Magnetic resonance imaging markers of Parkinson's disease nigrostriatal signature

Nigral MRI features of asymptomatic welders

INTRODUCTION

Manganese (Mn)-induced parkinsonism involves motor symptoms similar to those observed in Parkinson's disease (PD). Previous literature suggests that chronic Mn- exposure may increase PD risk, although Mn-induced clinical syndromes are considered atypical for PD. This study investigated whether asymptomatic welders display differences in the substantia nigra (SN), the key pathological locus of PD.

METHOD

Brain MRI data and occupational exposure history were obtained in welders (N = 43) and matched controls (N = 31). Diffusion tensor imaging fractional anisotropy (FA; estimate of microstructural integrity) and R2* (estimate of iron and other PD-related brain differences) values in the SN pars compacta (SNc), SN reticulata (SNr), and globus pallidus (GP) were compared between the two groups. The MRI markers of the SN and GP within welders were related to exposure estimates.

RESULTS

Compared to controls, welders who had chronic, but low-level, Mn-exposure had similar FA and R2* values in both SN regions (p's > 0.082), but significantly lower FA (p = 0.0013), although not R2* (p = 0.553), in the GP. In welders, FA values in the SN and GP showed a second-order polynomial relationship with cumulative lifetime welding exposure (p's < 0.03).

CONCLUSION

Neurotoxic processes associated with Mn-exposure may be different from those in PD when the exposure-level is relatively low. Greater welding duration and level, however, were associated with FA differences in the GP and SN, indicating that welding exposures above a certain level may induce neurotoxicity in the SN, a finding that should be explored further in future studies.

Inflammatory Mechanisms in Parkinson's Disease: From Pathogenesis to Targeted Therapies

Inflammation is a critical factor contributing to the progressive neurodegenerative process observed in Parkinson's disease (PD). Microglia, the immune cells of the central nervous system, are activated early in PD pathogenesis and can both trigger and propagate early disease processes via innate and adaptive immune mechanisms such as upregulated immune cells and antibody-mediated inflammation. Downstream cytokines and gene regulators such as microRNA (miRNA) coordinate later disease course and mediate disease progression. Biomarkers signifying the inflammatory and neurodegenerative processes at play within the central nervous system are of increasing interest to clinical teams. To be effective, such biomarkers must achieve the highest sensitivity and specificity for predicting PD risk, confirming diagnosis, or monitoring disease severity. The aim of this review was to summarize the current preclinical and clinical evidence that suggests that inflammatory processes contribute to the initiation and progression of neurodegenerative processes in PD. In this article, we further summarize the data about main inflammatory biomarkers described in PD to date and their potential for regulation as a novel target for disease-modifying pharmacological strategies.

Imaging iron and neuromelanin simultaneously using a single 3D gradient echo magnetization transfer sequence: Combining neuromelanin, iron and the nigrosome-1 sign as complementary imaging biomarkers in early stage Parkinson's disease

Diagnosing early stage Parkinson's disease (PD) is still a clinical challenge. Previous studies using iron, neuromelanin (NM) or the Nigrosome-1 (N1) sign in the substantia nigra (SN) by themselves have been unable to provide sufficiently high diagnostic performance for these methods to be adopted clinically. Our goal in this study was to extract the NM complex volume, iron content and volume representing the entire SN, and the N1 sign as potential complementary imaging biomarkers using a single 3D magnetization transfer contrast (MTC) gradient echo sequence and to evaluate their diagnostic performance and clinical correlations in early stage PD. A total of 40 early stage idiopathic PD subjects and 40 age- and sex-matched healthy controls (HCs) were imaged at 3T. NM boundaries (representing the SN pars compacta (SNpc) and parabrachial pigmented nucleus) and iron boundaries representing the total SN (SNpc and SN pars reticulata) were determined semi-automatically using a dynamic programming (DP) boundary detection algorithm. Receiver operating characteristic analyses were performed to evaluate the utility of these imaging biomarkers in diagnosing early stage PD. A correlation analysis was used to study the relationship between these imaging measures and the clinical scales. We also introduced the concept of NM and total iron overlap volumes to demonstrate the loss of NM relative to the iron containing SN. Furthermore, all 80 cases were evaluated for the N1 sign independently. The NM and SN volumes were lower while the iron content was higher in the SN for PD subjects compared to HCs. Interestingly, the PD subjects with bilateral loss of the N1 sign had the highest iron content. The area under the curve (AUC) values for the average of both hemispheres for single measures were: .960 for NM complex volume; .788 for total SN volume; .740 for SN iron content and .891 for the N1 sign. Combining NM complex volume with each of the following measures through binary logistic regression led to AUC values for the averaged right and left sides of: .976 for total iron content; .969 for total SN volume, .965 for overlap volume and .983 for the N1 sign. We found a negative correlation between SN volume and UPDRS-III (R² = .22, p = .002). While the N1 sign performed well, it does not contain any information about iron content or NM quantitatively, therefore, marrying this sign with the NM and iron measures provides a better physiological explanation of what is happening when the N1 sign disappears in PD subjects. In summary, the combination of NM complex volume, SN volume, iron content and the N1 sign as derived from a single MTC sequence provides complementary information for understanding and diagnosing early stage PD.

GraphNet-based imaging biomarker model to explain levodopa-induced dyskinesia in Parkinson's disease

BACKGROUND AND OBJECTIVE

Levodopa-induced dyskinesia (LID) is a disabling complication of Parkinson's disease (PD). Imaging-based measurements, especially those related to the surface shape of the basal ganglia, have shown potential for explaining the severity of LID in PD. Here, we aimed to explore a novel application of the methodology to find biomarkers of LID severity in PD using regularization.

METHODS

We proposed an application of graph-constrained elastic net (GraphNet) regularization to detect surface-based shape biomarkers explaining the severity of LID and compared the approach with other conventional regularization methods. To examine the methods, we used two independent datasets, one as a training dataset to build the model, and the other dataset was used to validate the constructed model.

RESULTS

We found that the left striatum (putamen was the greatest and the caudate was second) was the most significant surface-based biomarker related to the severity of LID. Our results improved the interpretability of identified surface-based biomarkers compared to competing methods. We also found that GraphNet regularization improved prediction of the severity of LID better than the conventional regularization methods. Our model performed better in terms of root-mean-squared error and correlation coefficient between predicted and actual clinical scores.

