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

Plasma Metabolite Markers of Parkinson's Disease and Atypical Parkinsonism

Differentiating between Parkinson’s disease (PD) and the atypical Parkinsonian disorders of multiple system atrophy (MSA) and progressive supranuclear palsy (PSP) is difficult clinically due to overlapping symptomatology, especially at early disease stages. Consequently, there is a need to identify metabolic markers for these diseases and to develop them into viable biomarkers. In the present investigation, solution nuclear magnetic resonance and mass spectrometry metabolomics were used to quantitatively characterize the plasma metabolomes (a total of 167 metabolites) of a cohort of 94 individuals comprising 34 PD, 12 MSA, and 17 PSP patients, as well as 31 control subjects. The distinct and statistically significant differences observed in the metabolite concentrations of the different disease and control groups enabled the identification of potential plasma metabolite markers of each disorder and enabled the differentiation between the disorders. These group-specific differences further implicate disturbances in specific metabolic pathways. The two metabolites, formic acid and succinate, were altered similarly in all three disease groups when compared to the control group, where a reduced level of formic acid suggested an effect on pyruvate metabolism, methane metabolism, and/or the kynurenine pathway, and an increased succinate level suggested an effect on the citric acid cycle and mitochondrial dysfunction.

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

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

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.

Diffusional kurtosis imaging in head and neck cancer: On the use of trace-weighted images to estimate indices of non-Gaussian water diffusion

PURPOSE

While previous studies have demonstrated the feasibility and potential usefulness of quantitative non-Gaussian diffusional kurtosis imaging (DKI) of the brain, more recent research has focused on oncological application of DKI in various body regions such as prostate, breast, and head and neck (HN). Given the need to minimize scan time during most routine magnetic resonance imaging (MRI) acquisitions of body regions, diffusion-weighted imaging (DWI) with only three orthogonal diffusion weighting directions (x, y, z) is usually performed. Moreover, as water diffusion within malignant tumors is generically thought to be almost isotropic, DWI with only three diffusion weighting directions is considered sufficient for oncological application and it represents the de facto standard in body DKI. In this context, since the kurtosis tensor and diffusion tensor cannot be obtained, the averages of the three directional (K_x , K_y , K_z ) and (D_x , D_y , D_z ) - namely K and D, respectively - represent the best-possible surrogates of directionless DKI-derived indices of kurtosis and diffusivity, respectively. This would require fitting the DKI model to the diffusion-weighted images acquired along each direction (x, y, z) prior to averaging. However, there is a growing tendency to perform only a single fit of the DKI model to the geometric means of the images acquired with diffusion-sensitizing gradient along (x, y, z), referred to as trace-weighted (TW) images. To the best of our knowledge, no in vivo studies have evaluated how TW images affect estimates of DKI-derived indices of K and D. Thus, the aim of this study was to assess the potential bias and error introduced in estimated K and D by fitting the DKI model to the TW images in HN cancer patients.

METHODS

Eighteen patients with histologically proven malignant tumors of the HN were enrolled in the study. They underwent pretreatment 3 T MRI, including DWI (b-values: 0, 500, 1000, 1500, 2000 s/mm² ). Some patients had multiple lesions, and thus a total of 34 lesions were analyzed. DKI-derived indices were estimated, voxel-by-voxel, using single diffusion-weighted images along (x, y, z) as well as TW images. A comparison between the two estimation methods was performed by calculating the percentage error in D (D_err ) and K (K_err ). Also, diffusivity anisotropy (D_anis ) and diffusional kurtosis anisotropy (K_anis ) were estimated. Agreements between the two estimation methods were assessed by Bland-Altman plots. The Spearman rank correlation test was used to study the correlations between K_err /D_err and D_anis /K_anis. RESULTS: The median (95% confidence interval) K_err and D_err were 5.1% (0.8%, 32.6%) and 1.7% (-2.5%, 5.3%), respectively. A significant relationship was observed between K_err  and D_anis (correlation coefficient R = 0.694, P < 0.0001), as well as between K_err and K_anis (R = 0.848, P < 0.0001).

CONCLUSIONS

In HN cancer, the fit of the DKI model to TW images can introduce bias and error in the estimation of K and D, which may be non-negligible for single lesions, and should hence be adopted with caution.

Structural Imaging in Atypical Parkinsonism

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

A 12-Week Cycling Training Regimen Improves Upper Limb Functions in People With Parkinson's Disease

Background: It has been proposed that physical exercise can help improve upper limb functions in Parkinson’s disease (PD) patients; yet evidence for this hypothesis is limited.

