalities for machine learning models need to be addressed.

Classification of PPMI MRI scans with voxel-based morphometry and machine learning to assist in the diagnosis of Parkinson's disease

BACKGROUND AND OBJECTIVES

Qualitative and quantitative analyses of Magnetic Resonance Imaging (MRI) scans are carried out to study and understand Parkinson's Disease, the second most common neurodegenerative disorder in people at their 60's. Some quantitative analyses are based on the application of voxel-based morphometry (VBM) on magnetic resonance images to determine the regions of interest, within gray matter, where there is a loss of the nerve cells that generate dopamine. This loss of dopamine is indicative of Parkinson's disease. The purpose of this research is the introduction of a new method to classify the 3-D magnetic resonance scans of an individual, as an assisting tool for diagnosis of Parkinson's disease by using the largest MRI dataset (Parkinson's Progression Markers Initiative) from a population of patients with Parkinson's disease and control individuals. A contribution is that separate studies are conducted for men and women since gender plays a significant role within Neurobiology, which is demonstrated by the fact that men are more prone to Parkinson's disease than women are.

METHODS

Previous to classification, VBM is conducted on magnetic resonance images to detect the regions where features are extracted by using first- and second-order statistics methods. Furthermore, the number of features is considerably reduced by using feature selection techniques. Seven classifiers are used and we are conducting separate experiments for men and women.

RESULTS

The best detection performance achieved in men is 99.01% of accuracy, 99.35% of sensitivity, 100% of specificity, and 100% of precision. The best detection performance achieved in women is 96.97% of accuracy, 100% of sensitivity, 96.15% of specificity, and 97.22% of precision. During classification of magnetic resonance images, the corresponding computational complexity is reduced since few features are selected.

CONCLUSIONS

The proposed method provides high performance as an assisting tool in the diagnosis of Parkinson's disease, by conducting separate experiments in men and women. While previous works have focused their analysis to the striatum region of the brain (the largest nuclear complex of the basal ganglia), the proposed approach is based on analysis over the whole brain by looking for decreases of tissue thickness, with the consequence of finding other regions of interest such as the cortex.

Lexical-semantic search related to side of onset and putamen volume in Parkinson's disease

Parkinson's disease (PD) is characterized by dopaminergic cell loss and reduced striatal volume. Prior studies have demonstrated striatal involvement in access to lexical-semantic knowledge and damage to this structure may be evident in the lexical properties of responses. Semantic fluency task responses from early stage, non-demented PD participants with right (PD-R) or left (PD-L) lateralizing symptoms were compared to matched controls on lexical properties (word frequency, age of acquisition) and correlated with striatal volumes segmented from T1-weighted brain MR images. PD-R participants produced semantic fluency responses of a lower age of acquisition than PD-L and control participants (p < 0.05). PD-R age of acquisition responses correlated positively with putamen volume (p < 0.05), while age of acquisition of responses correlated negatively with caudate volume in controls (p < 0.05). Findings provide evidence for a role of the striatum in lexical-semantic access and qualitative changes in lexical access in select PD patients.

Differential functional dysconnectivity of caudate nucleus subdivisions in Parkinson's disease

Caudate dopaminergic dysfunction is implied in the pathophysiology of patients with Parkinson's disease (PD). Still, connectivity specificities of the caudate nucleus (CN) subdivisions and the effect of dopamine are poorly understood. We collected MRI and neuropsychological data from 34 PD patients and 26 age- and sex-matched healthy elderly individuals (HEs) in this study. Resting-state functional connectivity analysis revealed that compared to the other CN subdivisions, the CN head was more strongly connected to the default mode network (DMN), the CN body to the frontoparietal network (FPN), and the CN tail to the visual network in HEs. PD patients off medication showed reduced connectivity within all these subdivision networks. In PD patients on medication, functional connectivity in the CN head network was significantly improved in the medial prefrontal cortex and in the body network it was improved in the dorsolateral prefrontal cortex. These improvements contributed to ameliorated motivation and cognitive function in PD patients. Our results highlighted the specific alterations and dopamine modulation in these CN subdivision networks in PD, which may provide insight into the pathophysiology and therapeutics of this disease.

VCP expression decrease as a biomarker of preclinical and early clinical stages of Parkinson's disease

Valosin-containing human protein (VCP) or p97 performs enzyme functions associated with the maintenance of protein homeostasis and control of protein quality. Disruption of its normal functioning might be associated with the development of Parkinson’s disease (PD). Tissues of mice with toxin-induced presymptomatic and early symptomatic stages of PD, as well as 52 treated and untreated patients with newly diagnosed PD and nine patients with a “predicted” form of PD, were investigated. Significant changes in Vcp gene expression were observed in almost all studied mouse tissues. A significant decrease in VCP expression specific for PD was also detected at both the late preclinical and the early clinical stages of PD in untreated patients. Thus, a decrease in VCP expression is important for changes in the function of the nervous system at early stages of PD. Analysis of changes in VCP expression in all patients with PD and in Vcp in the peripheral blood of mice used as models of PD revealed significant decreases in expression specific for PD. These data suggest that a decrease in the relative levels of VCP mRNA might serve as a biomarker for the development of pathology at the early clinical and preclinical stages of human PD.

