A review of the use of magnetic resonance imaging in Parkinson's disease

Lifestyle Modulators of Neuroplasticity in Parkinson's Disease: Evidence in Human Neuroimaging Studies

Parkinson's disease (PD) is a neurodegenerative disease characterized by both motor and non-motor symptoms. A progressive neuronal loss and the consequent clinical impairment lead to deleterious effects on daily living and quality of life. Despite effective symptomatic therapeutic approaches, no disease-modifying therapies are currently available. Emerging evidence suggests that adopting a healthy lifestyle can improve the quality of life of PD patients. In addition, modulating lifestyle factors can positively affect the microstructural and macrostructural brain levels, corresponding to clinical improvement. Neuroimaging studies may help to identify the mechanisms through which physical exercise, dietary changes, cognitive enrichment, and exposure to substances modulate neuroprotection. All these factors have been associated with a modified risk of developing PD, with attenuation or exacerbation of motor and non-motor symptomatology, and possibly with structural and molecular changes. In the present work, we review the current knowledge on how lifestyle factors influence PD development and progression and the neuroimaging evidence for the brain structural, functional, and molecular changes induced by the adoption of positive or negative lifestyle behaviours.

Diffusion and structural MRI as potential biomarkers in people with Parkinson's disease and cognitive impairment

OBJECTIVE

To explore the neuroimage change in Parkinson's disease (PD) patients with cognitive impairments, this study investigated the correlation between plasma biomarkers and morphological brain changes in patients with normal cognition and mild cognitive impairment. The objective was to identify the potential target deposition regions of the plasma biomarkers and to search for the relevant early neuroimaging biomarkers on the basis of different cognitive domains.

METHODS

Structural brain MRI and diffusion weighted images were analyzed from 49 eligible PD participants (male/female: 27/22; mean age: 73.4 ± 8.5 years) from a retrospective analysis. Plasma levels of α-synuclein, amyloid beta peptide, and total tau were collected. A comprehensive neuropsychological assessment of the general and specific cognitive domains was performed. Difference between PD patients with normal cognition and impairment was examined. Regression analysis was performed to evaluate the correlation between image-derived index and plasma biomarkers or neuropsychological assessments.

RESULTS

Significant correlation was found between plasma Aβ-42 level and fractional anisotropy of the middle occipital, angular, and middle temporal gyri of the left brain, as well as plasma T-tau level and the surface area of the isthmus or the average thickness of the posterior part of right cingulate gyrus. Visuospatial and executive function is positively correlated with axial diffusivity in bilateral cingulate gyri.

CONCLUSION

In nondemented PD patients, the target regions for plasma deposition might be located in the cingulate, middle occipital, angular, and middle temporal gyri. Changes from multiple brain regions can be correlated to the performance of different cognitive domains.

CLINICAL RELEVANCE STATEMENT

Cognitive impairment in Parkinson's disease is primarily linked to biomarkers associated with Alzheimer's disease rather than those related to Parkinson's disease and resembles the frontal variant of Alzheimer's disease, which may guide management strategies for cognitive impairment in Parkinson's disease.

KEY POINTS

• Fractional anisotropy, surface area, and thickness in the cingulate, middle occipital, angular, and middle temporal gyri can be significantly correlated with plasma Aβ-42 and T-tau level. • Axial diffusivity in the cingulate gyri was correlated with visuospatial and executive function. • The pattern of cognitive impairment in Parkinson's disease can be similar to the frontal variant than typical Alzheimer's disease.

Free water imaging unravels unique patterns of longitudinal structural brain changes in Parkinson's disease subtypes

Background

Research shows that individuals with Parkinson's disease (PD) who have a postural instability and gait difficulties (PIGD) subtype have a faster disease progression compared to those with a tremor dominant (TD) subtype. Nevertheless, our understanding of the structural brain changes contributing to these clinical differences remains limited, primarily because many brain imaging techniques are only capable of detecting changes in the later stages of the disease.

Objective

Free water (FW) has emerged as a robust progression marker in several studies, showing increased values in the posterior substantia nigra that predict symptom worsening. Here, we examined longitudinal FW changes in TD and PIGD across multiple brain regions.