CONCLUSION

The proposed algorithm offers an advantage of interpretable anatomical variations related to the deformation of the cortical surface. The experimental results showed that GraphNet regularization was robust to identify surface-based shape biomarkers related to both hypokinetic and hyperkinetic movement disorders.

Direct and specific assessment of axonal injury and spinal cord microenvironments using diffusion correlation imaging

We describe a practical two-dimensional (2D) diffusion MRI framework to deliver specificity and improve sensitivity to axonal injury in the spinal cord. This approach provides intravoxel distributions of correlations of water mobilities in orthogonal directions, revealing sub-voxel diffusion components. Here we use it to investigate water diffusivities along axial and radial orientations within spinal cord specimens with confirmed, tract-specific axonal injury. First, we show using transmission electron microscopy and immunohistochemistry that tract-specific axonal beading occurs following Wallerian degeneration in the cortico-spinal tract as direct sequelae to closed head injury. We demonstrate that although some voxel-averaged diffusion tensor imaging (DTI) metrics are sensitive to this axonal injury, they are non-specific, i.e., they do not reveal an underlying biophysical mechanism of injury. Then we employ 2D diffusion correlation imaging (DCI) to improve discrimination of different water microenvironments by measuring and mapping the joint water mobility distributions perpendicular and parallel to the spinal cord axis. We determine six distinct diffusion spectral components that differ according to their microscopic anisotropy and mobility. We show that at the injury site a highly anisotropic diffusion component completely disappears and instead becomes more isotropic. Based on these findings, an injury-specific MR image of the spinal cord was generated, and a radiological-pathological correlation with histological silver staining % area was performed. The resulting strong and significant correlation (r=0.70,p < 0.0001) indicates the high specificity with which DCI detects injury-induced tissue alterations. We predict that the ability to selectively image microstructural changes following axonal injury in the spinal cord can be useful in clinical and research applications by enabling specific detection and increased sensitivity to injury-induced microstructural alterations. These results also encourage us to translate DCI to higher spatial dimensions to enable assessment of traumatic axonal injury, and possibly other diseases and disorders in the brain.

Neuroimaging Advances in Parkinson's Disease and Atypical Parkinsonian Syndromes

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

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

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

Increased iron-deposition in lateral-ventral substantia nigra pars compacta: A promising neuroimaging marker for Parkinson's disease

BACKGROUND

To date there are no validated MRI biomarkers to assist diagnosis of Parkinson's disease (PD). Our aim was to investigate PD related iron changes in the substantia nigra pars compacta (SNpc) as defined by neuromelanin-sensitive MR contrast.

METHODS

Thirty-nine PD participants and 33 healthy controls were scanned at 3.0-T using a 16-echo gradient echo sequence to create R2* maps for the evaluation of iron content to find the overlap with a neuromelanin based SNpc mask. The SNpc overlap percentage with the R2* map, and the R2* values in both the whole SNpc and the overlap volume were compared between PD and control groups, and correlated with clinical features for PD participants. Finally, the diagnostic performance of the SNpc overlap percentage was evaluated using ROC analysis.

RESULTS

PD related iron changes mostly occur in the lateral-ventral part of the neuromelanin SNpc. The R2* values in the whole SNpc and the SNpc overlap volume, and the SNpc overlap percentage were larger in PD participants than in controls. Furthermore, the SNpc overlap percentage was positively correlated with the disease duration in PD. The SNpc overlap percentage provided excellent diagnostic accuracy for discriminating PD participants from controls (AUC = 0.93), while the R2* values in the whole SNpc or the overlap volume were less effective.

CONCLUSION

The overlap between the iron content as determined by R2* mapping and neuromelanin in the substantia nigra pars compacta has the potential to be a neuroimaging biomarker for diagnosing Parkinson's disease.

α-Synuclein Induces Progressive Changes in Brain Microstructure and Sensory-Evoked Brain Function That Precedes Locomotor Decline

In vivo functional and structural brain imaging of synucleinopathies in humans have provided a rich new understanding of the affected networks across the cortex and subcortex. Despite this progress, the temporal relationship between α-synuclein (α-syn) pathology and the functional and structural changes occurring in the brain is not well understood. Here, we examine the temporal relationship between locomotor ability, brain microstructure, functional brain activity, and α-syn pathology by longitudinally conducting rotarod, diffusion magnetic resonance imaging (MRI), resting-state functional MRI (fMRI), and sensory-evoked fMRI on 20 mice injected with α-syn fibrils and 20 PBS-injected mice at three timepoints (10 males and 10 females per group). Intramuscular injection of α-syn fibrils in the hindlimb of M83+/- mice leads to progressive α-syn pathology along the spinal cord, brainstem, and midbrain by 16 weeks post-injection. Our results suggest that peripheral injection of α-syn has acute systemic effects on the central nervous system such that structural and resting-state functional activity changes occur in the brain by four weeks post-injection, well before α-syn pathology reaches the brain. At 12 weeks post-injection, a separate and distinct pattern of structural and sensory-evoked functional brain activity changes was observed that are co-localized with previously reported regions of α-syn pathology and immune activation. Microstructural changes in the pons at 12 weeks post-injection were found to predict survival time and preceded measurable locomotor deficits. This study provides preliminary evidence for diffusion and fMRI markers linked to the progression of synuclein pathology and has translational importance for understanding synucleinopathies in humans.SIGNIFICANCE STATEMENT α-Synuclein (α-syn) pathology plays a critical role in neurodegenerative diseases such as Parkinson's disease, dementia with Lewy bodies, and multiple system atrophy. The longitudinal effects of α-syn pathology on locomotion, brain microstructure, and functional brain activity are not well understood. Using high field imaging, we show preliminary evidence that peripheral injection of α-syn fibrils induces unique patterns of functional and structural changes that occur at different temporal stages of α-syn pathology progression. Our results challenge existing assumptions that α-syn pathology must precede changes in brain structure and function. Additionally, we show preliminary evidence that diffusion and functional magnetic resonance imaging (fMRI) are capable of resolving such changes and thus should be explored further as markers of disease progression.

