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

Unraveling the complexity of human brain: Structure, function in healthy and disease states

The human brain stands as an intricate organ, embodying a nexus of structure, function, development, and diversity. This review delves into the multifaceted landscape of the brain, spanning its anatomical intricacies, diverse functional capacities, dynamic developmental trajectories, and inherent variability across individuals. The dynamic process of brain development, from early embryonic stages to adulthood, highlights the nuanced changes that occur throughout the lifespan. The brain, a remarkably complex organ, is composed of various anatomical regions, each contributing uniquely to its overall functionality. Through an exploration of neuroanatomy, neurophysiology, and electrophysiology, this review elucidates how different brain structures interact to support a wide array of cognitive processes, sensory perception, motor control, and emotional regulation. Moreover, it addresses the impact of age, sex, and ethnic background on brain structure and function, and gender differences profoundly influence the onset, progression, and manifestation of brain disorders shaped by genetic, hormonal, environmental, and social factors. Delving into the complexities of the human brain, it investigates how variations in anatomical configuration correspond to diverse functional capacities across individuals. Furthermore, it examines the impact of neurodegenerative diseases on the structural and functional integrity of the brain. Specifically, our article explores the pathological processes underlying neurodegenerative diseases, such as Alzheimer's, Parkinson's, and Huntington's diseases, shedding light on the structural alterations and functional impairments that accompany these conditions. We will also explore the current research trends in neurodegenerative diseases and identify the existing gaps in the literature. Overall, this article deepens our understanding of the fundamental principles governing brain structure and function and paves the way for a deeper understanding of individual differences and tailored approaches in neuroscience and clinical practice-additionally, a comprehensive understanding of structural and functional changes that manifest in neurodegenerative diseases.

Fractals in the Neurosciences: A Translational Geographical Approach

The chapter presents three new fractal indices (fractal fragmentation index, fractal tentacularity index, and fractal anisotropy index) and normalized Kolmogorov complexity with proven applicability in geographic research, developed by the authors, and the possibility of their future use in neuroscience. The research demonstrates the relevance of fractal analysis in different fields and the basic concepts and principles of fractal geometry being sufficient for the development of models relevant to the studied reality. Also, the research highlighted the need to continue interdisciplinary research based on known fractal indicators, as well as the development of new analysis methods with the translational potential between fields.

Sleep deprivation aggravated amyloid β oligomers-induced damage to the cerebellum of rats: Evidence from magnetic resonance imaging

For quite a long time, researches on Alzheimer's disease (AD) primarily focused on the cortex and hippocampus, while the cerebellum has been ignored because of its abnormalities considered to appear in the late stage of AD. In recent years, increasing evidence suggest that the cerebellar pathological changes possibly occur in the preclinical phase of AD, which is also associated with sleep disorder. Sleep disturbance is a high risk factor of AD. However, the changes and roles of cerebellum has rarely been reported under conditions of AD accompanied with sleep disorders. In this study, using an amyloid-β oligomers (AβO)-induced rat model of AD subjected to sleep deprivation, combining with a 7.0 T animals structural magnetic resonance imaging (MRI), we assessed structural changes of cerebellum in MRI. Our results showed that sleep deprivation combined with AβO led to an increased FA value in the anterior lobe of cerebellum, decreased ADC value in the cerebellar lobes and cerebellar nuclei, and increased cerebellum volume. Besides that, sleep deprivation exacerbated the damage of AβO to the cerebellar structural network. This study demonstrated that sleep deprivation could aggravate the damage to cerebellum induced by AβO. The present findings provide supporting evidence for the involvement of cerebellum in the early pathology of AD and sleep loss. Our data would contribute to advancing the understanding of the mysterious role of cerebellum in AD and sleep disorders, as well as would be helpful for developing non-invasive MRI biomarkers for screening early AD patients with self-reported sleep disturbances.

Multimodal Imaging of Substantia Nigra in Parkinson's Disease with Levodopa-Induced Dyskinesia

BACKGROUND

Degeneration of the substantia nigra (SN) may contribute to levodopa-induced dyskinesia (LID) in Parkinson's disease (PD), but the exact characteristics of SN in LID remain unclear.

OBJECTIVE

To further understand the pathogenesis of patients with PD with LID (PD-LID), we explored the structural and functional characteristics of SN in PD-LID using multimodal magnetic resonance imaging (MRI).

METHODS

Twenty-nine patients with PD-LID, 37 patients with PD without LID (PD-nLID), and 28 healthy control subjects underwent T1-weighted MRI, quantitative susceptibility mapping, neuromelanin-sensitive MRI, multishell diffusion MRI, and resting-state functional MRI. Different measures characterizing the SN were obtained using a region of interest-based approach.

RESULTS

Compared with patients with PD-nLID and healthy control subjects, the quantitative susceptibility mapping values of SN pars compacta (SNpc) were significantly higher (P = 0.049 and P = 0.00002), and the neuromelanin contrast-to-noise ratio values in SNpc were significantly lower (P = 0.012 and P = 0.000002) in PD-LID. The intracellular volume fraction of the posterior SN in PD-LID was significantly higher compared with PD-nLID (P = 0.037). Resting-state fMRI indicated that PD-LID in the medication off state showed higher functional connectivity between the SNpc and putamen compared with PD-nLID (P = 0.031), and the functional connectivity changes in PD-LID were positively correlated with Unified Dyskinesia Rating Scale total scores (R = 0.427, P = 0.042).

CONCLUSIONS

Our multimodal imaging findings highlight greater neurodegeneration in SN and the altered nigrostriatal connectivity in PD-LID. These characteristics provide a new perspective into the role of SN in the pathophysiological mechanisms underlying PD-LID. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Structural connectivity and brain network analyses in Parkinson's disease: A cross-sectional and longitudinal study

Introduction

Parkinson's disease (PD) is an idiopathic disease of the central nervous system characterized by both motor and non-motor symptoms. It is the second most common neurodegenerative disease. Magnetic resonance imaging (MRI) can reveal underlying brain changes associated with PD.