Objective: To assess the effects of aerobic exercise training (AET) on general upper limb functions in sedentary people with PD and healthy adults (HA).

Methods: Two groups, 19 PD patients (Hoehn & Yahr ≤ 2) and 20 HA, matched on age and sedentary level, followed a 3-month stationary bicycle AET regimen. We used the kinematic theory framework to characterize and quantify the different motor control commands involved in performing simple upper-limb movements as drawing lines. Repeated measures ANCOVA models were used to assess the effect of AET in each group, as well as the difference between groups following the training regimen.

Results: At baseline, PD individuals had a larger antagonist response, a longer elapsed time between the visual stimulus and the end of the movement, and a longer time of displacement of the stylus than the HA. Following the 12-week AET, PD participants showed significant decreases of the agonist and antagonist commands, as well as the antagonist response spread. A significant group ^∗ session interaction effect was observed for the agonist command and the response spread of the antagonist command, suggesting a significant change for these two parameters only in PD patients following the AET. Among the differences observed at baseline, only the difference for the time of movement remained after AET.

Conclusion: A 3-month AET has a significant positive impact on the capacity to draw lines in a more efficiency way, in PD patients, indicating an improvement in the upper limb motor function.

Validation of diffusion tensor imaging measures of nigrostriatal neurons in macaques

Objective

Interpretation of diffusion MRI in the living brain requires validation against gold standard histological measures. We compared diffusion values of the nigrostriatal tract to PET and histological results in non-human primates (NHPs) with varying degrees of unilateral nigrostriatal injury induced by MPTP, a toxin selective for dopaminergic neurons.

Methods

Sixteen NHPs had MRI and PET scans of three different presynaptic radioligands and blinded video-based motor ratings before and after unilateral carotid artery infusion of variable doses of MPTP. Diffusion measures of connections between midbrain and striatum were calculated. Then animals were euthanized to quantify striatal dopamine concentration, stereologic measures of striatal tyrosine hydroxylase (TH) immunostained fiber density and unbiased stereologic counts of TH stained nigral cells.

Results

Diffusion measures correlated with MPTP dose, nigral TH-positive cell bodies and striatal TH-positive fiber density but did not correlate with in vitro nigrostriatal terminal field measures or in vivo PET measures of striatal uptake of presynaptic markers. Once nigral TH cell count loss exceeded 50% the stereologic terminal field measures reached a near zero floor effect but the diffusion measures continued to correlate with nigral cell counts.

Conclusion

Diffusion measures in the nigrostriatal tract correlate with nigral dopamine neurons and striatal fiber density, but have the same relationship to terminal field measures as a previous report of striatal PET measures of presynaptic neurons. These diffusion measures have the potential to act as non-invasive index of the severity of nigrostriatal injury. Diffusion imaging of the nigrostriatal tract could potentially have diagnostic value in humans with Parkinson disease or related disorders.

Parkinson's Disease Diagnosis via Joint Learning From Multiple Modalities and Relations

Parkinson's disease (PD) is a neurodegenerative progressive disease that mainly affects the motor systems of patients. To slow this disease deterioration, early and accurate diagnosis of PD is an effective way, which alleviates mental and physical sufferings by clinical intervention. In this paper, we propose a joint regression and classification framework for PD diagnosis via magnetic resonance and diffusion tensor imaging data. Specifically, we devise a unified multitask feature selection model to explore multiple relationships among features, samples, and clinical scores. We regress four clinical variables of depression, sleep, olfaction, cognition scores, as well as perform the classification of PD disease from the multimodal data. The multitask model explores the relationships at the level of clinical scores, image features, and subjects, to select the most informative and diseased-related features for diagnosis. The proposed method is evaluated on the public Parkinson's progression markers initiative dataset. The extensive experimental results show that the multitask framework can effectively boost the performance of regression and classification and outperforms other state-of-the-art methods. The computerized predictions of clinical scores and label for PD diagnosis may offer quantitative reference for decision support as well.

