Progression marker of Parkinson's disease: a 4-year multi-site imaging study

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

INTRODUCTION

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

METHODS

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

RESULTS AND DISCUSSIONS

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

CONCLUSION

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

The Future of Brain Imaging in Parkinson's Disease

Parkinson’s disease (PD) is a progressive neurodegenerative disorder that is associated with distinct abnormalities in brain function and structure. Here we discuss how future developments in functional, structural and nuclear brain imaging may help us to better understand, diagnose, and potentially even treat PD. These new horizons may be reached by developing tracers that specifically bind to alpha synuclein, by looking into different places in the body (such as the gut) or in smaller cerebral nuclei (with improved spatial resolution), and by developing new approaches for quantifying and interpreting altered dynamics in large-scale brain networks.

Development and Validation of the Automated Imaging Differentiation in Parkinsonism (AID-P): A Multi-Site Machine Learning Study

Background

There is a critical need to develop valid, non-invasive biomarkers for Parkinsonian syndromes. The current 17-site, international study assesses whether non-invasive diffusion MRI (dMRI) can distinguish between Parkinsonian syndromes.

Methods

We used dMRI from 1002 subjects, along with the Movement Disorders Society Unified Parkinson's Disease Rating Scale part III (MDS-UPDRS III), to develop and validate disease-specific machine learning comparisons using 60 template regions and tracts of interest in Montreal Neurological Institute (MNI) space between Parkinson's disease (PD) and Atypical Parkinsonism (multiple system atrophy - MSA, progressive supranuclear palsy - PSP), as well as between MSA and PSP. For each comparison, models were developed on a training/validation cohort and evaluated in a test cohort by quantifying the area under the curve (AUC) of receiving operating characteristic (ROC) curves.

Findings

In the test cohort for both disease-specific comparisons, AUCs were high in the dMRI + MDS-UPDRS (PD vs. Atypical Parkinsonism: 0·962; MSA vs. PSP: 0·897) and dMRI Only (PD vs. Atypical Parkinsonism: 0·955; MSA vs. PSP: 0·926) models, whereas the MDS-UPDRS III Only models had significantly lower AUCs (PD vs. Atypical Parkinsonism: 0·775; MSA vs. PSP: 0·582).

Interpretations

This study provides an objective, validated, and generalizable imaging approach to distinguish different forms of Parkinsonian syndromes using multi-site dMRI cohorts. The dMRI method does not involve radioactive tracers, is completely automated, and can be collected in less than 12 minutes across 3T scanners worldwide. The use of this test could thus positively impact the clinical care of patients with Parkinson's disease and Parkinsonism as well as reduce the number of misdiagnosed cases in clinical trials.

Free-water imaging of the hippocampus is a sensitive marker of Alzheimer's disease

Validating sensitive markers of hippocampal degeneration is fundamental for understanding neurodegenerative conditions such as Alzheimer's disease. In this paper, we test the hypothesis that free-water in the hippocampus will be more sensitive to early stages of cognitive decline than hippocampal volume, and that free-water in hippocampus will increase across distinct clinical stages of Alzheimer's disease. We examined two separate cohorts (N = 126; N = 112) of cognitively normal controls, early and late mild cognitive impairment (MCI), and Alzheimer's disease. Demographic, clinical, diffusion-weighted and T1-weighted imaging, and positron emission tomography (PET) imaging were assessed. Results indicated elevated hippocampal free-water in early MCI individuals compared to controls across both cohorts. In contrast, there was no difference in volume of these regions between controls and early MCI. ADNI free-water values in the hippocampus was associated with low CSF AB_1–42 levels and high global amyloid PET values. Free-water imaging of the hippocampus can serve as an early stage marker for AD and provides a complementary measure of AD neurodegeneration using non-invasive imaging.

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Free-water imaging is a useful technique for detecting neurodegeneration

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Increased free-water in the left hippocampus for early MCI compared with cognitive normal controls across multiple sites

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We propose that changes in free-water may indicate hippocampal degeneration in AD

Assessment of a prognostic MRI biomarker in early de novo Parkinson's disease

BACKGROUND

Commonly used neuroimaging biomarkers in Parkinson's disease (PD) are useful for diagnosis but poor at predicting outcomes. We explored whether an atrophy pattern from whole-brain structural MRI, measured in the drug-naïve early stage, could predict PD prognosis.

