Asymmetrical diffusion tensor imaging indices of the rostral substantia nigra in Parkinson's disease

Ferroptosis in Parkinson's disease -- The iron-related degenerative disease

Parkinson's disease (PD) is a prevalent and advancing age-related neurodegenerative disorder, distinguished by the degeneration of dopaminergic neurons in the substantia nigra pars compacta (SNpc). Iron regional deposit in SNpc is a significant pathological characteristic of PD. Brain iron homeostasis is precisely regulated by iron metabolism related proteins, whereas disorder of these proteins can damage neurons and glial cells in the brain. Additionally, growing studies have reported iron metabolism related proteins are involved in the ferroptosis progression in PD. However, the effect of these proteins in the ferroptosis of PD has not been systematically summarized. This review focuses on the roles of iron metabolism related proteins in the ferroptosis of PD. Finally, we put forward the iron early diagnosis according to the observation of iron deposits in the brain and showed the recent advances in iron chelation therapy in PD.

Asymmetries of the subthalamic activity in Parkinson's disease: phase-amplitude coupling among local field potentials

The role of brain asymmetries of dopaminergic neurons in motor symptoms of Parkinson's disease is still undefined. Local field recordings from the subthalamic nucleus revealed some neurophysiological biomarkers of the disease: increased beta activity, increased low-frequency activity and high-frequency oscillations. Phase-amplitude coupling coordinates the timing of neuronal activity and allows determining the mechanism for communication within distinct regions of the brain. In this study, we discuss the use of phase-amplitude coupling to assess the differences between the two hemispheres in a cohort of 24 patients with Parkinson's disease before and after levodopa administration. Subthalamic low- (12-20 Hz) and high-beta (20-30 Hz) oscillations were compared with low- (30-45 Hz), medium- (70-100 Hz) and high-frequency (260-360 Hz) bands. We found a significant beta-phase-amplitude coupling asymmetry between left and right and an opposite-side-dependent effect of the pharmacological treatment, which is associated with the reduction of motor symptoms. In particular, high coupling between high frequencies and high-beta oscillations was found during the OFF condition (P < 0.01) and a low coupling during the ON state (P < 0.0001) when the right subthalamus was assessed; exactly the opposite happened when the left subthalamus was considered in the analysis, showing a lower coupling between high frequencies and high-beta oscillations during the OFF condition (P < 0.01), followed by a higher one during the ON state (P < 0.01). Interestingly, these asymmetries are independent of the motor onset side, either left or right. These findings have important implications for neural signals that may be used to trigger adaptive deep brain stimulation in Parkinson's and could provide more exhaustive insights into subthalamic dynamics.

Prediction of Parkinson's disease pathogenic variants using hybrid Machine learning systems and radiomic features

PURPOSE

In Parkinson's disease (PD), 5-10% of cases are of genetic origin with mutations identified in several genes such as leucine-rich repeat kinase 2 (LRRK2) and glucocerebrosidase (GBA). We aim to predict these two gene mutations using hybrid machine learning systems (HMLS), via imaging and non-imaging data, with the long-term goal to predict conversion to active disease.

METHODS

We studied 264 and 129 patients with known LRRK2 and GBA mutations status from PPMI database. Each dataset includes 513 features such as clinical features (CFs), conventional imaging features (CIFs) and radiomic features (RFs) extracted from DAT-SPECT images. Features, normalized by Z-score, were univariately analyzed for statistical significance by the t-test and chi-square test, adjusted by Benjamini-Hochberg correction. Multiple HMLSs, including 11 features extraction (FEA) or 10 features selection algorithms (FSA) linked with 21 classifiers were utilized. We also employed Ensemble Voting (EV) to classify the genes.

RESULTS

For prediction of LRRK2 mutation status, a number of HMLSs resulted in accuracies of 0.98 ± 0.02 and 1.00 in 5-fold cross-validation (80% out of total data points) and external testing (remaining 20%), respectively. For predicting GBA mutation status, multiple HMLSs resulted in high accuracies of 0.90 ± 0.08 and 0.96 in 5-fold cross-validation and external testing, respectively. We additionally showed that SPECT-based RFs added value to the specific prediction of of GBA mutation status.

CONCLUSION

We demonstrated that combining medical information with SPECT-based imaging features, and optimal utilization of HMLS can produce excellent prediction of the mutations status in PD patients.

A Predictive Visual Analytics System for Studying Neurodegenerative Disease Based on DTI Fiber Tracts

Diffusion tensor imaging (DTI) has been used to study the effects of neurodegenerative diseases on neural pathways, which may lead to more reliable and early diagnosis of these diseases as well as a better understanding of how they affect the brain. We introduce a predictive visual analytics system for studying patient groups based on their labeled DTI fiber tract data and corresponding statistics. The system's machine-learning-augmented interface guides the user through an organized and holistic analysis space, including the statistical feature space, the physical space, and the space of patients over different groups. We use a custom machine learning pipeline to help narrow down this large analysis space and then explore it pragmatically through a range of linked visualizations. We conduct several case studies using DTI and T1-weighted images from the research database of Parkinson's Progression Markers Initiative.

Mapping Motor Pathways in Parkinson’s Disease Patients with Subthalamic Deep Brain Stimulator: A Diffusion MRI Tractography Study

Introduction

This study assessed the safety of postoperative diffusion tensor imaging (DTI) with on-state deep brain stimulation (DBS) and the feasibility of reconstruction of the white matter tracts in the vicinity of the stimulation site of the subthalamic nucleus (STN). The association between the impact of DBS on the nigrostriatal pathway (NSP) and the treatment effect on motor symptoms in Parkinson’s disease (PD) was then evaluated.

Methods

Thirty-one PD patients implanted with STN-DBS (mean age: 66 years; 25 male) were scanned on a 1.5-T magnetic resonance imaging (MRI) scanner using the DTI sequence with DBS on. Twenty-three of them were scanned a second time with DBS off. The NSP, dentato-rubro-thalamic tract (DRTT), and hyperdirect pathway (HDP) were generated using both deterministic and probabilistic tractography methods. The DBS-on-state and off-state tractography results were validated and compared. Afterward, the relationships between the characteristics of the reconstructed white matter tracts and the clinical assessment of PD symptoms and the DBS effect were further examined.

Results

No adverse events related to DTI were identified in either the DBS-on-state or off-state. Overall, the NSP was best reconstructed, followed by the DRTT and HDP, using the probabilistic tractography method. The connection probability of the left NSP was significantly lower than that of the right side (p < 0.05), and a negative correlation (r = −0.39, p = 0.042) was identified between the preoperative symptom severity in the medication-on state and the connection probability of the left NSP in the DBS-on-state images. Furthermore, the distance from the estimated left-side volume of tissue activated (VTA) by STN-DBS to the ipsilateral NSP was significantly shorter in the DBS-responsive group compared to the DBS-non-responsive group (p = 0.046).

Conclusions

DTI scanning is safe and delineation of white matter pathway is feasible for PD patients implanted with the DBS device. Postoperative DTI is a useful technique to strengthen our current understanding of the therapeutic effect of DBS for PD and has the potential to refine target selection strategies for brain stimulation.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40120-022-00331-1.

