Dementia in Parkinson's disease: diffusion tensor imaging

Pathobiology of Cognitive Impairment in Parkinson Disease: Challenges and Outlooks

Cognitive impairment (CI) is a characteristic non-motor feature of Parkinson disease (PD) that poses a severe burden on the patients and caregivers, yet relatively little is known about its pathobiology. Cognitive deficits are evident throughout the course of PD, with around 25% of subtle cognitive decline and mild CI (MCI) at the time of diagnosis and up to 83% of patients developing dementia after 20 years. The heterogeneity of cognitive phenotypes suggests that a common neuropathological process, characterized by progressive degeneration of the dopaminergic striatonigral system and of many other neuronal systems, results not only in structural deficits but also extensive changes of functional neuronal network activities and neurotransmitter dysfunctions. Modern neuroimaging studies revealed multilocular cortical and subcortical atrophies and alterations in intrinsic neuronal connectivities. The decreased functional connectivity (FC) of the default mode network (DMN) in the bilateral prefrontal cortex is affected already before the development of clinical CI and in the absence of structural changes. Longitudinal cognitive decline is associated with frontostriatal and limbic affections, white matter microlesions and changes between multiple functional neuronal networks, including thalamo-insular, frontoparietal and attention networks, the cholinergic forebrain and the noradrenergic system. Superimposed Alzheimer-related (and other concomitant) pathologies due to interactions between α-synuclein, tau-protein and β-amyloid contribute to dementia pathogenesis in both PD and dementia with Lewy bodies (DLB). To further elucidate the interaction of the pathomechanisms responsible for CI in PD, well-designed longitudinal clinico-pathological studies are warranted that are supported by fluid and sophisticated imaging biomarkers as a basis for better early diagnosis and future disease-modifying therapies.

Cortical and subcortical morphological alterations in motor subtypes of Parkinson's disease

Parkinson's disease (PD) can be classified into an akinetic-rigid (AR) and a tremor-dominant (TD) subtype based on predominant motor symptoms. Patients with different motor subtypes often show divergent clinical manifestations; however, the underlying neural mechanisms remain unclear. This study aimed to characterize the cortical and subcortical morphological alterations in motor subtypes of PD. T1-weighted MRI images were obtained for 90 patients with PD (64 with the AR subtype and 26 with the TD subtype) and 56 healthy controls (HCs). Cortical surface area, sulcal depth (measured by Freesurfer's Sulc index), and subcortical volume were computed to identify the cortical and subcortical morphological alterations in the two motor subtypes. Compared with HCs, we found widespread surface area reductions in the AR subtype yet sparse surface area reductions in the TD subtype. We found no significant Sulc change in the AR subtype yet increased Sulc in the right supramarginal gyrus in the TD subtype. The hippocampal volumes in both subtypes were lower than those of HCs. In PD patients, the surface area of left posterior cingulate cortex was positively correlated with Mini-Mental State Examination (MMSE) score, while the Sulc value of right middle frontal gyrus was positively correlated with severity of motor impairments. Additionally, the hippocampal volumes were positively correlated with MMSE and Montreal Cognitive Assessment scores and negatively correlated with severity of motor impairments and Hoehn & Yahr scores. Taken together, these findings may contribute to a better understanding of the neural substrates underlying the distinct symptom profiles in the two PD subtypes.

Morphological basis of Parkinson disease-associated cognitive impairment: an update

Cognitive impairment is one of the most salient non-motor symptoms of Parkinson disease (PD) that poses a significant burden on the patients and carers as well as being a risk factor for early mortality. People with PD show a wide spectrum of cognitive dysfunctions ranging from subjective cognitive decline and mild cognitive impairment (MCI) to frank dementia. The mean frequency of PD with MCI (PD-MCI) is 25.8% and the pooled dementia frequency is 26.3% increasing up to 83% 20 years after diagnosis. A better understanding of the underlying pathological processes will aid in directing disease-specific treatment. Modern neuroimaging studies revealed considerable changes in gray and white matter in PD patients with cognitive impairment, cortical atrophy, hypometabolism, dopamine/cholinergic or other neurotransmitter dysfunction and increased amyloid burden, but multiple mechanism are likely involved. Combined analysis of imaging and fluid markers is the most promising method for identifying PD-MCI and Parkinson disease dementia (PDD). Morphological substrates are a combination of Lewy- and Alzheimer-associated and other concomitant pathologies with aggregation of α-synuclein, amyloid, tau and other pathological proteins in cortical and subcortical regions causing destruction of essential neuronal networks. Significant pathological heterogeneity within PD-MCI reflects deficits in various cognitive domains. This review highlights the essential neuroimaging data and neuropathological changes in PD with cognitive impairment, the amount and topographical distribution of pathological protein aggregates and their pathophysiological relevance. Large-scale clinicopathological correlative studies are warranted to further elucidate the exact neuropathological correlates of cognitive impairment in PD and related synucleinopathies as a basis for early diagnosis and future disease-modifying therapies.

Low soluble amyloid-β 42 is associated with smaller brain volume in Parkinson's disease

INTRODUCTION

We sought to examine whether levels of soluble alpha-synuclein (α-syn), amyloid-beta (Aβ42), phosphorylated tau (p-tau), and total tau (t-tau), as measured in cerebrospinal fluid (CSF), are associated with changes in brain volume in Parkinson's disease.

METHODS

We assessed the 4-year change in total brain volume (n = 99) and baseline CSF α-syn, Aβ42, p-tau, and t-tau of Parkinson Progression Markers Initiative participants. We used linear mixed models to assess the longitudinal effect of baseline CSF biomarkers on total and regional brain volume and thickness as well as linear regression for cross-sectional analyses at baseline and year 2. All models were adjusted for age and gender; brain volume models also adjusted for baseline intracranial volume. Bonferroni correction was applied.

RESULTS

The 4-year change in total brain volume was -21.2 mm³ (95% confidence interval, -26.1, -16.3). There were no significant associations between the 4-year change in total brain volume and baseline levels of any CSF biomarker (all p-values > 0.05). On cross-sectional analyses, CSF Aβ42 was linearly associated with total brain volume at baseline (R² = 0.60, p = 0.0004) and at year 2 (R² = 0.66, p < 0.0001), with CSF Aβ42 < 1100 pg/ml, the threshold for brain amyloid pathology, associated with smaller total brain volume at baseline (p = 0.0010) and at year 2 (p = 0.0002). CSF α-syn was linearly associated with total brain volume at baseline (R² = 0.58, p = 0.0044) but not at year 2 (R² = 0.58, p = 0.1342).

CONCLUSION

Reduction in soluble Aβ42 is associated with lower total brain volume in Parkinson's disease.