METHODS

362 de novo PD patients with T1-weighted MRI (n = 222 for the main analysis, 140 for the validation analysis) were recruited from the Parkinson's Progression Markers Initiative (PPMI). We investigated a previously identified PD-specific network atrophy pattern as a potential biomarker of disease severity and prognosis. Progression trajectories of motor function (MDS-UPDRS-part III), cognition (Montreal Cognitive Assessment (MoCA)), and a global composite outcome measure were compared between atrophy tertiles using mixed effect models. The prognostic value of the MRI atrophy measure was compared with 123I ioflupane single photon emission computed tomography, the postural-instability-gait-disturbance score, and cerebrospinal fluid markers.

FINDINGS

After 4.5 years follow-up, PD-specific atrophy network score at baseline significantly predicted change in UPDRS-part III (r = -0.197, p = .003), MoCA (r = 0.253, p = .0002) and global composite outcome (r = -0.249, p = .0002). Compared with the 3rd tertile (i.e. least atrophy), the tertile with the highest baseline atrophy (i.e. the 1st tertile) had a 3-point annual faster progression in UPDRS-part III (p = .012), faster worsening of posture-instability gait scores (+0.21 further annual increase, p < .0001), faster decline in MoCA (-0.74 further annual decline in MoCA, p = .0372) and a + 0.38 (p = .0029) faster annual increase in the global composite z-score. All findings were replicated in a validation analysis using 1.5T MRI. Receiver operating characteristic analysis confirmed the superiority of the MRI biomarker, although it had modest AUC values (0.63). By comparison, the other biomarkers were limited in their ability to predict prognosis either in the main or validation analysis.

INTERPRETATION

A PD-specific network atrophy pattern predicts progression of motor, cognitive, and global outcome in PD, and is a better predictor of prognosis than any of the other tested biomarkers. Therefore, it has potential as a prognostic biomarker for clinical trials of early PD.

Neurite orientation dispersion and density imaging (NODDI) and free-water imaging in Parkinsonism

Neurite orientation dispersion and density imaging (NODDI) uses a three-compartment model to probe brain tissue microstructure, whereas free-water (FW) imaging models two-compartments. It is unknown if NODDI detects more disease-specific effects related to neurodegeneration in Parkinson's disease (PD) and atypical Parkinsonism. We acquired multi- and single-shell diffusion imaging at 3 Tesla across two sites. NODDI (using multi-shell; isotropic volume [Viso]; intracellular volume [Vic]; orientation dispersion [ODI]) and FW imaging (using single-shell; FW; free-water corrected fractional anisotropy [FAt]) were compared with 44 PD, 21 multiple system atrophy Parkinsonian variant (MSAp), 26 progressive supranuclear palsy (PSP), and 24 healthy control subjects in the basal ganglia, midbrain/thalamus, cerebellum, and corpus callosum. There was elevated Viso in posterior substantia nigra across Parkinsonisms, and Viso, Vic, and ODI were altered in MSAp and PSP in the striatum, globus pallidus, midbrain, thalamus, cerebellum, and corpus callosum relative to controls. The mean effect size across regions for Viso was 0.163, ODI 0.131, Vic 0.122, FW 0.359, and FAt 0.125, with extracellular compartments having the greatest effect size. A key question addressed was if these techniques discriminate PD and atypical Parkinsonism. Both NODDI (AUC: 0.945) and FW imaging (AUC: 0.969) had high accuracy, with no significant difference between models. This study provides new evidence that NODDI and FW imaging offer similar discriminability between PD and atypical Parkinsonism, and FW had higher effect sizes for detecting Parkinsonism within regions across the basal ganglia and cerebellum.

Convolutional neural network-based segmentation can help in assessing the substantia nigra in neuromelanin MRI

Purpose

This study aimed to evaluate the accuracy and diagnostic test performance of the U-net-based segmentation method in neuromelanin magnetic resonance imaging (NM-MRI) compared to the established manual segmentation method for Parkinson’s disease (PD) diagnosis.