Breathing new life into neurotoxic-based monkey models of Parkinson's disease to study the complex biological interplay between serotonin and dopamine

Numerous clinical studies have shown that the serotonergic system also degenerates in patients with Parkinson's disease. The causal role of this impairment in Parkinson's symptomatology and the response to treatment remains to be refined, in particular thanks to approaches allowing the two components DA and 5-HT to be isolated if possible. We have developed a macaque monkey model of Parkinson's disease exhibiting a double lesion (dopaminergic and serotonergic) thanks to the sequential use of MPTP (1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine) and MDMA (3,4-methylenedioxy-N-methamphetamine) (or MDMA prior MPTP). We characterized this monkey model by multimodal imaging (PET, positron emission tomography with several radiotracers; DTI, diffusion tensor imaging), behavioral assessments (parkinsonism, dyskinesia, neuropsychiatric-like behavior) and post-mortem analysis (with DA and 5-HT markers). When administrated after MPTP, MDMA damaged the 5-HT presynaptic system without affecting the remaining DA neurons. The lesion of 5-HT fibers induced by MDMA altered rigidity and prevented dyskinesia and neuropsychiatric-like symptoms induced by levodopa therapy in MPTP-treated animals. Interestingly also, prior MDMA administration aggravates the parkinsonian deficits and associated DA injury. Dystonic postures, action tremor and global spontaneous activities were significantly affected. All together, these data clearly indicate that late or early lesions of the 5-HT system have a differential impact on parkinsonian symptoms in the macaque model of Parkinson's disease. Whether MDMA has an impact on neuropsychiatric-like symptoms such as apathy, anxiety, depression remains to be addressed. Despite its limitations, this toxin-based double-lesioned monkey model takes on its full meaning and provides material for the experimental study of the heterogeneity of patients.

The associations of BMI with mean diffusivity of basal ganglia among young adults with mild obesity and without obesity

Obesity causes a wide range of systemic diseases and is associated with mood and anxiety disorders. It is also associated with dopaminergic reward system function. However, the relationships between microstructural properties of the dopaminergic system and body mass index (BMI) have not been investigated. In this study, we investigated the associations of BMI with mean diffusivity (MD), diffusion tensor imaging measure in areas of the dopaminergic system (MDDS) in 435 healthy young adults with mild obesity and without obesity (BMI < 40). We detected the association between greater BMI and lower MD of the right globus pallidus and the right putamen. These results suggest that the property of the dopaminergic system is associated with BMI among young adults with mild obesity and without obesity.

Regional transcriptional architecture of Parkinson's disease pathogenesis and network spread

Although a significant genetic contribution to the risk of developing sporadic Parkinson's disease has been well described, the relationship between local genetic factors, pathogenesis, and subsequent spread of pathology throughout the brain has been largely unexplained in humans. To address this question, we use network diffusion modelling to infer probable pathology seed regions and patterns of disease spread from MRI atrophy maps derived from 232 de novo subjects in the Parkinson's Progression Markers Initiative study. Allen Brain Atlas regional transcriptional profiles of 67 Parkinson's disease risk factor genes were mapped to the inferred seed regions to determine the local influence of genetic risk factors. We used hierarchical clustering and L1 regularized regression analysis to show that transcriptional profiles of immune-related and lysosomal risk factor genes predict seed region location and the pattern of disease propagation from the most likely seed region, substantia nigra. By leveraging recent advances in transcriptomics, we show that regional microglial abundance quantified by high fidelity gene expression also predicts seed region location. These findings suggest that early disease sites are genetically susceptible to dysfunctional lysosomal α-synuclein processing and microglia-mediated neuroinflammation, which may initiate the disease process and contribute to spread of pathology along neural connectivity pathways.

Effects of Simultaneously Performed Dual-Task Training with Aerobic Exercise and Working Memory Training on Cognitive Functions and Neural Systems in the Elderly

Working memory (WM) training (WMT), aerobic exercise training (AET), and dual-task training improve cognitive functions and alter neural systems in older adults. In particular, the effects have been investigated of dual-task training that combines a walking or standing activity (balance exercise) simultaneously performed with cognitive training (which is ecologically difficult for the elderly). In this study, we investigated the effects of simultaneously performed dual-task training incorporating both AET and WMT (SDAEWMT), using a recumbent ergocycle bicycle and a WMT program that provided a portable console and made the training ecologically easy for the elderly. Older adults (65.9±13.7 years old) participated in 3 months of SDAEWMT, WMT, or AET after random allocation, and the effects of SDAEWMT were compared with those of WMT and AET. Prior to and after training, all the subjects underwent cognitive testing, magnetic resonance imaging (MRI) involving diffusion tensor imaging (DTI), and functional MRI during performance of an N-back WM task. SDAEWMT improved executive function (performance of a frontal assessment battery); however, there was no evidence of broader transfer effects or enhanced learning with WMT. SDAEWMT resulted in mean diffusivity changes in brain areas involving the dopaminergic system, suggesting that neural tissue changes occurred in these areas. SDAEWMT also resulted in an increase in brain activity during the 2-back working memory task in brain areas involved in attentional reorientation. These results suggest that SDAEWMT is effective for improving cognitive functions and inducing beneficial neural changes in older adults.

Uncinate fasciculus and word selection processing in Parkinson's disease

We explored with Diffusion Tensor Imaging (DTI) technique whether the ability to select words among competitive alternatives during word production is related to the integrity of the left uncinate fasciculus (UF) in Parkinson's disease (PD). Nineteen PD patients (10 right-sided and 9 left-sided) and 17 matched healthy controls (HC) took part in the study. Participants were asked to derive nouns from verbs (reading from to read) or to generate verbs from nouns (to build from building). Noun and verb production, in this task, differ in the number of lexical entries among which the response is selected, as the noun must be selected from a larger number of alternatives compared to the verb, and thus is more demanding of processing resources. DTI evaluation was obtained for each subject. Fractional anisotropy (FA) and mean diffusivity (MD) maps were derived from DTI and median FA and MD values were computed within the left and right UF. Then, FA and MD of the left and right UF were correlated with noun and verb production. Both the left and right UF-FA correlated with the global (noun + verb) production and noun production in the whole PD group. In right-sided PD, correlations were found with the contralateral UF-FA; in left-sided PD the correlations emerged with both the left and right UF-FA. The most difficult task, noun production, significantly correlated with the right UF-FA in left-sided PD. The left UF is involved in word selection processes, and the right UF intervenes when the selection is particularly demanding of attentional resources.