Methods

Participants were TD and PIGD enrolled in the Parkinson's Progression Marker Initiative (PPMI) study who underwent diffusion MRI at baseline and 2 years later. FW changes were quantified for regions of interest (ROI) within the basal ganglia, thalamus, brainstem, and cerebellum.

Results

Baseline FW in all ROIs did not differ between groups. Over 2 years, PIGD had a greater percentage increase in FW in the putamen, globus pallidus, and cerebellar lobule V. A logistic regression model incorporating percent change in motor scores and FW in these brain regions achieved 91.4% accuracy in discriminating TD and PIGD, surpassing models based solely on clinical measures (74.3%) or imaging (76.1%).

Conclusion

The results further suggest the use of FW to study disease progression in PD and provide insight into the differential course of brain changes in early-stage PD subtypes.

Imaging the lower limb network in Parkinson's disease

BACKGROUND

Despite the significant impact of lower limb symptoms on everyday life activities in Parkinson's disease (PD), knowledge of the neural correlates of lower limb deficits is limited.

OBJECTIVE

We ran an fMRI study to investigate the neural correlates of lower limb movements in individuals with and without PD.

METHODS

Participants included 24 PD and 21 older adults who were scanned while performing a precisely controlled isometric force generation task by dorsiflexing their ankle. A novel MRI-compatible ankle dorsiflexion device that limits head motion during motor tasks was used. The PD were tested on their more affected side, whereas the side in controls was randomized. Importantly, PD were tested in the off-state, following overnight withdrawal from antiparkinsonian medication.

RESULTS

The foot task revealed extensive functional brain changes in PD compared to controls, with reduced fMRI signal during ankle dorsiflexion within the contralateral putamen and M1 foot area, and ipsilateral cerebellum. The activity of M1 foot area was negatively correlated with the severity of foot symptoms based on the Movement Disorder Society-Sponsored Revision of the Unified Parkinson's Disease Rating Scale (MDS-UPDRS-III).

CONCLUSION

Overall, current findings provide new evidence of brain changes underlying motor symptoms in PD. Our results suggest that pathophysiology of lower limb symptoms in PD appears to involve both the cortico-basal ganglia and cortico-cerebellar motor circuits.

Promising biomarkers and therapeutic targets for the management of Parkinson's disease: recent advancements and contemporary research

Parkinson's disease (PD) is one of the progressive neurological diseases which affect around 10 million population worldwide. The clinical manifestation of motor symptoms in PD patients appears later when most dopaminergic neurons have degenerated. Thus, for better management of PD, the development of accurate biomarkers for the early prognosis of PD is imperative. The present work will discuss the potential biomarkers from various attributes covering biochemical, microRNA, and neuroimaging aspects (α-synuclein, DJ-1, UCH-L1, β-glucocerebrosidase, BDNF, etc.) for diagnosis, recent development in PD management, and major limitations with current and conventional anti-Parkinson therapy. This manuscript summarizes potential biomarkers and therapeutic targets, based on available preclinical and clinical evidence, for better management of PD.

Sex Differences in Brain Structure in de novo Parkinson's Disease: A Cross-Sectional and Longitudinal Neuroimaging Study

BACKGROUND

Parkinson's disease (PD) varies in occurrence, presentation, and severity between males and females. However, the sex effects on the patterns of brain structure, cross-sectionally and longitudinally, are still unclear.

OBJECTIVE

We aimed to compare sex differences in brain features cross-sectionally and longitudinally using grey matter volume (GMV) and cortical thickness in a large sample of newly diagnosed drug-naive PD patients.

METHODS

Cognitive assessments and structural MR images of 262 PD patients (171 males) and 113 healthy controls (68 males) were selected from the Parkinson's Progression Markers Initiative. Of these, 97 PD patients (66 males) completed 12- and 24-month follow-up examinations. After regressing out the expected effects of age and sex, brain maps of GMV and cortical thickness were compared using two-sample t tests cross-sectionally and were compared using repeated measurement analyses of variance longitudinally.