Parkinson's Disease Diagnostic Observations (PADDO): study rationale and design of a prospective cohort study for early differentiation of parkinsonism

Background

Differentiation of Parkinson’s disease (PD) from the various types of atypical parkinsonism (AP) such as multiple system atrophy (MSA), progressive supranuclear palsy (PSP), dementia with Lewy bodies (DLB), corticobasal syndrome (CBS) and vascular parkinsonism (VP), can be challenging, especially early in the disease course when symptoms overlap. A major unmet need in the diagnostic workup of these disorders is a diagnostic tool that differentiates the various disorders, preferably in the earliest disease stages when the clinical presentation is similar. Many diagnostic tests have been evaluated, but their added value was studied mostly in retrospective case-control studies that included patients with a straightforward clinical diagnosis. Here, we describe the design of a prospective cohort study in patients with parkinsonism in an early disease stage who have an uncertain clinical diagnosis. Our aim is to evaluate the diagnostic accuracy of (1) detailed clinical examination by a movement disorder specialist, (2) magnetic resonance imaging (MRI) techniques and (3) cerebrospinal fluid (CSF) biomarkers.

Methods/design

Patients with parkinsonism with an uncertain clinical diagnosis and a disease course less than three years will be recruited. Patients will undergo extensive neurological examination, brain MRI including conventional and advanced sequences, and a lumbar puncture. The diagnosis (including level of certainty) will be defined by a movement disorders expert, neuroradiologist and neurochemist based on clinical data, MRI results and CSF results, respectively. The clinical diagnosis after three years’ follow-up will serve as the “gold standard” reference diagnosis, based on consensus criteria and as established by two movement disorder specialists (blinded to the test results). Diagnostic accuracy of individual instruments and added value of brain MRI and CSF analysis after evaluation by a movement disorder expert will be calculated, expressed as the change in percentage of individuals that are correctly diagnosed with PD or AP.

Discussion

This study will yield new insights into the diagnostic value of clinical evaluation by a movement disorder specialist, brain MRI and CSF analysis in discriminating PD from AP in early disease stages. The outcome has the potential to help clinicians in choosing the optimal diagnostic strategy for patients with an uncertain clinical diagnosis.

Trial registration

NCT01249768, registered November 26 2010.

Electronic supplementary material

The online version of this article (10.1186/s12883-018-1072-x) contains supplementary material, which is available to authorized users.

Principles of diffusion kurtosis imaging and its role in early diagnosis of neurodegenerative disorders

Pathology of neurodegenerative diseases can be correlated with intra-neuronal as well as extracellular changes which lead to neuronal degeneration. The central nervous system (CNS) is a complex structure comprising of many biological barriers. These microstructural barriers might be affected by a variety of pathological processes. Specifically, changes in the brain tissue's microstructure affect the diffusion of water which can be assessed non-invasively by diffusion weighted (DW) magnetic resonance imaging (MRI) techniques. Diffusion tensor imaging (DTI) is a diffusion MRI technique that considers diffusivity as a Gaussian process, i.e. does not account for any diffusion hindrance. However, environment of the brain tissues is characterized by a non-Gaussian diffusion. Therefore, diffusion kurtosis imaging (DKI) was developed as an extension of DTI method in order to quantify the non-Gaussian distribution of water diffusion. This technique represents a promising approach for early diagnosis of neurodegenerative diseases when the neurodegenerative process starts. Hence, the purpose of this article is to summarize the ongoing clinical and preclinical research on Parkinson's, Alzheimer's and Huntington diseases, using DKI and to discuss the role of this technique as an early stage biomarker of neurodegenerative conditions.

Clinical Application of Brain MRI in the Diagnostic Work-up of Parkinsonism

BACKGROUND

Differentiating Parkinson's disease and atypical parkinsonism on clinical parameters is challenging, especially in early disease courses. This is due to large overlap in symptoms and because the so called red flags, i.e. symptoms indicating atypical parkinsonism, have not (fully) developed. Brain MRI can aid to improve the accuracy and confidence about the diagnosis.

OBJECTIVE AND METHODS

In the current paper, we discuss when brain MRI should be performed in the diagnostic work-up of parkinsonism, our preferred brain MRI scanning protocol, and the diagnostic value of specific abnormalities.

RESULTS AND CONCLUSIONS

The main purpose of brain MRI is to assess cerebrovascular damage, and to exclude other possible - and sometimes treatable - causes of parkinsonism, such as normal pressure hydrocephalus. Furthermore, brain MRI can support the possible or probable diagnosis of a specific form of atypical parkinsonism.

Longitudinal Diffusion Tensor Imaging-Based Assessment of Tract Alterations: An Application to Amyotrophic Lateral Sclerosis

Objective: The potential of magnetic resonance imaging (MRI) as a technical biomarker for cerebral microstructural alterations in neurodegenerative diseases is under investigation. In this study, a framework for the longitudinal analysis of diffusion tensor imaging (DTI)-based mapping was applied to the assessment of predefined white matter tracts in amyotrophic lateral sclerosis (ALS), as an example for a rapid progressive neurodegenerative disease.