Neuroimaging Advances in Parkinson's Disease and Atypical Parkinsonian Syndromes

Parkinson's disease (PD) and atypical Parkinsonian syndromes are progressive heterogeneous neurodegenerative diseases that share clinical characteristic of parkinsonism as a common feature, but are considered distinct clinicopathological disorders. Based on the predominant protein aggregates observed within the brain, these disorders are categorized as, (1) α-synucleinopathies, which include PD and other Lewy body spectrum disorders as well as multiple system atrophy, and (2) tauopathies, which comprise progressive supranuclear palsy and corticobasal degeneration. Although, great strides have been made in neurodegenerative disease research since the first medical description of PD in 1817 by James Parkinson, these disorders remain a major diagnostic and treatment challenge. A valid diagnosis at early disease stages is of paramount importance, as it can help accommodate differential prognostic and disease management approaches, enable the elucidation of reliable clinicopathological relationships ideally at prodromal stages, as well as facilitate the evaluation of novel therapeutics in clinical trials. However, the pursuit for early diagnosis in PD and atypical Parkinsonian syndromes is hindered by substantial clinical and pathological heterogeneity, which can influence disease presentation and progression. Therefore, reliable neuroimaging biomarkers are required in order to enhance diagnostic certainty and ensure more informed diagnostic decisions. In this article, an updated presentation of well-established and emerging neuroimaging biomarkers are reviewed from the following modalities: (1) structural magnetic resonance imaging (MRI), (2) diffusion-weighted and diffusion tensor MRI, (3) resting-state and task-based functional MRI, (4) proton magnetic resonance spectroscopy, (5) transcranial B-mode sonography for measuring substantia nigra and lentiform nucleus echogenicity, (6) single photon emission computed tomography for assessing the dopaminergic system and cerebral perfusion, and (7) positron emission tomography for quantifying nigrostriatal functions, glucose metabolism, amyloid, tau and α-synuclein molecular imaging, as well as neuroinflammation. Multiple biomarkers obtained from different neuroimaging modalities can provide distinct yet corroborative information on the underlying neurodegenerative processes. This integrative "multimodal approach" may prove superior to single modality-based methods. Indeed, owing to the international, multi-centered, collaborative research initiatives as well as refinements in neuroimaging technology that are currently underway, the upcoming decades will mark a pivotal and exciting era of further advancements in this field of neuroscience.

Diffusion Tensor Imaging in Parkinson's Disease and Parkinsonian Syndrome: A Systematic Review

Diffusion tensor imaging (DTI) allows measuring fractional anisotropy and similar microstructural indices of the brain white matter. Lower than normal fractional anisotropy as well as higher than normal diffusivity is associated with loss of microstructural integrity and neurodegeneration. Previous DTI studies in Parkinson's disease (PD) have demonstrated abnormal fractional anisotropy in multiple white matter regions, particularly in the dopaminergic nuclei and dopaminergic pathways. However, DTI is not considered a diagnostic marker for the earliest Parkinson's disease since anisotropic alterations present a temporally divergent pattern during the earliest Parkinson's course. This article reviews a majority of clinically employed DTI studies in PD, and it aims to prove the utilities of DTI as a marker of diagnosing PD, correlating clinical symptomatology, tracking disease progression, and treatment effects. To address the challenge of DTI being a diagnostic marker for early PD, this article also provides a comparison of the results from a longitudinal, early stage, multicenter clinical cohort of Parkinson's research with previous publications. This review provides evidences of DTI as a promising marker for monitoring PD progression and classifying atypical PD types, and it also interprets the possible pathophysiologic processes under the complex pattern of fractional anisotropic changes in the first few years of PD. Recent technical advantages, limitations, and further research strategies of clinical DTI in PD are additionally discussed.

Investigation of local white matter abnormality in Parkinson's disease by using an automatic fiber tract parcellation

The deficits of white matter (WM) microstructure are involved during Parkinson's disease (PD) progression. Most current methods identify key WM tracts relying on cortical regions of interest (ROIs). However, such ROI methods can be challenged due to low diffusion anisotropy near the gray matter (GM), which could result in a low sensitivity of tract identification. This work proposes an automatic WM parcellation method to improve the accuracy of WM tract identification and locate abnormal tracts by using sensitive features. The proposed method consists of 1) whole brain WM parcellation using an established fiber clustering method, without using any ROIs, 2) features of fasciculus were calculated to quantify diffusion measures at each equal cross-section along the whole cluster. Then, we use the proposed features to investigate the WM difference in PD compared with healthy controls (HC). We also use these features to investigate the relationship of clinical symptoms and specific fiber tracts. The novelty of the proposed method is that it automatically identifies the abnormal WM fibers in cluster degree. Experiment results indicated that the proposed method had advantage in detecting the local WM abnormality by performing between-group statistical analysis in 30 patients with PD and 28 HC. We found 13 hemisphere clusters and 8 commissural clusters had significant group difference (p < 0.05, corrected by FDR method) in local regions, which belonged to multiple fiber tracts including cingulum bundle (CB), inferior occipito-frontal fasciculus (IoFF), corpus callosum (CC), external capsule (EC), uncinate fasciculus (UF), superior longitudinal fasciculus (SLF) and thalamo front (TF). We also found clusters that had relevance with clinical indices of cognitive function (2 clusters), athletic function (6 clusters), and depressive state (2 clusters) in these significant clusters. From the experiment results, it confirmed the ability of the proposed method to identify potential WM microstructure abnormality.

Local White Matter Fiber Clustering Differentiates Parkinson's Disease Diagnoses

Scans without evidence of dopaminergic deficit (SWEDD) patients are often misdiagnosed with Parkinson's disease (PD) but have normal dopamine transporter scans. We hypothesised that white matter tracts associated with motor and cognition functions may be affected differently by SWEDD and PD. Automatically annotated fibre clustering (AAFC) is a novel clustering method based on diffusion magnetic resonance imaging (dMRI) tractography that enables highly robust reconstruction of white matter tracts that are composed of corresponding clusters. This study aimed to investigate the white matter properties in the subdivisions of white matter tracts among SWEDD and PD groups. We applied AAFC to identify white matter tracts related to motion and cognition functions in the dataset consisting of SWEDD (n = 22), PD (n = 30) and normal control (NC) (n = 30). Then, we resampled 200 nodes along fibres of cluster, and the diffusion metric values corresponding to each node were calculated and used for comparison. Compared with NC, PD showed significant difference (p < 0.05) in two clusters in thalamo-frontal (TF), one cluster in thalamo-parietal (TP) and one cluster in thalamo-occipital (TO), whereas SWEDD presented no significant difference. Three clusters in cingulum bundle (CB) commonly exhibited significant differences in PD versus SWEDD and NC versus SWEDD. The support vector machine classifier achieved high accuracies in PD-NC, PD-SWEDD and NC-SWEDD classifications. This outcome validated these local white matter differences were useful to separate the three groups. These results suggest that PD exerts more significant effects on thalamo tracts than SWEDD, and unique microstructural changes occur in CB tract in SWEDD.

Neuropsychiatric aspects of Parkinson disease psychopharmacology: Insights from circuit dynamics

Parkinson disease (PD) is a neurodegenerative disorder with a complex pathophysiology characterized by the progressive loss of dopaminergic neurons within the substantia nigra. Persons with PD experience several motoric and neuropsychiatric symptoms. Neuropsychiatric features of PD include depression, anxiety, psychosis, impulse control disorders, and apathy. In this chapter, we will utilize the National Institutes of Mental Health Research Domain Criteria (RDoC) to frame and integrate observations from two prevailing disease constructions: neurotransmitter anomalies and circuit physiology. When there is available evidence, we posit how unified translational observations may have clinical relevance and postulate importance outside of PD. Finally, we review the limited evidence available for pharmacologic management of these symptoms.