Methods

NM-MRI datasets from two different 3T-scanners were used: a “principal dataset” with 122 participants and an “external validation dataset” with 24 participants, including 62 and 12 PD patients, respectively. Two radiologists performed SNpc manual segmentation. Inter-reader precision was determined using Dice coefficients. The U-net was trained with manual segmentation as ground truth and Dice coefficients used to measure accuracy. Training and validation steps were performed on the principal dataset using a 4-fold cross-validation method. We tested the U-net on the external validation dataset. SNpc hyperintense areas were estimated from U-net and manual segmentation masks, replicating a previously validated thresholding method, and their diagnostic test performances for PD determined.

Results

For SNpc segmentation, U-net accuracy was comparable to inter-reader precision in the principal dataset (Dice coefficient: U-net, 0.83 ± 0.04; inter-reader, 0.83 ± 0.04), but lower in external validation dataset (Dice coefficient: U-net, 079 ± 0.04; inter-reader, 0.85 ± 0.03). Diagnostic test performances for PD were comparable between U-net and manual segmentation methods in both principal (area under the receiver operating characteristic curve: U-net, 0.950; manual, 0.948) and external (U-net, 0.944; manual, 0.931) datasets.

Conclusion

U-net segmentation provided relatively high accuracy in the evaluation of the SNpc in NM-MRI and yielded diagnostic performance comparable to that of the established manual method.

Electronic supplementary material

The online version of this article (10.1007/s00234-019-02279-w) contains supplementary material, which is available to authorized users.

Ventral posterior substantia nigra iron increases over 3 years in Parkinson's disease

BACKGROUND

Parkinson's disease (PD) is characterized in part by the progressive accumulation of iron within the substantia nigra (SN); however, its spatial and temporal dynamics remain relatively poorly understood.

OBJECTIVES

The objective of this study was to investigate spatial patterns and temporal evolution of SN iron accumulation in PD.

METHODS

A total of 18 PD patients (mean disease duration = 6.2 years) receiving dopaminergic therapy and 16 healthy controls were scanned with 3T MRI at baseline and 3 years later using quantitative susceptibility mapping, an indirect marker of iron content. Iron was assessed separately in the posterior SN and anterior SN at the ventral and dorsal levels of the SN. The results were corrected for the false discovery rate.

RESULTS

A significant group effect was found for the ventral posterior SN (P < .001) and anterior SN (P = .042) quantitative susceptibility mapping as well as significant group x time interaction effects (P = .02 and P = .043, respectively). In addition, a significant intragroup change during 3 years of follow-up was found only in the ventral posterior SN of PD (P = .012), but not healthy controls. No significant effects were detected for any dorsal SN measures. No associations were identified with clinical measures.

CONCLUSIONS

We found both cross-sectional and longitudinal SN iron changes to be confined to its more ventral location in PD. Because pathology studies also show the ventral SN to degenerate early and to the greatest extent in PD, the assessment of iron levels by quantitative susceptibility mapping in this area may potentially represent a disease progression biomarker in PD. © 2019 International Parkinson and Movement Disorder Society.

Substantia nigra locations of iron-content, free-water and mean diffusivity abnormalities in moderate stage Parkinson's disease

BACKGROUND

Prior work demonstrated that free water in the posterior substantia nigra (SN) was elevated in Parkinson's disease (PD) compared to healthy controls (HC) across single- and multi-site cohorts, and increased over 1 year in Parkinson's disease but not in relation with the iron deposition in SN with the relaxometry T2*.

OBJECTIVES

The main objective of the present study was to evaluate changes in the SN using relaxometry T2*, single- and bi-tensor models of diffusion magnetic resonance imaging between PD patients and HC.

METHODS

39 subjects participated in this study, including 21 HCs and 18 PD patients, in moderate stage (7 years), whose data were collected at two visits separated by approximately 2 years, underwent 3-T MRI comprising: T2*-weighted, T1-weighted and diffusion tensor imaging (DTI) scans. Relaxometry T2*, bi-tensor free water (FW), free-water-corrected fractional anisotropy, free-water-corrected mean diffusivity, single-tensor fractional anisotropy, and single-tensor mean diffusivity were computed for the anterior, posterior and whole substantia nigra.

RESULTS

In the anterior SN, relaxometry T2* values were greater for PD patients than HCs. In the posterior SN, free water, single- and bi-tensor mean diffusivity values were greater for PD patients than HCs. No significant change were found over time in FW/MD/R2* maps for PD patients with moderate stage.

CONCLUSION

The specific increase of R2* in the anterior SN concomitant with the specific increase of FW in posterior SN suggests a complementary aspect of the two parameters and, perhaps, different underlying pathophysiological processes.