Striatum Shape Hypertrophy in Early Stage Parkinson's Disease With Excessive Daytime Sleepiness

INTRODUCTION

Excessive daytime sleepiness (EDS) is one of the common and burdensome non-motor symptoms of Parkinson's disease (PD). However, the underlying neuropathology mechanism in PD patients with EDS (PD-EDS) remains unclear. The present study aims to delineate potential locations of structural alteration of subcortical regions in early stage and drug-naïve PD-EDS.

METHODS

The study had 252 patients with PD and 92 matched healthy controls (HC). EDS was estimated with the Epworth Sleepiness Scale, with a cutoff of 10. Ultimately, 59 patients were considered as PD-EDS. The remaining 193 were PD patients without EDS (PD-nEDS). FMRIB's Integrated Registration and Segmentation Tool (FIRST) was employed to assess the volumetric and surface alterations of subcortical nuclei in PD and PD-EDS.

RESULTS

Volumetric analyses found no difference in the subcortical nucleus volume between PD and HC, or PD-EDS and PD-nEDS groups. The shape analyses revealed the local atrophic changes in bilateral caudate and right putamen in patients with PD. In addition, the hypertrophic changes were located in the right putamen and left pallidum in PD-EDS than in PD-nEDS.

CONCLUSION

Our findings revealed the regional hypertrophy of the striatum in PD-EDS. Our results indicate that local hypertrophic striatum would be a valuable early biomarker for detecting the alteration in PD-EDS. The shape analysis contributes valuable information when investigating PD-EDS.

Amnestic mild cognitive impairment in Parkinson's disease: White matter structural changes and mechanisms

Mild cognitive impairment (MCI) is a heterogeneous cognitive disorder that is often comorbid with Parkinson's diseases (PD). The amnestic subtype of PD-MCI (PD-aMCI) has a higher risk to develop dementia. However, there is a lack of studies on the white matter (WM) structural changes of PD-aMCI. We characterized the WM structural changes of PD-aMCI (n = 17) with cognitively normal PD (PD-CN, n = 19) and normal controls (n = 20), using voxel-based and tract-based spatial statistics (TBSS) analyses on fractional anisotropy (FA) axial diffusivity (AD), and radial diffusivity (RD). By excluding and then including the motor performance as a covariate in the comparison analysis between PD-aMCI and PD-CN, we attempted to discern the influences of two neuropathological mechanisms on the WM structural changes of PD-aMCI. The correlation analyses between memory and voxel-based WM measures in all PD patients were also performed (n = 36). The results showed that PD-aMCI had smaller FA values than PD-CN in the diffuse WM areas, and PD-CN had higher AD and RD values than normal controls in the right caudate. Most FA difference between PD-aMCI and PD-CN could be weakened by the motor adjustment. The FA differences between PD-aMCI and PD-CN were largely spatially overlapped with the memory-correlated FA values. Our findings demonstrated that the WM structural differences between PD-aMCI and PD-CN were mainly memory-related, and the influence of motor adjustment might indicate a common mechanism underlying both motor and memory impairment in PD-aMCI, possibly reflecting a predominant influence of dopaminergic neuropathology.

Differentiation of multiple system atrophy from Parkinson's disease by structural connectivity derived from probabilistic tractography

Recent studies combining diffusion tensor-derived metrics and machine learning have shown promising results in the discrimination of multiple system atrophy (MSA) and Parkinson’s disease (PD) patients. This approach has not been tested using more complex methodologies such as probabilistic tractography. The aim of this work is assessing whether the strength of structural connectivity between subcortical structures, measured as the number of streamlines (NOS) derived from tractography, can be used to classify MSA and PD patients at the single-patient level. The classification performance of subcortical FA and MD was also evaluated to compare the discriminant ability between diffusion tensor-derived metrics and NOS. Using diffusion-weighted images acquired in a 3 T MRI scanner and probabilistic tractography, we reconstructed the white matter tracts between 18 subcortical structures from a sample of 54 healthy controls, 31 MSA patients and 65 PD patients. NOS between subcortical structures were compared between groups and entered as features into a machine learning algorithm. Reduced NOS in MSA compared with controls and PD were found in connections between the putamen, pallidum, ventral diencephalon, thalamus, and cerebellum, in both right and left hemispheres. The classification procedure achieved an overall accuracy of 78%, with 71% of the MSA subjects and 86% of the PD patients correctly classified. NOS features outperformed the discrimination performance obtained with FA and MD. Our findings suggest that structural connectivity derived from tractography has the potential to correctly distinguish between MSA and PD patients. Furthermore, NOS measures obtained from tractography might be more useful than diffusion tensor-derived metrics for the detection of MSA.