Iron Imaging as a Diagnostic Tool for Parkinson's Disease: A Systematic Review and Meta-Analysis

Background: Parkinson's disease (PD) is a progressive neurodegenerative disease whose main neuropathological feature is the loss of dopaminergic neurons of the substantia nigra (SN). There is also an increase in iron content in the SN in postmortem and imaging studies using iron-sensitive MRI techniques. However, MRI results are variable across studies. Objectives: We performed a systematic meta-analysis of SN iron imaging studies in PD to better understand the role of iron-sensitive MRI quantification to distinguish patients from healthy controls. We also studied the factors that may influence iron quantification and analyzed the correlations between demographic and clinical data and iron load. Methods: We searched PubMed and ScienceDirect databases (from January 1994 to December 2019) for studies that analyzed iron load in the SN of PD patients using T2^*, R2^*, susceptibility weighting imaging (SWI), or quantitative susceptibility mapping (QSM) and compared the values with healthy controls. Details for each study regarding participants, imaging methods, and results were extracted. The effect size and confidence interval (CI) of 95% were calculated for each study as well as the pooled weighted effect size for each marker over studies. Hence, the correlations between technical and clinical metrics with iron load were analyzed. Results: Forty-six articles fulfilled the inclusion criteria including 27 for T2^*/R2^* measures, 10 for SWI, and 17 for QSM (3,135 patients and 1,675 controls). Eight of the articles analyzed both R2^* and QSM. A notable effect size was found in the SN in PD for R2^* increase (effect size: 0.84, 95% CI: 0.60 to 1.08), for SWI measurements (1.14, 95% CI: 0.54 to 1.73), and for QSM increase (1.13, 95% CI: 0.86 to 1.39). Correlations between imaging measures and Unified Parkinson's Disease Rating Scale (UPDRS) scores were mostly observed for QSM. Conclusions: The consistent increase in MRI measures of iron content in PD across the literature using R2^*, SWI, or QSM techniques confirmed that these measurements provided reliable markers of iron content in PD. Several of these measurements correlated with the severity of motor symptoms. Lastly, QSM appeared more robust and reproducible than R2^* and more suited to multicenter studies.

Parkinson's Disease Diagnosis Using Neostriatum Radiomic Features Based on T2-Weighted Magnetic Resonance Imaging

Background: Parkinson's disease (PD) is a neurodegenerative disease in which the neostriatum, including the caudate nucleus (CN) and putamen (PU), has an important role in the pathophysiology. However, conventional magnetic resonance imaging (MRI) lacks sufficient specificity to diagnose PD. Therefore, the study's aim was to investigate the feasibility of using a radiomics approach to distinguish PD patients from healthy controls on T2-weighted images of the neostriatum and provide a basis for the clinical diagnosis of PD.

Methods: T2-weighted images from 69 PD patients and 69 age- and sex-matched healthy controls were obtained on the same 3.0T MRI scanner. Regions of interest (ROIs) were manually placed at the CN and PU on the slices showing the largest respective sizes of the CN and PU. We extracted 274 texture features from each ROI and then used the least absolute shrinkage and selection operator regression to perform feature selection and radiomics signature building to identify the CN and PU radiomics signatures consisting of optimal features. We used a receiver operating characteristic curve analysis to assess the diagnostic performance of two radiomics signatures in a training group and estimate the generalization performance in the test group.

Results: There were no significant differences in the demographic and clinical characteristics between the PD patients and healthy controls. The CN and PU radiomics signatures were built using 12 and 7 optimal features, respectively. The performance of the two radiomics signatures to distinguish PD patients from healthy controls was good. In the training and test groups, the AUCs of the CN radiomics signatures were 0.9410 (95% confidence interval [CI]: 0.8986–0.9833) and 0.7732 (95% CI: 0.6292–0.9173), respectively, and the AUCs of the PU radiomics signature were 0.8767 (95% CI: 0.8066–0.9469) and 0.7143 (95% CI: 0.5540–0.8746), respectively. Vertl_GlevNonU_R appeared simultaneously in both the CN and PU radiomics signatures as an optimal feature. A t-test analysis revealed significantly higher levels of texture values of the CN and PU in the PD patients than healthy controls (P < 0.05).

Conclusion: Neostriatum radiomics signatures achieved good diagnostic performance for PD and potentially could serve as a basis for the clinical diagnosis of PD.

MRI biomarkers of motor and non-motor symptoms in Parkinson's disease

Parkinson's disease is a heterogeneous disorder with both motor and non-motor symptoms that contribute to functional impairment. To develop effective, disease modifying treatments for these symptoms, biomarkers are necessary to detect neuropathological changes early in the disease course and monitor changes over time. Advances in MRI scan sequences and analytical techniques present numerous promising metrics to detect changes within the nigrostriatal system, implicated in the cardinal motor symptoms of the disease, and detect broader dysfunction involved in the non-motor symptoms, such as cognitive impairment. There is emerging evidence that iron sensitive, neuromelanin sensitive, diffusion sensitive, and resting state functional magnetic imaging measures can capture changes within the nigrostriatal system. Iron, neuromelanin, and diffusion sensitive measures demonstrate high specificity and sensitivity in distinguishing Parkinson's disease relative to controls, with inconsistent results differentiating Parkinson's disease relative to atypical parkinsonian disorders. They may also serve as useful monitoring biomarkers, with each possibly detecting different aspects of the disease course (early nigrosome changes versus broader substantia nigra changes). Investigations of non-motor symptoms, such as cognitive impairment, require careful consideration of the nature of cognitive deficits to characterize regional and network specific impairment. While the early, executive dysfunction observed is consistent with nigrostriatal degeneration, the memory and visuospatial impairments, the harbingers of a dementia process reflect dopaminergic independent dysfunction involving broader regions of the brain.

Mean diffusivity associated with trait emotional intelligence

Previous neuroimaging studies have suggested that the neural bases of trait emotional intelligence (TEI) lie in the social cognition network (SCN) and the somatic marker circuitry (SMC). The current study was the first to investigate the associations of total TEI factors and subfactors with mean diffusivity (MD) of these networks as well as regional MD of the dopaminergic system (MDDS). We found that TEI intrapersonal factor score and total TEI score were negatively correlated with regional MDDS in the vicinity of the right putamen and right pallidum and that TEI intrapersonal factor score was negatively correlated with MD values of the fusiform gyrus. Total TEI score and TEI factor scores were positively correlated with MD values of various areas within or adjacent to SCN components, SMC structures and the lateral prefrontal cortex (LPFC). Our MD findings demonstrated the importance of the dopaminergic system to TEI and implicate the SCN, SMC and LPFC in TEI. Future studies are required to investigate the implications of positive and negative associations with MD values.