Neurocognitive and psychiatric disorders-related axonal degeneration in Parkinson's disease

Neurocognitive and psychiatric disorders have significant consequences for quality of life in patients with Parkinson's disease (PD). In the current study, we evaluated microstructural white matter (WM) alterations associated with neurocognitive and psychiatric disorders in PD using neurite orientation dispersion and density imaging (NODDI) and linked independent component analysis (LICA). The indices of NODDI were compared between 20 and 19 patients with PD with and without neurocognitive and psychiatric disorders, respectively, and 25 healthy controls using tract‐based spatial statistics and tract‐of‐interest analyses. LICA was applied to model inter‐subject variability across measures. A widespread reduction in axonal density (indexed by intracellular volume fraction [ICVF]) was demonstrated in PD patients with and without neurocognitive and psychiatric disorders, as compared with healthy controls. Compared with patients without neurocognitive and psychiatric disorders, patients with neurocognitive and psychiatric disorders exhibited more extensive (posterior predominant) decreases in axonal density. Using LICA, ICVF demonstrated the highest contribution (59% weight) to the main effects of diagnosis that reflected widespread decreases in axonal density. These findings suggest that axonal loss is a major factor underlying WM pathology related to neurocognitive and psychiatric disorders in PD, whereas patients with neurocognitive and psychiatric disorders had broader axonal pathology, as compared with those without. LICA suggested that the ICVF can be used as a useful biomarker of microstructural changes in the WM related to neurocognitive and psychiatric disorders in PD.

A longitudinal fixel-based analysis of white matter alterations in patients with Parkinson's disease

INTRODUCTION

Disruption to white matter pathways is an important contributor to the pathogenesis of Parkinson's disease. Fixel-based analysis has recently emerged as a useful fiber-specific tool for examining white matter structure. In this longitudinal study, we used Fixel-based analysis to investigate white matter changes occurring over time in patients with Parkinson's disease.

METHODS

Fifty patients with idiopathic Parkinson's disease (27 men and 23 women; mean age: 61.8 ± 6.1 years), were enrolled. Diffusion-weighted imaging and clinical examinations were performed at three different time points (baseline, first follow-up [after a mean of 24±2 months], and second follow-up [after a mean of 40 ± 3 months]). Additional 76 healthy control subjects (38 men and 38 women; mean age: 62.3 ± 5.5 years) were examined at baseline. The following fixel-based metrics were obtained: fiber density (FD), fiber bundle cross-section (FC), and a combined measure of both (FDC). Paired comparisons of metrics between three different time points were performed in patients. Linear regression was implemented between longitudinal changes of fixel-based metrics and the corresponding modifications in clinical parameters. A family-wise error corrected p < 0.05 was considered statistically significant.

RESULTS AND DISCUSSIONS

Early degeneration in the splenium of corpus callosum was identified as a typical alteration of Parkinson's disease over time. At follow-up, we observed significant FDC reductions compared with baseline in white matter, noticeably in corpus callosum; tapetum; cingulum, posterior thalamic radiation, corona radiata, and sagittal stratum. We also identified significant FC decreases that reflected damage to white matter structures involved in Parkinson's disease -related pathways. Fixel-based metrics were found to relate with a deterioration of 39-item Parkinson's Disease Questionnaire, Unified Parkinson's Disease Rating Scale and activity of daily living. A Parkinson's disease -facilitated aging effect was observed in terms of white matter disruption.

CONCLUSION

This study provides a thorough fixel-based profile of longitudinal white matter alterations occurring in patients with Parkinson's disease and new evidence of FC as an important role in white matter degeneration in this setting.

Multifocal alterations of white matter accompany the transition from normal cognition to dementia in Parkinson's disease patients

The purpose of the present study was to investigate the pattern of white matter (WM) changes associated with Parkinson's disease (PD)-related cognitive impairment by using fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD) and radial diffusivity (RD) measures. Diffusion Tensor Imaging (DTI) was performed in 21 PD-patients with dementia (PDD) and in an age-matched control group including 40 PD-patients without dementia (PD-CTRL). The Parkinson's disease-Cognitive Rating Scale (PD-CRS) was used for patients' neuropsychological assessment. Local microstructural WM differences associated with the presence of cognitive impairment were tested using tract-based spatial statistics analysis. Multiple regression models investigated the association of DTI indices with total PD-CRS score, PD-CRS raw items and other clinical measures across the whole study sample. Significant FA decreases were found in PDD compared to PD-CTRL patients mainly in the body of corpus callosum, corona radiata and cingulum. Lower PD-CRS score was significantly associated with decreased FA, MD and AD values in multiple WM tracts primarily located in prefrontal and limbic areas as well as across the corpus callosum. Lower performance in specific PD-CRS raw items was also associated with FA decreases in major WM tracts. The results suggest that multifocal microstructural changes of WM accompany the transition from normal to demented cognitive state in PD-patients. The corpus callosum, the corona radiata and the cingulum are among the regions mostly affected during this course. A progressive axonal degeneration is proposed as a key underlying mechanism.

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.

Neurorehabilitation in Parkinson's Disease: A Critical Review of Cognitive Rehabilitation Effects on Cognition and Brain

Background

Parkinson's disease (PD) patients experience cognitive impairment which has been related to reduced quality of life and functional disability. These symptoms usually progress until dementia occurs. Some studies have been published assessing the efficacy of cognitive treatments on improving cognition, functional outcome, and producing changes in brain activity.

Objective

A critical review was performed to present up-to-date neurorehabilitation effects of cognitive rehabilitation in PD, with special emphasis on the efficacy on cognition, quality of life aspects, brain changes, and the longitudinal maintenance of these changes.

Results

After exclusions, 13 studies were reviewed, including 6 randomized controlled trials for the efficacy on cognition, 2 randomized controlled trials regarding the brain changes after cognitive training, and 5 studies which evaluated the long-term effects of cognitive treatments.

Conclusions

Cognitive rehabilitation programs have demonstrated to be effective on improving cognitive functions, but more research is needed focusing on the efficacy on improving behavioral aspects and producing brain changes in patients with PD. Moreover, there is a need of randomized controlled trials with long-term follow-up periods.

White matter degeneration profile in the cognitive cortico-subcortical tracts in Parkinson's disease

BACKGROUND

In Parkinson's disease cognitive impairment is an early nonmotor feature, but it is still unclear why some patients are able to maintain their cognitive performance at normal levels, as quantified by neuropsychological tests, whereas others cannot. The objectives of this study were to perform a cross-sectional study and analyze the white matter changes in the cognitive and motor bundles in patients with Parkinson's disease.

METHODS

Sixteen Parkinson's disease patients with normal cognitive performance, 19 with mild cognitive impairment (based on their performance of 1.5 standard deviations below the healthy population mean), and 16 healthy controls were compared with respect to their tractography patterns between the cortical cognitive / motor regions and subcortical structures, using high angular resolution diffusion imaging and constrained spherical deconvolution computation.

RESULTS

Motor bundles showed decreased apparent fiber density in both PD groups, associated with a significant increase in diffusivity metrics, number of reconstructed streamlines, and track volumes, compared with healthy controls. By contrast, in the cognitive bundles, decreased fiber density in both Parkinson's groups was compounded by the absence of changes in diffusivity in patients with normal cognition, whereas patients with cognitive impairment had increased diffusivity metrics, lower numbers of reconstructed streamlines, and lower track volumes.

CONCLUSIONS

Both PD groups showed similar patterns of white matter neurodegeneration in the motor bundles, whereas cognitive bundles showed a distinct pattern: Parkinson's patients with normal cognition had white matter diffusivity metrics similar to healthy controls, whereas in patients with cognitive impairment white matter showed a neurodegeneration pattern. © 2018 International Parkinson and Movement Disorder Society.