RESULTS

At baseline, male PD patients exhibited a greater extent of brain atrophy and cortical thickness reduction than females, which mainly occurred in the cerebellum, frontal lobe, parietal lobe, and temporal lobe. At follow-up, female and male PD patients showed similar dynamics of disease progression, as both groups declined over time while the females maintained the advantage. The cortical thickness of the right precentral gyrus at baseline was negatively associated with the longitudinal changes of motor function in male PD patients.

CONCLUSION

The current findings might demonstrate sex effect in neuroanatomy during the course of PD, provide new insights into the neurodegenerative process, and facilitate the development of more effective sex-specific therapeutic strategies.

A systematic review of brain morphometry related to deep brain stimulation outcome in Parkinson's disease

While the efficacy of deep brain stimulation (DBS) is well-established in Parkinson’s Disease (PD), the benefit of DBS varies across patients. Using imaging features for outcome prediction offers potential in improving effectiveness, whereas the value of presurgical brain morphometry, derived from the routinely used imaging modality in surgical planning, remains under-explored. This review provides a comprehensive investigation of links between DBS outcomes and brain morphometry features in PD. We systematically searched PubMed and Embase databases and retrieved 793 articles, of which 25 met inclusion criteria and were reviewed in detail. A majority of studies (24/25), including 1253 of 1316 patients, focused on the outcome of DBS targeting the subthalamic nucleus (STN), while five studies included 57 patients receiving globus pallidus internus (GPi) DBS. Accumulated evidence showed that the atrophy of motor cortex and thalamus were associated with poor motor improvement, other structures such as the lateral-occipital cortex and anterior cingulate were also reported to correlated with motor outcome. Regarding non-motor outcomes, decreased volume of the hippocampus was reported to correlate with poor cognitive outcomes. Structures such as the thalamus, nucleus accumbens, and nucleus of basalis of Meynert were also reported to correlate with cognitive functions. Caudal middle frontal cortex was reported to have an impact on postsurgical psychiatric changes. Collectively, the findings of this review emphasize the utility of brain morphometry in outcome prediction of DBS for PD. Future efforts are needed to validate the findings and demonstrate the feasibility of brain morphometry in larger cohorts.

Decreased soluble Nogo-B in serum as a promising biomarker for Parkinson's disease

Background

Recently, the neurite outgrowth inhibitor-B (Nogo-B) receptor has been reported as a novel candidate gene for Parkinson's disease (PD). Nogo-B receptors need to combine with soluble Nogo-B to exert their physiological function. However, little is known about the relationship between serum soluble Nogo-B and PD.

Methods

Serum levels of sNogo-B and α-Synuclein (α-Syn) were measured in a cohort of 53 patients with PD and 49 healthy controls with the ELISA kit method.

Results

Serum sNogo-B level is significantly lower in the PD group than that in healthy controls and is negatively correlated with UPDRS-III score (p = 0.049), H&Y stage (p = 0.0108) as well as serum α-Syn level (p = 0.0001). The area under the curve (AUC) of serum sNogo-B in differentiating patients with PD from controls was 0.801 while the AUC of serum α-Syn was 0.93. Combining serum sNogo-B and α-Syn in differentiating patients with PD from HC presented higher discriminatory potential (AUC = 0.9534).

Conclusion

Decreased serum sNogo-B may be a potential biomarker for PD. Lower Nogo-B level reflects worse motor function and disease progression of PD. Serum sNogo-B is of added value to serum α-Syn panel in distinguishing PD from controls. Future studies are needed to confirm in larger samples and different populations.

A brief history of brain iron accumulation in Parkinson disease and related disorders

Iron has a long and storied history in Parkinson disease and related disorders. This essential micronutrient is critical for normal brain function, but abnormal brain iron accumulation has been associated with extrapyramidal disease for a century. Precisely why, how, and when iron is implicated in neuronal death remains the subject of investigation. In this article, we review the history of iron in movement disorders, from the first observations in the early twentieth century to recent efforts that view extrapyramidal iron as a novel therapeutic target and diagnostic indicator.