Intranigral Injection of Endotoxin Suppresses Proliferation of Hippocampal Progenitor Cells

Brain inflammation can result in functional disorders observed in several neurodegenerative diseases and that can be also associated with reduced neurogenesis. In this study, we investigate the effect of mild inflammation, induced by unilateral injection of Endotoxin (ET) in the substantia nigra (SN)/Ventral Tegmental Area, on the proliferation and survival of stem/progenitor cells in the dentate gyrus (DG) of the hippocampus. Adult female rats received unilateral injection of ET (2 μg/2 μl saline) or sterile saline (2 μl) in the right SN followed by 5′-Bromo-2′-deoxyuridine (BrdU) injections (66 mg/kg/injection). Intranigral ET injection induced bilateral decrease in the number of newly born BrdU positive cells in the DG. This effect was paralleled by a significant decrease in the exploratory behavior of rats, as assessed by the Y-maze novel arm exploration task. ET also induced a transient decrease in the number of tyrosine hydroxylase-positive cells in the injected SN, impaired motor behavior, and caused microglial activation in the SN. This study provides an experimental simulation of the remote effects of moderate and reversible neuroinflammation resulting in impaired communication between midbrain dopaminergic neurons and the hippocampus.

Structural Imaging in Atypical Parkinsonism

Qualitative and quantitative structural magnetic resonance imaging offer objective measures of the underlying neurodegeneration in atypical parkinsonism. Regional changes in tissue volume, signal changes and increased deposition of iron as assessed with different structural MRI techniques are surrogate markers of underlying neurodegeneration and may reflect cell loss, microglial proliferation and astroglial activation. Structural MRI has been explored as a tool to enhance diagnostic accuracy in differentiating atypical parkinsonian disorders (APDs). Moreover, the longitudinal assessment of serial structural MRI-derived parameters offers the opportunity for robust inferences regarding the progression of APDs. This review summarizes recent research findings as (1) a diagnostic tool for APDs as well as (2) as a tool to assess longitudinal changes of serial MRI-derived parameters in the different APDs.

Structural MRI in Idiopathic Parkinson's Disease

Among modern neuroimaging modalities, magnetic resonance imaging (MRI) is a widely available, non-invasive, and cost-effective method to detect structural and functional abnormalities related to neurodegenerative disorders. In the last decades, MRI have been widely implemented to support PD diagnosis as well as to provide further insights into motor and non-motor symptoms pathophysiology, complications and treatment-related effects. Different aspects of the brain morphology and function may be derived from a single scan, by applying different analytic approaches. Biomarkers of neurodegeneration as well as tissue microstructural changes may be extracted from structural MRI techniques. In this chapter, we analyze the role of structural imaging to differentiate PD patients from controls and to define neural substrates of motor and non-motor PD symptoms. Evidence collected in the premotor PD phase will be also critically discussed. White matter as well as gray matter integrity imaging studies has been reviewed, aiming to highlight points of strength and limits to their potential application in clinical settings.

Striatal changes in Parkinson disease: An investigation of morphology, functional connectivity and their relationship to clinical symptoms

We sought to investigate morphological and resting state functional connectivity changes to the striatal nuclei in Parkinson disease (PD) and examine whether changes were associated with measures of clinical function. Striatal nuclei were manually segmented on 3T-T1 weighted MRI scans of 74 PD participants and 27 control subjects, quantitatively analysed for volume, shape and also functional connectivity using functional MRI data. Bilateral caudate nuclei and putamen volumes were significantly reduced in the PD cohort compared to controls. When looking at left and right hemispheres, the PD cohort had significantly smaller left caudate nucleus and right putamen volumes compared to controls. A significant correlation was found between greater atrophy of the caudate nucleus and poorer cognitive function, and between greater atrophy of the putamen and more severe motor symptoms. Resting-state functional MRI analysis revealed altered functional connectivity of the striatal structures in the PD group. This research demonstrates that PD involves atrophic changes to the caudate nucleus and putamen that are linked to clinical dysfunction. Our work reveals important information about a key structure-function relationship in the brain and provides support for caudate nucleus and putamen atrophy as neuroimaging biomeasures in PD.

A Fully-Automated Subcortical and Ventricular Shape Generation Pipeline Preserving Smoothness and Anatomical Topology

In this paper, we present a fully-automated subcortical and ventricular shape generation pipeline that acts on structural magnetic resonance images (MRIs) of the human brain. Principally, the proposed pipeline consists of three steps: (1) automated structure segmentation using the diffeomorphic multi-atlas likelihood-fusion algorithm; (2) study-specific shape template creation based on the Delaunay triangulation; (3) deformation-based shape filtering using the large deformation diffeomorphic metric mapping for surfaces. The proposed pipeline is shown to provide high accuracy, sufficient smoothness, and accurate anatomical topology. Two datasets focused upon Huntington's disease (HD) were used for evaluating the performance of the proposed pipeline. The first of these contains a total of 16 MRI scans, each with a gold standard available, on which the proposed pipeline's outputs were observed to be highly accurate and smooth when compared with the gold standard. Visual examinations and outlier analyses on the second dataset, which contains a total of 1,445 MRI scans, revealed 100% success rates for the putamen, the thalamus, the globus pallidus, the amygdala, and the lateral ventricle in both hemispheres and rates no smaller than 97% for the bilateral hippocampus and caudate. Another independent dataset, consisting of 15 atlas images and 20 testing images, was also used to quantitatively evaluate the proposed pipeline, with high accuracy having been obtained. In short, the proposed pipeline is herein demonstrated to be effective, both quantitatively and qualitatively, using a large collection of MRI scans.