Abnormal resting-state functional connectivity in posterior cingulate cortex of Parkinson's disease with mild cognitive impairment and dementia

OBJECTIVE

To investigate changes in the functional connectivity (FC) pattern in the posterior cingulate cortex (PCC) of Parkinson's disease (PD) patients with mild cognitive impairment and dementia by employing resting-state functional magnetic resonance imaging (RS-fMRI).

METHODS

Twenty-seven PD patients with different cognitive status and 9 healthy control subjects (control group) were enrolled for RS-fMRI. The RS-fMRI data were analyzed with DPARSF and REST software. Regions with changed functional connectivity were determined by the seed-based voxelwise method and compared between groups. Correlation between the intensity of FC and the MoCA scores of PD group was analyzed.

RESULTS

Parametric maps showed statistical increases in PCC functional connectivity in PD-MCI patients and decreases in PCC connectivity in PDD patients. The latter group of patients also showed evidence for increased connectivity between prefrontal cortices and posterior cerebellum. A significant positive correlation was found between the MoCA scores and the strength of PCC connectivity in the angular gyrus and posterior cerebellum and a negative correlation between MoCA scores and PCC connectivity in all other brain regions.

CONCLUSION

When patients transition from PD-NCI to PD-MCI, there appears to be an increase in functional connectivity in the PCC, suggesting an expansion of the cortical network. Another new network (a compensatory prefrontal cortical-cerebellar loop) later develops during the transition from PD-MCI to PDD.

Merging Clinical and Imaging Biomarkers to Tackle Parkinson's Disease

Background

In Parkinson's disease, biomarkers represent tools that are potentially suitable for either clinical or research settings and are useful in predicting onset, confirming diagnosis, detecting progression, and evaluating response to potential disease-modifying treatments. The range of available biomarkers in Parkinson's disease is fast expanding and includes an increasing amount of laboratory, clinical, and imaging data. Indeed, the latter 2 represent the cornerstones of the diagnostic criteria for Parkinson's disease recently proposed by the International Parkinson and Movement Disorders Society Task Force on the definition of Parkinson's disease.

Methods and Results

In this review, we describe current knowledge and emerging findings on clinical (with emphasis on nonmotor symptoms) and imaging biomarkers for Parkinson's disease, with a focus on prodromal, diagnostic, and middle/advanced phases.

Conclusion

An increasing body of evidence suggests that merging clinical and imaging biomarkers through disease stages may be the best, fastest track to tackle Parkinson's disease.

The role of diffusion magnetic resonance imaging in Parkinson's disease and in the differential diagnosis with atypical parkinsonism

Parkinson's disease is one of the most common neurodegenerative diseases. Clinically, it is characterized by motor symptoms. Parkinson's disease should be differentiated from atypical parkinsonism conditions. Conventional magnetic resonance imaging is the primary imaging method employed in order to facilitate the differential diagnosis, and its role has grown after the development of advanced techniques such as diffusion-weighted imaging. The purpose of this article was to review the role of magnetic resonance imaging in Parkinson's disease and in the differential diagnosis with atypical parkinsonism, emphasizing the diffusion technique.

Diffusion tensor imaging in Parkinson's disease: Review and meta-analysis

BACKGROUND

Neuroimaging studies help us better understand the pathophysiology and symptoms of Parkinson's disease (PD). In several of these studies, diffusion tensor imaging (DTI) was used to investigate structural changes in cerebral tissue. Although data have been provided as regards to specific brain areas, a whole brain meta-analysis is still missing.

METHODS

We compiled 39 studies in this meta-analysis: 14 used fractional anisotropy (FA), 1 used mean diffusivity (MD), and 24 used both indicators. These studies comprised 1855 individuals, 1087 with PD and 768 healthy controls. Regions of interest were classified anatomically (subcortical structures; white matter; cortical areas; cerebellum). Our statistical analysis considered the disease effect size (DES) as the main variable; the heterogeneity index (I2) and Pearson's correlations between the DES and co-variables (demographic, clinical and MRI parameters) were also calculated.

RESULTS

Our results showed that FA-DES and MD-DES were able to distinguish between patients and healthy controls. Significant differences, indicating degenerations, were observed within the substantia nigra, the corpus callosum, and the cingulate and temporal cortices. Moreover, some findings (particularly in the corticospinal tract) suggested opposite brain changes associated with PD. In addition, our results demonstrated that MD-DES was particularly sensitive to clinical and MRI parameters, such as the number of DTI directions and the echo time within white matter.

CONCLUSIONS

Despite some limitations, DTI appears as a sensitive method to study PD pathophysiology and severity. The association of DTI with other MRI methods should also be considered and could benefit the study of brain degenerations in PD.

Cognition in Parkinson's Disease

Cognitive decline is now recognized as a common nonmotor symptom of Parkinson's disease, and it has been the subject of increasing research in recent decades. Cognitive deficits in Parkinson's disease can be distinguished as dopaminergically mediated executive dysfunction seen in the milder stages vs a global dementia syndrome that can occur with disease progression. The neural basis of these deficits has been explored from the perspective of multimodal imaging techniques to measure the structural, functional, and metabolic correlates of cognitive decline in Parkinson's disease. Increasingly, changes in neurotransmitter systems beyond dopamine, including the noradrenergic, serotonergic, and cholinergic systems, are being recognized for their contribution to cognitive decline. The impact of certain genetic variations on cognitive function has also been established, including links between cognitive decline and polymorphisms affecting COMT, MAPT, APOE, and GBA genotypes. Although therapeutic options for cognitive decline are still far less established than for motor systems, both pharmacological and nonpharmacological strategies are continuing to develop.

Imaging biomarkers in Parkinson's disease and Parkinsonian syndromes: current and emerging concepts

Two centuries ago in 1817, James Parkinson provided the first medical description of Parkinson’s disease, later refined by Jean-Martin Charcot in the mid-to-late 19th century to include the atypical parkinsonian variants (also termed, Parkinson-plus syndromes). Today, Parkinson’s disease represents the second most common neurodegenerative disorder with an estimated global prevalence of over 10 million. Conversely, atypical parkinsonian syndromes encompass a group of relatively heterogeneous disorders that may share some clinical features with Parkinson’s disease, but are uncommon distinct clinicopathological diseases. Decades of scientific advancements have vastly improved our understanding of these disorders, including improvements in in vivo imaging for biomarker identification. Multimodal imaging for the visualization of structural and functional brain changes is especially important, as it allows a ‘window’ into the underlying pathophysiological abnormalities. In this article, we first present an overview of the cardinal clinical and neuropathological features of, 1) synucleinopathies: Parkinson’s disease and other Lewy body spectrum disorders, as well as multiple system atrophy, and 2) tauopathies: progressive supranuclear palsy, and corticobasal degeneration. A comprehensive presentation of well-established and emerging imaging biomarkers for each disorder are then discussed. Biomarkers for the following imaging modalities are reviewed: 1) structural magnetic resonance imaging (MRI) using T1, T2, and susceptibility-weighted sequences for volumetric and voxel-based morphometric analyses, as well as MRI derived visual signatures, 2) diffusion tensor MRI for the assessment of white matter tract injury and microstructural integrity, 3) proton magnetic resonance spectroscopy for quantifying proton-containing brain metabolites, 4) single photon emission computed tomography for the evaluation of nigrostriatal integrity (as assessed by presynaptic dopamine transporters and postsynaptic dopamine D2 receptors), and cerebral perfusion, 5) positron emission tomography for gauging nigrostriatal functions, glucose metabolism, amyloid and tau molecular imaging, as well as neuroinflammation, 6) myocardial scintigraphy for dysautonomia, and 7) transcranial sonography for measuring substantia nigra and lentiform nucleus echogenicity. Imaging biomarkers, using the ‘multimodal approach’, may aid in making early, accurate and objective diagnostic decisions, highlight neuroanatomical and pathophysiological mechanisms, as well as assist in evaluating disease progression and therapeutic responses to drugs in clinical trials.