Association of iron levels in hair with brain structures and functions in young adults

BACKGROUND

Iron plays a critical role in normal brain functions and development, but it has also been known to have adverse neurological effects.

METHODS

Here, we investigated the associations of iron levels in hair with regional gray matter volume (rGMV), regional cerebral blood flow (rCBF), fractional anisotropy (FA), mean diffusivity (MD), and cognitive differences in a study cohort of 590 healthy young adults.

RESULTS

Our findings showed that high iron levels were associated with lower rGMV in areas including the hippocampus, lower rCBF in the anterior and posterior parts of the brain, greater FA in areas including the part of the splenium of the corpus callosum, lower MD in the overlapping area including the splenium of the corpus callosum, as well as greater MD in the left hippocampus and areas including the frontal lobe.

CONCLUSION

These results are compatible with the notion that iron plays diverse roles in neural mechanisms in healthy young adults.

Enhanced Bidirectional Connectivity of the Subthalamo-pallidal Pathway in 6-OHDA-mouse Model of Parkinson's Disease Revealed by Probabilistic Tractography of Diffusion-weighted MRI at 9.4T

An important challenge in Parkinson’s disease (PD) based neuroscience and neuroimaging is mapping the neuronal connectivity of the basal ganglia to understand how the disease affects brain circuitry. However, a majority of diffusion tractography studies have shown difficulties in revealing connections between distant anatomic brain regions and visualizing basal ganglia connectome. In this current study, we investigated the differences in basal ganglia connectivity between 6-OHDA induced ex-vivo PD mouse model and normal ex-vivo mouse model by using diffusion tensor imaging tractography from diffusion-weighted images obtained with a high resolution 9.4 T MR scanner. Connectivity pattern of the basal ganglia were compared between five 6-OHDA and five control ex-vivo mouse brains using results of probabilistic tractography generated with PROBTRACKX. When compared with control mouse, 6-OHDA mouse showed significant enhancements to motor territory-related subthalamo-pallidal and pallido-subthalamic connectivity. Multi-fiber tractography combined with diffusion MRI data has the potential to help recognize the abnormalities found in connectivity of psychiatric and neurologic disease models.

Striatum Shape Hypertrophy in Early Stage Parkinson's Disease With Excessive Daytime Sleepiness

INTRODUCTION

Excessive daytime sleepiness (EDS) is one of the common and burdensome non-motor symptoms of Parkinson's disease (PD). However, the underlying neuropathology mechanism in PD patients with EDS (PD-EDS) remains unclear. The present study aims to delineate potential locations of structural alteration of subcortical regions in early stage and drug-naïve PD-EDS.

METHODS

The study had 252 patients with PD and 92 matched healthy controls (HC). EDS was estimated with the Epworth Sleepiness Scale, with a cutoff of 10. Ultimately, 59 patients were considered as PD-EDS. The remaining 193 were PD patients without EDS (PD-nEDS). FMRIB's Integrated Registration and Segmentation Tool (FIRST) was employed to assess the volumetric and surface alterations of subcortical nuclei in PD and PD-EDS.

RESULTS

Volumetric analyses found no difference in the subcortical nucleus volume between PD and HC, or PD-EDS and PD-nEDS groups. The shape analyses revealed the local atrophic changes in bilateral caudate and right putamen in patients with PD. In addition, the hypertrophic changes were located in the right putamen and left pallidum in PD-EDS than in PD-nEDS.

CONCLUSION

Our findings revealed the regional hypertrophy of the striatum in PD-EDS. Our results indicate that local hypertrophic striatum would be a valuable early biomarker for detecting the alteration in PD-EDS. The shape analysis contributes valuable information when investigating PD-EDS.

Visualization of Nigrosome 1 from the Viewpoint of Anatomic Structure

BACKGROUND AND PURPOSE

Parkinson disease is related to neurodegeneration and iron deposition in the substantia nigra pars compacta and nigrosome 1. However, visualization of nigrosome 1 via MR imaging is poor owing to the bilateral asymmetry, regardless of whether it is healthy. We focused on the magic angle and susceptibility effect and evaluated the anatomic slant structure of nigrosome 1 by tilting subjects' heads in the B₀ direction.

MATERIALS AND METHODS

To investigate the effectiveness of the magic angle, we tilted the volunteers' heads to the right and left in the B₀ direction or not at all for evaluating correlations between the degree of head tilting and visualization of the right nigrosome 1 and left nigrosome 1 using 3D spoiled gradient-echo sequences with multiecho acquisitions. We evaluated the susceptibility of nigrosome 1 and the local field using quantitative susceptibility mapping to assess static magnetic field inhomogeneity.

RESULTS

The heads tilted to the right and left showed significantly higher contrasts of nigrosome 1 and the substantia nigra pars compacta than the nontilted heads. No significant differences were observed in the visualization and susceptibility between the right nigrosome 1 and left nigrosome 1 for each head tilt. The effect of the magic angle was remarkable in the nontilted heads. This finding was supported by quantitative susceptibility mapping because the anatomic slant structure of nigrosome 1 was coherent between the axis of nigrosome 1 and the magic angle.

CONCLUSIONS

The asymmetric visualization of nigrosome 1 is affected by the magic angle and susceptibility. The anatomic slant structure of nigrosome 1 causes these challenges in visualization.

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

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

Differentiation of multiple system atrophy from Parkinson's disease by structural connectivity derived from probabilistic tractography

Recent studies combining diffusion tensor-derived metrics and machine learning have shown promising results in the discrimination of multiple system atrophy (MSA) and Parkinson’s disease (PD) patients. This approach has not been tested using more complex methodologies such as probabilistic tractography. The aim of this work is assessing whether the strength of structural connectivity between subcortical structures, measured as the number of streamlines (NOS) derived from tractography, can be used to classify MSA and PD patients at the single-patient level. The classification performance of subcortical FA and MD was also evaluated to compare the discriminant ability between diffusion tensor-derived metrics and NOS. Using diffusion-weighted images acquired in a 3 T MRI scanner and probabilistic tractography, we reconstructed the white matter tracts between 18 subcortical structures from a sample of 54 healthy controls, 31 MSA patients and 65 PD patients. NOS between subcortical structures were compared between groups and entered as features into a machine learning algorithm. Reduced NOS in MSA compared with controls and PD were found in connections between the putamen, pallidum, ventral diencephalon, thalamus, and cerebellum, in both right and left hemispheres. The classification procedure achieved an overall accuracy of 78%, with 71% of the MSA subjects and 86% of the PD patients correctly classified. NOS features outperformed the discrimination performance obtained with FA and MD. Our findings suggest that structural connectivity derived from tractography has the potential to correctly distinguish between MSA and PD patients. Furthermore, NOS measures obtained from tractography might be more useful than diffusion tensor-derived metrics for the detection of MSA.