Methods: DTI was performed every 3 months in six patients with ALS (mean (M) = 7.7; range 3 to 15 scans) and in six controls (M = 3; range 2–5 scans) with the identical scanning protocol, resulting in a total of 65 longitudinal DTI datasets. Fractional anisotropy (FA), mean diffusivity (MD), axonal diffusivity (AD), radial diffusivity (RD), and the ratio AD/RD were studied to analyze alterations within the corticospinal tract (CST) which is a prominently affected tract structure in ALS and the tract correlating with Braak’s neuropathological stage 1. A correlation analysis was performed between progression rates based on DTI metrics and the revised ALS functional rating scale (ALS-FRS-R).

Results: Patients with ALS showed an FA and AD/RD decline along the CST, while DTI metrics of controls did not change in longitudinal DTI scans. The FA and AD/RD decrease progression correlated significantly with ALS-FRS-R decrease progression.

Conclusion: On the basis of the longitudinal assessment, DTI-based metrics can be considered as a possible noninvasive follow-up marker for disease progression in neurodegeneration. This finding was demonstrated here for ALS as a fast progressing neurodegenerative disease.

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.

Magnetic resonance imaging for the diagnosis of Parkinson's disease

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

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.

Differential diagnosis of parkinsonism by a combined use of diffusion kurtosis imaging and quantitative susceptibility mapping

PURPOSE

We investigated whether diffusion kurtosis imaging (DKI) and quantitative susceptibility mapping (QSM) could detect pathological changes that occur in Parkinson's disease (PD), multiple system atrophy with predominant parkinsonism (MSA-P) or predominant cerebellar ataxia (MSA-C), and progressive supranuclear palsy syndrome (PSPS) and thus be used for differential diagnosis that is often difficult.

METHODS

Seventy patients (41 with PD, 6 with MSA-P, 7 with MSA-C, 16 with PSPS) and 20 healthy controls were examined using a 3.0 T MRI scanner. From DKI and QSM data, we automatically obtained mean kurtosis (MK), fractional anisotropy (FA), and mean diffusivity (MD) values of the midbrain tegmentum (MBT), pontine crossing tract (PCT), and superior/middle cerebellar peduncles (CPs), which were used to calculate diffusion MBT/PCT ratios (dMPRs) and diffusion superior/middle CP ratios (dCPRs), as well as MS (magnetic susceptibility) values of the anterior/posterior putamen (PUa and PUp) and globus pallidus (GP).

RESULTS

dMPRs of MK were significantly decreased in PSPS and increased in MSA-C compared with the other groups, while dCPRs of MK showed significant differences only between MSA-C and PD, PSPS, or control. MS values were significantly increased in the PUp of MSA-P and in the PUa and GP of PSPS compared with those in PD. The combined use of MK-dMPR and MS-PUp showed sensitivities of 83-100% and specificities of 81-100% for discriminating among the disease groups, respectively.

CONCLUSION

A quantitative assessment using DKI and QSM analyses, particularly MK-dMPR and MS-PUp values, can readily identify patients with parkinsonism.

Structural Brain Connectome and Cognitive Impairment in Parkinson Disease

Purpose To investigate the structural brain connectome in patients with Parkinson disease (PD) and mild cognitive impairment (MCI) and in patients with PD without MCI. Materials and Methods This prospective study was approved by the local ethics committees, and written informed consent was obtained from all subjects prior to enrollment. The individual structural brain connectome of 170 patients with PD (54 with MCI, 116 without MCI) and 41 healthy control subjects was obtained by using deterministic diffusion-tensor tractography. A network-based statistic was used to assess structural connectivity differences among groups. Results Patients with PD and MCI had global network alterations when compared with both control subjects and patients with PD without MCI (range, P = .004 to P = .048). Relative to control subjects, patients with PD and MCI had a large basal ganglia and frontoparietal network with decreased fractional anisotropy (FA) in the right hemisphere and a subnetwork with increased mean diffusivity (MD) involving similar regions bilaterally (P < .01). When compared with patients with PD without MCI, those with PD and MCI had a network with decreased FA, including basal ganglia and frontotemporoparietal regions bilaterally (P < .05). Similar findings were obtained by adjusting for motor disability (P < .05, permutation-corrected P = .06). At P < .01, patients with PD and MCI did not show network alterations relative to patients with PD without MCI. Network FA and MD values were used to differentiate patients with PD and MCI from healthy control subjects and patients with PD without MCI with fair to good accuracy (cross-validated area under the receiver operating characteristic curve [principal + secondary connected components] range, 0.75-0.85). Conclusion A disruption of structural connections between brain areas forming a network contributes to determine an altered information integration and organization and thus cognitive deficits in patients with PD. These results provide novel information concerning the structural substrates of MCI in patients with PD and may offer markers that can be used to differentiate between patients with PD and MCI and patients with PD without MCI. ^© RSNA, 2016 Online supplemental material is available for this article.