Objective

In this study, structural connectivity and white matter networks were analyzed by diffusion MRI and graph theory in a cohort of patients with PD and a cohort of healthy controls (HC) obtained from the Parkinson's Progression Markers Initiative (PPMI) database in a cross-sectional analysis. Furthermore, we investigated longitudinal changes in the PD cohort over 36 months.

Result

Compared with the control group, participants with PD showed lower structural connectivity in several brain areas, including the corpus callosum, fornix, and uncinate fasciculus, which were also confirmed by a large effect-size. Additionally, altered connectivity between baseline and after 36 months was found in different network paths inside the white matter with a medium effect-size. Network analysis showed trends toward lower network density in PD compared with HC at baseline and after 36 months, though not significant after correction. Significant differences were observed in nodal degree and strength in several nodes.

Conclusion

In conclusion, altered structural and network metrics in several brain regions, such as corpus callosum, fornix, and cingulum were found in PD, compared to HC. We also report altered connectivity in the PD group after 36 months, reflecting the impact of both PD pathology and aging processes. These results indicate that structural and network metrics might yield insight into network reorganization that occurs in PD.

Nigral diffusivity, but not free water, correlates with iron content in Parkinson's disease

The loss of melanized neurons in the substantia nigra pars compacta is a primary feature in Parkinson's disease. Iron deposition occurs in conjunction with this loss. Loss of nigral neurons should remove barriers for diffusion and increase diffusivity of water molecules in regions undergoing this loss. In metrics from single-compartment diffusion tensor imaging models, these changes should manifest as increases in mean diffusivity and reductions in fractional anisotropy as well as increases in the free water compartment in metrics derived from bi-compartment models. However, studies examining nigral diffusivity changes from Parkinson's disease with single-compartment models have yielded inconclusive results and emerging evidence in control subjects indicates that iron corrupts diffusivity metrics derived from single-compartment models. We aimed to examine Parkinson's disease-related changes in nigral iron and diffusion measures from single- and bi-compartment models as well as assess the effect of iron on these diffusion measures in two separate Parkinson's cohorts. Iron-sensitive data and diffusion data were analysed in two cohorts: First, a discovery cohort consisting of 71 participants (32 control participants and 39 Parkinson's disease participants) was examined. Second, an external validation cohort, obtained from the Parkinson's Progression Marker's Initiative, consisting of 110 participants (58 control participants and 52 Parkinson's disease participants) was examined. The effect of iron on diffusion measures from single- and bi-compartment models was assessed in both cohorts. Measures sensitive to the free water compartment (discovery cohort: P = 0.006; external cohort: P = 0.01) and iron content (discovery cohort: P < 0.001; validation cohort: P = 0.02) were found to increase in substantia nigra of the Parkinson's disease group in both cohorts. However, diffusion markers derived from the single-compartment model (i.e. mean diffusivity and fractional anisotropy) were not replicated across cohorts. Correlations were seen between single-compartment diffusion measures and iron markers in the discovery cohort (iron-mean diffusivity: r = -0.400, P = 0.006) and validation cohort (iron-mean diffusivity: r = -0.387, P = 0.003) but no correlation was observed between a measure from the bi-compartment model related to the free water compartment and iron markers in either cohort. In conclusion, the variability of nigral diffusion metrics derived from the single-compartment model in Parkinson's disease may be attributed to competing influences of increased iron content, which tends to drive diffusivity down, and increases in the free water compartment, which tends to drive diffusivity up. In contrast to diffusion metrics derived from the single-compartment model, no relationship was seen between iron and the free water compartment in substantia nigra.

White matter and nigral alterations in multiple system atrophy-parkinsonian type

Multiple system atrophy (MSA) is classified into two main types: parkinsonian and cerebellar ataxia with oligodendrogliopathy. We examined microstructural alterations in the white matter and the substantia nigra pars compacta (SNc) of patients with MSA of parkinsonian type (MSA-P) using multishell diffusion magnetic resonance imaging (dMRI) and myelin sensitive imaging techniques. Age- and sex-matched patients with MSA-P (n = 21, n = 10 first and second cohorts, respectively), Parkinson’s disease patients (n = 19, 17), and healthy controls (n = 20, 24) were enrolled. Magnetization transfer saturation imaging (MT-sat) and dMRI were obtained using 3-T MRI. Measurements obtained from diffusion tensor imaging (DTI), free-water elimination DTI, neurite orientation dispersion and density imaging (NODDI), and MT-sat were compared between groups. Tract-based spatial statistics analysis revealed differences in diffuse white matter alterations in the free-water fractional volume, myelin volume fraction, and intracellular volume fraction between the patients with MSA-P and healthy controls, whereas free-water and MT-sat differences were limited to the middle cerebellar peduncle in comparison with those with Parkinson’s disease. Region-of-interest analysis of white matter and SNc revealed significant differences in the middle and inferior cerebellar peduncle, pontine crossing tract, corticospinal tract, and SNc between the MSA-P and healthy controls and/or Parkinson’s disease patients. Our results shed light on alterations to brain microstructure in MSA.

Convolutional neural network optimizes the application of diffusion kurtosis imaging in Parkinson's disease

Objectives

The literature regarding the use of diffusion-tensor imaging-derived metrics in the evaluation of Parkinson’s disease (PD) is controversial. This study attempted to assess the feasibility of a deep-learning-based method for detecting alterations in diffusion kurtosis measurements associated with PD.

Methods

A total of 68 patients with PD and 77 healthy controls were scanned using scanner-A (3 T Skyra) (DATASET-1). Meanwhile, an additional five healthy volunteers were scanned with both scanner-A and an additional scanner-B (3 T Prisma) (DATASET-2). Diffusion kurtosis imaging (DKI) of DATASET-2 had an extra b shell compared to DATASET-1. In addition, a 3D-convolutional neural network (CNN) was trained from DATASET-2 to harmonize the quality of scalar measures of scanner-A to a similar level as scanner-B. Whole-brain unpaired t test and Tract-Based Spatial Statistics (TBSS) were performed to validate the differences between the PD and control groups using the model-fitting method and CNN-based method, respectively. We further clarified the correlation between clinical assessments and DKI results.