The cholinergic contribution to the resting-state functional network in non-demented Parkinson's disease

The cholinergic system arising from the basal forebrain plays an important role in cognitive performance in Parkinson's disease (PD). Here, we analyzed cholinergic status-dependent cortical and subcortical resting-state functional connectivity in PD. A total of 61 drug-naïve PD patients were divided into tertiles based on normalized substantia innominata (SI) volumes. We compared the resting-state network from seed region of interest in the caudate, posterior cingulate cortex (PCC), and SI between the lowest (PD-L) and highest tertile (PD-H) groups. Correlation analysis of the functional networks was also performed in all subjects. The functional network analysis showed that PD-L subjects displayed decreased striato-cortical functional connectivity compared with PD-H subjects. Selecting the PCC as a seed, the PD-L patients displayed decreased functional connectivity compared to PD-H patients. Meanwhile, PD-L subjects had significantly increased cortical functional connectivity with the SI compared with PD-H subjects. Correlation analysis revealed that SI volume had a positive correlation with functional connectivity from the right caudate and PCC. The present study demonstrated that PD patients exhibited unique functional connectivity from the caudate and the PCC that may be closely associated with cholinergic status, suggesting an important role for the cholinergic system in PD-associated cognition.

Cortical and subcortical gray matter bases of cognitive deficits in REM sleep behavior disorder

OBJECTIVE

To investigate cortical and subcortical gray matter abnormalities underlying cognitive impairment in patients with REM sleep behavior disorder (RBD) with or without mild cognitive impairment (MCI).

METHODS

Fifty-two patients with RBD, including 17 patients with MCI, were recruited and compared to 41 controls. All participants underwent extensive clinical assessments, neuropsychological examination, and 3-tesla MRI acquisition of T1 anatomical images. Vertex-based cortical analyses of volume, thickness, and surface area were performed to investigate cortical abnormalities between groups, whereas vertex-based shape analysis was performed to investigate subcortical structure surfaces. Correlations were performed to investigate associations between cortical and subcortical metrics, cognitive domains, and other markers of neurodegeneration (color discrimination, olfaction, and autonomic measures).

RESULTS

Patients with MCI had cortical thinning in the frontal, cingulate, temporal, and occipital cortices, and abnormal surface contraction in the lenticular nucleus and thalamus. Patients without MCI had cortical thinning restricted to the frontal cortex. Lower patient performance in cognitive domains was associated with cortical and subcortical abnormalities. Moreover, impaired performance on olfaction, color discrimination, and autonomic measures was associated with thinning in the occipital lobe.

CONCLUSIONS

Cortical and subcortical gray matter abnormalities are associated with cognitive status in patients with RBD, with more extensive patterns in patients with MCI. Our results highlight the importance of distinguishing between subgroups of patients with RBD according to cognitive status in order to better understand the neurodegenerative process in this population.

Predicting auditory feedback control of speech production from subregional shape of subcortical structures

Although a growing body of research has focused on the cortical sensorimotor mechanisms that support auditory feedback control of speech production, much less is known about the subcortical contributions to this control process. This study examined whether subregional anatomy of subcortical structures assessed by statistical shape analysis is associated with vocal compensations and cortical event-related potentials in response to pitch feedback errors. The results revealed significant negative correlations between the magnitudes of vocal compensations and subregional shape of the right thalamus, between the latencies of vocal compensations and subregional shape of the left caudate and pallidum, and between the latencies of cortical N1 responses and subregional shape of the left putamen. These associations indicate that smaller local volumes of the basal ganglia and thalamus are predictive of slower and larger neurobehavioral responses to vocal pitch errors. Furthermore, increased local volumes of the left hippocampus and right amygdala were predictive of larger vocal compensations, suggesting that there is an interplay between the memory-related subcortical structures and auditory-vocal integration. These results, for the first time, provide evidence for differential associations of subregional morphology of the basal ganglia, thalamus, hippocampus, and amygdala with neurobehavioral processing of vocal pitch errors, suggesting that subregional shape measures of subcortical structures can predict behavioral outcome of auditory-vocal integration and associated neural features. Hum Brain Mapp 39:459-471, 2018. © 2017 Wiley Periodicals, Inc.