A brief history of brain iron accumulation in Parkinson disease and related disorders

Iron has a long and storied history in Parkinson disease and related disorders. This essential micronutrient is critical for normal brain function, but abnormal brain iron accumulation has been associated with extrapyramidal disease for a century. Precisely why, how, and when iron is implicated in neuronal death remains the subject of investigation. In this article, we review the history of iron in movement disorders, from the first observations in the early twentieth century to recent efforts that view extrapyramidal iron as a novel therapeutic target and diagnostic indicator.

Structural and Functional Alterations of Substantia Nigra and Associations With Anxiety and Depressive Symptoms Following Traumatic Brain Injury

Backgrounds

Although there are a certain number of studies dedicated to the disturbances of the dopaminergic system induced by traumatic brain injury (TBI), the associations of abnormal dopaminergic systems with post-traumatic anxiety and depressive disorders and their underlying mechanisms have not been clarified yet. In the midbrain, dopaminergic neurons are mainly situated in the substantia nigra (SN) and the ventral tegmental area (VTA). Thus, we selected SN and VTA as regions of interest and performed a seed-based global correlation to evaluate the altered functional connectivity throughout the dopaminergic system post-TBI.

Methods

Thirty-three individuals with TBI and 21 healthy controls were recruited in the study. Anxiety and depressive symptoms were examined by the Hospital Anxiety and Depression Scale. All MRI data were collected using a Siemens Prisma 3.0 Tesla MRI system. The volume of SN and the global functional connectivity of the SN and VTA were analyzed.

Results

In the present study, patients with TBI reported more anxiety and depressive symptoms. More importantly, some structural and functional alterations, such as smaller SN and reduced functional connectivity in the left SN, were seen in individuals with TBI. Patients with TBI had smaller substantia nigra on both right and left sides, and the left substantia nigra was relatively small in contrast with the right one. Among these findings, functional connectivity between left SN and left angular gyrus was positively associated with post-traumatic anxiety symptoms and negatively associated with depressive symptoms.

Conclusions

The TBI causes leftward lateralization of structural and functional alterations in the substantia nigra. An impaired mesocortical functional connectivity might be implicated in post-traumatic anxiety and depression.

Application of the anatomical fiducials framework to a clinical dataset of patients with Parkinson's disease

Establishing spatial correspondence between subject and template images is necessary in neuroimaging research and clinical applications such as brain mapping and stereotactic neurosurgery. Our anatomical fiducial (AFID) framework has recently been validated to serve as a quantitative measure of image registration based on salient anatomical features. In this study, we sought to apply the AFIDs protocol to the clinic, focusing on structural magnetic resonance images obtained from patients with Parkinson's disease (PD). We confirmed AFIDs could be placed to millimetric accuracy in the PD dataset with results comparable to those in normal control subjects. We evaluated subject-to-template registration using this framework by aligning the clinical scans to standard template space using a robust open preprocessing workflow. We found that registration errors measured using AFIDs were higher than previously reported, suggesting the need for optimization of image processing pipelines for clinical grade datasets. Finally, we examined the utility of using point-to-point distances between AFIDs as a morphometric biomarker of PD, finding evidence of reduced distances between AFIDs that circumscribe regions known to be affected in PD including the substantia nigra. Overall, we provide evidence that AFIDs can be successfully applied in a clinical setting and utilized to provide localized and quantitative measures of registration error. AFIDs provide clinicians and researchers with a common, open framework for quality control and validation of spatial correspondence and the location of anatomical structures, facilitating aggregation of imaging datasets and comparisons between various neurological conditions.