For some more seriously affected Parkinson’s disease (PD) patients, drugs are no longer effective in treating their symptoms. An alternate treatment is to use deep brain stimulation (DBS), a commonly used neurosurgical therapy for PD patients. For those DBS treatments targeting the subthalamic nucleus (STN), the electrical stimulation used may impact nearby white matter tracts and alter the effectiveness of the DBS treatment. The nigrostriatal pathway (NSP), dentato-rubro-thalamic tract, and hyperdirect pathway are three white matter tracts near the STN. They are all relevant to motor symptoms in PD. This study examined whether imaging these tracts using magnetic resonance imaging (MRI) is safe and feasible in the presence of DBS leads. The relationships between the fiber-tracking characteristics and distance to the DBS leads were then evaluated. For this purpose, 31 PD patients with stimulation-on were scanned on a 1.5 T MRI scanner using a diffusion tensor imaging sequence. A total of 23 subjects underwent another scan using the same sequence with stimulation-off. No adverse events related to diffusion tensor imaging were found. Among the white matter tracts near the STN, the NSP was best delineated, followed by the dentato-rubro-thalamic tract and the hyperdirect pathway. The connection probability of the left NSP was significantly lower than that of the right side as were the subject’s motor symptoms. The closer the distance between the NSP and the stimulation location, the better the DBS outcome. These findings indicate that imaging white matter tracts with DBS on is safe and useful in mapping DBS outcomes.

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.

Diffusion Measure Changes of Substantia Nigra Subregions and the Ventral Tegmental Area in Newly Diagnosed Parkinson's Disease

Historically, studies have extensively examined the basal ganglia in Parkinson’s disease for specific characteristics that can be observed with medical imaging. One particular methodology used for detecting changes that occur in Parkinson’s disease brains is diffusion tensor imaging, which yields diffusion indices such as fractional anisotropy and radial diffusivity that have been shown to correlate with axonal damage. In this study, we compare the diffusion measures of basal ganglia structures (with substantia nigra divided into subregions, pars compacta, and pars reticula), as well as the diffusion measures of the diffusion tracts that pass through each pair of basal ganglia structures to see if significant differences in diffusion measures can be observed in structures or tracts in newly diagnosed Parkinson’s disease patients. Additionally, we include the ventral tegmental area, a structure connected to various basal ganglia structures affected by dopaminergic neuronal loss and have historically shown significant alterations in Parkinson’s disease, in our analysis. We found significant fractional anisotropy differences in the putamen, and in the diffusion tracts that pass through pairs of both substantia nigra subregions, subthalamic nucleus, parabrachial pigmental nucleus, ventral tegmental area. Additionally, we found significant radial diffusivity differences in diffusion tracts that pass through the parabrachial nucleus, putamen, both substantia nigra subregions, and globus pallidus externa. We were able to find significant diffusion measure differences in structures and diffusion tracts, potentially due to compensatory mechanisms in response to dopaminergic neuronal loss that occurs in newly diagnosed Parkinson’s disease patients.

Brain functional specialization and cooperation in Parkinson's disease

Cerebral specialization and inter-hemispheric cooperation are two of the most prominent functional architectures of the human brain. Their dysfunctions may be related to pathophysiological changes in patients with Parkinson's disease (PD), who are characterized by unbalanced onset and progression of motor symptoms. This study aimed to characterize the two intrinsic architectures of hemispheric functions in PD using resting-state functional magnetic resonance imaging. Seventy idiopathic PD patients and 70 age-, sex-, and education-matched healthy subjects were recruited. All participants underwent magnetic resonance image scanning and clinical evaluations. The cerebral specialization (Autonomy index, AI) and inter-hemispheric cooperation (Connectivity between Functionally Homotopic voxels, CFH) were calculated and compared between groups. Compared with healthy controls, PD patients showed stronger AI in the left angular gyrus. Specifically, this difference in specialization resulted from increased functional connectivity (FC) of the ipsilateral areas (e.g., the left prefrontal area), and decreased FC in the contralateral area (e.g., the right supramarginal gyrus). Imaging-cognitive correlation analysis indicated that these connectivity were positively related to the score of Montreal Cognitive Assessment in PD patients. CFH between the bilateral sensorimotor regions was significantly decreased in PD patients compared with controls. No significant correlation between CFH and cognitive scores was found in PD patients. This study illustrated a strong leftward specialization but weak inter-hemispheric coordination in PD patients. It provided new insights to further clarify the pathological mechanism of PD.

Differentiating Parkinson's disease motor subtypes: A radiomics analysis based on deep gray nuclear lesion and white matter

OBJECTIVE

To investigate the feasibility of radiomics analysis of brain MR images to differentiate Parkinson's disease motor subtypes.

METHODS

42 postural instability gait difficulty (PIGD) patients, 92 tremor-dominant (TD) patients and 96 healthy controls were included from the Parkinson's Progressive Marker Initiative public database. For each subject, 4850 radiomic features from 148 cortical and 14 subcortical brain regions were extracted. The variance threshold and the least absolute shrinkage and selection operator were used to select the optimal features. Classification models based on Support Vector Machine, Logistic Regrcession, and Multi-Layer Perceptron were constructed to assess the performance of optimal features in the discrimination of the two subtypes. Correlations between radiomic features and clinical scores of the two subtypes were estimated.

RESULTS

The Support Vector Machine demonstrated the best performance in discriminating between the two subtypes, and the mean area under the curve was 0.833 (specificity = 83.3%, sensitivity = 75.0%, and accuracy = 80.7%). For the postural instability gait difficulty patients, these optimal features in the hippocampal showed closed correlations with the Montreal Cognitive Assessment scores (P < 0.05).

CONCLUSION

The results of our study provide preliminary evidence that radiomics analysis of brain MR images could allow discrimination between patients with TD, PIGD and control subjects and has great potential value in the clinical practice.

Imaging the Substantia Nigra in Parkinson Disease and Other Parkinsonian Syndromes

Parkinson disease is characterized by dopaminergic cell loss in the substantia nigra of the midbrain. There are various imaging markers for Parkinson disease. Recent advances in MRI have enabled elucidation of the underlying pathophysiologic changes in the nigral structure. This has contributed to accurate and early diagnosis and has improved disease progression monitoring. This article aims to review recent developments in nigral imaging for Parkinson disease and other parkinsonian syndromes, including nigrosome imaging, neuromelanin imaging, quantitative iron mapping, and diffusion-tensor imaging. In particular, this article examines nigrosome imaging using 7-T MRI and 3-T susceptibility-weighted imaging. Finally, this article discusses volumetry and its clinical importance related to symptom manifestation. This review will improve understanding of recent advancements in nigral imaging of Parkinson disease. Published under a CC BY 4.0 license.

Brain White-Matter Degeneration Due to Aging and Parkinson Disease as Revealed by Double Diffusion Encoding

Microstructure imaging by means of multidimensional diffusion encoding is increasingly applied in clinical research, with expectations that it yields a parameter that better correlates with clinical disability than current methods based on single diffusion encoding. Under the assumption that diffusion within a voxel can be well described by a collection of diffusion tensors, several parameters of this diffusion tensor distribution can be derived, including mean size, variance of sizes, orientational dispersion, and microscopic anisotropy. The information provided by multidimensional diffusion encoding also enables us to decompose the sources of the conventional fractional anisotropy and mean kurtosis. In this study, we explored the utility of the diffusion tensor distribution approach for characterizing white-matter degeneration in aging and in Parkinson disease by using double diffusion encoding. Data from 23 healthy older subjects and 27 patients with Parkinson disease were analyzed. Advanced age was associated with greater mean size and size variances, as well as smaller microscopic anisotropy. By analyzing the parameters underlying diffusion kurtosis, we found that the reductions of kurtosis in aging and Parkinson disease reported in the literature are likely driven by the reduction in microscopic anisotropy. Furthermore, microscopic anisotropy correlated with the severity of motor impairment in the patients with Parkinson disease. The present results support the use of multidimensional diffusion encoding in clinical studies and are encouraging for its future clinical implementation.