Signal Alteration of Substantia Nigra on 3.0T Susceptibility-weighted Imaging in Parkinson's Disease and Vascular Parkinsonism

Recent researches have found that 7 Tesla SWI can detect the alteration of substantia nigra hyperintensity in Parkinson's disease (PD), multiple system atrophy (MSA), and progressive supranuclear palsy (PSP). The aim of this study was to investigate whether 3 Tesla SWI (3T SWI) can visualize anatomical alterations occurring in a hyperintense structure of the substantia nigra in PD and vascular parkinsonism (VP), and whether the evaluation of abnormal signal can be used as a factor in the differential diagnosis of PD and VP. Using 3 Tesla MRI, we evaluated 38 healthy subjects, 33 patients with PD and 34 patients with VP. Two blinded readers independently assessed the images. We found that the dorsolateral nigral hyperintensity was absent in 31 of 33 patients with PD and 15 of 34 patients with VP. The dorsolateral nigral hyperintensity was present in 19 of 34 patients with VP and 35 of 38 healthy controls. Group comparisons of absence of dorsolateral nigral hyperintensity revealed significant differences between the patients with PD and those with VP (P<0.001). The sensitivity of SWI for PD was 93.9% and the specificity was 92.1%. Visual assessment of dorsolateral nigral hyperintensity on high-field SWI scans may serve as a new simple diagnostic imaging marker for PD. And our study results indicate that 3T SWI can be used as a tool to identify PD and VP.

The early diagnosis of Parkinson's disease through combined biomarkers

OBJECTIVE

This study primarily aims to explore the value of combining the measurement of plasma α-synuclein oligomer levels with enhanced T2 star-weighted angiography (ESWAN) in the early diagnosis of Parkinson's disease.

METHODS

Sixty patients with early Parkinson's disease and 30 normal adults, with similar ages and genders, were enrolled in the study. Their levels of plasma α-synuclein oligomers were measured, and ESWAN was performed. The amplitudes, phases and R2* values of the head, body and tail of the ipsilateral and contralateral substantia nigra pars compacta (SNc) were measured, at the side of the limb with severe symptoms or early symptoms. The receiver operating characteristic (ROC) curve was used to explore the value of these indexes in the early diagnosis of Parkinson's disease.

RESULTS

The plasma level of α-synuclein oligomer was significantly higher in the experimental group than in the control group (P < 0.05). The amplitude values of the head and tail of contralateral SNcs were significantly lower in the experimental group than in the control group (P < 0.05). In the single-index assessment, the serum α-synuclein oligomer had the highest specificity (70%), while the sensitivity of the amplitude of the head and tail of the contralateral SNc was 75% and 80%, respectively. The area under the curve, for the combination of these three indicators, was 0.827, diagnostic efficiency was particularly high, and sensitivity and specificity both reached 80%.

CONCLUSION

The combined detection of plasma α-synuclein oligomer and amplitude of the head and tail of the SNc has high diagnostic specificity and sensitivity.

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.

Alterations in White Matter Network and Microstructural Integrity Differentiate Parkinson's Disease Patients and Healthy Subjects

Parkinson’s disease (PD) is a neurodegenerative disease, neuropathologically characterized by progressive loss of neurons in distinct brain areas. We hypothesize that quantifiable network alterations are caused by neurodegeneration. The primary motivation of this study was to assess the specific network alterations in PD patients that are distinct but appear in conjunction with physiological aging. 178 subjects (130 females) stratified into PD patients, young, middle-aged and elderly healthy controls (age- and sex-matched with PD patients), were analyzed using 3D-T1 magnetization-prepared rapid gradient-echo (MPRAGE) and diffusion weighted images acquired in 3T MRI scanner. Diffusion modeling and probabilistic tractography analysis were applied for generating voxel-based connectivity index maps from each seed voxel. The obtained connectivity matrices were analyzed using graph theoretical tools for characterization of involved network. By network-based statistic (NBS) the interregional connectivity differences between the groups were assessed. Measures evaluating local diffusion properties for anisotropy and diffusivity were computed for characterization of white matter microstructural integrity. The graph theoretical analysis showed a significant decrease in distance measures – eccentricity and characteristic path length – in PD patients in comparison to healthy subjects. Both measures as well were lower in PD patients when compared to young and middle-aged healthy controls. NBS analysis demonstrated lowered structural connectivity in PD patients in comparison to young and middle-aged healthy subject groups, mainly in frontal, cingulate, olfactory, insula, thalamus, and parietal regions. These specific network differences were distinct for PD and were not observed between the healthy subject groups. Microstructural analysis revealed diffusivity alterations within the white matter tracts in PD patients, predominantly in the body, splenium and tapetum of corpus callosum, corticospinal tract, and corona radiata, which were absent in normal aging. The identified alterations of network connectivity presumably caused by neurodegeneration indicate the disruption in global network integration in PD patients. The microstructural changes identified within the white matter could endorse network reconfiguration. This study provides a clear distinction between the network changes occurring during aging and PD. This will facilitate a better understanding of PD pathophysiology and the direct link between white matter changes and their role in the restructured network topology.