Magnetic resonance imaging for the diagnosis of Parkinson's disease

The differential diagnosis of parkinsonian syndromes is considered one of the most challenging in neurology and error rates in the clinical diagnosis can be high even at specialized centres. Despite several limitations, magnetic resonance imaging (MRI) has undoubtedly enhanced the diagnostic accuracy in the differential diagnosis of neurodegenerative parkinsonism over the last three decades. This review aims to summarize research findings regarding the value of the different MRI techniques, including advanced sequences at high- and ultra-high-field MRI and modern image analysis algorithms, in the diagnostic work-up of Parkinson's disease. This includes not only the exclusion of alternative diagnoses for Parkinson's disease such as symptomatic parkinsonism and atypical parkinsonism, but also the diagnosis of early, new onset, and even prodromal Parkinson's disease.

Stereological Evaluation of the Brains in Patients with Parkinson’s disease Compared to Controls

Parkinson’s disease (PD) is a chronic and progressive neurological disorder. A tetrad of bradykinesia, rigidity, tremor and postural instability are the core features of the disease. The aim of this study was to evaluate stereological changes in the brain of patients with PD and compare them with that of healthy controls. This case-control study was conducted on 29 patients with PD and 12 controls (C) in Zahedan, Iran. All subjects enrolled into the study through the convenience sampling method. MRI images of the brains of two groups in frontal and sagittal axis with consecutive 5mm distance slices were captured. Parameters including total volume (V) and volume density (Vv) of different parts of the brain were estimated based on Cavalries’ point counting stereological method. To analyze the data, descriptive statistics, Mann-Whitney U-Test applied for comparing the PD and C groups were used. Significance level was set at p<0.05. Our study showed that the volume of the brain and total volume and volume density (Vv) of cerebral hemispheres, cerebellum, ventricles, hippocampus, pons, mid brain and superior cerebellar peduncles in the PD group did not indicate significant difference from the control group. Total volume of brain stem in PD group wasn’t significantly different from the control group. The volume density of brain stem (p= 0.012) and total volume and volume density of middle cerebellar peduncle (p< 0.0001) in PD group were significantly larger than the control group. This study shows that PD stereological parameters related to volume and volume density of middle cerebellar peduncle and volume density of brain stem were significantly larger in patients compared to the controls. Therefore, stereological parameters can be used for early diagnosis and probably for follow-up in patients with PD.

Levodopa response differs in Parkinson's motor subtypes: A task-based effective connectivity study

Parkinson's disease (PD) is a circuit-level disorder with clinically-determined motor subtypes. Despite evidence suggesting each subtype may have different pathophysiology, few neuroimaging studies have examined levodopa-induced differences in neural activation between tremor dominant (TD) and postural instability/gait difficulty (PIGD) subtype patients during a motor task. The goal of this functional MRI (fMRI) study was to examine task-induced activation and connectivity in the cortico-striatal-thalamo-cortical motor circuit in healthy controls, TD patients, and PIGD patients before and after levodopa administration. Fourteen TD and 12 PIGD cognitively-intact patients and 21 age- and sex-matched healthy controls completed a right-hand, paced tapping fMRI paradigm. Collectively, PD patients off medication (OFF) showed hypoactivation of the motor cortex relative to healthy controls, even when controlling for performance. After levodopa intake, the PIGD patients had significantly increased activation in the left putamen compared with TD patients and healthy controls. Psychophysiological interaction analysis revealed that levodopa increased effective connectivity between the posterior putamen and other areas of the motor circuit during tapping in TD patients, but not in PIGD patients. This novel, levodopa-induced difference in the neural responses between PD motor subtypes may have significant implications for elucidating the mechanisms underlying the distinct phenotypic manifestations and enabling the classification of motor subtypes objectively using fMRI.

Comparison of accuracy between FSL's FIRST and Freesurfer for caudate nucleus and putamen segmentation

Although several methods have been developed to automatically delineate subcortical gray matter structures from MR images, the accuracy of these algorithms has not been comprehensively examined. Most of earlier studies focused primarily on the hippocampus. Here, we assessed the accuracy of two widely used non-commercial programs (FSL-FIRST and Freesurfer) for segmenting the caudate and putamen. T1-weighted 1 mm³ isotropic resolution MR images were acquired for thirty healthy subjects (15 females). Caudate nucleus and putamen were segmented manually by two independent observers and automatically by FIRST and Freesurfer (v4.5 and v5.3). Utilizing manual labels as reference standard the following measures were studied: Dice coefficient (D), percentage volume difference (PVD), absolute volume difference as well as intraclass correlation coefficient (ICC) for consistency and absolute agreement. For putamen segmentation, FIRST achieved higher D, lower PVD and higher ICC for absolute agreement with manual tracing than either version of Freesurfer. Freesurfer overestimated the putamen, while FIRST was not statistically different from manual tracing. The ICC for consistency with manual tracing was similar between the two methods. For caudate segmentation, FIRST and Freesurfer performed more similarly. In conclusion, Freesurfer and FIRST are not equivalent when comparing to manual tracing. FIRST was superior for putaminal segmentation.