Neurodegenerative Disorders of Alzheimer, Parkinsonism, Amyotrophic Lateral Sclerosis and Multiple Sclerosis: An Early Diagnostic Approach for Precision Treatment

Neurodegenerative diseases (NDs) are characterised by progressive dysfunction of synapses, neurons, glial cells and their networks. Neurodegenerative diseases can be classified according to primary clinical features (e.g., dementia, parkinsonism, or motor neuron disease), anatomic distribution of neurodegeneration (e.g., frontotemporal degenerations, extrapyramidal disorders, or spinocerebellar degenerations), or principal molecular abnormalities. The most common neurodegenerative disorders are amyloidosis, tauopathies, a-synucleinopathy, and TAR DNA-binding protein 43 (TDP-43) proteopathy. The protein abnormalities in these disorders have abnormal conformational properties along with altered cellular mechanisms, and they exhibit motor deficit, mitochondrial malfunction, dysfunctions in autophagic-lysosomal pathways, synaptic toxicity, and more emerging mechanisms such as the roles of stress granule pathways and liquid-phase transitions. Finally, for each ND, microglial cells have been reported to be implicated in neurodegeneration, in particular, because the microglial responses can shift from neuroprotective to a deleterious role. Growing experimental evidence suggests that abnormal protein conformers act as seed material for oligomerization, spreading from cell to cell through anatomically connected neuronal pathways, which may in part explain the specific anatomical patterns observed in brain autopsy sample. In this review, we mention the human pathology of select neurodegenerative disorders, focusing on how neurodegenerative disorders (i.e., Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, and multiple sclerosis) represent a great healthcare problem worldwide and are becoming prevalent because of the increasing aged population. Despite many studies have focused on their etiopathology, the exact cause of these diseases is still largely unknown and until now with the only available option of symptomatic treatments. In this review, we aim to report the systematic and clinically correlated potential biomarker candidates. Although future studies are necessary for their use in early detection and progression in humans affected by NDs, the promising results obtained by several groups leads us to this idea that biomarkers could be used to design a potential therapeutic approach and preclinical clinical trials for the treatments of NDs.

Can Dopamine Responsiveness Be Predicted in Parkinson's Disease Without an Acute Administration Test?

BACKGROUND

Dopamine responsiveness (dopa-sensitivity) is an important parameter in the management of patients with Parkinson's disease (PD). For quantification of this parameter, patients undergo a challenge test with acute Levodopa administration after drug withdrawal, which may lead to patient discomfort and use of significant resources.

OBJECTIVE

Our objective was to develop a predictive model combining clinical scores and imaging.

METHODS

350 patients, recruited by 13 specialist French centers and considered for deep brain stimulation, underwent an acute L-dopa challenge (dopa-sensitivity > 30%), full assessment, and MRI investigations, including T1w and R2* images. Data were randomly divided into a learning base from 10 centers and data from the remaining centers for testing. A machine selection approach was applied to choose the optimal variables and these were then used in regression modeling. Complexity of the modelling was incremental, while the first model considered only clinical variables, the subsequent included imaging features. The performances were evaluated by comparing the estimated values and actual valuesResults:Whatever the model, the variables age, sex, disease duration, and motor scores were selected as contributors. The first model used them and the coefficients of determination (R2) was 0.60 for the testing set and 0.69 in the learning set (p < 0.001). The models that added imaging features enhanced the performances: with T1w (R2 = 0.65 and 0.76, p < 0.001) and with R2* (R2 = 0.60 and 0.72, p < 0.001).

CONCLUSION

These results suggest that modeling is potentially a simple way to estimate dopa-sensitivity, but requires confirmation in a larger population, including patients with dopa-sensitivity < 30.

Subcortical Iron Accumulation Pattern May Predict Neuropsychological Outcomes After Subthalamic Nucleus Deep Brain Stimulation: A Pilot Study

BACKGROUND:

Neuropsychological outcomes after deep brain stimulation (DBS) are variable and may arise from the heterogeneous neuropathological processes in Parkinson’s disease (PD).

OBJECTIVE:

To explore if brain iron accumulation patterns and its region-specific alterations relate to neuropsychological outcomes post-DBS.

METHODS:

Thirty-two PD subjects were identified from our database with susceptibility MRI prior to bilateral subthalamic nucleus (STN) DBS between 2011–2016. Demographic (age, sex, education), clinical information (disease duration, neuropsychological scores), and R2* (susceptibility MRI measure reflecting iron) in 11 subcortical regions of interest were obtained. Neuropsychological outcomes were defined as changes in psychomotor speed, executive function, attention, memory, and depression by subtracting pre- and post-DBS scores. A penalized logistic analysis was used to identify the best pre-DBS clinical and R2* predictors for each neuropsychological domain. Pearson’s partial correlations explored R2* associations with neuropsychological outcomes.