Matching ex vivo MRI With Iron Histology: Pearls and Pitfalls

Iron levels in the brain can be estimated using newly developed specific magnetic resonance imaging (MRI) sequences. This technique has several applications, especially in neurodegenerative disorders like Alzheimer's disease or Parkinson's disease. Coupling ex vivo MRI with histology allows neuroscientists to better understand what they see in the images. Iron is one of the most extensively studied elements, both by MRI and using histological or physical techniques. Researchers were initially only able to make visual comparisons between MRI images and different types of iron staining, but the emergence of specific MRI sequences like R2* or quantitative susceptibility mapping meant that quantification became possible, requiring correlations with physical techniques. Today, with advances in MRI and image post-processing, it is possible to look for MRI/histology correlations by matching the two sorts of images. For the result to be acceptable, the choice of methodology is crucial, as there are hidden pitfalls every step of the way. In order to review the advantages and limitations of ex vivo MRI correlation with iron-based histology, we reviewed all the relevant articles dealing with the topic in humans. We provide separate assessments of qualitative and quantitative studies, and after summarizing the significant results, we emphasize all the pitfalls that may be encountered.

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

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

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

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

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.

A totally data-driven whole-brain multimodal pipeline for the discrimination of Parkinson's disease, multiple system atrophy and healthy control

Parkinson's Disease (PD) and Multiple System Atrophy (MSA) are two parkinsonian syndromes that share many symptoms, albeit having very different prognosis. Although previous studies have proposed multimodal MRI protocols combined with multivariate analysis to discriminate between these two populations and healthy controls, studies combining all MRI indexes relevant for these disorders (i.e. grey matter volume, fractional anisotropy, mean diffusivity, iron deposition, brain activity at rest and brain connectivity) with a completely data-driven voxelwise analysis for discrimination are still lacking. In this study, we used such a complete MRI protocol and adapted a fully-data driven analysis pipeline to discriminate between these populations and a healthy controls (HC) group. The pipeline combined several feature selection and reduction steps to obtain interpretable models with a low number of discriminant features that can shed light onto the brain pathology of PD and MSA. Using this pipeline, we could discriminate between PD and HC (best accuracy = 0.78), MSA and HC (best accuracy = 0.94) and PD and MSA (best accuracy = 0.88). Moreover, we showed that indexes derived from resting-state fMRI alone could discriminate between PD and HC, while mean diffusivity in the cerebellum and the putamen alone could discriminate between MSA and HC. On the other hand, a more diverse set of indexes derived by multiple modalities was needed to discriminate between the two disorders. We showed that our pipeline was able to discriminate between distinct pathological populations while delivering sparse model that could be used to better understand the neural underpinning of the pathologies.

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Structuro-functional MRI can discriminate between parkinsonian syndromes

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Discriminant MRI modalities vary as a function of the discrimination task

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fMRI is crucial in discriminating between Parkinson's disease patients and controls

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Structural MRI discriminate between Multiple System Atrophy patients and controls

Gender specific decrease of a set of circulating N-acylphosphatidyl ethanolamines (NAPEs) in the plasma of Parkinson's disease patients

INTRODUCTION

Current markers of Parkinson's disease (PD) fail to detect the early progression of disease state. Conversely, current omics techniques allow the investigation of hundreds of molecules potentially altered by disease conditions. Based on evidence previously collected by our group in a mouse model of PD, we speculated that a particular set of circulating lipids might be significantly altered by the pathology.

OBJECTIVES

The aim of current study was to evaluate the potential of a particular set of N-acyl-phosphatidylethanolamines (NAPEs) as potential non-invasive plasma markers of ongoing neurodegeneration from Parkinson's disease in human subjects.

METHODS

A panel of seven NAPEs were quantified by LC-MS/MS in the plasma of 587 individuals (healthy controls, n = 319; Parkinson's disease, n = 268); Random Forest classification and statistical modeling was applied to compare Parkinson's disease versus controls. All p-values obtained in different tests were corrected for multiplicity by controlling the false discovery rate (FDR).

RESULTS

The results indicate that this panel of NAPEs is able to distinguish female PD patients from the corresponding healthy controls. Further to this, the observed downregulation of these NAPEs is in line with the results in plasma of a mouse model of Parkinson's (6-OHDA).

CONCLUSIONS

In the current study we have shown the downregulation of NAPEs in plasma of PD patients and we thus speculate that these lipids might serve as candidate biomarkers for PD. We also suggest a molecular mechanism, explaining our findings, which involves gut microbiota.

T2*-weighted MRI values correlate with motor and cognitive dysfunction in Parkinson's disease

Brain iron load is one of the main neuropathologic hallmarks of Parkinson's disease (PD). Previous studies indicated that iron in the substantia nigra (SN) is related to disease duration and motor impairment. We explore, through a cross-sectional study, the association between brain iron distribution, evaluated by T2*-weighted magnetic resonance imaging (T2*), and clinical features in a cohort of patients with PD. Thirty-two patients with PD, compared with 10 control subjects, were evaluated for motor and cognitive features (attention and working memory, executive functions, language, memory, and visuospatial function). They underwent a magnetic resonance imaging protocol including T2* analysis of specific brain regions of interest to measure iron load compared with healthy control subjects. We found that iron content of the SN correlated positively with both disease duration and Unified Parkinson's Disease Rating Scale III off score. Montreal Cognitive Assessment, Spatial Span, and Graded Naming Test scores were inversely associated with iron load of the SN, whereas Wechsler Adult Intelligence Scale-IV Similarities score showed an inverse relationship with iron content in all the regions of interest examined. Our findings suggest a relationship between topographic brain iron distribution and cognitive domain impairment.

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.

Iron-related nigral degeneration influences functional topology mediated by striatal dysfunction in Parkinson's disease

In Parkinson's disease (PD), iron accumulation in the substantia nigra (SN) exacerbates oxidative stress and α-synuclein aggregation, leading to neuronal death. However, the influence of iron-related nigral degeneration on the subcortical function and global network configuration in PD remains unknown. Ninety PD patients and 38 normal controls underwent clinical assessments and multimodality magnetic resonance imaging scans. Iron accumulation in the inferior SN and disrupted functional connectivity between the bilateral striatums were observed in PD, and negative correlation between them was found in the whole population. The binarized functional network exhibited enhanced global efficiency and reduced local efficiency while the weighted functional network exhibited reduction in both, and both changes were correlated with nigral iron accumulation in PD. Mediation analysis demonstrated that the functional connectivity between bilateral striatums was a mediator between the nigral iron accumulation and weighted functional network alterations. In conclusion, our findings reveal that iron-related nigral degeneration possibly influences the functional topology mediated by striatal dysfunction, which extends the scientific understanding of PD pathogenesis.

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.

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.