Striatal and Hippocampal Atrophy in Idiopathic Parkinson's Disease Patients without Dementia: A Morphometric Analysis

Background

Analyses of subcortical gray structure volumes in non-demented idiopathic Parkinson’s disease (PD) often, but not always, show volume loss of the putamen, caudate nucleus, nucleus accumbens, and hippocampus. There is building evidence that structure morphometry might be more sensitive to disease-related processes than volume.

Objective

To assess morphometric differences of subcortical structures (putamen, caudate nucleus, thalamus, globus pallidus, nucleus accumbens, and amygdala) as well as the hippocampus in non-demented individuals with PD relative to age and education matched non-PD peers.

Methods

Prospective recruitment of idiopathic no-dementia PD and non-PD peers as part of a federally funded investigation. T1-weighted isovoxel metrics acquired via 3-T Siemens Verio for all individuals [PD n = 72 (left side onset n = 27, right side onset n = 45); non-PD n = 48]. FIRST (FMRIB Software Library) applications provided volumetric and vertex analyses on group differences for structure size and morphometry.

Results

Group volume differences were observed only for putamen and hippocampi (PD < non-PD) with hippocampal volume significantly associating with disease duration. Group shape differences were observed for bilateral putamen, caudate nucleus, and hippocampus with greater striatal atrophy contralateral to side of motor symptom onset. Hippocampal shape differences disappeared when removing the effects of volume.

Conclusion

The putamen was the primary structure to show both volume and shape differences in PD, indicating that the putamen is the predominant site of basal ganglia atrophy in early- to mid-stage PD. Side of PD symptom onset associates with contralateral striatal atrophy. Left-onset PD might experience more extensive striatal atrophy than right-onset PD. Hippocampus morphometric results suggest possible primary atrophy of CA3/4 and dentate gyrus.

Marked brain asymmetry with intact cognitive functioning in idiopathic Parkinson's disease: a longitudinal analysis

OBJECTIVE

A 71-year-old (MN) with an 11-year history of left onset tremor diagnosed as Parkinson's disease (PD) completed longitudinal brain magnetic resonance imaging (MRI) and neuropsychological testing. MRI scans showed an asymmetric caudate nucleus (right < left volume). We describe this asymmetry at baseline and the progression over time relative to other subcortical gray, frontal white matter, and cortical gray matter regions of interest. Isolated structural changes are compared to MN's cognitive profiles.

METHOD

MN completed yearly MRIs and neuropsychological assessments. For comparison, left onset PD (n = 15) and non-PD (n = 43) peers completed the same baseline protocol. All MRI scans were processed with FreeSurfer and the FMRIB Software Library to analyze gray matter structures and frontal fractional anisotropy (FA) metrics. Processing speed, working memory, language, verbal memory, abstract reasoning, visuospatial, and motor functions were examined using reliable change methods.

RESULTS

At baseline, MN had striatal volume and frontal lobe thickness asymmetry relative to peers with mild prefrontal white matter FA asymmetry. Over time only MN's right caudate nucleus showed accelerated atrophy. Cognitively, MN had slowed psychomotor speed and visuospatial-linked deficits with mild visuospatial working memory declines longitudinally.

CONCLUSIONS

This is a unique report using normative neuroimaging and neuropsychology to describe an individual diagnosed with PD who had striking striatal asymmetry followed secondarily by cortical thickness asymmetry and possible frontal white matter asymmetry. His decline and variability in visual working memory could be linked to ongoing atrophy of his right caudate nucleus.

Altered Expression of Growth Associated Protein-43 and Rho Kinase in Human Patients with Parkinson's Disease

Causative treatment strategies for Parkinson's disease (PD) will have to address multiple underlying pathomechanisms to attenuate neurodegeneration. Additionally, the intrinsic regenerative capacity of the central nervous system is also an important factor contributing to restoration. Extracellular cues can limit sprouting and regrowth of adult neurons, but even aged neurons have a low intrinsic regeneration capacity. Whether this capacity has been lost or if growth inhibitory cues are increased during PD progression has not been resolved yet. In this study, we assessed the regenerative potential in the nigrostriatal system in post-mortem brain sections of PD patients compared to age-matched and young controls. Investigation of the expression pattern of the regeneration-associated protein GAP-43 suggested a lower regenerative capacity in nigral dopaminergic neurons of PD patients. Furthermore, the increase in protein expression of the growth-inhibitory protein ROCK2 in astrocytes and a similar trend in microglia, suggests an important role for ROCK2 in glial PD pathology, which is initiated already in normal aging. Considering the role of astro- and microglia in PD pathogenesis as well as beneficial effects of ROCK inhibition on neuronal survival and regeneration in neurodegenerative disease models, our data strengthens the importance of the ROCK pathway as a therapeutic target in PD.