Targeting kinases in Parkinson's disease: A mechanism shared by LRRK2, neurotrophins, exenatide, urate, nilotinib and lithium

Several kinases have been implicated in the pathogenesis of Parkinson's disease (PD), most notably leucine-rich repeat kinase 2 (LRRK2), as LRRK2 mutations are the most common genetic cause of a late-onset parkinsonism that is clinically indistinguishable from sporadic PD. More recently, several other kinases have emerged as promising disease-modifying targets in PD based on both preclinical studies and clinical reports on exenatide, the urate precursor inosine, nilotinib and lithium use in PD patients. These kinases include protein kinase B (Akt), glycogen synthase kinases-3β and -3α (GSK-3β and GSK-3α), c-Abelson kinase (c-Abl) and cyclin-dependent kinase 5 (cdk5). Activities of each of these kinases are involved either directly or indirectly in phosphorylating tau or increasing α-synuclein levels, intracellular proteins whose toxic oligomeric forms are strongly implicated in the pathogenesis of PD. GSK-3β, GSK-3α and cdk5 are the principle kinases involved in phosphorylating tau at sites critical for the formation of tau oligomers. Exenatide analogues, urate, nilotinib and lithium have been shown to affect one or more of the above kinases, actions that can decrease the formation and increase the clearance of intraneuronal phosphorylated tau and α-synuclein. Here we review the current preclinical and clinical evidence supporting kinase-targeting agents as potential disease-modifying therapies for PD patients enriched with these therapeutic targets and incorporate LRRK2 physiology into this novel model.

Alpha-Synuclein Pathology and the Role of the Microbiota in Parkinson's Disease

There is a principle in science, known as Occam’s razor, that says the correct solution is usually the one with the simplest explanation. The microbiota-gut-brain axis, an interdependent series of communication loops between the enteric nervous system (ENS), the microbiota, the gut, and the brain, offers important insight into how changes in our gut affect distant organs like our brains. The inherent complexity of this axis with the crosstalk between the immune system, inflammatory states, and the thousands of bacteria, viral, and fungal species that together make up the microbiota make studying the interactions that govern this axis difficult and far from parsimonious. It is becoming increasingly clear that the microbiota is integral to this axis. Disruption of the healthy flora, a phenomenon collectively referred to as dysbiosis, has been implicated as a driver for several diseases such as irritable bowel syndrome, rheumatoid arthritis, obesity, diabetes, liver disease, and neurological disorders such as depression, anxiety, and Parkinson’s disease (PD). Teasing apart these complex interactions as they pertain to PD is critical for our understanding of this debilitating disease, but more importantly, for the development of future treatments. So far, treatments have been unable to stop this neurodegenerative disease, succeeding only in briefly dampening symptoms and buying patients time before the inevitable loss of function ensues. Given that the 10 years prognosis for death or life-limiting disability with someone diagnosed with PD is upwards of 80%, there is a desperate need for curative treatments that go beyond symptom management. If PD does begin in the periphery with bidirectional communication between the microbiota and the immune system, as recent literature suggests, there is an exciting possibility that progression could be stopped before it reaches the brain. This systematic review assesses the current literature surrounding the role of the microbiota in the pathogenesis of alpha-synucleinopathies and explores the hypothesis that alpha-synuclein folding is modulated by the microbiota. Furthermore, we discuss how changes in the gut environment can lead to pathology and outline the implications that advances in understanding the interactions between host and microbiota will have on future research and the development of potential biomarkers.

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.

Neurite density is reduced in the presymptomatic phase of C9orf72 disease

OBJECTIVE

To assess the added value of neurite orientation dispersion and density imaging (NODDI) compared with conventional diffusion tensor imaging (DTI) and anatomical MRI to detect changes in presymptomatic carriers of chromosome 9 open reading frame 72 (C9orf72) mutation.

METHODS

The PREV-DEMALS (Predict to Prevent Frontotemporal Lobar Degeneration and Amyotrophic Lateral Sclerosis) study is a prospective, multicentre, observational study of first-degree relatives of individuals carrying the C9orf72 mutation. Sixty-seven participants (38 presymptomatic C9orf72 mutation carriers (C9+) and 29 non-carriers (C9-)) were included in the present cross-sectional study. Each participant underwent one single-shell, multishell diffusion MRI and three-dimensional T1-weighted MRI. Volumetric measures, DTI and NODDI metrics were calculated within regions of interest. Differences in white matter integrity, grey matter volume and free water fraction between C9+ and C9- individuals were assessed using linear mixed-effects models.