Diffusion alterations associated with Parkinson's disease symptomatology: A review of the literature

Parkinson's disease (PD) is a heterogeneous neurological disorder with a variety of motor and non-motor symptoms. The underlying mechanisms of these symptoms are not fully understood. An increased interest in structural connectivity analyses using diffusion tensor imaging (DTI) in PD has led to an expansion of our understanding of the impact of abnormalities in diffusivity on phenotype. This review outlines the contribution of these abnormalities to symptoms of PD including bradykinesia, tremor and non-tremor phenotypes, freezing of gait, cognitive impairment, mood, sleep disturbances, visual hallucinations and olfactory dysfunction. Studies have shown that impairments in cognitive functioning are related to diffusion abnormalities in frontal and parietal regions, as well as in the corpus callosum and major fibres connecting midbrain and subcortical structures with the neocortex. However, the impact of diffusion alterations on motor, mood and other symptoms of PD are less well understood. The findings presented here highlight the challenges faced and the potential areas of future research avenues where DTI may be beneficial. Larger cohort studies and standardized imaging protocols are required to investigate current promising preliminary findings.

Combined Diffusion Tensor Imaging and Arterial Spin Labeling as Markers of Early Parkinson's disease

This study aimed to identify a PD-specific MRI pattern using combined diffusion tensor imaging (DTI) and arterial spin labeling (ASL) to discriminate patients with early PD from healthy subjects and evaluate disease status. Twenty-one early and 22 mid-late PD patients, and 22 healthy, age/gender-matched controls underwent 3-T MRI with apparent diffusion coefficient (ADC), fractional anisotropy (FA), fiber number (FN) and cerebral blood flow (CBF) measurements. We found that compared with healthy subjects, there was a profound reduction in FN passing through the SN in PD. FA in the SN and CBF in the caudate nucleus were inversely correlated with motor dysfunction. A negative correlation was observed between FA in the hippocampus (Hip) and the NMSS-Mood score, whereas CBF in the Hip and the prefrontal cortex(PFC) correlated with declined cognition. Stratified five-fold cross-validation identified FA in the SN(FA-SN_Av), CBF in the PFC(CBF-PFC_Av) and FA in the parietal white matter(FA-PWM_Av), and the combination of these measurements offered relatively high accuracy (AUC 0.975, 90% sensitivity and 100% specificity) in distinguishing those with early PD from healthy subjects. We demonstrate that the decreased FNs through SN in combination with changes in FA-SN_Av, CBF-PFC_Av and FA-PWM_Av values might serve as potential markers of early-stage PD.

Biomarkers for dementia and mild cognitive impairment in Parkinson's disease

Cognitive decline is one of the most frequent and disabling nonmotor features of Parkinson's disease. Around 30% of patients with Parkinson's disease experience mild cognitive impairment, a well-established risk factor for the development of dementia. However, mild cognitive impairment in patients with Parkinson's disease is a heterogeneous entity that involves different types and extents of cognitive deficits. Because it is not currently known which type of mild cognitive impairment confers a higher risk of progression to dementia, it would be useful to define biomarkers that could identify these patients to better study disease progression and possible interventions. In this sense, the identification among patients with Parkinson's disease and mild cognitive impairment of biomarkers associated with dementia would allow the early detection of this process. This review summarizes studies from the past 25 years that have assessed the potential biomarkers of dementia and mild cognitive impairment in Parkinson's disease patients. Despite the potential importance, no biomarker has as yet been validated. However, features such as low levels of epidermal and insulin-like growth factors or uric acid in plasma/serum and of Aß in CSF, reduction of cerebral cholinergic innervation and metabolism measured by PET mainly in posterior areas, and hippocampal atrophy in MRI might be indicative of distinct deficits with a distinct risk of dementia in subgroups of patients. Longitudinal studies combining the existing techniques and new approaches are needed to identify patients at higher risk of dementia. © 2016 International Parkinson and Movement Disorder Society.

Imaging synucleinopathies

In this review the structural and functional imaging changes associated with the synucleinopathies PD, MSA, and dementias associated with Lewy bodies are reviewed. The role of imaging for supporting differential diagnosis, detecting subclinical disease, and following disease progression is discussed and its potential use for monitoring disease progression is debated. © 2016 International Parkinson and Movement Disorder Society.

Neuroanatomical Correlates of Theory of Mind Deficit in Parkinson's Disease: A Multimodal Imaging Study

BACKGROUND

Parkinson's disease (PD) patients show theory of mind (ToM) deficit since the early stages of the disease, and this deficit has been associated with working memory, executive functions and quality of life impairment. To date, neuroanatomical correlates of ToM have not been assessed with magnetic resonance imaging in PD. The main objective of this study was to assess cerebral correlates of ToM deficit in PD. The second objective was to explore the relationships between ToM, working memory and executive functions, and to analyse the neural correlates of ToM, controlling for both working memory and executive functions.

METHODS

Thirty-seven PD patients (Hoehn and Yahr median = 2.0) and 15 healthy controls underwent a neuropsychological assessment and magnetic resonance images in a 3T-scanner were acquired. T1-weighted images were analysed with voxel-based morphometry, and white matter integrity and diffusivity measures were obtained from diffusion weighted images and analysed using tract-based spatial statistics.

RESULTS

PD patients showed impairments in ToM, working memory and executive functions; grey matter loss and white matter reduction compared to healthy controls. Grey matter volume decrease in the precentral and postcentral gyrus, middle and inferior frontal gyrus correlated with ToM deficit in PD. White matter in the superior longitudinal fasciculus (adjacent to the parietal lobe) and white matter adjacent to the frontal lobe correlated with ToM impairment in PD. After controlling for executive functions, the relationship between ToM deficit and white matter remained significant for white matter areas adjacent to the precuneus and the parietal lobe.

CONCLUSIONS

Findings reinforce the existence of ToM impairment from the early Hoehn and Yahr stages in PD, and the findings suggest associations with white matter and grey matter volume decrease. This study contributes to better understand ToM deficit and its neural correlates in PD, which is a basic skill for development of healthy social relationships.

Structural connectivity in Parkinson's disease

In the last decades a rapid evolution of structural advanced MRI techniques has occurred supporting the diagnosis of idiopathic Parkinson's disease, allowing us to further investigate the disease progression from nigral to extra-nigral degeneration and finally to detect pre-manifest Parkinson's disease. Diffusion-weighted imaging and diffusion tensor imaging represent advanced morphological approaches useful to detect changes in white matter integrity. These techniques, indeed, by measuring the translational displacement of water molecules in terms of fractional anisotropy and mean diffusivity, represent a powerful tool for the visualization of white matter changes, offering a unique window on brain structural connectivity. Microstructural changes can either be extracted locally in predefined regions using a region of interest analysis and tractography or, alternatively, globally into the brain using a voxel-based analysis or tract-based spatial statistics. The aim of this report was not only to summarize the distribution and nature of these alterations in Parkinson's disease but also to highlight the potential correlations between clinical, cognitive parameters and microstructural tissue loss.