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.

Joint Multi-modal Parcellation of the Human Striatum: Functions and Clinical Relevance

The human striatum is essential for both low- and high-level functions and has been implicated in the pathophysiology of various prevalent disorders, including Parkinson's disease (PD) and schizophrenia (SCZ). It is known to consist of structurally and functionally divergent subdivisions. However, previous parcellations are based on a single neuroimaging modality, leaving the extent of the multi-modal organization of the striatum unknown. Here, we investigated the organization of the striatum across three modalities-resting-state functional connectivity, probabilistic diffusion tractography, and structural covariance-to provide a holistic convergent view of its structure and function. We found convergent clusters in the dorsal, dorsolateral, rostral, ventral, and caudal striatum. Functional characterization revealed the anterior striatum to be mainly associated with cognitive and emotional functions, while the caudal striatum was related to action execution. Interestingly, significant structural atrophy in the rostral and ventral striatum was common to both PD and SCZ, but atrophy in the dorsolateral striatum was specifically attributable to PD. Our study revealed a cross-modal convergent organization of the striatum, representing a fundamental topographical model that can be useful for investigating structural and functional variability in aging and in clinical conditions.

Microstructural abnormalities of substantia nigra in Parkinson's disease: A neuromelanin sensitive MRI atlas based study

Microstructural changes associated with degeneration of dopaminergic neurons of the substantia nigra pars compacta (SNc) in Parkinson's disease (PD) have been studied using Diffusion Tensor Imaging (DTI). However, these studies show inconsistent results, mainly due to methodological variations in delineation of SNc. To mitigate this, our work aims to construct a probabilistic atlas of SNc based on a 3D Neuromelanin Sensitive MRI (NMS‐MRI) sequence and demonstrate its applicability to investigate microstructural changes on a large dataset of PD. Using manual segmentation and deformable registration we created a novel SNc atlas in the MNI space using NMS‐MRI sequences of 27 healthy controls (HC). We first quantitatively evaluated this atlas and then employed it to investigate the micro‐structural abnormalities in SNc using diffusion MRI from 133 patients with PD and 99 HCs. Our results demonstrated significant increase in diffusivity with no changes in anisotropy. In addition, we also observed an asymmetry of the diffusion metrics with a higher diffusivity and lower anisotropy in the left SNc than the right. Finally, a multivariate classifier based on SNc diffusion features could delineate patients with PD with an average accuracy of 71.7%. Overall, from this work we establish a normative baseline for the SNc region of interest using NMS‐MRI while the application on PD data emphasizes on the contribution of diffusivity measures rather than anisotropy of white matter in PD.

Diffusion tensor and restriction spectrum imaging reflect different aspects of neurodegeneration in Parkinson's disease

To meet the need for Parkinson's disease biomarkers and evidence for amount and distribution of pathological changes, MRI diffusion tensor imaging (DTI) has been explored in a number of previous studies. However, conflicting results warrant further investigations. As tissue microstructure, particularly of the grey matter, is heterogeneous, a more precise diffusion model may benefit tissue characterization. The purpose of this study was to analyze the diffusion-based imaging technique restriction spectrum imaging (RSI) and DTI, and their ability to detect microstructural changes within brain regions associated with motor function in Parkinson's disease. Diffusion weighted (DW) MR images of a total of 100 individuals, (46 Parkinson's disease patients and 54 healthy controls) were collected using b-values of 0-4000s/mm2. Output diffusion-based maps were estimated based on the RSI-model combining the full set of DW-images (Cellular Index (CI), Neurite Density (ND)) and DTI-model combining b = 0 and b = 1000 s/mm2 (fractional anisotropy (FA), Axial-, Mean- and Radial diffusivity (AD, MD, RD)). All parametric maps were analyzed in a voxel-wise group analysis, with focus on typical brain regions associated with Parkinson's disease pathology. CI, ND and DTI diffusivity metrics (AD, MD, RD) demonstrated the ability to differentiate between groups, with strongest performance within the thalamus, prone to pathology in Parkinson's disease. Our results indicate that RSI may improve the predictive power of diffusion-based MRI, and provide additional information when combined with the standard diffusivity measurements. In the absence of major atrophy, diffusion techniques may reveal microstructural pathology. Our results suggest that protocols for MRI diffusion imaging may be adapted to more sensitive detection of pathology at different sites of the central nervous system.

The Combination of DAT-SPECT, Structural and Diffusion MRI Predicts Clinical Progression in Parkinson's Disease

There is an increasing interest in identifying non-invasive biomarkers of disease severity and prognosis in idiopathic Parkinson’s disease (PD). Dopamine-transporter SPECT (DAT-SPECT), diffusion tensor imaging (DTI), and structural magnetic resonance imaging (sMRI) provide unique information about the brain’s neurotransmitter and microstructural properties. In this study, we evaluate the relative and combined capability of these imaging modalities to predict symptom severity and clinical progression in de novo PD patients. To this end, we used MRI, SPECT, and clinical data of de novo drug-naïve PD patients (n = 205, mean age 61 ± 10) and age-, sex-matched healthy controls (n = 105, mean age 58 ± 12) acquired at baseline. Moreover, we employed clinical data acquired at 1 year follow-up for PD patients with or without L-Dopa treatment in order to predict the progression symptoms severity. Voxel-based group comparisons and covariance analyses were applied to characterize baseline disease-related alterations for DAT-SPECT, DTI, and sMRI. Cortical and subcortical alterations in de novo PD patients were found in all evaluated imaging modalities, in line with previously reported midbrain-striato-cortical network alterations. The combination of these imaging alterations was reliably linked to clinical severity and disease progression at 1 year follow-up in this patient population, providing evidence for the potential use of these modalities as imaging biomarkers for disease severity and prognosis that can be integrated into clinical trials.