Increased fractional anisotropy in the motor tracts of Parkinson's disease suggests compensatory neuroplasticity or selective neurodegeneration

OBJECTIVE

To determine the differences in motor pathways and selected non-motor pathways of the basal ganglia in Parkinson's disease (PD) patients compared to healthy controls (HCs).

METHODS

We analysed diffusion weighted imaging data of 24 PD patients and 26 HCs. We performed deterministic tractography analysis using the spherical deconvolution-based damped Richardson-Lucy algorithm and subcortical volume analysis.

RESULTS

We found significantly increased fractional anisotropy (FA) in the motor pathways of PD patients: the bilateral corticospinal tract (right; corrected p = 0.0003, left; corrected p = 0.03), bilateral thalamus-motor cortex tract (right; corrected p = 0.02, left; corrected p = 0.004) and the right supplementary area-putamen tract (corrected p = 0.001). We also found significantly decreased FA in the right uncinate fasiculus (corrected p = 0.01) and no differences of FA in the bilateral supero-lateral medial forebrain bundles (p > 0.05) of PD patients compared to HCs. There were no subcortical volume differences (p > 0.05) between the PD patients and HCs.

CONCLUSION

These results can inform biological models of neurodegeneration and neuroplasticity in PD. We suggest that increased FA values in the motor tracts in PD may reflect compensatory reorganization of neural circuits indicative of adaptive or extended neuroplasticity.

KEY POINTS

• Fractional anisotropy was higher in motor pathways of PD patients compared to healthy controls. • Fractional anisotropy was lower in the uncinate fasciculus of PD patients compared to healthy controls. • Increased fractional anisotropy could suggest adaptive neuroplasticity or selective neurodegeneration.

Magnetic resonance imaging as a potential biomarker for Parkinson's disease

Although a magnetic resonance imaging (MRI) biomarker for Parkinson's disease (PD) remains an unfulfilled objective, there have been numerous developments in MRI methodology and some of these have shown promise for PD. With funding from the National Institutes of Health and the Michael J Fox Foundation there will be further validation of structural, diffusion-based, and iron-focused MRI methods as possible biomarkers for PD. In this review, these methods and other strategies such as neurochemical and metabolic MRI have been covered. One of the challenges in establishing a biomarker is in the selection of individuals as PD is a heterogeneous disease with varying clinical features, different etiologies, and a range of pathologic changes. Additionally, longitudinal studies are needed of individuals with clinically diagnosed PD and cohorts of individuals who are at great risk for developing PD to validate methods. Ultimately an MRI biomarker will be useful in the diagnosis of PD, predicting the course of PD, providing a means to track its course, and provide an approach to select and monitor treatments.

Nigrosome-1 on Susceptibility Weighted Imaging to Differentiate Parkinson's Disease From Atypical Parkinsonism: An In Vivo and Ex Vivo Pilot Study

BACKGROUND

Previous case-control studies have suggested that the absence of a swallow-tail appearance in the substantia nigra on high-resolution SWI, representing nigrosome-1, has high accuracy to identify Parkinson's disease (PD). The first goal of our study was to evaluate nigrosome-1 ex vivo using optimized high-resolution susceptibility sensitive MRI. Our second goal was to evaluate its diagnostic value in vivo using a clinical 3T SWI sequence to differentiate between PD and atypical parkinsonism (AP) in a cohort of patients with early-stage parkinsonism.

MATERIAL/METHODS

Case-control pilot study to evaluate nigrosome-1 ex vivo (2 PD, 2 controls), using high-resolution susceptibility sensitive sequences at 11.7 T MRI. Next, evaluation of nigrosome-1 in vivo using a clinical 3 T SWI sequence in a prospective cohort of 60 patients with early-stage parkinsonism (39 PD, 21 AP). Moreover, 12 control subjects were scanned. The bilateral substantia nigra was evaluated by two neuroradiologists for the presence, absence or indecisive presence of nigrosome-1. The discriminative power was evaluated by Receiver-Operating Characteristic.