RESULTS

Compared with C9-, C9+ demonstrated white matter abnormalities in 10 tracts with neurite density index and only 5 tracts with DTI metrics. Effect size was significantly higher for the neurite density index than for DTI metrics in two tracts. No tract had a significantly higher effect size for DTI than for NODDI. For grey matter cortical analysis, free water fraction was increased in 13 regions in C9+, whereas 11 regions displayed volumetric atrophy.

CONCLUSIONS

NODDI provides higher sensitivity and greater tissue specificity compared with conventional DTI for identifying white matter abnormalities in the presymptomatic C9orf72 carriers. Our results encourage the use of neurite density as a biomarker of the preclinical phase.

TRIAL REGISTRATION NUMBER

NCT02590276.

Reproducible detection of nigral iron deposition in 2 Parkinson's disease cohorts

BACKGROUND

Previous studies investigating nigral iron accumulation used T2 or T2 *-weighted contrasts to define the regions of interest (ROIs) in the substantia nigra with mixed results. Because these contrasts are not sensitive to neuromelanin, ROIs may have inadvertently missed the SNpc. An approach sensitive to neuromelanin should yield consistent results. We examine iron deposition in ROIs derived from neuromelanin-sensitive and T2 *-weighted contrasts, respectively.

METHODS

T1 -weighted and multiecho gradient echo imaging data were obtained in 2 cohorts. Multiecho gradient echo imaging data were analyzed using neuromelanin-sensitive SNpc ROIs as well as T2 *-weighted SNr ROIs.

RESULTS

When compared with controls, significantly larger R2 * values were seen in the SNpc of PD patients in both cohorts. Mean R2 * values in the SNr of PD patients showed no consistency, with 1 cohort showing a small, statistically significant increase, whereas the other cohort exhibited no statistical difference.

CONCLUSION

Mean R2 * in the SNpc defined by neuromelanin-sensitive MRI is significantly increased in PD. © 2018 International Parkinson and Movement Disorder Society.

Multimodal dopaminergic and free-water imaging in Parkinson's disease

INTRODUCTION

When using free-water diffusion imaging or positron emission tomography (PET), it is established that substania nigra microstructure and presynaptic dopamine activity are impaired in early PD. It is not well understood if these two forms of degeneration are redundant, or if they each provide a unique contribution to the clinical motor and cognitive symptoms.

METHODS

A total of 129 PD and 75 control individuals underwent motor and cognitive evaluations, and in vivo [11C]dihydrotetrabenazine (DTBZ) monoaminergic brain PET imaging and diffusion imaging. Correlations between free-water in the substantia nigra and striatal PET measures were analyzed. Unbiased multiple regression using a backward elimination method was performed between clinical severity and all imaging measures.

RESULTS

Inverse correlations were found between free-water in posterior substantia nigra and DTBZ binding in putamen and caudate. Multiple regression revealed that increased free-water in the posterior substantia nigra, decreased DTBZ binding in putamen, and age were predictors of higher Hoehn and Yahr stage, MDS-UPDRS III scores, and posture and gait sub-scores. Increased posterior substantia nigra free-water alone was associated tremor scores. Free-water in caudate and putamen did not predict measures of motor performance. Decreased DTBZ binding in caudate, increased free-water in caudate and posterior substantia nigra were associated with higher dementia ratings.

CONCLUSIONS

These findings suggest that free-water in the posterior substantia nigra and presynaptic dopamine imaging in striatum are uniquely associated with the clinical symptoms of PD, indicating that each imaging modality may be measuring a unique mechanism relevant to nigrostriatal degeneration.

Magnetic resonance T1w/T2w ratio: A parsimonious marker for Parkinson disease

OBJECTIVE

Newer magnetic resonance imaging (MRI) techniques have shown promise in capturing early Parkinson disease (PD)-related changes in the substantia nigra pars compacta (SNc), the key pathological loci. Their translational value, however, is hindered by technical complexity and inconsistent results.