Gray and white matter imaging: A biomarker for cognitive impairment in early Parkinson's disease?

BACKGROUND

The aim of this work was to investigate the cortical and white matter changes that underlie cognitive impairment in patients with incident Parkinson's disease (PD) disease using voxel-based morphometry and diffusion tensor imaging.

METHODS

Newly diagnosed nondemented PD (n = 125) and control subjects (n = 50) were recruited from the Incidence of Cognitive Impairment in Cohorts with Longitudinal Evaluation in Parkinson's Disease Study and completed cognitive assessments and 3T structural and diffusion tensor MR imaging. Voxel-based morphometry was performed to investigate the relationship between gray matter volume and cognitive ability. Microstructural white matter changes were assessed with diffusion tensor imaging measures of fractional anisotropy and mean diffusivity using tract-based spatial statistics.

RESULTS

Increased mean diffusivity was observed bilaterally in subjects with PD, relative to controls (P = 0.019). Increased mean diffusivity was associated with performance on the semantic fluency and Tower of London tasks in frontal and parietal white matter tracts, including the cingulum, superior longitudinal fasciculus, inferior longitudinal fasciculus, and inferior fronto-occipital fasciculus. There was no difference in total gray matter volume between groups; however, bilateral reductions in frontal and parietal gray matter volume were associated with reduced performance on measures of executive function in PD subjects.

CONCLUSIONS

At the earliest stages of PD, regionally specific increases in central white matter mean diffusivity are present and suggest early axonal damage. Such changes are not accompanied by significant gray matter volume loss and are consistent with proposed models of pathological progression of the disease. Structural MRI, especially diffusion tensor imaging analysis, offers potential as a noninvasive biomarker reflecting cognitive impairment in PD.

Parkinson's disease dementia: a neural networks perspective

In the long-term, with progression of the illness, Parkinson's disease dementia affects up to 90% of patients with Parkinson's disease. With increasing life expectancy in western countries, Parkinson's disease dementia is set to become even more prevalent in the future. However, current treatments only give modest symptomatic benefit at best. New treatments are slow in development because unlike the pathological processes underlying the motor deficits of Parkinson's disease, the neural mechanisms underlying the dementing process and its associated cognitive deficits are still poorly understood. Recent insights from neuroscience research have begun to unravel the heterogeneous involvement of several distinct neural networks underlying the cognitive deficits in Parkinson's disease dementia, and their modulation by both dopaminergic and non-dopaminergic transmitter systems in the brain. In this review we collate emerging evidence regarding these distinct brain networks to give a novel perspective on the pathological mechanisms underlying Parkinson's disease dementia, and discuss how this may offer new therapeutic opportunities.

Assessment of Optic Nerve Impairment in Patients with Neuromyelitis Optica by MR Diffusion Tensor Imaging

BACKGROUND

Diffusion tensor imaging (DTI) has been used for the evaluation of the white matter integrity. In this study, we evaluated optic nerve impairment in patients with neuromyelitis optica (NMO) using DTI.

METHODOLOGY/PRINCIPAL FINDINGS

Optic nerve DTI were performed on 28 NMO patients and 38 normal controls. Fractional anisotropy (FA) values were measured in the anterior, middle, and posterior parts of the intraorbital optic nerve segment. For the posterior intraorbital optic nerve, FA values of BI (0.20±0.07), MI (0.24±0.16), and NA (0.25±0.14) decreased significantly compared with that of NC (0.43±0.07) (P<0.05), and ROC analysis demonstrated that the area under the curve (AUC) measurements for BI vs. NC, MI vs. NC, NA vs. NC, and NMO (including BI, MI, and NA) vs. NC were 0.99, 0.93, 0.88, and 0.96, respectively. The corresponding diagnostic sensitivities of ROC analysis were 100%, 80%, 80%, and 91%; and the specificities were 93%, 97%, 91%, and 93%.

CONCLUSIONS/SIGNIFICANCE

Decreased FA value in the intraorbital optic nerve, especially in the posterior part of the nerve, was demonstrated as a characteristic MR feature for NMO-related optic nerve impairment.

Corpus Callosum and Cingulum Tractography in Parkinson's Disease

Background:

In Parkinson's disease (PD) cell loss in the substantia nigra is known to result in motor symptoms; however widespread pathological changes occur and may be associated with non-motor symptoms such as cognitive impairment. Diffusion tensor imaging is a quantitative imaging method sensitive to the micro-structure of white matter tracts.

Objective:

To measure fractional anisotropy (FA) and mean diffusivity (MD) values in the corpus callosum and cingulum pathways, defined by diffusion tensor tractography, in patients with PD, PD with dementia (PDD) and controls and to determine if these measures correlate with Mini-Mental Status Examination (MMSE) scores in parkinsonian patients.

Methods:

Patients with PD (17 Males [M], 12 Females [F]), mild PDD (5 M, 1F) and controls (8 M, 7F) underwent cognitive testing and MRI scans. The corpus callosum was divided into four regions and the cingulum into two regions bilaterally to define tracts using the program DTIstudio (Johns Hopkins University) using the fiber assignment by continuous tracking algorithm. Volumetric MRI scans were used to measure white and gray matter volumes.

Results:

Groups did not differ in age or education. There were no overall FA or MD differences between groups in either the corpus callosum or cingulum pathways. In PD subjects the MMSE score correlated with MD within the corpus callosum. These findings were independent of age, sex and total white matter volume.

Conclusions:

The data suggest that the corpus callosum or its cortical connections are associated with cognitive impairment in PD patients.

Cortical-subcortical interactions in hypersomnia disorders: mechanisms underlying cognitive and behavioral aspects of the sleep-wake cycle

Subcortical circuits mediating sleep–wake functions have been well characterized in animal models, and corroborated by more recent human studies. Disruptions in these circuits have been identified in hypersomnia disorders (HDs) such as narcolepsy and Kleine–Levin Syndrome, as well as in neurodegenerative disorders expressing excessive daytime sleepiness. However, the behavioral expression of sleep–wake functions is not a simple on-or-off state determined by subcortical circuits, but encompasses a complex range of behaviors determined by the interaction between cortical networks and subcortical circuits. While conceived as disorders of sleep, HDs are equally disorders of wake, representing a fundamental instability in neural state characterized by lapses of alertness during wake. These episodic lapses in alertness and wakefulness are also frequently seen in neurodegenerative disorders where electroencephalogram demonstrates abnormal function in cortical regions associated with cognitive fluctuations (CFs). Moreover, functional connectivity MRI shows instability of cortical networks in individuals with CFs. We propose that the inability to stabilize neural state due to disruptions in the sleep–wake control networks is common to the sleep and cognitive dysfunctions seen in hypersomnia and neurodegenerative disorders.

A preliminary diffusional kurtosis imaging study of Parkinson disease: comparison with conventional diffusion tensor imaging

INTRODUCTION

Diffusional kurtosis imaging (DKI) is a more sensitive technique than conventional diffusion tensor imaging (DTI) for assessing tissue microstructure. In particular, it quantifies the microstructural integrity of white matter, even in the presence of crossing fibers. The aim of this preliminary study was to compare how DKI and DTI show white matter alterations in Parkinson disease (PD).

METHODS

DKI scans were obtained with a 3-T magnetic resonance imager from 12 patients with PD and 10 healthy controls matched by age and sex. Tract-based spatial statistics were used to compare the mean kurtosis (MK), mean diffusivity (MD), and fractional anisotropy (FA) maps of the PD patient group and the control group. In addition, a region-of-interest analysis was performed for the area of the posterior corona radiata and superior longitudinal fasciculus (SLF) fiber crossing.