RESULTS

We identified nigrosome-1 in ex vivo control subjects. Nigrosome-1 was not identified in the ex vivo PD cases. In our prospective clinical cohort study, the AUC for the swallow-tail sign to discriminate between PD and AP was 0.56 (0.41-0.71) for reader 1 and 0.68 (0.55-0.82) for reader 2.

CONCLUSIONS

The diagnostic accuracy of the swallow-tail sign was marginal to discriminate between PD and AP using our clinical 3 T SWI sequence.

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 tensor imaging of the extracorticospinal network in the brains of patients with Wilson disease

OBJECTIVE

To evaluate damage to the extracorticospinal tract in Wilson disease (WD) patients using diffusion tensor imaging (DTI).

METHODS

70 patients with WD, including 50 with cerebral type and 20 with hepatic type, and 20 age-matched healthy controls were enrolled. Neurological symptoms were scored using the modified Young Scale. Patients with cerebral type WD were divided into four subgroups: those with (1) hypokinesia, (2) parkinsonism, (3) mouth and throat dystonia, and (4) psychiatric symptoms. All study subjects underwent DTI of the brain. Five regions of interest (ROIs) were chosen. Fractional anisotropy (FA) and fiber volumes between ROIs were determined, and the relationships between DTI metrics and clinical status were evaluated.

RESULTS

FA values and fiber volumes between subcortical nuclei were lower in WD patients. Fiber volumes between the putamen (PU) and the globus pallidus (GP), substantia nigra (SN), and thalamus (TH); between the head of the caudate nucleus (CA) and the GP and TH; and between the TH and cerebellum were lower in group 1 than in the other groups of WD patients. Fiber volumes between the GP and the SN and TH were lower in group 2, and fiber volumes between the SN and TH were lower in group 3. DTI metrics differed between patients with the cerebral and hepatic types of WD.

CONCLUSIONS

DTI can reconstruct the network of the extracorticospinal tract. Fiber projection between subcortical nuclei was abnormal in WD patients. Damage to fiber connections may correlate with neurological symptoms in WD patients.

Substantia Nigra Hyperechogenicity: Validation of Transcranial Sonography for Parkinson Disease Diagnosis in a Large Estonian Cohort

OBJECTIVES

Substantia nigra hyperechogenicity is a promising biomarker for Parkinson disease (PD). Substantia nigra hyperechogenicity has previously been established as a useful diagnostic criterion in several European and Asian patient cohorts. However, diagnostic cutoff values for substantia nigra hyperechogenicity remain unknown for most patient populations. This study validated the diagnostic accuracy of substantia nigra hyperechogenicity in a large cohort of patients with PD in Estonia.

METHODS

The study included 300 patients with PD from Estonia, representing 10% of the national PD patient population, and 200 healthy control participants. To define the optimal cutoff value in the PD cohort, data from a single assessment versus repetitive assessments by transcranial sonography were compared. With the use of 3 repetitive assessments, the diagnostic accuracy of the data was measured. In addition, calculations for percentile values were used to define substantia nigra hyperechogenicity among controls.

RESULTS

Our data showed that the multiassessment approach yielded higher diagnostic accuracy than a single assessment (P = .021). The highest diagnostic accuracy was achieved by using the measurement mean to define substantia nigra hyperechogenicity, which was 0.23 cm(2) (sensitivity, 88.7%; specificity, 92.2%), whereas single measurements detected PD with higher sensitivity (sensitivity, 93.2%; specificity, 85.1%). No significant difference was found between mean and median measurements (P= .18).

CONCLUSIONS

This study indicates the diagnostic merit of transcranial sonography in PD diagnosis in an additional population and demonstrates that transcranial sonography of the substantia nigra is a relevant and useful diagnostic tool for patients with PD.

Differentiation among parkinsonisms using quantitative diffusion kurtosis imaging

Differential diagnoses among Parkinson's disease (PD), multiple system atrophy (MSA), and progressive supranuclear palsy syndrome (PSPS) are often difficult. Hence, we investigated whether diffusion kurtosis imaging (DKI) could detect pathological changes that occur in these disorders and be used to differentiate between such patients. Fourteen patients (five with PD, four MSA, and five PSPS) and six healthy controls were examined using a 1.5-T scanner. Mean kurtosis (MK), fractional anisotropy, and mean diffusivity maps were generated, and these values of the midbrain tegmentum (MBT) and pontine crossing tract (PCT), as well as MBT/PCT ratios, were obtained. We found no significant differences in MBT and PCT values on DKI maps among the groups. In contrast, MBT/PCT ratios from MK maps were significantly increased in the MSA group and decreased in the PSPS group compared with the other groups. MBT/PCT ratios from mean diffusivity maps showed a significant increase in the PSPS group. Therefore, quantitative DKI analyses, particularly the MBT/PCT ratio from MK maps, can differentiate patients with parkinsonisms.