Results

An increase in mean diffusivity (MD) was found in the left substantia nigra (SN) in the PD group. In the right SN, fractional anisotropy (FA) and mean kurtosis (MK) values were negatively correlated with Hoehn and Yahr (H&Y) scales. In the putamen (Put), FA values were positively correlated with the H&Y scales. It is worth noting that these findings were only observed with the deep learning method. There was neither a group difference nor a correlation with clinical assessments in the SN or striatum exceeding the significance level using the conventional model-fitting method.

Conclusions

The CNN-based method improves the robustness of DKI and can help to explore PD-associated imaging features.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40708-021-00139-z.

Altered cerebral perfusion and microstructure in advanced Parkinson's disease and their associations with clinical features

OBJECTIVE

To explore the whole cerebral perfusion and microstructure alteration patterns in Parkinson's disease (PD) and the associations of these patterns with clinical features.

METHODS

Forty-one subjects [20 PD patients and 21 healthy controls (HCs)] underwent arterial spin labeling (ASL), diffusion tensor imaging (DTI) and 3D T1-weighted imaging (T1WI) MRI. The cerebral blood flow (CBF) of the whole brain and the fractional anisotropy (FA), axial diffusivity (AD), radial diffusivity (RD) and mean diffusivity (MD) of subcortical and cerebellar regions were measured and compared between groups. Pearson's correlation was calculated between MRI measurements and clinical features [Unified Parkinson's Disease Rating Scale (UPDRS), UPDRS III, Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA) and olfactory test scores].

RESULTS

Compared to HCs, PD patients showed lower CBF in the frontal, parietal and temporal lobes but higher CBF in bilateral hippocampi, red nuclei, right substantia nigra, thalamus and most cerebellar regions. The MD in the right thalamus and several regions in the cerebellum increased in PD compared to HCs. In PD patients, the total UPDRS, UPDRS III, MoCA, MMSE and olfactory test scores were related to FA or CBF in cerebellum. (all p < 0.05).

CONCLUSION

Hypoperfusion in cortical regions, together with hyperperfusion in subcortical and cerebellar regions may be the characteristic perfusion pattern in advanced PD patients. The microstructures of the right thalamus and cerebellum were changed in PD patients. The cognitive, motor and olfactory performance of PD patients is closely related to the perfusion and microstructure of the brain, especially the cerebellum.

Sex effects on brain structure in de novo Parkinson's disease: a multimodal neuroimaging study

Parkinson's disease varies in severity and age of onset. One source of this variability is sex. Males are twice as likely as females to develop Parkinson's disease, and tend to have more severe symptoms and greater speed of progression. However, to date, there is little information in large cohorts on sex differences in the patterns of neurodegeneration. Here we used MRI and clinical information from the Parkinson Progression Markers Initiative to measure structural brain differences between sexes in Parkinson's disease after regressing out the expected effect of age and sex. We derived atrophy maps from deformation-based morphometry of T1-weighted MRI and connectivity from diffusion-weighted MRI in de novo Parkinson's disease patients (149 males: 83 females) with comparable clinical severity, and healthy control participants (78 males: 39 females). Overall, even though the two patient groups were matched for disease duration and severity, males demonstrated generally greater brain atrophy and disrupted connectivity. Males with Parkinson's disease had significantly greater tissue loss than females in 11 cortical regions including bilateral frontal and left insular lobe, right postcentral gyrus, left inferior temporal and cingulate gyrus and left thalamus, while females had greater atrophy in six cortical regions, including regions in the left frontal lobe, right parietal lobe, left insular gyrus and right occipital cortex. Local efficiency of white matter connectivity showed greater disruption in males in multiple regions such as basal ganglia, hippocampus, amygdala and thalamus. These findings support the idea that development of Parkinson's disease may involve different pathological mechanisms and yield distinct prognosis in males and females, which may have implications for research into neuroprotection, and stratification for clinical trials.

Bundle analytics, a computational framework for investigating the shapes and profiles of brain pathways across populations

Tractography has created new horizons for researchers to study brain connectivity in vivo. However, tractography is an advanced and challenging method that has not been used so far for medical data analysis at a large scale in comparison to other traditional brain imaging methods. This work allows tractography to be used for large scale and high-quality medical analytics. BUndle ANalytics (BUAN) is a fast, robust, and flexible computational framework for real-world tractometric studies. BUAN combines tractography and anatomical information to analyze the challenging datasets and identifies significant group differences in specific locations of the white matter bundles. Additionally, BUAN takes the shape of the bundles into consideration for the analysis. BUAN compares the shapes of the bundles using a metric called bundle adjacency which calculates shape similarity between two given bundles. BUAN builds networks of bundle shape similarities that can be paramount for automating quality control. BUAN is freely available in DIPY. Results are presented using publicly available Parkinson's Progression Markers Initiative data.

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.

Mean Apparent Propagator MRI Is Better Than Conventional Diffusion Tensor Imaging for the Evaluation of Parkinson's Disease: A Prospective Pilot Study

Background and Purpose

Mean apparent propagator (MAP) MRI is a novel diffusion imaging method to map tissue microstructure. The purpose of this study was to evaluate the diagnostic value of the MAP MRI in Parkinson’s disease (PD) in comparison with conventional diffusion tensor imaging (DTI).

Methods

23 PD patients and 22 age- and gender-matched healthy controls were included. MAP MRI and DTI were performed on a 3T MR scanner with a 20-channel head coil. The MAP metrics including mean square displacement (MSD), return to the origin probability (RTOP), return to the axis probability (RTAP), and return to the plane probability (RTPP), and DTI metrics including fractional anisotropy (FA), and mean diffusivity (MD), were measured in subcortical gray matter and compared between the two groups. The receiver operating characteristic (ROC) curve was used to analyze the diagnostic performance of all the metrics. The association between the diffusion metrics and disease severity was assessed by Pearson correlation analysis.