METHODS

A novel yet simple MRI contrast, the T1w/T2w ratio, was used to study 76 PD patients and 70 controls. The T1w/T2w ratio maps were analyzed using both voxel-based and region-of-interest approaches in normalized space. The sensitivity and specificity of the SNc T1w/T2w ratio in discriminating between PD and controls also were assessed. In addition, its diagnostic performance was tested in a subgroup of PD patients with disease duration ≤2 years (PDE). A second independent cohort of 73 PD patients and 49 controls was used for validation.

RESULTS

Compared to controls, PD patients showed a higher T1w/T2w ratio in both the right (cluster size = 164mm3 , p < 0.0001) and left (cluster size = 213mm3 , p < 0.0001) midbrain that was located ventrolateral to the red nucleus and corresponded to the SNc. The region-of-interest approach confirmed the group difference in the SNc T1w/T2w ratio between PD and controls (p < 0.0001). The SNc T1w/T2w ratio had high sensitivity (0.908) and specificity (0.80) to separate PD and controls (area under the curve [AUC] = 0.926), even for PDE patients (AUC = 0.901, sensitivity = 0.857, specificity = 0.857). These results were validated in the second cohort.

INTERPRETATION

The T1w/T2w ratio can detect PD-related changes in the SNc and may be used as a novel, parsimonious in vivo biomarker for the disease, particularly for early stage patients, with high translational value for clinical practice and research. ANN NEUROL 2019;85:96-104.

A robust deconvolution method to disentangle multiple water pools in diffusion MRI

The diffusion-weighted magnetic resonance imaging (dMRI) signal measured in vivo arises from multiple diffusion domains, including hindered and restricted water pools, free water and blood pseudo-diffusion. Not accounting for the correct number of components can bias metrics obtained from model fitting because of partial volume effects that are present in, for instance, diffusion tensor imaging (DTI) and diffusion kurtosis imaging (DKI). Approaches that aim to overcome this shortcoming generally make assumptions about the number of considered components, which are not likely to hold for all voxels. The spectral analysis of the dMRI signal has been proposed to relax assumptions on the number of components. However, it currently requires a clinically challenging signal-to-noise ratio (SNR) and accounts only for two diffusion processes defined by hard thresholds. In this work, we developed a method to automatically identify the number of components in the spectral analysis, and enforced its robustness to noise, including outlier rejection and a data-driven regularization term. Furthermore, we showed how this method can be used to take into account partial volume effects in DTI and DKI fitting. The proof of concept and performance of the method were evaluated through numerical simulations and in vivo MRI data acquired at 3 T. With simulations our method reliably decomposed three diffusion components from SNR = 30. Biases in metrics derived from DTI and DKI were considerably reduced when components beyond hindered diffusion were taken into account. With the in vivo data our method determined three macro-compartments, which were consistent with hindered diffusion, free water and pseudo-diffusion. Taking free water and pseudo-diffusion into account in DKI resulted in lower mean diffusivity and higher fractional anisotropy values in both gray and white matter. In conclusion, the proposed method allows one to determine co-existing diffusion compartments without prior assumptions on their number, and to account for undesired signal contaminations within clinically achievable SNR levels.

Imaging Markers of Progression in Parkinson's Disease

Background

Parkinson's disease (PD) is the second-most common neurodegenerative disorder after Alzheimer's disease; however, to date, there is no approved treatment that stops or slows down disease progression. Over the past decades, neuroimaging studies, including molecular imaging and MRI are trying to provide insights into the mechanisms underlying PD.

Methods

This work utilized a literature review.

Results

It is now becoming clear that these imaging modalities can provide biomarkers that can objectively detect brain changes related to PD and monitor these changes as the disease progresses, and these biomarkers are required to establish a breakthrough in neuroprotective or disease-modifying therapeutics.

Conclusions

Here, we provide a review of recent observations deriving from PET, single-positron emission tomography, and MRI studies exploring PD and other parkinsonian disorders.

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

Therapeutic strategies for Parkinson disease: beyond dopaminergic drugs

Existing therapeutic strategies for managing Parkinson disease (PD), which focus on addressing the loss of dopamine and dopaminergic function linked with degeneration of dopaminergic neurons, are limited by side effects and lack of long-term efficacy. In recent decades, research into PD pathophysiology and pharmacology has focused on understanding and tackling the neurodegenerative processes and symptomology of PD. In this Review, we discuss the challenges associated with the development of novel therapies for PD, highlighting emerging agents that aim to target cell death, as well as new targets offering a symptomatic approach to managing features and progression of the disease.