Cerebral small vessel disease and incident parkinsonism: The RUN DMC study

OBJECTIVE

To investigate the relation between baseline cerebral small vessel disease (SVD) and the risk of incident parkinsonism using different MRI and diffusion tensor imaging (DTI) measures.

METHODS

In the Radboud University Nijmegen Diffusion Tensor and Magnetic Resonance Cohort (RUN DMC) study, a prospective cohort study, 503 elderly participants with SVD and without parkinsonism were included in 2006. During follow-up (2011-2012), parkinsonism was diagnosed according to UK Brain Bank criteria. Cox regression analysis was used to investigate the association between baseline imaging measures and incident all-cause parkinsonism and vascular parkinsonism (VP). Tract-based spatial statistics analysis was used to identify differences in baseline DTI measures of white matter (WM) tracts between participants with VP and without parkinsonism.

RESULTS

Follow-up was available from 501 participants (mean age 65.6 years; mean follow-up duration 5.2 years). Parkinsonism developed in 20 participants; 15 were diagnosed with VP. The 5-year risk of (any) parkinsonism was increased for those with a high white matter hyperintensity (WMH) volume (hazard ratio [HR] 1.8 per SD increase, 95% confidence interval [CI] 1.3-2.4) and a high number of lacunes (HR 1.4 per number increase, 95% CI 1.1-1.8) at baseline. For VP, this risk was also increased by the presence of microbleeds (HR 5.7, 95% CI 1.9-16.8) and a low gray matter volume (HR 0.4 per SD increase, 95% CI 0.2-0.8). Lower fractional anisotropy values in bifrontal WM tracts involved in movement control were observed in participants with VP compared to participants without parkinsonism.

CONCLUSIONS

SVD at baseline, especially a high WMH volume and a high number of lacunes, is associated with incident parkinsonism. Our findings favor a role of SVD in the etiology of parkinsonism.

Conventional 3T brain MRI and diffusion tensor imaging in the diagnostic workup of early stage parkinsonism

Introduction

The aim of this study is to evaluate whether the diagnostic accuracy of 3 T brain MRI is improved by region of interest (ROI) measures of diffusion tensor imaging (DTI), to differentiate between neurodegenerative atypical parkinsonism (AP) and Parkinson’s disease (PD) in early stage parkinsonism.

Methods

We performed a prospective observational cohort study of 60 patients presenting with early stage parkinsonism and initial uncertain diagnosis. At baseline, patients underwent a 3 T brain MRI including DTI. After clinical follow-up (mean 28.3 months), diagnoses could be made in 49 patients (30 PD and 19 AP). Conventional brain MRI was evaluated for regions of atrophy and signal intensity changes. Tract-based spatial statistics and ROI analyses of DTI were performed to analyze group differences in mean diffusivity (MD) and fractional anisotropy (FA), and diagnostic thresholds were determined. Diagnostic accuracy of conventional brain MRI and DTI was assessed with the receiver operating characteristic (ROC).

Results

Significantly higher MD of the centrum semiovale, body corpus callosum, putamen, external capsule, midbrain, superior cerebellum, and superior cerebellar peduncles was found in AP. Significantly increased MD of the putamen was found in multiple system atrophy–parkinsonian form (MSA-P) and increased MD in the midbrain and superior cerebellar peduncles in progressive supranuclear palsy (PSP). The diagnostic accuracy of brain MRI to identify AP as a group was not improved by ROI measures of MD, though the diagnostic accuracy to identify MSA-P was slightly increased (AUC 0.82 to 0.85).

Conclusion

The diagnostic accuracy of brain MRI to identify AP as a group was not improved by the current analysis approach to DTI, though DTI measures could be of added value to identify AP subgroups.

Dorsolateral nigral hyperintensity on 3.0T susceptibility-weighted imaging in neurodegenerative Parkinsonism

BACKGROUND

Absence of a hyperintense, ovoid area within the dorsolateral border of the otherwise hypointense pars compacta of the substantia nigra (referred to as dorsolateral nigral hyperintensity) on iron-sensitive high-field magnetic resonance imaging sequences seems to be a typical finding for patients with Parkinson's disease (PD).