Results

For MAP MRI, the mean values of MSD in the bilateral caudate, pallidum, putamen, thalamus and substantia nigra (SN) were higher in PD patients than in healthy controls (p_FDR ≤ 0.001); the mean values of the zero displacement probabilities (RTOP, RTAP, and RTPP) in the bilateral caudate, pallidum, putamen and thalamus were lower in PD patients (p_FDR < 0.001). For DTI, only FA in the bilateral SN was significantly higher in PD patients than those in the controls (p_FDR < 0.001). ROC analysis showed that the areas under the curves of MAP MRI metrics (MSD, RTOP, RTAP, and RTPP) in the bilateral caudate, pallidum, putamen and thalamus (range, 0.85–0.94) were greater than those of FA and MD of DTI (range, 0.55–0.69) in discriminating between PD patients and healthy controls. RTAP in the ipsilateral pallidum (r = −0.56, p_FDR = 0.027), RTOP in the bilateral and contralateral putamen (r = −0.58, p_FDR = 0.019; r = −0.57, p_FDR = 0.024) were negatively correlated with UPDRS III motor scores.

Conclusion

MAP MRI outperformed the conventional DTI in the diagnosis of PD and evaluation of the disease severity.

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.

Feasibility of diffusion and probabilistic white matter analysis in patients implanted with a deep brain stimulator

Deep brain stimulation (DBS) for Parkinson's disease (PD) is an established advanced therapy that produces therapeutic effects through high frequency stimulation. Although this therapeutic option leads to improved clinical outcomes, the mechanisms of the underlying efficacy of this treatment are not well understood. Therefore, investigation of DBS and its postoperative effects on brain architecture is of great interest. Diffusion weighted imaging (DWI) is an advanced imaging technique, which has the ability to estimate the structure of white matter fibers; however, clinical application of DWI after DBS implantation is challenging due to the strong susceptibility artifacts caused by implanted devices. This study aims to evaluate the feasibility of generating meaningful white matter reconstructions after DBS implantation; and to subsequently quantify the degree to which these tracts are affected by post-operative device-related artifacts. DWI was safely performed before and after implanting electrodes for DBS in 9 PD patients. Differences within each subject between pre- and post-implantation FA, MD, and RD values for 123 regions of interest (ROIs) were calculated. While differences were noted globally, they were larger in regions directly affected by the artifact. White matter tracts were generated from each ROI with probabilistic tractography, revealing significant differences in the reconstruction of several white matter structures after DBS. Tracts pertinent to PD, such as regions of the substantia nigra and nigrostriatal tracts, were largely unaffected. The aim of this study was to demonstrate the feasibility and clinical applicability of acquiring and processing DWI post-operatively in PD patients after DBS implantation. The presence of global differences provides an impetus for acquiring DWI shortly after implantation to establish a new baseline against which longitudinal changes in brain connectivity in DBS patients can be compared. Understanding that post-operative fiber tracking in patients is feasible on a clinically-relevant scale has significant implications for increasing our current understanding of the pathophysiology of movement disorders, and may provide insights into better defining the pathophysiology and therapeutic effects of DBS.

Combined Assessment of Diffusion Parameters and Cerebral Blood Flow Within Basal Ganglia in Early Parkinson's Disease

Diffusion tensor imaging (DTI) is a sensitive tool for detecting brain tissue microstructural alterations in Parkinson’s disease (PD). Abnormal cerebral perfusion patterns have also been reported in PD patients using arterial spin labeling (ASL) MRI. In this study we aimed to perform a combined DTI and ASL assessment in PD patients within the basal ganglia, in order to test the relationship between microstructural and perfusion alterations. Fifty-two subjects participated in this study. Specifically, 26 PD patients [mean age (SD) = 66.7 (8.9) years, 21 males, median (IQR) Modified Hoehn and Yahr = 1.5 (1–1.6)] and twenty-six healthy controls [HC, mean age (SD) = 65.2 (7.5), 15 males] were scanned with 1.5T MRI. Fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), radial diffusivity (RD) maps were derived from diffusion-weighted images, while cerebral blood flow (CBF) maps were computed from ASL data. After registration to Montreal Neurological Institute standard space, FA, MD, AD, RD and CBF median values were extracted within specific regions of interest: substantia nigra, caudate, putamen, globus pallidus, thalamus, red nucleus and subthalamic nucleus. DTI measures and CBF were compared between the two groups. The relationship between diffusion parameters and CBF was tested with Spearman’s correlations. False discovery rate (FDR)-corrected p-values lower than 0.05 were considered significant, while uncorrected p-values <0.05 were considered a trend. No significant FA, MD and RD differences were observed. AD was significantly increased in PD patients compared with HC in the putamen (p = 0.005, p_FDR = 0.035). No significant CBF differences were found between PD patients and HC. Diffusion parameters were not significantly correlated with CBF in the HC group, while a significant correlation emerged for PD patients in the caudate nucleus, for all DTI measures (with FA: r = 0.543, p_FDR = 0.028; with MD: r = −0.661, p_FDR = 0.002; with AD: r = −0.628, p_FDR = 0.007; with RD: r = −0.635, p_FDR = 0.003). This study showed that DTI is a more sensitive technique than ASL to detect alterations in the basal ganglia in the early phase of PD. Our results suggest that, although DTI and ASL convey different information, a relationship between microstructural integrity and perfusion changes in the caudate may be present.

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.