Transcriptome Profile Changes in Mice with MPTP-Induced Early Stages of Parkinson's Disease

Parkinson's disease (PD) is one of the most common neurodegenerative diseases. Despite progress in the study of the molecular, genetic, and pathogenic mechanisms of PD, it is unclear which processes trigger the development of the pathology associated with PD. Models of the presymptomatic and early symptomatic stages of PD induced by MPTP have been used to analyze changes in transcriptome profile in brain tissues, to identify specific patterns and mechanisms underlying neurodegeneration in PD. The whole-transcriptome analysis in the brain tissues of the mice with MPTP-induced PD showed that striatum is involved in the pathogenesis in the earliest stages and the processes associated with vesicular transport may be altered. The expression profiles of the genes studied in the substantia nigra and peripheral blood confirm that lymphocytes from peripheral blood may reflect processes occurring in the brain. These data suggest that messenger RNA (mRNA) levels in peripheral blood may provide potential biomarkers of the neurodegeneration occurring in PD. The changes in expression at the mRNA and protein levels suggest that Snca may be involved in neurodegeneration and Drd2 may participate in the development of the compensatory mechanisms in the early stages of PD pathogenesis. Our data suggest that the brain cortex may be involved in the pathological processes in the early stages of PD, including the presymptomatic stage.

Volumetric and shape analysis of the thalamus and striatum in amnestic mild cognitive impairment

Alterations in brain structures, including progressive neurodegeneration, are a hallmark in patients with Alzheimer's disease (AD). However, pathological mechanisms, such as the accumulation of amyloid and the proliferation of tau, are thought to begin years, even decades, before the initial clinical manifestations of AD. In this study, we compare the brain anatomy of amnestic mild cognitive impairment patients (aMCI, n = 16) to healthy subjects (CS, n = 22) using cortical thickness, subcortical volume, and shape analysis, which we believe to be complimentary to volumetric measures. We were able to replicate "classical" cortical thickness alterations in aMCI in the hippocampus, amygdala, putamen, insula, and inferior temporal regions. Additionally, aMCI showed significant thalamic and striatal shape differences. We observed higher global amyloid deposition in aMCI, a significant correlation between striatal displacement and global amyloid, and an inverse correlation between executive function and right-hemispheric thalamic displacement. In contrast, no volumetric differences were detected in thalamic, striatal, and hippocampal regions. Our results provide new evidence for early subcortical neuroanatomical changes in patients with aMCI, which are linked to cognitive abilities and amyloid deposition. Hence, shape analysis may aid in the identification of structural biomarkers for identifying individuals at highest risk of conversion to AD.

Structural Brain Alterations in Motor Subtypes of Parkinson's Disease: Evidence from Probabilistic Tractography and Shape Analysis

BACKGROUND AND OBJECTIVES

The postural instability and gait disorder (PIGD) and tremor dominant (TD) subtypes of Parkinson's disease (PD) show different patterns of alterations in functional connectivity (FC) between specific brain regions. This study aimed to investigate the relation between symptomatic heterogeneity in PD and structural alterations underlying these FC changes.

METHODS

68 PD patients classified as PIGD (n = 41) or TD (n = 19) and 19 age-matched controls underwent Magnetic Resonance Imaging (MRI). Diffusion-weighted images were used to assess fractional anisotropy (FA) and mean diffusivity (MD) at the whole-brain level using tract-based spatial statistics (TBSS). In addition, structural connectivity was assessed between regions that previously showed altered FC using probabilistic tractography. Anatomical images were used to determine shape and volume of the putamen, caudate and pallidum.

RESULTS

TBSS revealed widespread FA reductions in PIGD compared to controls involving the superior longitudinal fasciculi and corpus callosum. No such differences were found in TD. Both PD subgroups had increased MD compared to controls in tracts connecting the left caudate with the bilateral ventral putamen. TD patients additionally showed increased MD compared to PIGD and controls in tracts connecting the right inferior parietal lobule with the right premotor and primary motor cortex, which previously showed altered FC. We also found grey matter atrophy in the rostrodorsal head of the caudate in PIGD compared to controls.

CONCLUSION

Microstructural changes in white matter tracts, particularly in those connecting striatal sub-areas, partly underlie FC alterations in PD subtypes. Caudate shape alterations further implicate the striatum in PIGD pathophysiology.

Structural Imaging and Parkinson's Disease: Moving Toward Quantitative Markers of Disease Progression

Parkinson's disease (PD) is a progressive age-related neurodegenerative disorder. Although the pathological hallmark of PD is dopaminergic cell death in the substantia nigra pars compacta, widespread neurodegenerative changes occur throughout the brain as disease progresses. Postmortem studies, for example, have demonstrated the presence of Lewy pathology, apoptosis, and loss of neurotransmitters and interneurons in both cortical and subcortical regions of PD patients. Many in vivo structural imaging studies have attempted to gauge PD-related pathology, particularly in gray matter, with the hope of identifying an imaging biomarker. Reports of brain atrophy in PD, however, have been inconsistent, most likely due to differences in the studied populations (i.e. different disease stages and/or clinical subtypes), experimental designs (i.e. cross-sectional vs. longitudinal), and image analysis methodologies (i.e. automatic vs. manual segmentation). This review attempts to summarize the current state of gray matter structural imaging research in PD in relationship to disease progression, reconciling some of the differences in reported results, and to identify challenges and future avenues.