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.

Neuroimaging abnormalities in individuals exhibiting Parkinson's disease risk markers

BACKGROUND

The concept of prodromal Parkinson's disease (PD) involves variable combinations of nonmotor features and subtle motor abnormalities as a result of ongoing neurodegeneration in the brain stem including substantia nigra (SN) and abnormal findings upon transcranial sonography and nuclear imaging. Except for nuclear imaging, the predictive value of risk markers for the conversion to overt PD is low.

OBJECTIVE

The objective of this study was to determine whether PD risk markers are associated with changes in brain structure and to what extent cognitive changes are risk markers for PD.

METHODS

Diffusion-weighted imaging, voxel-based morphometry, and cortical thickness analysis was performed in 29 individuals with hyposmia and/or an increased SN hyperechogenicity (SN+) upon transcranial sonography and 28 controls without these 2 risk markers. Classical parkinsonian signs were an exclusion criterion. All of the participants underwent a neuropsychological test battery addressing executive functions, learning ability, and verbal fluency.

RESULTS

In the PD risk group, diffusion-weighted imaging mean diffusivity was increased in 4 left hemisphere clusters (posterior thalamus, inferior longitudinal fasciculus, fornix, corticospinal tract). A negative relationship of mean diffusivity and smell function was present for the posterior thalamus and the corticospinal tract. There was a significant correlation of mean diffusivity values and SN+ in all clusters. Neither voxel-based morphometry nor cortical thickness analysis revealed any group differences. No relevant group differences were observed for cognitive tests included.

CONCLUSION

PD-free individuals with PD risk markers show microstructural changes of the white matter, including areas relevant for motor and limbic processes. In addition, our study provides for the first time a neuroanatomical correlate for SN hyperechogenicity. © 2018 International Parkinson and Movement Disorder Society.

Distinct progression pattern of susceptibility MRI in the substantia nigra of Parkinson's patients

BACKGROUND

Susceptibility MRI may capture Parkinson's disease-related pathology. This study delineated longitudinal changes in different substantia nigra regions.

METHODS

Seventy-two PD patients and 62 controls were studied at both baseline and after 18 months with MRI. R2* and quantitative susceptibility mapping values from the substantia nigra pars compacta and substantia nigra pars reticulata were calculated. Mixed-effects models compared controls with PD or PD subgroups having different disease durations: early (<1 year), middle (<5 years, middle-stage PD), and late (>5 years, late-stage PD). Pearson's correlation assessed associations between imaging and clinical measures.

RESULTS

At baseline, R2* and quantitative susceptibility mapping were higher in both the substantia nigra pars compacta and substantia nigra pars reticulata in all PD patients (group effect, P ≤ 0.003). Longitudinally, the substantia nigra pars compacta R2* showed a faster increase in PD compared with controls (time × group, P = 0.002), whereas quantitative susceptibility mapping did not (P = 0.668). The substantia nigra pars reticulata R2* and quantitative susceptibility mapping did not differ between PD and controls (time × group, P ≥ 0.084), although both decreased longitudinally (time effect, P ≤ 0.004). Baseline substantia nigra pars compacta R2* was higher in all PD subgroups (group, P ≤ 0.006), but showed a significantly faster increase only in later-stage PD (time × group, P < 0.0001) that correlated with changes in nonmotor symptoms (r = 0.746, P = 0.002). Baseline substantia nigra pars reticulata quantitative susceptibility mapping was higher in middle-stage PD and later-stage PD (group, P ≤ 0.002), but showed a longitudinal decrease (time × group, P = 0.004) only in later-stage PD that correlated with changes in motor signs (r = 0.837, P < 0.001).

CONCLUSION

Susceptibility MRI revealed distinct patterns of PD progression in the substantia nigra pars compacta and substantia nigra pars reticulata. The different patterns are particularly clear in later-stage patients. These findings may resolve past controversies and have implications in the pathophysiological processes during PD progression. © 2018 International Parkinson and Movement Disorder Society.