Influence of analytic techniques on comparing DTI-derived measurements in early stage Parkinson's disease

Diffusion tensor imaging (DTI) studies in early Parkinson's disease (PD) to understand pathologic changes in white matter (WM) organization are variable in their findings. Evaluation of different analytic techniques frequently employed to understand the DTI-derived change in WM organization in a multisite, well-characterized, early stage PD cohort should aid the identification of the most robust analytic techniques to be used to investigate WM pathology in this disease, an important unmet need in the field. Thus, region of interest (ROI)-based analysis, voxel-based morphometry (VBM) analysis with varying spatial smoothing, and the two most widely used skeletonwise approaches (tract-based spatial statistics, TBSS, and tensor-based registration, DTI-TK) were evaluated in a DTI dataset of early PD and Healthy Controls (HC) from the Parkinson's Progression Markers Initiative (PPMI) cohort. Statistical tests on the DTI-derived metrics were conducted using a nonparametric approach from this cohort of early PD, after rigorously controlling for motion and signal artifacts during DTI scan which are frequent confounds in this disease population. Both TBSS and DTI-TK revealed a significantly negative correlation of fractional anisotropy (FA) with disease duration. However, only DTI-TK revealed radial diffusivity (RD) to be driving this FA correlation with disease duration. HC had a significantly positive correlation of MD with cumulative DaT score in the right middle-frontal cortex after a minimum smoothing level (at least 13mm) was attained. The present study found that scalar DTI-derived measures such as FA, MD, and RD should be used as imaging biomarkers with caution in early PD as the conclusions derived from them are heavily dependent on the choice of the analysis used. This study further demonstrated DTI-TK may be used to understand changes in DTI-derived measures with disease progression as it was found to be more accurate than TBSS. In addition, no singular region was identified that could explain both disease duration and severity in early PD. The results of this study should help standardize the utilization of DTI-derived measures in PD in an effort to improve comparability across studies and time, and to minimize variability in reported results due to variation in techniques.

Longitudinal Progression Markers of Parkinson's Disease: Current View on Structural Imaging

PURPOSE OF REVIEW

Advances in neuroimaging techniques pave a rich avenue for in vivo progression biomarkers, which can objectively and noninvasively assess the long-term dynamic alterations in the brain of Parkinson's disease (PD) patients. This article reviews recent progress in structural magnetic resonance imaging (MRI) tools to track disease progression in PD, and discusses specific criteria a neuroimaging tool needs to meet to be a progression biomarker of PD and the potential applications of these techniques in PD based on current evidence.

RECENT FINDINGS

Recent longitudinal studies showed that quantitative structural MRI markers derived from T1-weighted, diffusion-weighted, neuromelanin-sensitive, and iron-sensitive imaging have the potential to track disease progression in PD. However, validation of these progression biomarkers is only beginning, and more work is required for multisite validation, the sample size for use in a clinical trial, and drug-responsiveness of most of these biomarkers. At present, the most clinical trial-ready biomarker is free-water diffusion imaging of the substantia nigra and seems well established to be used in disease-modifying studies in PD. A variety of structural imaging biomarkers are promising candidates to be progression biomarkers in PD. Further studies are needed to elucidate the sensitivity, reliability, sample size, and effect of confounding factors of these progression biomarkers.

Imaging of Motor Cortex Physiology in Parkinson's Disease

There is abundant evidence that the pathophysiology of Parkinson's disease (PD) is not confined to the nigrostriatal dopaminergic pathway but propagates along the cortico‐basal ganglia‐thalamo‐cortical neural network. A critical node in this functional circuit impacted by PD is the primary motor cortex (M1), which plays a key role in generating neural impulses that regulate movements. The past several decades have lay witness to numerous in vivo neuroimaging techniques that provide a window into the function and structure of M1. A consistent observation from numerous studies is that during voluntary movement, but also at rest, the functional activity of M1 is altered in PD relative to healthy individuals, and it relates to many of the motor signs. Although this abnormal functional activity can be partially restored with acute dopaminergic medication, it continues to deteriorate with disease progression and may predate structural degeneration of M1. The current review discusses the evidence that M1 is fundamental to the pathophysiology of PD, as measured by neuroimaging techniques such as positron emission tomography, single‐photon emission computed tomography, electroencephalography, magnetoencephalography, and functional and structural MRI. Although novel treatments that target the cortex will not cure PD, they could significantly slow down and alter the progressive course of the disease and thus improve clinical care for this degenerative disease. © 2018 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society

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.

Alteration of putaminal fractional anisotropy in Parkinson's disease: a longitudinal diffusion kurtosis imaging study

Purpose

In Parkinson’s disease (PD), pathological microstructural changes occur that may be detected using diffusion magnetic resonance imaging (dMRI). However, there are few longitudinal studies that explore the effect of disease progression on diffusion indices.

Methods

We prospectively included 76 patients with PD and 38 healthy controls (HC), all of whom underwent diffusion kurtosis imaging (DKI) as part of the prospective Swedish BioFINDER study at baseline and 2 years later. Annualized rates of change in DKI parameters, including fractional anisotropy (FA), mean diffusivity (MD), and mean kurtosis (MK), were estimated in the gray matter (GM) by placing regions of interest (ROIs) in the basal ganglia and the thalamus, and in the white matter (WM) by tract-based spatial statistics (TBSS) analysis.

Results

When adjusting for potential confounding factors (age, gender, baseline-follow-up interval, and software upgrade of MRI scanner), only a decrease in FA in the putamen of PD patients (β = − 0.248, P < .01) over 2 years was significantly different from the changes observed in HC over the same time period. This 2-year decrease in FA in the putamen in PD correlated with higher l-dopa equivalent dose at baseline (Spearman’s rho = .399, P < .0001).

Conclusion

The study indicates that in PD microstructural changes in the putamen occur selectively over a 2-year period and can be detected with DKI.

Electronic supplementary material

The online version of this article (10.1007/s00234-017-1971-3) contains supplementary material, which is available to authorized users.

Analysis of white matter characteristics with tract-based spatial statistics according to diffusion tensor imaging in early Parkinson's disease

OBJECTIVE

To analyze the microstructure of brain white matter according to diffusion tensor imaging (DTI) based on tract-based spatial statistics (TBSS) in early Parkinson's disease (PD).