RESULTS:

Combined clinical and MRI metrics were associated better with neuropsychological outcomes (R²≥0.373, p-value≤0.008) than either alone. Adding R2* metrics increased prediction of executive function (R²=0.455, p=0.008) and attention (R²=0.182, p=0.018) outcomes over clinical metrics alone. Specifically, R2* in the substantia nigra, caudate, STN, and hippocampus improved prediction of executive function, and in the putamen for attention. Interestingly, higher caudate R2* correlated with better executive function (p=0.043), whereas higher putamen R2* associated with worsening attention (p=0.018).

CONCLUSIONS:

Brain iron accumulation patterns, captured by susceptibility MRI, may add value to clinical evaluation in predicting neuropsychological outcomes post-DBS in PD. Further studies are warranted to validate these findings and understand the region-specific relationships between iron and DBS outcomes.

Multi-Focus Image Fusion Based on Convolution Neural Network for Parkinson's Disease Image Classification

Parkinson's disease (PD) is a common neurodegenerative disease that has a significant impact on people's lives. Early diagnosis is imperative since proper treatment stops the disease's progression. With the rapid development of CAD techniques, there have been numerous applications of computer-aided diagnostic (CAD) techniques in the diagnosis of PD. In recent years, image fusion has been applied in various fields and is valuable in medical diagnosis. This paper mainly adopts a multi-focus image fusion method primarily based on deep convolutional neural networks to fuse magnetic resonance images (MRI) and positron emission tomography (PET) neural photographs into multi-modal images. Additionally, the study selected Alexnet, Densenet, ResNeSt, and Efficientnet neural networks to classify the single-modal MRI dataset and the multi-modal dataset. The test accuracy rates of the single-modal MRI dataset are 83.31%, 87.76%, 86.37%, and 86.44% on the Alexnet, Densenet, ResNeSt, and Efficientnet, respectively. Moreover, the test accuracy rates of the multi-modal fusion dataset on the Alexnet, Densenet, ResNeSt, and Efficientnet are 90.52%, 97.19%, 94.15%, and 93.39%. As per all four networks discussed above, it can be concluded that the test results for the multi-modal dataset are better than those for the single-modal MRI dataset. The experimental results showed that the multi-focus image fusion method according to deep learning can enhance the accuracy of PD image classification.

The role of neuroimaging in Parkinson's disease

Parkinson's disease (PD) is a neurodegenerative disorder that affects millions of people worldwide. Two hallmarks of PD are the accumulation of alpha-synuclein and the loss of dopaminergic neurons in the brain. There is no cure for PD, and all existing treatments focus on alleviating the symptoms. PD diagnosis is also based on the symptoms, such as abnormalities of movement, mood, and cognition observed in the patients. Molecular imaging methods such as magnetic resonance imaging (MRI), single-photon emission computed tomography (SPECT), and positron emission tomography (PET) can detect objective alterations in the neurochemical machinery of the brain and help diagnose and study neurodegenerative diseases. This review addresses the application of functional MRI, PET, and SPECT in PD patients. We provide an overview of the imaging targets, discuss the rationale behind target selection, the agents (tracers) with which the imaging can be performed, and the main findings regarding each target's state in PD. Molecular imaging has proven itself effective in supporting clinical diagnosis of PD and has helped reveal that PD is a heterogeneous disorder, which has important implications for the development of future therapies. However, the application of molecular imaging for early diagnosis of PD or for differentiation between PD and atypical parkinsonisms has remained challenging. The final section of the review is dedicated to new imaging targets with which one can detect the PD-related pathological changes upstream from dopaminergic degeneration. The foremost of those targets is alpha-synuclein. We discuss the progress of tracer development achieved so far and challenges on the path toward alpha-synuclein imaging in humans.