Nucleus basalis of Meynert degeneration precedes and predicts cognitive impairment in Parkinson's disease

Currently, no reliable predictors of cognitive impairment in Parkinson's disease exist. We hypothesized that microstructural changes at grey matter T1-weighted MRI and diffusion tensor imaging in the cholinergic system nuclei and associated limbic pathways underlie cognitive impairment in Parkinson's disease. We performed a cross-sectional comparison between patients with Parkinson's disease with and without cognitive impairment. We also performed a longitudinal 36-month follow-up study of cognitively intact Parkinson's disease patients, comparing patients who remained cognitively intact to those who developed cognitive impairment. Patients with Parkinson's disease with cognitive impairment showed lower grey matter volume and increased mean diffusivity in the nucleus basalis of Meynert, compared to patients with Parkinson's disease without cognitive impairment. These results were confirmed both with region of interest and voxel-based analyses, and after partial volume correction. Lower grey matter volume and increased mean diffusivity in the nucleus basalis of Meynert was predictive for developing cognitive impairment in cognitively intact patients with Parkinson's disease, independent of other clinical and non-clinical markers of the disease. Structural and microstructural alterations in entorhinal cortex, amygdala, hippocampus, insula, and thalamus were not predictive for developing cognitive impairment in Parkinson's disease. Our findings provide evidence that degeneration of the nucleus basalis of Meynert precedes and predicts the onset of cognitive impairment, and might be used in a clinical setting as a reliable biomarker to stratify patients at higher risk of cognitive decline.

Multimodal neuroimaging and behavioral assessment of α-synuclein polymorphism rs356219 in older adults

The single-nucleotide polymorphism rs356219 in the α-synuclein (SNCA) gene has been shown to significantly contribute to an earlier age at onset of Parkinson's disease (PD), and regulates SNCA expression in PD brain regions, blood, and plasma. Here, we used multimodal magnetic resonance imaging (MRI) to study healthy adults with and without the rs356219 risk genotype. Motor and cognitive tests were administered, and all participants underwent functional and structural MRI. Imaging analyses included (1) task-based functional MRI; (2) task-based functional connectivity; (3) free-water diffusion MRI of the substantia nigra; (4) voxel-based morphometry; and (5) surface-based morphometry. There were no differences between the 2 groups in motor and cognitive performance, or brain structure. However, carrying a PD risk variant was associated with reduced functional activity in the posterior putamen and primary motor cortex. Moreover, the posterior putamen had reduced functional connectivity with the motor cortex during motor control in those with a risk genotype compared to those without. These findings point to functional abnormalities in the striatocortical circuit of rs356219 risk genotype carriers.

Substantia Nigra Free Water Increases Longitudinally in Parkinson Disease

BACKGROUND AND PURPOSE

Free water in the posterior substantia nigra obtained from a bi-tensor diffusion MR imaging model has been shown to significantly increase over 1- and 4-year periods in patients with early-stage idiopathic Parkinson disease compared with healthy controls, which suggests that posterior substantia nigra free water may be an idiopathic Parkinson disease progression biomarker. Due to the known temporal posterior-to-anterior substantia nigra degeneration in idiopathic Parkinson disease, we assessed longitudinal changes in free water in both the posterior and anterior substantia nigra in patients with later-stage idiopathic Parkinson disease and age-matched healthy controls for comparison.

MATERIALS AND METHODS

Nineteen subjects with idiopathic Parkinson disease and 19 age-matched healthy control subjects were assessed on the same 3T MR imaging scanner at baseline and after approximately 3 years.

RESULTS

Baseline mean idiopathic Parkinson disease duration was 7.1 years. Both anterior and posterior substantia nigra free water showed significant intergroup differences at baseline (P < .001 and P = .014, respectively, idiopathic Parkinson disease versus healthy controls); however, only anterior substantia nigra free water showed significant longitudinal group × time interaction increases (P = .021, idiopathic Parkinson disease versus healthy controls). There were no significant longitudinal group × time interaction differences found for conventional diffusion tensor imaging or free water-corrected DTI assessments in either the anterior or posterior substantia nigra.

CONCLUSIONS

Results from this study provide further evidence supporting substantia nigra free water as a promising disease-progression biomarker in idiopathic Parkinson disease that may help to identify disease-modifying therapies if used in future clinical trials. Our novel finding of longitudinal increases in anterior but not posterior substantia nigra free water is potentially a result of the much longer disease duration of our cohort compared with previously studied cohorts and the known posterior-to-anterior substantia nigra degeneration that occurs over time in idiopathic Parkinson disease.