MATERIALS AND METHODS

A total of 31 age- and sex-matched early PD patients and 22 healthy volunteers were recruited in the present study. DTI was performed, and the data analyzed with fsl4.0 software. The fractional anisotropy (FA) was compared between both groups with an independent t test, and the differential area was analyzed. White matter fiber tracts with significant difference in FA between the two groups were selected, and their FAs were measured. Pearson's correlation analysis was employed to analyze the unified Parkinson's disease rating scale (UPDRS) score and its association with FA of different tracts.

RESULTS

When compared with healthy volunteers, early PD patients had reduced FA in the following areas: bilateral anterior corona radiate, upper corona radiate, fasciculus arcuatus, crus anterius capsulae internae, crus posterius capsulae internae, capsula externa, posterior thalamic radiation, optic radiation, sagittal layer (including fasciculus arcuatus and inferior fronto-occipital fasciculus), crura fornicis, stria terminalis, fornix, genu, body and pad of corpus callosum, left unciform fasciculus, right cingulate bundle, right medipeduncle, and arcuate fibers in the bilateral frontal, temporal, and occipital lobes (P < 0.05). When compared with healthy volunteers, early PD patients showed abnormal FA of fasciculus in the white matter mainly in following areas: bilateral crus anterius capsulae internae, bilateral capsula externa, right anterior corona radiate, body and pad of bilateral corpus callosum, and left sagittal layer (including fasciculi longitudinalis inferior and fasciculus occipitofrontalis inferior) (P < 0.05). In addition, in early PD patients, the UPDRS score and movement score had no relationship with the FA of different fasciculi in the white matter (P > 0.05).

CONCLUSION

There is wide alteration of white matter microstructure in early PD patients, which is characterized by disruption of projection fibers in the descending pathway, limbic system-related fasciculi, corpus callosum, thalamus after radiation, posterior thalamic radiation, Gratiolet's bundle and other fasciculi in the white matter.

Evaluation of striatonigral connectivity using probabilistic tractography in Parkinson's disease

The cardinal movement abnormalities of Parkinson's disease (PD), including tremor, muscle rigidity, and reduced speed and frequency of movements, are caused by degeneration of dopaminergic neurons in the substantia nigra that project to the putamen, compromising information flow through frontal-subcortical circuits. Typically, the nigrostriatal pathway is more severely affected on the side of the brain opposite (contralateral) to the side of the body that manifests initial symptoms. Several studies have suggested that PD is also associated with changes in white matter microstructural integrity. The goal of the present study was to further develop methods for measuring striatonigral connectivity differences between PD patients and age-matched controls using diffusion weighted magnetic resonance imaging (MRI).

In this cross-sectional study, 40 PD patients and 44 controls underwent diffusion weighted imaging (DWI) using a 40-direction MRI sequence as well as an optimized 60-direction sequence with overlapping slices. Regions of interest (ROIs) encompassing the putamen and substantia nigra were hand drawn in the space of the 40-direction data using high-contrast structural images and then coregistered to the 60-direction data. Probabilistic tractography was performed in the native space of each dataset by seeding the putamen ROI with an ipsilateral substantia nigra classification target. The effect of disease group (PD versus control) on mean putamen-SN connection probability and streamline density were then analyzed using generalized linear models controlling for age, gender, education, as well as seed and target region characteristics.

Mean putamen-SN streamline density was lower in PD on both sides of the brain and in both 40- and 60-direction data. The optimized sequence provided a greater separation between PD and control means; however, individual values overlapped between groups. The 60-direction data also yielded mean connection probability values either trending (ipsilateral) or significantly (contralateral) lower in the PD group. There were minor between-group differences in average diffusion measures within the substantia nigra ROIs that did not affect the results of the GLM analyses when included as covariates. Based on these results, we conclude that mean striatonigral structural connectivity differs between PD and control groups and that use of an optimized 60-direction DWI sequence with overlapping slices increases the sensitivity of the technique to putative disease-related differences. However, overlap in individual values between disease groups limits its use as a classifier.

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The nigrostriatal pathway degenerates in Parkinson's disease.

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Two diffusion tensor imaging (DTI) sequences were acquired in 84 participants.

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Structural connectivity between putamen and substantia nigra was quantified.

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Parkinson's patients had lower connection probability and streamline density.

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A 60-direction DTI sequence with overlapping slices was most sensitive.

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.

A test-retest study on Parkinson's PPMI dataset yields statistically significant white matter fascicles

In this work, we propose a diffusion MRI protocol for mining Parkinson's disease diffusion MRI datasets and recover robust disease-specific biomarkers. Using advanced high angular resolution diffusion imaging (HARDI) crossing fiber modeling and tractography robust to partial volume effects, we automatically dissected 50 white matter (WM) fascicles. These fascicles connect deep nuclei (thalamus, putamen, pallidum) to different cortical functional areas (associative, motor, sensorimotor, limbic), basal forebrain and substantia nigra. Then, among these 50 candidate WM fascicles, only the ones that passed a test-retest reproducibility procedure qualified for further tractometry analysis. Leveraging the unique 2-timepoints test-retest Parkinson's Progression Markers Initiative (PPMI) dataset of over 600 subjects, we found statistically significant differences in tract profiles along the subcortico-cortical pathways between Parkinson's disease patients and healthy controls. In particular, significant increases in FA, apparent fiber density, tract-density and generalized FA were detected in some locations of the nigro-subthalamo-putaminal-thalamo-cortical pathway. This connection is one of the major motor circuits balancing the coordination of motor output. Detailed and quantifiable knowledge on WM fascicles in these areas is thus essential to improve the quality and outcome of Deep Brain Stimulation, and to target new WM locations for investigation.