High-Spatial-Resolution Diffusion MRI in Parkinson Disease: Lateral Asymmetry of the Substantia Nigra

Background Motor symptoms in Parkinson disease (PD) have exhibited lateral asymmetry, suggesting asymmetric neuronal loss in the substantia nigra (SN). Diffusion MRI may be able to help confirm tissue microstructural alterations in the substantia nigra to probe for the presence of asymmetry. Purpose To investigate lateral asymmetry in the SN of patients with PD by using diffusion MRI with both Gaussian and non-Gaussian models. Materials and Methods In this cross-sectional study conducted from March 2015 to March 2017, 27 participants with PD and 27 age-matched healthy control (HC) participants, all right handed, underwent MRI at 3.0 T. High-spatial-resolution diffusion images were acquired with a reduced field of view by using seven b values up to 3000 sec/mm². A continuous-time random-walk (CTRW) non-Gaussian diffusion model was used to produce anomalous diffusion coefficient (D_m) and temporal (α) and spatial (β) diffusion heterogeneity indexes followed by a Gaussian diffusion model to yield an apparent diffusion coefficient (ADC). Individual or linear combinations of diffusion parameters in the SN were unilaterally and bilaterally compared between the PD and HC groups. Results In the bilateral comparison between the PD and HC groups, differences were observed in β (0.67 ± 0.06 [standard deviation] vs 0.64 ± 0.04, respectively; P = .016), ADC (0.48 μm²/msec ± 0.08 vs 0.53 μm²/msec ± 0.06, respectively; P = .03), and the combination of CTRW parameters (P = .02). In the unilateral comparison, differences were observed in all diffusion parameters on the left SN (P < .03), but not on the right (P > .20). In a receiver operating characteristic (ROC) analysis to delineate left SN abnormality in PD, the combination of D_m, α, and β produced the best sensitivity (sensitivity, 0.78); the combination of D_m and β produced the best specificity (specificity, 0.85); and the combination of α and β produced the largest area under the ROC curve (area under the ROC curve, 0.73). Conclusion These results suggest that quantitative diffusion MRI is sensitive to brain tissue changes in participants with Parkinson disease and provide evidence of substantia nigra lateral asymmetry in this disease. © RSNA, 2019 Online supplemental material is available for this article.

Lateralisation in Parkinson disease

Asymmetry of dopaminergic neurodegeneration and subsequent lateralisation of motor symptoms are distinctive features of Parkinson's disease compared to other forms of neurodegenerative or symptomatic parkinsonism. Even 200 years after the first description of the disease, the underlying causes for this striking clinicopathological feature are not yet fully understood. There is increasing evidence that lateralisation of disease is due to a complex interplay of hereditary and environmental factors that are reflected not only in the concept of dominant hemispheres and handedness but also in specific susceptibilities of neuronal subpopulations within the substantia nigra. As a consequence, not only the obvious lateralisation of motor symptoms occurs but also patterns of associated non-motor signs are defined, which include cognitive functions, sleep behaviour or olfaction. Better understanding of the mechanisms contributing to lateralisation of neurodegeneration and the resulting patterns of clinical phenotypes based on bilateral post-mortem brain analyses and clinical studies focusing on right/left hemispheric symptom origin will help to develop more targeted therapeutic approaches, taking into account subtypes of PD as a heterogeneous disorder.

A meta-analysis of diffusion tensor imaging of substantia nigra in patients with Parkinson's disease

Parkinson’s disease (PD) is a common neurodegenerative disease characterized by severe, selective loss of pigmented neurons in the substantial nigra (SN). Previous studies have indicated that such loss could be detected by diffusion tensor imaging (DTI). Here, we try to consolidate current DTI data to both quantitatively determine the imaging changes in SN, as well as explore the potential use of DTI for PD diagnosis. Fourteen research articles are included in this meta-analysis, each obtained by searching PubMed, EMBASE, or Cochrane library database dated until July 2017. The articles contain 14 trials with 298 total PD patients and 283 healthy controls (HCs). The results show not only significantly lower FA values of SN in PD compared to that of HCs (WMD = −0.02, 95% CI = [−0.03, −0.02], p < 0.00001), but also a significantly higher MD in PD compared to HCs (WMD = 0.05, 95% CI = [0.03, 0.07], P < 0.0001). This indicates that the sharp difference detected between PD patients and HCs can be detected by DTI. By further analyzing the heterogeneity, we found that FA measurement of SN could be potentially used as a surrogate, noninvasive diagnostic marker toward PD diagnosis.

Lateralized Basal Ganglia Vulnerability to Pesticide Exposure in Asymptomatic Agricultural Workers

Pesticide exposure is linked to Parkinson's disease, a neurodegenerative disorder marked by dopamine cell loss in the substantia nigra of the basal ganglia (BG) that often presents asymmetrically. We previously reported that pesticide-exposed agricultural workers (AW) have nigral diffusion tensor imaging (DTI) changes. The current study sought to confirm this finding, and explore its hemisphere and regional specificity within BG structures using an independent sample population. Pesticide exposure history, standard neurological exam, high-resolution magnetic resonance imaging (T1/T2-weighted and DTI), and [123I]ioflupane SPECT images (to quantify striatal dopamine transporters) were obtained from 20 AW with chronic pesticide exposure and 11 controls. Based on median cumulative days of pesticide exposure, AW were subdivided into high (AWHi, n = 10) and low (AWLo, n = 10) exposure groups. BG (nigra, putamen, caudate, and globus pallidus [GP]) fractional anisotropy (FA), mean diffusivity (MD), and striatal [123I]ioflupane binding in each hemisphere were quantified, and compared across exposure groups using analysis of variance. Left, but not right, nigral and GP FA were significantly lower in AW compared with controls (p's < .029). None of the striatal (putamen and caudate) DTI or [123I]ioflupane binding measurements differed between AW and controls. Subgroup analyses indicated that significant left nigral and GP DTI changes were present only in the AWHi (p ≤ .037) but not the AWLo subgroup. AW, especially those with higher pesticide exposure history, demonstrate lateralized microstructural changes in the nigra and GP, whereas striatal areas appear relatively unaffected. Future studies should elucidate how environmental toxicants cause differential lateralized- and regionally specific brain vulnerability.

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.

Application of high-field magnetic resonance imaging in Parkinson's disease

The present study aimed to observe the structural changes of the extracorticospinal tract in Parkinson's disease (PD) using susceptibility-weighted imaging (SWI) and diffusion tensor imaging (DTI) magnetic resonance (MR) scans. The association of DTI parameters and brain-iron accumulation with PD was examined and imaging signs useful in the diagnosis of PD were explored. The study included 30 patients with PD and 30 age- and gender-matched healthy controls who underwent routine MR, SWI and DTI scans. The corrected phase (CP) values of the substantia nigra (SN), red nucleus (RN), globus pallidus (GP) and putamen (PUT) were measured, and fractional anisotropy (FA) and apparent diffusion coefficient (ADC) values were obtained. Significant differences were found in the CP values between the PD and control groups in the SN, RN and PUT, but there were no differences in other regions of interest (ROIs). The FA values of the SN and PUT in the PD group were significantly decreased compared with those of the control group, but there was no significant difference in the FA values of the GP. Furthermore, there was no significant inter-group difference in the ADC values of any ROIs. In conclusion, SWI is a method useful for evaluating brain-iron deposition in PD. Increasing iron storage levels have previously been shown to be associated with PD pathogenesis but not with the degree of PD severity. FA values may be useful for diagnosing PD, and DTI may offer some insight into PD pathomechanisms and clinical diagnosis.