RESULTS

FA values in the frontal white matter were significantly lower in PD patients than in healthy controls. Reductions in MK occurred more extensively throughout the brain: in addition to frontal white matter, MK was lower in the parietal, occipital, and right temporal white matter. The MK value of the area of the posterior corona radiata and SLF fiber crossing was also lower in the PD group.

CONCLUSION

DKI detects changes in the cerebral white matter of PD patients more sensitively than conventional DTI. In addition, DKI is useful for evaluating crossing fibers. By providing a sensitive index of brain pathology in PD, DKI may enable improved monitoring of disease progression.

Brain aging in humans, chimpanzees (Pan troglodytes), and rhesus macaques (Macaca mulatta): magnetic resonance imaging studies of macro- and microstructural changes

Among primates, humans are uniquely vulnerable to many age-related neurodegenerative disorders. We used structural and diffusion magnetic resonance imaging (MRI) to examine the brains of chimpanzees and rhesus monkeys across each species' adult lifespan, and compared these results with published findings in humans. As in humans, gray matter volume decreased with age in chimpanzees and rhesus monkeys. Also like humans, chimpanzees showed a trend for decreased white matter volume with age, but this decrease occurred proportionally later in the chimpanzee lifespan than in humans. Diffusion MRI revealed widespread age-related decreases in fractional anisotropy and increases in radial diffusivity in chimpanzees and macaques. However, both the fractional anisotropy decline and the radial diffusivity increase started at a proportionally earlier age in humans than in chimpanzees. Thus, even though overall patterns of gray and white matter aging are similar in humans and chimpanzees, the longer lifespan of humans provides more time for white matter to deteriorate before death, with the result that some neurological effects of aging may be exacerbated in our species.

Neuroimaging biomarkers of neurodegenerative diseases and dementia

Neurodegenerative disorders leading to dementia are common diseases that affect many older and some young adults. Neuroimaging methods are important tools for assessing and monitoring pathological brain changes associated with progressive neurodegenerative conditions. In this review, the authors describe key findings from neuroimaging studies (magnetic resonance imaging and radionucleotide imaging) in neurodegenerative disorders, including Alzheimer's disease (AD) and prodromal stages, familial and atypical AD syndromes, frontotemporal dementia, amyotrophic lateral sclerosis with and without dementia, Parkinson's disease with and without dementia, dementia with Lewy bodies, Huntington's disease, multiple sclerosis, HIV-associated neurocognitive disorder, and prion protein associated diseases (i.e., Creutzfeldt-Jakob disease). The authors focus on neuroimaging findings of in vivo pathology in these disorders, as well as the potential for neuroimaging to provide useful information for differential diagnosis of neurodegenerative disorders.

A Comparative White Matter Study with Parkinson's disease, Parkinson's Disease with Dementia and Alzheimer's Disease

Alzheimer's disease (AD) and Parkinson's disease (PD) are among the most common neurodegenerative disorders affecting older populations. AD is characterized by impaired memory and cognitive decline while the primary symptoms of PD include resting tremor, bradykinesia and rigidity. In PD, mild cognitive changes are frequently present, which could progress to dementia (PD dementia (PDD)). PDD and AD dementias are different in pathology although the difference in microstructural changes remains unknown. To further understand these diseases, it is essential to understand the distinct mechanism of their microstructural changes. We used diffusion tensor imaging (DTI) to investigate white matter tract differences between early stage individuals with AD (n=14), PD (n=12), PDD (n=9), and healthy non-demented controls (CON) (n=13). We used whole brain tract based spatial statistics (TBSS) and a region of interest (ROI) analysis focused on the substantia nigra (SN). We found that individuals with PDD had more widespread white matter degeneration compared to PD, AD, and CON. Individuals with AD had few regional abnormalities in the anterior and posterior projections of the corpus callosum while PD and CON did not appear to have significant white matter degeneration when compared to other groups. ROI analyses showed that PDD had the highest diffusivity in the SN and were significantly different from CON. There were no significant ROI differences between CON, PD, or AD. In conclusion, global white matter microstructural deterioration is evident in individuals with PDD, and DTI may provide a means with which to tease out pathological differences between AD and PD dementias.

Update on diffusion MRI in Parkinson's disease and atypical parkinsonism

Differentiating Parkinson's disease (PD) from other types of neurodegenerative atypical parkinsonism (AP) can be challenging, especially in early disease stages. Routine brain magnetic resonance imaging (MRI) can show atrophy or signal changes in several parts of the brain with fairly high specificity for particular forms of AP, but the overall diagnostic value of routine brain MRI is limited. In recent years, various advanced MRI sequences have become available, including diffusion weighted imaging (DWI) and diffusion tensor imaging (DTI). Here, we review available literature on the value of diffusion MRI for identifying and quantifying different patterns of neurodegeneration in PD and AP, in relation to what is known of underlying histopathologic changes and clinical presentation of these diseases. Next, we evaluate the value of diffusion MRI to differentiate between PD and AP and the potential value of serial diffusion MRI to monitor disease progression. We conclude that diffusion MRI may quantify patterns of neurodegeneration which could be of additional value in clinical use. Future prospective clinical cohort studies are warranted to assess the added diagnostic value of diffusion MRI.

Automatic extraction of the cingulum bundle in diffusion tensor tract-specific analysis: feasibility study in Parkinson's disease with and without dementia

PURPOSE

Tract-specific analysis (TSA) measures diffusion parameters along a specific fiber that has been extracted by fiber tracking using manual regions of interest (ROIs), but TSA is limited by its requirement for manual operation, poor reproducibility, and high time consumption. We aimed to develop a fully automated extraction method for the cingulum bundle (CB) and to apply the method to TSA in neurobehavioral disorders such as Parkinson's disease (PD).

MATERIALS AND METHODS

We introduce the voxel classification (VC) and auto diffusion tensor fiber-tracking (AFT) methods of extraction. The VC method directly extracts the CB, skipping the fiber-tracking step, whereas the AFT method uses fiber tracking from automatically selected ROIs. We compared the results of VC and AFT to those obtained by manual diffusion tensor fiber tracking (MFT) performed by 3 operators. We quantified the Jaccard similarity index among the 3 methods in data from 20 subjects (10 normal controls [NC] and 10 patients with Parkinson's disease dementia [PDD]). We used all 3 extraction methods (VC, AFT, and MFT) to calculate the fractional anisotropy (FA) values of the anterior and posterior CB for 15 NC subjects, 15 with PD, and 15 with PDD.

RESULTS

The Jaccard index between results of AFT and MFT, 0.72, was similar to the inter-operator Jaccard index of MFT. However, the Jaccard indices between VC and MFT and between VC and AFT were lower. Consequently, the VC method classified among 3 different groups (NC, PD, and PDD), whereas the others classified only 2 different groups (NC, PD or PDD).

CONCLUSION

For TSA in Parkinson's disease, the VC method can be more useful than the AFT and MFT methods for extracting the CB. In addition, the results of patient data analysis suggest that a reduction of FA in the posterior CB may represent a useful biological index for monitoring PD and PDD.

Diffusion tensor imaging in parkinsonian syndromes: a systematic review and meta-analysis

OBJECTIVES

We performed a systematic review to assess alterations in measures of diffusion tensor imaging (DTI) in parkinsonian syndromes, exploring the potential role of DTI in diagnosis and as a candidate biomarker.