Lateralized microstructural changes in early-stage Parkinson's disease in anterior olfactory structures, but not in substantia nigra

Parkinson's disease (PD) is a progressive neurological disorder characterized by motor symptoms as well as severe deficits in olfactory function and microstructural changes in olfactory brain regions. Because of the evidence of asymmetric neuropathological features in early-stage PD, we examined whether lateralized microstructural changes occur in olfactory brain regions and the substantia nigra in a group of early-stage PD patients. Using diffusion tensor imaging (DTI) and the University of Pennsylvania Smell Identification Test (UPSIT), we assessed 24 early-stage PD patients (Hoehn and Yahr stage 1 or 2) and 26 healthy controls (HC). We used DTI and a region of interest (ROI) approach to study the microstructure of the left and right anterior olfactory structures (AOS; comprising the olfactory bulbs and anterior end of the olfactory tracts) and the substantia nigra (SN). PD patients had reduced UPSIT scores relative to HC and showed increased mean diffusivity (MD) in the SN, with no lateralized differences. Significant group differences in fractional anisotropy (FA) and MD were seen in the AOS, but these differences were restricted to the right side and were not associated with the primary side of motor symptoms amongst PD patients. No associations were observed between lateralized motor impairment and lateralized microstructural changes in AOS. Impaired olfaction and microstructural changes in AOS are useful for early identification of PD but asymmetries in AOS microstructure seem unrelated to the laterality of PD motor symptoms.

Network evolution in mesial temporal lobe epilepsy revealed by diffusion tensor imaging

OBJECTIVE

The objective of the present study is to identify novel, time-indexed imaging biomarkers of epileptogenesis in mesial temporal lobe epilepsy (MTLE).

METHODS

We used high-resolution brain diffusion tensor imaging (DTI) of the translationally relevant methionine sulfoximine (MSO) brain infusion model of MTLE. MSO inhibits astroglial glutamine synthetase, which is deficient in the epileptogenic hippocampal formation of patients with MTLE. MSO-infused (epileptogenic) rats were compared with phosphate-buffered saline (PBS)-infused (nonepileptogenic) rats at early (3-4 days) and late (6-9 weeks) time points during epileptogenesis.

RESULTS

The epileptogenic rats exhibited significant changes in DTI-measured fractional anisotropy (FA) in numerous brain regions versus nonepileptogenic rats. Changes included decreases and increases in FA in regions such as the entorhinal-hippocampal area, amygdala, corpus callosum, thalamus, striatum, accumbens, and neocortex. The FA changes evolved over time as animals transitioned from early to late epileptogenesis. For example, some areas with significant decreases in FA early in epileptogenesis changed to significant increases late in epileptogenesis. Finally, the FA changes significantly correlated with the seizure load.

SIGNIFICANCE

Our results suggest (1) that high-resolution DTI can be used for early identification and tracking of the epileptogenic process in MTLE, and (2) that the process identified by DTI is present in multiple brain areas, even though infusion of MSO is restricted to the unilateral entorhinal-hippocampal region.

Early and progressive microstructural brain changes in mice overexpressing human α-Synuclein detected by diffusion kurtosis imaging

Diffusion kurtosis imaging (DKI) is sensitive in detecting α-Synuclein (α-Syn) accumulation-associated microstructural changes at late stages of the pathology in α-Syn overexpressing TNWT-61 mice. The aim of this study was to perform DKI in young TNWT-61 mice when α-Syn starts to accumulate and to compare the imaging results with an analysis of motor and memory impairment and α-Syn levels. Three-month-old (3mo) and six-month-old (6mo) mice underwent DKI scanning using the Bruker Avance 9.4T magnetic resonance imaging system. Region of interest (ROI) analyses were performed in the gray matter; tract-based spatial statistics (TBSS) analyses were performed in the white matter. In the same mice, α-Syn expression was evaluated using quantitative immunofluorescence. Mean kurtosis (MK) was the best differentiator between TNWT-61 mice and wildtype (WT) mice. We found increases in MK in 3mo TNWT-61 mice in the striatum and thalamus but not in the substantia nigra (SN), hippocampus, or sensorimotor cortex, even though the immunoreactivity of human α-Syn was similar or even higher in the latter regions. Increases in MK in the SN were detected in 6mo mice. These findings indicate that α-Syn accumulation-associated changes may start in areas with a high density of dopaminergic nerve terminals. We also found TBSS changes in white matter only at 6mo, suggesting α-Syn accumulation-associated changes start in the gray matter and later progress to the white matter. MK is able to detect microstructural changes induced by α-Syn overexpression in TNWT-61 mice and could be a useful clinical tool for detecting early-stage Parkinson's disease in human patients.

Combining nanoscale magnetic nimodipine liposomes with magnetic resonance image for Parkinson's disease targeting therapy

AIM

To enhance drug targeting and blood-brain barrier penetration for Parkinson's disease (PD), a novel nanoscale magnetic nimodipine (NMD) delivery system was designed and prepared.

MATERIALS & METHODS

The PD rats were established and treated with free NMD or Fe₃O₄-modified NMD liposomes (Fe₃O₄-NMD-lips). Then, factional anisotropy values were measured by MRI to evaluate therapy efficacy.

RESULTS

Fe₃O₄-NMD-lips showed the best neuroprotective effect, and the NMD concentration of lesions was 2.5-fold higher in Fe₃O₄-NMD-lips group than that of free NMD group.

CONCLUSION

These results demonstrated that the magnetic drug system had a great potential to cross the blood-brain barrier and provided a noninvasive and effective therapeutic strategy for PD.