Gray Matter Abnormalities in Idiopathic Parkinson's Disease: Evaluation by Diffusional Kurtosis Imaging and Neurite Orientation Dispersion and Density Imaging

Mapping gray matter (GM) pathology in Parkinson's disease (PD) with conventional MRI is challenging, and the need for more sensitive brain imaging techniques is essential to facilitate early diagnosis and assessment of disease severity. GM microstructure was assessed with GM-based spatial statistics applied to diffusion kurtosis imaging (DKI) and neurite orientation dispersion imaging (NODDI) in 30 participants with PD and 28 age- and gender-matched controls. These were compared with currently used assessment methods such as diffusion tensor imaging (DTI), voxel-based morphometry (VBM), and surface-based cortical thickness analysis. Linear discriminant analysis (LDA) was also used to test whether subject diagnosis could be predicted based on a linear combination of regional diffusion metrics. Significant differences in GM microstructure were observed in the striatum and the frontal, temporal, limbic, and paralimbic areas in PD patients using DKI and NODDI. Significant correlations between motor deficits and GM microstructure were also noted in these areas. Traditional VBM and surface-based cortical thickness analyses failed to detect any GM differences. LDA indicated that mean kurtosis (MK) and intra cellular volume fraction (ICVF) were the most accurate predictors of diagnostic status. In conclusion, DKI and NODDI can detect cerebral GM abnormalities in PD in a more sensitive manner when compared with conventional methods. Hence, these methods may be useful for the diagnosis of PD and assessment of motor deficits. Hum Brain Mapp 38:3704-3722, 2017. © 2017 Wiley Periodicals, Inc.

Diffusion kurtosis imaging for diagnosis of Parkinson's disease: A novel software tool proposal

In order to diagnose Parkinson disease (PD) at an early stage, it is important to develop a sensitive method for detecting structural changes in the substantia nigra (SN). Diffusion weighted imaging (DWI) and diffusion tensor imaging (DTI) have become important tools in supporting diagnosis of PD, with findings based on increased apparent diffusion coefficients (ADCs) in basal ganglia and decreased fractional anisotropy (FA) in SN. Based on the hypothesis that a diffusion kurtosis imaging (DKI) theory is a valuable method for PD diagnosis based on the non-Gaussian diffusion of water in biologic systems, the purpose of this study is to develop an image processing scheme (software) based on Image-J for the facilitating the application of DKI to assist PD diagnosis. Using the new DKI software enables to estimate the diffusional kurtosis and diffusion coefficients, which reflect the structural differences between regions of interest. The experimental results of applying the new software showed that diffusional kurtosis was highly sensitive to microstructural tissue changes, which were not noticeable in the diffusion coefficient values. Thus, the study results may suggest that applying the new image processing software can be useful for assessing tissue structural abnormalities, monitoring and following disease progression.

Cortical asymmetry in Parkinson's disease: early susceptibility of the left hemisphere

BACKGROUND AND PURPOSE

Clinically, Parkinson's disease (PD) presents with asymmetric motor symptoms. The left nigrostriatal system appears more susceptible to early degeneration than the right, and a left-lateralized pattern of early neuropathological changes is also described in several neurodegenerative conditions, including Alzheimer's disease, frontotemporal dementia, and Huntington's disease. In this study, we evaluated hemispheric differences in estimated rates of atrophy in a large, well-characterized cohort of PD patients.

METHODS

Our cohort included 205 PD patients who underwent clinical assessments and T1-weighted brain MRI's. Patients were classified into Early (n = 109) and Late stage (n = 96) based on disease duration, defined as greater than or less than 10 years of motor symptoms. Cortical thickness was determined using FreeSurfer, and a bootstrapped linear regression model was used to estimate differences in rates of atrophy between Early and Late patients.

RESULTS

Our results show that patients classified as Early stage exhibit a greater estimated rate of cortical atrophy in left frontal regions, especially the left insula and olfactory sulcus. This pattern was replicated in left-handed patients, and was not influenced by the degree of motor symptom asymmetry (i.e., left-sided predominant motor symptoms). Patients classified as Late stage exhibited greater atrophy in the bilateral occipital, and right hemisphere-predominant cortical areas.

CONCLUSIONS

We show that cortical degeneration in PD differs between cerebral hemispheres, and findings suggest a pattern of early left, and late right hemisphere with posterior cortical atrophy. Further investigation is warranted to elucidate the underlying mechanisms of this asymmetry and pathologic implications.

Substantia nigra fractional anisotropy is not a diagnostic biomarker of Parkinson's disease: A diagnostic performance study and meta-analysis

OBJECTIVES

Our goal was to estimate the diagnostic accuracy of substantia nigra fractional anisotropy (SN-FA) for Parkinson's disease (PD) diagnosis in a sample similar to the clinical setting, including patients with essential tremor (ET) and healthy controls (HC). We also performed a systematic review and meta-analysis to estimate mean change in SN-FA induced by PD and its diagnostic accuracy.

METHODS

Our sample consisted of 135 subjects: 72 PD, 21 ET and 42 HC. To address inter-scanner variability, two 3.0-T MRI scans were performed. MRI results of this sample were pooled into a meta-analysis that included 1,432 subjects (806 PD and 626 HC). A bivariate model was used to evaluate diagnostic accuracy measures.

RESULTS

In our sample, we did not observe a significant effect of disease on SN-FA and it was uninformative for diagnosis. The results of the meta-analysis estimated a 0.03 decrease in mean SN-FA in PD relative to HC (CI: 0.01-0.05). However, the discriminatory capability of SN-FA to diagnose PD was low: pooled sensitivity and specificity were 72 % (CI: 68-75) and 63 % (CI: 58-70), respectively. There was high heterogeneity between studies (I² = 91.9 %).

CONCLUSIONS

SN-FA cannot be used as an isolated measure to diagnose PD.

KEY POINTS

• SN-FA appears insufficiently sensitive and specific to diagnose PD. • Radiologists must be careful when translating mean group results to clinical practice. • Imaging protocol and analysis standardization is necessary for developing reproducible quantitative biomarkers.

Default mode network differences between rigidity- and tremor-predominant Parkinson's disease

BACKGROUND

Parkinson's disease (PD) traditionally is characterized by tremor, rigidity, and bradykinesia, although cognitive impairment also is a common symptom. The clinical presentation of PD is heterogeneous and associated with different risk factors for developing cognitive impairment. PD patients with primary akinetic/rigidity (PDAR) are more likely to develop cognitive deficits compared to those with tremor-predominant symptoms (PDT). Because cognitive impairment in PD appears to be related to changes in the default mode network (DMN), this study tested the hypothesis that DMN integrity is different between PDAR and PDT subtypes.

METHOD

Resting state fMRI (rs-fMRI) and whole brain volumetric data were obtained from 17 PDAR, 15 PDT and 24 healthy controls (HCs) using a 3T scanner. PD patients were matched closely to HCs for demographic and cognitive variables, and showed no symptoms of dementia. Voxel-based morphometry (VBM) was used to examine brain gray matter (GM) volume changes between groups. Independent component analysis (ICA) interrogated differences in the DMN among PDAR, PDT, and HC.

RESULTS

There was decreased activity in the left inferior parietal cortex (IPC) and the left posterior cingulate cortex (PCC) within the DMN between PDAR and both HC and PDT subjects, even after controlling for multiple comparisons, but not between PDT and HC. GM volume differences between groups were detected at a lower threshold (p < 0.001, uncorrected). Resting state activity in IPC and PCC were correlated with some measures of cognitive performance in PD but not in HC.

CONCLUSION

This is the first study to demonstrate DMN differences between cognitively comparable PDAR and PDT subtypes. The DMN differences between PD and HC appear to be driven by the PDAR subtype. Further studies are warranted to understand the underlying neural mechanisms and their relevance to clinical and cognitive outcomes in PDAR and PDT subtypes.