Magnetic Resonance Imaging Features of the Nigrostriatal System: Biomarkers of Parkinson's Disease Stages?

Introduction

Magnetic resonance imaging (MRI) can be used to identify biomarkers in Parkinson’s disease (PD); R2* values reflect iron content related to high levels of oxidative stress, whereas volume and/or shape changes reflect neuronal death. We sought to assess iron overload in the nigrostriatal system and characterize its relationship with focal and overall atrophy of the striatum in the pivotal stages of PD.

Methods

Twenty controls and 70 PD patients at different disease stages (untreated de novo patients, treated early-stage patients and advanced-stage patients with L-dopa-related motor complications) were included in the study. We determined the R2* values in the substantia nigra, putamen and caudate nucleus, together with striatal volume and shape analysis. We also measured R2* in an acute MPTP mouse model and in a longitudinal follow-up two years later in the early-stage PD patients.

Results

The R2* values in the substantia nigra, putamen and caudate nucleus were significantly higher in de novo PD patients than in controls. Early-stage patients displayed significantly higher R2* values in the substantia nigra (with changes in striatal shape), relative to de novo patients. Measurements after a two-year follow-up in early-stage patients and characterization of the acute MPTP mouse model confirmed that R2* changed rapidly with disease progression. Advanced-stage patients displayed significant atrophy of striatum, relative to earlier disease stages.

Conclusion

Each pivotal stage in PD appears to be characterized by putative nigrostriatal MRI biomarkers: iron overload at the de novo stage, striatal shape changes at early-stage disease and generalized striatal atrophy at advanced disease.

Morphological alterations in the caudate, putamen, pallidum, and thalamus in Parkinson's disease

Like many neurodegenerative diseases, the clinical symptoms of Parkinsons disease (PD) do not manifest until significant progression of the disease has already taken place, motivating the need for sensitive biomarkers of the disease. While structural imaging is a potentially attractive method due to its widespread availability and non-invasive nature, global morphometric measures (e.g., volume) have proven insensitive to subtle disease change. Here we use individual surface displacements from deformations of an average surface model to capture disease related changes in shape of the subcortical structures in PD. Data were obtained from both the University of British Columbia (UBC) [n = 54 healthy controls (HC) and n = 55 Parkinsons disease (PD) patients] and the publicly available Parkinsons Progression Markers Initiative (PPMI) [n = 137 (HC) and n = 189 (PD)] database. A high dimensional non-rigid registration algorithm was used to register target segmentation labels (caudate, putamen, pallidum, and thalamus) to a set of segmentation labels defined on the average-template. The vertex-wise surface displacements were significantly different between PD and HC in thalamic and caudate structures. However, overall displacements did not correlate with disease severity, as assessed by the Unified Parkinson's Disease Rating Scale (UPDRS). The results from this study suggest disease-relevant shape abnormalities can be robustly detected in subcortical structures in PD. Future studies will be required to determine if shape changes in subcortical structures are seen in the prodromal phases of the disease.

Progressive brain metabolic changes under deep brain stimulation of subthalamic nucleus in parkinsonian rats

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is an efficient neurosurgical treatment for advanced Parkinson's disease. Non-invasive metabolic neuroimaging during the course of DBS in animal models may contribute to our understanding of its action mechanisms. Here, DBS was adapted to in vivo proton magnetic resonance spectroscopy at 11.7 T in the rat to follow metabolic changes in main basal ganglia structures, the striatum, and the substantia nigra pars reticulata (SNr). Measurements were repeated OFF and ON acute and subchronic (7 days) STN-DBS in control and parkinsonian (6-hydroxydopamine lesion) conditions. Acute DBS reversed the increases in glutamate, glutamine, and GABA levels induced by the dopamine lesion in the striatum but not in the SNr. Subchronic DBS normalized GABA in both the striatum and SNr, and glutamate in the striatum. Taurine levels were markedly decreased under subchronic DBS in the striatum and SNr in both lesioned and unlesioned rats. Microdialysis in the striatum further showed that extracellular taurine was increased. These data reveal that STN-DBS has duration-dependent metabolic effects in the basal ganglia, consistent with development of adaptive mechanisms. In addition to counteracting defects induced by the dopamine lesion, prolonged DBS has proper effects independent of the pathological condition. Non-invasive metabolic neuroimaging might be useful to understand the physiological mechanisms of deep brain stimulation (DBS). Here, we demonstrate the feasibility of repeated high-field proton magnetic resonance spectroscopy of basal ganglia structures under subthalamic nucleus DBS in control and parkinsonian rats. Results show that DBS has both rapid and delayed effects either dependent or independent of disease state.