Detecting dopaminergic neuronal degeneration using diffusion tensor imaging in a rotenone-induced rat model of Parkinson's disease: fractional anisotropy and mean diffusivity values

Dopamine content in the basal ganglia is strongly associated with the degree of dopaminergic neuron loss in the substantia nigra pars compacta. Symptoms of Parkinson's disease might not arise until more than 50% of the substantia nigra pars compacta is lost and the dopamine content in the basal ganglia is reduced by more than 80%. Greater diagnostic sensitivity and specificity would allow earlier detection of Parkinson's disease. Diffusion tensor imaging is a recently developed magnetic resonance imaging technique that measures mean diffusivity and fractional anisotropy, and responds to changes in brain microstructure. When the microscopic barrier (including cell membranes, microtubules and other structures that interfere with the free diffusion of water) is destroyed and extracellular fluid volume accumulates, the mean diffusivity value increases; when the integrity of the microstructure (such as myelin) is destroyed, fractional anisotropy value decreases. However, there is no consensus as to whether these changes can reflect the early pathological alterations in Parkinson's disease. Here, we established a rat model of Parkinson's disease by injecting rotenone (or sunflower oil in controls) into the right substantia nigra. Diffusion tensor imaging results revealed that in the stages of disease, at 1, 2, 4, and 6 weeks after rotenone injection, fractional anisotropy value decreased, but mean diffusivity values increased in the right substantia nigra in the experimental group. Fractional anisotropy values were lower at 4 weeks than at 6 weeks in the right substantia nigra of rats from the experimental group. Mean diffusivity values were markedly greater at 1 week than at 6 weeks in the right corpus striatum of rats from the experimental group. These findings suggest that mean diffusivity and fractional anisotropy values in the brain of rat models of Parkinson's disease 4 weeks after model establishment can reflect early degeneration of dopaminergic neurons. The change in fractional anisotropy values after destruction of myelin integrity is likely to be of greater early diagnostic significance than the change in mean diffusivity values.

Progression of Regional Microstructural Degeneration in Parkinson's Disease: A Multicenter Diffusion Tensor Imaging Study

This study aimed to identify the utility of diffusion tensor imaging (DTI) in measuring the regional distribution of abnormal microstructural progression in patients with Parkinson’s disease who were enrolled in the Parkinson's progression marker initiative (PPMI). One hundred and twenty two de-novo PD patients (age = 60.5±9) and 50 healthy controls (age = 60.6±11) had DTI scans at baseline and 12.6±1 months later. Automated image processing included an intra-subject registration of all time points and an inter-subjects registration to a brain atlas. Annualized rates of DTI variations including fractional anisotropy (FA), radial (rD) and axial (aD) diffusivity were estimated in a total of 118 white matter and subcortical regions of interest. A mixed effects model framework was used to determine the degree to which DTI changes differed in PD relative to changes in healthy subjects. Significant DTI changes were also tested for correlations with changes in clinical measures, dopaminergic imaging and CSF biomarkers in PD patients. Compared to normal aging, PD was associated with higher rates of FA reduction, rD and aD increases predominantly in the substantia nigra, midbrain and thalamus. The highest rates of FA reduction involved the substantia nigra (3.6±1.4%/year from baseline, whereas the highest rates of increased diffusivity involved the thalamus (rD: 8.0±2.9%/year, aD: 4.0±1.5%/year). In PD patients, high DTI changes in the substantia nigra correlated with increasing dopaminergic deficits as well as with declining α-synuclein and total tau protein concentrations in cerebrospinal fluid. Increased DTI rates in the thalamus correlated with progressive decline in global cognition in PD. The results suggest that higher rates of regional microstructural degeneration are potential markers of PD progression.

White matter microstructural characteristics in newly diagnosed Parkinson's disease: An unbiased whole-brain study

Parkinson’s disease (PD) is a debilitating neurodegenerative disorder. Findings on specific white matter (WM) alterations in PD have been inconsistent. We hypothesized that WM changes occur in early PD patients and unbiased whole-brain analysis may provide additional evidence of pathological WM changes in PD. In this study, we examined various indexes of WM microstructure in newly diagnosed PD patients at the whole-brain level. 64 PDs with Hoehn & Yahr stage 1 (HY1PDs), 87 PDs with Hoehn & Yahr stage 2 (HYPD2s), and 60 controls (HCs) were recruited. Tract-based spatial statistics (TBSS) and diffusion connectometry were used to identify changes of WM pathways associated with PD. There were no significant differences in axial diffusivity, but HY1PDs exhibited greater fractional anisotropy (FA) and decreased mean and radial diffusivities (MD and RD) in callosal, projection, and association fibres than HCs and HY2PDs. Motor severity was inversely correlated with FA, but positively correlated with MD and RD in PD patients. Connectometry analysis also revealed increased WM density in the aforementioned tracts in PD patients, compared with HCs. Our study reveals WM enhancement, suggesting neural compensations in early PD. Longitudinal follow-up studies are warranted to identify the trajectory of WM changes alongside the progression of PD.

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.

Frontal white matter injuries predestine gait difficulties in Parkinson's disease

OBJECTIVES

This study applies diffusion tensor imaging (DTI) to determine differences in neuronal integrity between motor phenotypes in Parkinson's disease.

MATERIAL AND METHODS

One hundred and twenty-two patients (47 females, mean age = 70.3 years) were included at baseline. Forty patients were tremor dominant (TD), 64 had postural imbalance and gait difficulty (PIGD), and 18 patients were indeterminate. The DTI was repeated after one, three and 5 years, including reassessment of phenotype. DTI was quantified using fractional anisotropy (FA), and mean, radial and axial diffusion. Targeted white matter involved six regions of interests (ROIs) in prefrontal cortex (PFC), the entrance to the external capsule (EEC) and lateral to the horn of the anterior ventricle (LVAH). Grey matter involved the basal ganglia. Data were analysed using mixed linear models with P < 0.05 (Bonferroni corrected) as significance threshold.

RESULTS

PIGD and Indeterminate had reduced FA and axial diffusion in PFC, EEC and LVAH compared to Tremor dominant (P < 0.05). Basal ganglia showed no differences. Post hoc analysis showed that FA correlated negatively, and mean and radial diffusion positively, to PIGD symptoms in EEC, LVAH and four ROIs in PFC (P < 0.05). Tremor symptoms showed no correlations. Patients converting to PIGD and Indeterminate had lower FA, and higher mean and radial diffusion, at baseline in EEC, LVAH and four areas in PFC compared to non-converting patients (P < 0.05).

CONCLUSION

Degeneration in frontal white matter is connected to PIGD symptoms in Parkinson's disease and if present at an early stage, the risk for conversion to the PIGD phenotype increases.