Microstructural Changes within the Basal Ganglia Differ between Parkinson Disease Subtypes

Diffusion tensor imaging (DTI) of the substantia nigra has shown promise in detecting and quantifying neurodegeneration in Parkinson disease (PD). It remains unknown, however, whether differences in microstructural changes within the basal ganglia underlie PD motor subtypes. We investigated microstructural changes within the basal ganglia of mild to moderately affected PD patients using DTI and sought to determine if microstructural changes differ between the tremor dominant (TD) and postural instability/gait difficulty (PIGD) subtypes. Fractional anisotropy, mean diffusivity, radial, and axial diffusivity were obtained from bilateral caudate, putamen, globus pallidus, and substantia nigra of 21 PD patients (12 TD and 9 PIGD) and 20 age-matched healthy controls. T-tests and ANOVA methods were used to compare PD patients, subtypes, and controls, and Spearman correlations tested for relationships between DTI and clinical measures. We found our cohort of PD patients had reduced fractional anisotropy within the substantia nigra and increased mean and radial diffusivity within the substantia nigra and globus pallidus compared to controls, and that changes within those structures were largely driven by the PIGD subtype. Across all PD patients fractional anisotropy within the substantia nigra correlated with disease stage, while in PIGD patients increased diffusivity within the globus pallidus correlated with disease stage and motor severity. We conclude that PIGD patients have more severely affected microstructural changes within the substantia nigra compared to TD, and that microstructural changes within the globus pallidus may be particularly relevant for the manifestation of the PIGD subtype.

A novel method for evaluating brain function and microstructural changes in Parkinson's disease

In this study, microstructural brain damage in Parkinson's disease patients was examined using diffusion tensor imaging and tract-based spatial statistics. The analyses revealed the presence of neuronal damage in the substantia nigra and putamen in the Parkinson's disease patients. Moreover, disease symptoms worsened with increasing damage to the substantia nigra, confirming that the substantia nigra and basal ganglia are the main structures affected in Parkinson's disease. We also found that microstructural damage to the putamen, caudate nucleus and frontal lobe positively correlated with depression. Based on the tract-based spatial statistics, various white matter tracts appeared to have microstructural damage, and this correlated with cognitive disorder and depression. Taken together, our results suggest that diffusion tensor imaging and tract-based spatial statistics can be used to effectively study brain function and microstructural changes in patients with Parkinson's disease. Our novel findings should contribute to our understanding of the histopathological basis of cognitive dysfunction and depression in Parkinson's disease.

Diffusion Kurtosis Imaging of Substantia Nigra Is a Sensitive Method for Early Diagnosis and Disease Evaluation in Parkinson's Disease

Background. To diagnose Parkinson disease (PD) in an early stage and accurately evaluate severity, it is important to develop a sensitive method for detecting structural changes in the substantia nigra (SN). Method. Seventy-two untreated patients with early PD and 72 healthy controls underwent diffusion tensor and diffusion kurtosis imaging. Regions of interest were drawn in the rostral, middle, and caudal SN by two blinded and independent raters. Mean kurtosis (MK) and fractional anisotropy in the SN were compared between the groups. Receiver operating characteristic (ROC) and Spearman correlation analyses were used to compare the diagnostic accuracy and correlate imaging findings with Hoehn-Yahr (H-Y) staging and part III of the Unified Parkinson's Disease Rating Scale (UPDRS-III). Result. MK in the SN was increased significantly in PD patients compared with healthy controls. The area under the ROC curve was 0.976 for MK in the SN (sensitivity, 0.944; specificity, 0.917). MK in the SN had a positive correlation with H-Y staging and UPDRS-III scores. Conclusion. Diffusion kurtosis imaging is a sensitive method for PD diagnosis and severity evaluation. MK in the SN is a potential biomarker for imaging studies of early PD that can be widely used in clinic.

Deterministic Tractography of the Nigrostriatal-Nigropallidal Pathway in Parkinson's Disease

We hypothesized that deterministic tractography is practical and sensitive to changes in the complex nigrostriatal and nigropallidal pathway (NSP) in Parkinson’s disease (PD). Using diffusion tensor imaging (DTI) tractography, we investigated the NSP to evaluate differences between PD patients and controls, and examined their clinico-radiologic correlation. Structural and DTI brain scans were obtained in 40 subjects (21 PD patients and 19 healthy controls). We isolated the NSP using a user-friendly DTI toolkit based on deterministic brute-force tractography. DTI parameters of fractional anisotropy (FA), mean, axial, and radial diffusivity, and streamline count of the NSP were measured. Average FA (p < 0.01) and streamline count (p < 0.001) were significantly lower in the PD compared to control group. Mean diffusivity and radial diffusivity were significantly higher in the PD group (p < 0.05). Average streamline count correlated with the United Parkinson’s Disease Rating Scale motor score (p < 0.05). Point-to-point FA profiles of the tract demonstrated peak divergence between PD and control towards the tract midpoint rather than the distal grey matter. Our findings demonstrated a clinically and radiologically practical application of DTI tractography to the NSP in PD, without requiring complex imaging sequences for anatomical localization or segmentation software.

Effects of acute levodopa challenge on resting cerebral blood flow in Parkinson's Disease patients assessed using pseudo-continuous arterial spin labeling

Introduction. Levodopa is the gold-standard for treatment of Parkinson’s disease (PD) related motor symptoms. In this study, we used pseudo-continuous arterial spin labeling (pCASL) to quantify changes in cerebral blood flow (CBF) after acute oral administration of levodopa in PD patients.

Materials and Methods. Thirteen patients (3 females, age 66.2 ± 8.7 years) with moderately advanced PD (Hoehn and Yahr stage >2 (median 2.5), disease duration >3 years) were scanned on a 3T Siemens MR scanner before and after oral levodopa administration. Statistical parametric mapping was used to detect drug-induced changes in CBF and its correlation to clinical severity scales. Images were normalized and flipped in order to examine effects on the more affected (left) and less affected (right) cerebral hemispheres across the cohort.

Results. Levodopa did not change global CBF but increased regional CBF in dorsal midbrain, precuneus/cuneus, more affected inferior frontal pars opercularis and triangularis, bilateral pre- and postcentral gyri, more affected inferior parietal areas, as well as less affected putamen/globus pallidus by 27–74% (p < 0.05, FWE corrected for multiple comparisons). CBF change was negatively correlated with improvement in bradykinesia UPDRS-III subscore in the more affected precentral gyrus, and total predrug UPDRS-III score in the mid-cingulate region. Drug-induced CBF change in a widespread network of regions including parietal and postcentral areas was also negatively correlated with the predrug rigidity UPDRS-III subscore.

Conclusion. These findings are in line with prior reports of abnormal activity in the nigrostriatal pathway of PD patients and demonstrate the feasibility of pCASL as a neuroimaging tool for investigating in vivo physiological effects of acute drug administration in PD.

Neurite orientation dispersion and density imaging in the substantia nigra in idiopathic Parkinson disease

OBJECTIVES

We used neurite orientation dispersion and density imaging (NODDI) to quantify changes in the substantia nigra pars compacta (SNpc) and striatum in Parkinson disease (PD).