Neuroplasticity mediated by motor rehabilitation in Parkinson's disease: a systematic review on structural and functional MRI markers

Parkinson's disease (PD) is the second most common neurological disease affecting the elderly population. Pharmacological and surgical interventions usually employed for PD treatment show transient effectiveness and are associated with the insurgence of side effects. Therefore, motor rehabilitation has been proposed as a promising supplement in the treatment of PD, reducing the global burden of the disease and improving patients quality of life. The present systematic review aimed to critically analyse the literature concerning MRI markers of brain functional and structural response to motor rehabilitation in PD. Fourteen out of 1313 studies were selected according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses criteria. Despite the limited number of retrieved studies coupled with their heterogeneity prevent ultimate conclusions from being drawn, motor rehabilitation seems to have beneficial effects on PD as measured both with clinical outcomes and MRI derived indices. Interestingly, consistent results seem to indicate that motor rehabilitation acts via a dual mechanism of strengthening cortico-subcortical pathways, restoring movements automaticity, or activating compensatory networks such as the fronto-parietal one. The employment of more advanced and quantitative MRI methods is warranted to establish and validate standardized metrics capable of reliably determining the changes induced by rehabilitative intervention.

Alpha-Synuclein as a Biomarker of Parkinson's Disease: Good, but Not Good Enough

Parkinson's disease (PD) is the second most common neurodegenerative disorder of the elderly, presenting primarily with symptoms of motor impairment. The disease is diagnosed most commonly by clinical examination with a great degree of accuracy in specialized centers. However, in some cases, non-classical presentations occur when it may be difficult to distinguish the disease from other types of degenerative or non-degenerative movement disorders with overlapping symptoms. The diagnostic difficulty may also arise in patients at the early stage of PD. Thus, a biomarker could help clinicians circumvent such problems and help them monitor the improvement in disease pathology during anti-parkinsonian drug trials. This review first provides a brief overview of PD, emphasizing, in the process, the important role of α-synuclein in the pathogenesis of the disease. Various attempts made by the researchers to develop imaging, genetic, and various biochemical biomarkers for PD are then briefly reviewed to point out the absence of a definitive biomarker for this disorder. In view of the overwhelming importance of α-synuclein in the pathogenesis, a detailed analysis is then made of various studies to establish the biomarker potential of this protein in PD; these studies measured total α-synuclein, oligomeric, and post-translationally modified forms of α-synuclein in cerebrospinal fluid, blood (plasma, serum, erythrocytes, and circulating neuron-specific extracellular vesicles) and saliva in combination with certain other proteins. Multiple studies also examined the accumulation of α-synuclein in various forms in PD in the neural elements in the gut, submandibular glands, skin, and the retina. The measurements of the levels of certain forms of α-synuclein in some of these body fluids or their components or peripheral tissues hold a significant promise in establishing α-synuclein as a definitive biomarker for PD. However, many methodological issues related to detection and quantification of α-synuclein have to be resolved, and larger cross-sectional and follow-up studies with controls and patients of PD, parkinsonian disorders, and non-parkinsonian movement disorders are to be undertaken.

Imaging the Substantia Nigra in Parkinson Disease and Other Parkinsonian Syndromes

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

MRI Signs of Parkinson's Disease and Atypical Parkinsonism

BACKGROUND

 Diagnosis of Parkinson's disease and atypical parkinsonism is based on clinical evaluation of the patient's symptoms and on magnetic resonance imaging (MRI) of the brain, which can be supplemented by nuclear medicine techniques. MRI plays a leading role in the differentiation between Parkinson's disease and atypical parkinsonism. While atypical parkinsonism is characterized by relatively specific MRI signs, imaging of Parkinson's disease previously lacked such signs. However, high-field MRI and new optimized MRI sequences now make it possible to define specific MRI signs of Parkinson's disease and have significant potential regarding differentiated imaging, early diagnosis, and imaging of disease progression.

METHODS

 PubMed was selectively searched for literature regarding the definition and discussion of specific MRI signs of Parkinson's disease, as well as the most common types of atypical parkinsonism with a leading motor component. No time frame was set, but the search was particularly focused on current literature.