OBJECTIVE

This study was undertaken to evaluate the diagnostic value of the dorsolateral nigral hyperintensity in a cohort of patients with neurodegenerative parkinsonism including PD, multiple system atrophy (MSA), and progressive supranuclear palsy (PSP) as well as healthy controls using high-field susceptibility-weighted imaging (SWI) at 3.0 Tesla (T).

METHODS

Absence of dorsolateral nigral hyperintensity was assessed on visual inspection of anonymized 3.0T SWI scans in a case-control study including 148 patients with neurodegenerative parkinsonism (PD: n = 104; MSA: n = 22; PSP: n = 22) and 42 healthy controls.

RESULTS

Dorsolateral nigral hyperintensity was absent unilaterally in all patients with MSA or PSP, in 83 of 90 patients with PD, but only in one of the healthy controls resulting in an overall correct classification of 95.2% in discriminating neurodegenerative parkinsonism from controls in the per-protocol analysis. Overall correct classification was 93.2% in the intent-to-diagnose analysis, including also SWI scans with poor quality (12.1% of all scans) for nigral evaluation.

CONCLUSION

Visual assessment of dorsolateral nigral hyperintensity on high-field SWI scans may serve as a new simple diagnostic imaging marker for neurodegenerative parkinsonian disorders.

The 'swallow tail' appearance of the healthy nigrosome - a new accurate test of Parkinson's disease: a case-control and retrospective cross-sectional MRI study at 3T

There is no well-established in vivo marker of nigral degeneration in Parkinson's disease (PD). An ideal imaging marker would directly mirror the loss of substantia nigra dopaminergic neurones, which is most prominent in sub-regions called nigrosomes. High-resolution, iron-sensitive, magnetic resonance imaging (MRI) at 7T allows direct nigrosome-1 visualisation in healthy people but not in PD. Here, we investigated the feasibility of nigrosome-1 detection using 3T - susceptibility-weighted (SWI) MRI and the diagnostic accuracy that can be achieved for diagnosing PD in a clinical population. 114 high-resolution 3T - SWI-scans were reviewed consisting of a prospective case-control study in 19 subjects (10 PD, 9 controls) and a retrospective cross-sectional study in 95 consecutive patients undergoing routine clinical SWI-scans (>50 years, 9 PD, 81 non-PD, 5 non-diagnostic studies excluded). Two raters independently classified subjects into PD and non-PD according to absence or presence of nigrosome-1, followed by consensus reading. Diagnostic accuracy was assessed against clinical diagnosis as gold standard. Absolute inter- and intra-rater agreement was ≥94% (kappa≥0.82, p<0.001). In the prospective study 8/9 control and 8/10 PD; and in the retrospective study 77/81 non-PD and all 9 PD subjects were correctly classified. Diagnostic accuracy of the retrospective cohort was: sensitivity 100%, specificity 95%, NPV 1, PPV 0.69 and accuracy 96% which dropped to 91% when including non-diagnostic scans ('intent to diagnose'). The healthy nigrosome-1 can be readily depicted on high-resolution 3T - SWI giving rise to a 'swallow tail' appearance of the dorsolateral substantia nigra, and this feature is lost in PD. Visual radiological assessment yielded a high diagnostic accuracy for PD vs. an unselected clinical control population. Assessing the substantia nigra on SWI for the typical 'swallow tail' appearance has potential to become a new and easy applicable 3T MRI diagnostic tool for nigral degeneration in PD.

Towards translational therapies for multiple system atrophy

Multiple system atrophy (MSA) is a fatal adult-onset neurodegenerative disorder of uncertain etiopathogenesis manifesting with autonomic failure, parkinsonism, and ataxia in any combination. The underlying neuropathology affects central autonomic, striatonigral and olivopontocerebellar pathways and it is associated with distinctive glial cytoplasmic inclusions (GCIs, Papp-Lantos bodies) that contain aggregates of α-synuclein. Current treatment options are very limited and mainly focused on symptomatic relief, whereas disease modifying options are lacking. Despite extensive testing, no neuroprotective drug treatment has been identified up to now; however, a neurorestorative approach utilizing autologous mesenchymal stem cells has shown remarkable beneficial effects in the cerebellar variant of MSA. Here, we review the progress made over the last decade in defining pathogenic targets in MSA and summarize insights gained from candidate disease-modifying interventions that have utilized a variety of well-established preclinical MSA models. We also discuss the current limitations that our field faces and suggest solutions for possible approaches in cause-directed therapies of MSA.