METHODS

Diffusion-weighted magnetic resonance images were acquired from 58 PD patients and 36 age- and sex-matched controls. The intracellular volume fraction (Vic), orientation dispersion index (OD), and isotropic volume fraction (Viso) of the basal ganglia were compared between groups. Multivariate logistic regression analysis determined which diffusion parameters were independent predictors of PD. Receiver operating characteristic (ROC) analysis compared the diagnostic accuracies of the evaluated indices. Pearson coefficient analysis correlated each diffusional parameter with disease severity.

RESULTS

Vic in the contralateral SNpc and putamen were significantly lower in PD patients than in healthy controls (P < 0.00058). Vic and OD in the SNpc and putamen showed significant negative correlations (P < 0.05) with disease severity. Multivariate logistic analysis revealed that Vic (P = 0.0000046) and mean diffusivity (P = 0.019) in the contralateral SNpc were the independent predictors of PD. In the ROC analysis, Vic in the contralateral SNpc showed the best diagnostic performance (mean cutoff, 0.62; sensitivity, 0.88; specificity, 0.83).

CONCLUSION

NODDI is likely to be useful for diagnosing PD and assessing its progression.

KEY POINTS

• Neurite orientation dispersion and density imaging (NODDI) is a new diffusion MRI technique • NODDI estimates neurite microstructure more specifically than diffusion tensor imaging • By using NODDI, nigrostriatal alterations in PD can be evaluated in vivo • NOODI is useful for diagnosing PD and assessing its disease progression.

Chemical Exchange Saturation Transfer MR Imaging is Superior to Diffusion-Tensor Imaging in the Diagnosis and Severity Evaluation of Parkinson's Disease: A Study on Substantia Nigra and Striatum

Parkinson's disease (PD) is a neurodegenerative disorder characterized by nigrostriatal cell loss. To date, the diagnosis of PD is still based primarily on the clinical manifestations, which may be typical and obvious only in advanced-stage PD. Thus, it is crucial to find a reliable marker for the diagnosis of PD. We conducted this study to assess the diagnostic efficiency of chemical exchange saturation transfer (CEST) imaging and diffusion-tensor imaging (DTI) in PD at 3 T by evaluating changes on substantia nigra and striatum. Twenty-three PD patients and twenty-three age-matched normal controls were recruited. All patients and controls were imaged on a 3-T MR system, using an eight-channel head coil. CEST imaging was acquired in two transverse slices of the head, including substantia nigra and striatum. The magnetization transfer ratio asymmetry at 3.5 ppm, MTRasym(3.5 ppm), and the total CEST signal intensity between 0 and 4 ppm were calculated. Multi-slice DTI was acquired for all the patients and normal controls. Quantitative analysis was performed on the substantia nigra, globus pallidus, putamen, and caudate. The MTRasym(3.5 ppm) value, the total CEST signal intensity, and fractional anisotropy value of the substantia nigra were all significantly lower in PD patients than in normal controls (P = 0.003, P = 0.004, and P < 0.001, respectively). The MTRasym(3.5 ppm) values of the putamen and the caudate were significantly higher in PD patients than in normal controls (P = 0.010 and P = 0.009, respectively). There were no significant differences for the mean diffusivity in these four regions between PD patients and normal controls. In conclusion, CEST MR imaging provided multiple CEST image contrasts in the substantia nigra and the striatum in PD and may be superior to DTI in the diagnosis of PD.

Diffusion imaging of nigral alterations in early Parkinson's disease with dopaminergic deficits

BACKGROUND

This study reports the baseline characteristics of diffusion tensor imaging data in Parkinson's disease (PD) patients and healthy control subjects from the Parkinson's Progression Markers Initiative. The main goals were to replicate previous findings of abnormal diffusion imaging values from the substantia nigra. in a large multicenter cohort and determine whether nigral diffusion alterations are associated with dopamine deficits.

METHODS

Two hundred twenty subjects (PD = 153; control = 67) from 10 imaging sites were included. All subjects had a full neurological exam, a ((123) I)ioflupane dopamine transporter (DAT) single-photon emission computer tomography scan, and diffusion tensor imaging. Fractional anisotropy as well as radial and axial diffusivity was computed within multiple regions across the substantia nigra.

RESULTS

A repeated-measures analysis of variance found a marginally nonsignificant interaction between regional fractional anisotropy of the substantia nigra and disease status (P = 0.08), conflicting with an earlier study. However, a linear mixed model that included control regions in addition to the nigral regions revealed a significant interaction between regions and disease status (P = 0.002), implying a characteristic distribution of reduced fractional anisotropy across the substantia nigra in PD. Reduced fractional anisotropy in PD was also associated with diminished DAT binding ratios. Both axial and radial diffusivity were also abnormal in PD.

CONCLUSIONS

Although routine nigral measurements of fractional anisotropy are clinically not helpful, the findings in this study suggest that more-sophisticated diffusion imaging protocols should be used when exploring the clinical utility of this imaging modality.

Diffusion tensor imaging of the nigrostriatal fibers in Parkinson's disease

BACKGROUND

Parkinson's disease (PD) is histopathologically characterized by the loss of dopamine neurons in the substantia nigra pars compacta. The depletion of these neurons is thought to reduce the dopaminergic function of the nigrostriatal pathway, as well as the neural fibers that link the substantia nigra to the striatum (putamen and caudate), causing a dysregulation in striatal activity that ultimately leads to lack of movement control. Based on diffusion tensor imaging, visualizing this pathway and measuring alterations of the fiber integrity remain challenging. The objectives were to 1) develop a diffusion tensor tractography protocol for reliably tracking the nigrostriatal fibers on multicenter data; 2) test whether the integrities measured by diffusion tensor imaging of the nigrostriatal fibers are abnormal in PD; and 3) test whether abnormal integrities of the nigrostriatal fibers in PD patients are associated with the severity of motor disability and putaminal dopamine binding ratios.

METHODS

Diffusion tensor tractography was performed on 50 drug-naïve PD patients and 27 healthy control subjects from the international multicenter Parkinson's Progression Marker Initiative.

RESULTS

Tractography consistently detected the nigrostriatal fibers, yielding reliable diffusion measures. Fractional anisotropy, along with radial and axial diffusivity of the nigrostriatal tract, showed systematic abnormalities in patients. In addition, variations in fractional anisotropy and radial diffusivity of the nigrostriatal tract were associated with the degree of motor deficits in PD patients.

CONCLUSION

Taken together, the findings imply that the diffusion tensor imaging characteristic of the nigrostriatal tract is potentially an index for detecting and staging of early PD.

Fractional anisotropy in the substantia nigra in Parkinson's disease: a complex picture

BACKGROUND AND PURPOSE

This study employs magnetic resonance imaging (MRI) diffusion tensor imaging to compare diffusion measures in the brains of patients with Parkinson's disease (PD) with healthy controls using longitudinal data.

METHODS

One-hundred and twenty-two patients and 34 controls were included at baseline. The MRI investigations were repeated after 1, 3 and 5 years. The diffusion measures were quantified using fractional anisotropy and mean, radial and axial diffusion (FA, MD, RD, AD). Regions of interest included the anterior, middle and posterior substantia nigra (SN), but also other areas. Linear models were used to test for the effect of disease and hemispheric lateralization. The P value was set at 0.05 (Bonferroni corrected).