METHODS

We searched EMBASE and Medline databases for DTI studies comparing parkinsonian syndromes or related dementias with controls or another defined parkinsonian syndrome. Key details for each study regarding participants, imaging methods, and results were extracted. Estimates were pooled, where appropriate, by random-effects meta-analysis.

RESULTS

Of 333 results, we identified 43 studies suitable for inclusion (958 patients, 764 controls). DTI measures detected alterations in all parkinsonian syndromes, with distribution varying differentially with disease type. Nine studies were included in a meta-analysis of the substantia nigra in Parkinson disease. A notable effect size was found for lowered fractional anisotropy in the substantia nigra for patients with Parkinson disease vs controls (-0.639, 95% confidence interval -0.860 to -0.417, p < 0.0001).

CONCLUSION

DTI may be a promising biomarker in parkinsonian syndromes and have a future role in differential diagnosis. Larger cohort studies are required to investigate some encouraging preliminary findings. Given the complexity of the parkinsonian syndromes, it is likely that any potential DTI biomarker would be used in combination with other relevant biomarkers.

White-matter changes correlate with cognitive functioning in Parkinson's disease

Diffusion tensor imaging (DTI) findings from emerging studies of cortical white-matter integrity in Parkinson’s disease (PD) without dementia are inconclusive. When white-matter changes have been found, their relationship to cognitive functioning in PD has not been carefully investigated. To better characterize changes in tissue diffusivity and to understand their functional significance, the present study conducted DTI in 25 PD patients without dementia and 26 controls of similar ages. An automated tract-based DTI method was used. Fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) were analyzed. Neuropsychological measures of executive functioning (working memory, verbal fluency, cognitive flexibility, inhibitory control) and visuospatial ability were then correlated with regions of interest that showed abnormal diffusivity in the PD group. We found widespread reductions in FA and increases in MD in the PD group relative to controls. These changes were predominantly related to an increase in RD. Increased AD in the PD group was limited to specific frontal tracks of the right hemisphere, possibly signifying more significant tissue changes. Motor symptom severity did not correlate with FA. However, different measures of executive functioning and visuospatial ability correlated with FA in different segments of tracts, which contain fiber pathways to cortical regions that are thought to support specific cognitive processes. The findings suggest that abnormal tissue diffusivity may be sensitive to subtle cognitive changes in PD, some of which may be prognostic of future cognitive decline.

Diffusion tensor imaging reveals white matter changes associated with cognitive status in patients with Parkinson's disease

Objective : Cognitive deficit and white matter alteration relationships in Parkinson's disease (PD) were investigated. Methods : Comparison of 64 patients with PD (M:F, 34:30; 64.4 ± 10.4 years) classified as cognitively normal (PD-CogNL, n = 24), mild cognitive impairment (PD-MCI, n = 30), and dementia (PD-D, n = 10) with 21 healthy participants (M:F, 10:11; 60.1 ± 13.6 years) was conducted using white matter fractional anisotropy (FA), region-of-interest analysis, and diffusion tensor imaging. Results : The PD-D and PD-MCI exhibited higher Unified Parkinson's Disease Rating Scale motor scores (P < .001; P < .01) and Hoehn-Yahr stages (P < .001; P < .05) and FA reductions in left frontal/right temporal white matter and bilateral anterior cingulated bundles. Largest FA reductions occurred in PD-D left anterior cingulated bundle and corpus callosum splenium. Disease durations of PD-D = 6.8 ± 6.86, PD-MCI = 5.1 ± 2.9, and PD-CogNL = 4.7 ± 3.4 years, suggesting progressive deterioration. Conclusions : Cerebral white matter deterioration may underlie progressive cognitive impairment in PD.

Magnetic resonance imaging: a biomarker for cognitive impairment in Parkinson's disease?

Dementia is a frequent and disabling complication of Parkinson's disease (PD). Clinicians and researchers lack a biomarker capable of tracking the structural and functional changes that underlie the evolution of cognitive dysfunction in PD. Magnetic resonance imaging (MRI) has been adopted as a biomarker in natural history and interventional studies of Alzheimer's disease (AD) and amnestic mild cognitive impairment (MCI), but its utility as a biomarker for PD and Parkinson's disease dementia (PDD) is unclear. In this review, the authors summarize the studies that have used MRI to investigate cognitive decline in PD, outline limitations of those studies, and suggest directions for future research. PD dementia is associated with extensive cortical atrophy, which may be quantified with structural MRI. More promisingly, patterns of atrophy may be present in those who have PD with MCI (PD-MCI). Subcortical white matter tract degeneration is detectable early in the disease with diffusion tensor imaging and may precede changes observed on conventional structural MRI. Although less well studied, other MR techniques, such as functional MRI, MR perfusion imaging with arterial spin labeling, and MR spectroscopy, have demonstrated differences in activation and metabolism between PD and PDD. In this review, the ability to compare studies was limited by the heterogeneity of study populations, cognitive testing methods, and imaging protocols. Future work should adopt agreed scan protocols, should be adequately powered, and should use carefully phenotyped patients to fully maximize the contribution of MRI as a biomarker for PDD.

Relationship between cognitive impairment and white-matter alteration in Parkinson's disease with dementia: tract-based spatial statistics and tract-specific analysis

Objectives

We investigated the relationship between white-matter alteration and cognitive status in Parkinson’s disease (PD) with and without dementia by using diffusion tensor imaging.

Methods

Twenty PD patients, 20 PDD (Parkinson’s disease with dementia) patients and 20 age-matched healthy controls underwent diffusion tensor imaging. The mean diffusivity and fractional anisotropy (FA) map of each patient group were compared with those of the control group by using tract-based spatial statistics. Tractography images of the genu of the corpus callosum fibre tracts were generated, and mean diffusivity and FA were measured.

Results

FA values in many major tracts were significantly lower in PDD patients than in control subjects; in the prefrontal white matter and the genu of the corpus callosum they were significantly lower in PDD patients than in PD patients. There was a significant correlation between the Mini-Mental State Examination (MMSE) scores and the FA values of the prefrontal white matter and the genu of the corpus callosum in patients with PD.

Conclusions

Our study shows a relationship between cognitive impairment and alteration of the prefrontal white matter and genu of the corpus callosum. These changes may be useful in assessing the onset of dementia in PD patients.

Key Points

• Dementia is a common and important non-motor sign of Parkinson’s disease (PD).

• The neuropathological basis of dementia in PD is not clear.

• DTI shows abnormalities in the prefrontal white matter in PD with dementia.

• Prefrontal white matter alteration may be useful biomarker of dementia in PD.

Nonmotor manifestations in Parkinson disease

BACKGROUND

Although the diagnosis of Parkinson disease (PD) still relies mainly on the appearance of its classical motor features of resting tremor, rigidity, bradykinesia, and postural instability, nonmotor manifestations in PD are now recognized as an integral component of this multisystem disorder.

REVIEW SUMMARY

Nonmotor complications in PD occur commonly. The current understanding of cognitive dysfunction; neuropsychiatric manifestations including psychosis, impulsive control, and compulsive disorders, depression, anxiety and apathy; autonomic complications such as hypotension, erectile dysfunction, and urinary complications; sleep disorders and other nonmotor manifestations are summarized in this review.

CONCLUSION

Nonmotor complications often carry a greater impact than motor features in PD. Therefore, heightened awareness and proper recognition of these features are critical in improving a Parkinson patient's quality of life.