Brain Iron Accumulation in Atypical Parkinsonian Syndromes: in vivo MRI Evidences for Distinctive Patterns

Recent data suggest mechanistic links among perturbed iron homeostasis, oxidative stress, and misfolded protein aggregation in neurodegenerative diseases. Iron overload and toxicity toward dopaminergic neurons have been established as playing a role in the pathogenesis of Parkinson's disease (PD). Brain iron accumulation has also been documented in atypical parkinsonian syndromes (APS), mainly comprising multiple system atrophy (MSA), and progressive supranuclear palsy (PSP). Iron-sensitive magnetic resonance imaging (MRI) has been applied to identify iron-related signal changes for the diagnosis and differentiation of these disorders. Topographic patterns of widespread iron deposition in deep brain nuclei have been described as differing between patients with MSA and PSP and those with PD. A disease-specific increase of iron occurs in the brain regions mainly affected by underlying disease pathologies. However, whether iron changes are a primary pathogenic factor or an epiphenomenon of neuronal degeneration has not been fully elucidated. Moreover, the clinical implications of iron-related pathology in APS remain unclear. In this review study, we collected data from qualitative and quantitative MRI studies on brain iron accumulation in APS to identify disease-related patterns and the potential role of iron-sensitive MRI.

Association of copper levels in the hair with gray matter volume, mean diffusivity, and cognitive functions

Although copper plays a critical role in normal brain functions and development, it is known that excess copper causes toxicity. Here we investigated the associations of copper levels in the hair with regional gray matter volume (rGMV), mean diffusivity (MD), and cognitive differences in a study cohort of 924 healthy young adults. Our findings showed that high copper levels were associated mostly with low cognitive abilities (low scores on the intelligence test consisting of complex speed tasks, involving reasoning task, a complex arithmetic task, and a reading comprehension task) as well as lower reverse Stroop interference, high rGMV over widespread areas of the brain [mainly including the bilateral lateral and medial parietal cortices, medial temporal structures (amygdala, hippocampus, and parahippocampal gyrus), middle cingulate cortex, orbitofrontal cortex, insula, perisylvian areas, inferior temporal lobe, temporal pole, occipital lobes, and supplementary motor area], as well as high MD of the right substantia nigra and bilateral hippocampus, which are indicative of low density in brain tissues. These results suggest that copper levels are associated with mostly aberrant cognitive functions, greater rGMV in extensive areas, greater MD (which are indicative of low density in brain tissues) in subcortical structures in the healthy young adults, possibly reflecting copper's complex roles in neural mechanisms.

Cortical thinning across Parkinson's disease stages and clinical correlates

BACKGROUND

Imaging studies have revealed cortical thinning and subcortical atrophy occurring in Parkinson's disease (PD); however, the topographical distribution and clinical associations related to advancing stages of PD remains unclear.

OBJECTIVE

We aimed to investigate the topographical distribution of cortical and subcortical morphometric changes, and their clinical associations, related to increasing disease severity.

METHODS

In this cross-sectional imaging study, T1-weighted structural magnetic resonance imaging data for 80 non-demented PD patients and 30 age-matched healthy controls were analysed using FreeSurfer software suite to derive morphometric changes using whole-brain vertex-wise analysis, and surface-based (cortical) and volume-based (subcortical) parcellation maps. PD patients were divided into three groups of mild (n = 27), moderate (n = 27), and severe (n = 26) PD based disease duration and Hoehn and Yahr and Unified Parkinson's Disease Rating Scale Part-III motor severity scores.

RESULTS

Whole-brain vertex-wise analysis revealed cortical thinning in the orbitofrontal cortex in early PD (P = .011), and in the superior frontal (P = .002), caudal middle frontal gyrus (P = .001) and inferior parietal cortex (P = .006) in moderate PD. Severe PD patients showed additional cortical thinning in temporal and occipital cortices (P < .005). Subcortical volume loss was detected in the thalamus (P = .012) and hippocampus (P = .032) in moderate PD, which extended to the caudate (P = .012), putamen (P = .042) and amygdala (P = .008) in severe PD. Increasing disease duration and motor severity scores, correlated with cortical thinning in frontal, temporal, parietal and occipital cortices, and subcortical volumetric loss in the thalamus, caudate, putamen, amygdala and hippocampus. Lower global cognitive status, measured with MMSE, correlated with cortical thinning in temporal, parietal, frontal and cingulate cortices, and with volumetric loss in the hippocampus (r = 0.31; P = .009); suggesting subclinical pathogenic changes occur prior to the onset of cognitive impairment.

CONCLUSION

In conclusion, in more severe disease stages PD patients exhibit progressive cortical thinning and subcortical volume loss which could have relevance to the development of cognitive impairment.

Neuroimaging and Neurolaw: Drawing the Future of Aging

Human brain-aging is a complex, multidimensional phenomenon. Knowledge of the numerous aspects that revolve around it is therefore essential if not only the medical issues, but also the social, psychological, and legal issues related to this phenomenon are to be managed correctly. In the coming decades, it will be necessary to find solutions to the management of the progressive aging of the population so as to increase the number of individuals that achieve successful aging. The aim of this article is to provide a current overview of the physiopathology of brain aging and of the role and perspectives of neuroimaging in this context. The progressive development of neuroimaging has opened new perspectives in clinical and basic research and it has modified the concept of brain aging. Neuroimaging will play an increasingly important role in the definition of the individual's brain aging in every phase of the physiological and pathological process. However, when the process involved in age-related brain cognitive diseases is being investigated, factors that might affect this process on a clinical and behavioral level (genetic susceptibility, risks factors, endocrine changes) cannot be ignored but must, on the contrary, be integrated into a neuroimaging evaluation to ensure a correct and global management, and they are therefore discussed in this article. Neuroimaging appears important to the correct management of age-related brain cognitive diseases not only within a medical perspective, but also legal, according to a wider approach based on development of relationship between neuroscience and law. The term neurolaw, the neologism born from the relationship between these two disciplines, is an emerging field of study, that deals with various issues in the impact of neurosciences on individual rights. Neuroimaging, enhancing the detection of physiological and pathological brain aging, could give an important contribution to the field of neurolaw in elderly where the full control of cognitive and volitional functions is necessary to maintain a whole series of rights linked to legal capacity. For this reason, in order to provide the clinician and researcher with a broad view of the brain-aging process, the role of neurolaw will be introduced into the brain-aging context.

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.