RESULTS

Fractional anisotropy and AD were increased in the three nigral subareas in PD (P < 0.01), but MD and RD were unaltered. The right SN had higher FA than the left in all subareas (P < 0.01). MD and AD were increased in the right anterior part (P < 0.04), whereas MD and RD were decreased in the right middle and posterior parts (P < 0.001). The left middle cerebellar peduncle had increased FA and AD (P < 0.001) and decreased MD and RD (P < 0.01) compared to the right. Diffusion measures did not progress over time and side differences were not related to disease or lateralization of symptoms.

CONCLUSIONS

Increased FA in the SN in PD indicates gliosis and inflammation in the nuclei, but possibly also intrusion of surrounding fibres into the shrinking structure. The hemispheric side differences of diffusion might reflect natural lateralization of connectivity, but their relation to PD must be studied further.

Neural substrates of motor and non-motor symptoms in Parkinson's disease: a resting FMRI study

Background

Recently, non-motor symptoms of Parkinson’s disease (PD) have been considered crucial factors in determining a patient’s quality of life and have been proposed as the predominant features of the premotor phase. Researchers have investigated the relationship between non-motor symptoms and the motor laterality; however, this relationship remains disputed. This study investigated the neural connectivity correlates of non-motor and motor symptoms of PD with respect to motor laterality.

Methods

Eight-seven patients with PD were recruited and classified into left-more-affected PD (n = 44) and right-more affected PD (n = 37) based on their MDS-UPDRS (Movement Disorder Society-sponsored revision of the Unified Parkinson’s Disease Rating Scale) motor examination scores. The patients underwent MRI scanning, which included resting fMRI. Brain regions were labeled as ipsilateral and contralateral to the more-affected body side. Correlation analysis between the functional connectivity across brain regions and the scores of various symptoms was performed to identify the neural connectivity correlates of each symptom.

Results

The resting functional connectivity centered on the ipsilateral inferior orbito-frontal area was negatively correlated with the severity of non-motor symptoms, and the connectivity of the contralateral inferior parietal area was positively correlated with the severity of motor symptoms (p < 0.001, |r| > 0.3).

Conclusions

These results suggest that the inferior orbito-frontal area may play a crucial role in non-motor dysfunctions, and that the connectivity information may be utilized as a neuroimaging biomarker for the early diagnosis of PD.

Why psychosis is frequently associated with Parkinson's disease?

Psychosis is a common non-motor symptom of Parkinson's disease whose pathogenesis remains poorly understood. Parkinson's disease in conjunction with psychosis has been shown to induce injury to extracorticospinal tracts as well as within some cortical areas. In this study, Parkinson's disease patients with psychosis who did not receive antipsychotic treatment and those without psychosis underwent diffusion tensor imaging. Results revealed that in Parkinson's disease patients with psychosis, damage to the left frontal lobe, bilateral occipital lobe, left cingulated gyrus, and left hippocampal white-matter fibers were greater than damage to the substantia nigra or the globus pallidus. Damage to white-matter fibers in the right frontal lobe and right cingulate gyrus were also more severe than in the globus pallidus, but not the substantia nigra. Damage to frontal lobe and cingulate gyrus white-matter fibers was more apparent than that to occipital or hippocampal fiber damage. Compared with Parkinson's disease patients without psychosis, those with psychosis had significantly lower fractional anisotropy ratios of left frontal lobe, bilateral occipital lobe, left cingu-lated gyrus, and left hippocampus to ipsilateral substantia nigra or globus pallidus, indicating more severe damage to white-matter fibers. These results suggest that psychosis associated with Par-kinson's disease is probably associated with an imbalance in the ratio of white-matter fibers be-tween brain regions associated with psychiatric symptoms (frontal lobe, occipital lobe, cingulate gyrus, and hippocampus) and those associated with the motor symptoms of Parkinson's disease (the substantia nigra and globus pallidus). The relatively greater damage to white-matter fibers in psychiatric symptom-related brain regions than in extracorticospinal tracts might explain why chosis often occurs in Parkinson's disease patients.

The evolving role of diffusion magnetic resonance imaging in movement disorders

Significant advances have allowed diffusion magnetic resonance imaging (MRI) to evolve into a powerful tool in the field of movement disorders that can be used to study disease states and connectivity between brain regions. Diffusion MRI is a promising potential biomarker for Parkinson's disease and other forms of parkinsonism, and may allow the distinction of different forms of parkinsonism. Techniques such as tractography have contributed to our current thinking regarding the pathophysiology of dystonia and possible mechanisms of penetrance. Diffusion MRI measures could potentially assist in monitoring disease progression in Huntington's disease, and in uncovering the nature of the processes and structures involved the development of essential tremor. The ability to represent structural connectivity in vivo also makes diffusion MRI an ideal adjunctive tool for the surgical treatment of movement disorders. We review recent studies using diffusion MRI in movement disorders research and present the current state of the science as well as future directions.

Diffusion tensor imaging of nigral degeneration in Parkinson's disease: A region-of-interest and voxel-based study at 3 T and systematic review with meta-analysis

There is increasing interest in developing a reliable, affordable and accessible disease biomarker of Parkinson's disease (PD) to facilitate disease modifying PD-trials. Imaging biomarkers using magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI) can describe parameters such as fractional anisotropy (FA), mean diffusivity (MD) or apparent diffusion coefficient (ADC). These parameters, when measured in the substantia nigra (SN), have not only shown promising but also varying and controversial results.

To clarify the potential diagnostic value of nigral DTI in PD and its dependency on selection of region-of-interest, we undertook a high resolution DTI study at 3 T. 59 subjects (32 PD patients, 27 age and sex matched healthy controls) were analysed using manual outlining of SN and substructures, and voxel-based analysis (VBA). We also performed a systematic literature review and meta-analysis to estimate the effect size (D_ES) of disease related nigral DTI changes.

We found a regional increase in nigral mean diffusivity in PD (mean ± SD, PD 0.80 ± 0.10 vs. controls 0.73 ± 0.06 · 10^− 3 mm²/s, p = 0.002), but no difference using a voxel based approach. No significant disease effect was seen using meta-analysis of nigral MD changes (10 studies, D_ES = + 0.26, p = 0.17, I² = 30%). None of the nigral regional or voxel based analyses of this study showed altered fractional anisotropy. Meta-analysis of 11 studies on nigral FA changes revealed a significant PD induced FA decrease. There was, however, a very large variation in results (I² = 86%) comparing all studies. After exclusion of five studies with unusual high values of nigral FA in the control group, an acceptable heterogeneity was reached, but there was non-significant disease effect (D_ES = − 0.5, p = 0.22, I² = 28%).

The small PD related nigral MD changes in conjunction with the negative findings on VBA and meta-analysis limit the usefulness of nigral MD measures as biomarker of Parkinson's disease. The negative results of nigral FA measurements at regional, sub-regional and voxel level in conjunction with the results of the meta-analysis of nigral FA changes question the stability and validity of this measure as a PD biomarker.

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Investigating diagnostic accuracy of nigral diffusion MRI to diagnose Parkinson's

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There is small, inconsistent increase of mean diffusivity of the substantia nigra.

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There is no change in nigral fractional anisotropy (FA) in the case–control study.

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Meta-analysis revealed nigral FA change is dependent on high FA in controls.

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This questions the usefulness of nigral diffusion MRI as biomarker in Parkinson's.

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.