RESULTS

 This review article discusses the different MRI signs of Parkinson's disease, multiple system atrophy, and progressive supranuclear palsy. The pathogenesis of the MRI signs is described, and imaging examples are given. The technical aspects of image acquisition are briefly defined, and the different signs are discussed and compared with regard to their diagnostic significance according to current literature.

CONCLUSION

 The MRI signs of Parkinson's disease, which can be defined with high-field MRI and new optimized MRI sequences, enable differentiated structural image interpretation and consecutive diagnostic workup. Despite the fact that the signs are in need of further validation by bigger studies, they have the potential to achieve significant diagnostic relevance regarding the imaging of Parkinson's disease and atypical parkinsonism.

KEY POINTS

  · High-field MRI and specialized sequences make it possible to define specific MRI signs for neurodegenerative disorders. · Cerebral alterations can be detected in prodromal stages of Parkinson's disease. · The combination of specific MRI signs makes it possible to differentiate between Parkinson's disease and atypical parkinsonism.

CITATION FORMAT

· Aludin S, Schmill LA. MRI Signs of Parkinson's Disease and Atypical Parkinsonism. Fortschr Röntgenstr 2021; DOI: 10.1055/a-1460-8795.

A Systematic Review of MRI Neuroimaging for Education Research

This study aims to disclose how the magnetic resonance imaging (MRI) neuroimaging approach has been applied in education studies, and what kind of learning themes has been investigated in the reviewed MRI neuroimaging research. Based on the keywords “brain or neuroimaging or neuroscience” and “MRI or diffusion tensor imaging (DTI) or white matter or gray matter or resting-state,” a total of 25 papers were selected from the subject areas “Educational Psychology” and “Education and Educational Research” from the Web of Science and Scopus from 2000 to 2019. Content analysis showed that MRI neuroimaging and learning were studied under the following three major topics and nine subtopics: cognitive function (language, creativity, music, physical activity), science education (mathematical learning, biology learning, physics learning), and brain development (parenting, personality development). As for the type of MRI neuroimaging research, the most frequently used approaches were functional MRI, followed by structural MRI and DTI, although the choice of approach was often motivated by the specific research question. Research development trends show that the neural plasticity theme has become more prominent recently. This study concludes that in educational research, the MRI neuroimaging approach provides objective and empirical evidence to connect learning processes, outcomes, and brain mechanisms.

No Detectable Effect on Visual Responses Using Functional MRI in a Rodent Model of α-Synuclein Expression

Parkinson's disease (PD) is a progressive neurodegenerative disease that is typically diagnosed late in its progression. There is a need for biomarkers suitable for monitoring the disease progression at earlier stages to guide the development of novel neuroprotective therapies. One potential biomarker, α-synuclein, has been found in both the familial cases of PD, as well as the sporadic cases and is considered a key feature of PD. α-synuclein is naturally present in the retina, and it has been suggested that early symptoms of the visual system may be used as a biomarker for PD. Here, we use a viral vector to induce a unilateral expression of human wild-type α-synuclein in rats as a mechanistic model of protein aggregation in PD. We employed functional magnetic resonance imaging (fMRI) to investigate whether adeno-associated virus (AAV) mediated expression of human wild-type α-synuclein alter functional activity in the visual system. A total of 16 rats were injected with either AAV-α-synuclein (n = 7) or AAV-null (n = 9) in the substantia nigra pars compacta (SNc) of the left hemisphere. The expression of α-synuclein was validated by a motor assay and postmortem immunohistochemistry. Five months after the introduction of the AAV-vector, fMRI showed robust blood oxygen level-dependent (BOLD) responses to light stimulation in the visual systems of both control and AAV-α-synuclein animals. However, our results demonstrate that the expression of AAV-α-synuclein does not affect functional activation of the visual system. This negative finding suggests that fMRI-based read-outs of visual responses may not be a sensitive biomarker for PD.

Multiparametric Quantitative MRI in Neurological Diseases

Magnetic resonance imaging (MRI) is the gold standard imaging technique for diagnosis and monitoring of many neurological diseases. However, the application of conventional MRI in clinical routine is mainly limited to the visual detection of macroscopic tissue pathology since mixed tissue contrasts depending on hardware and protocol parameters hamper its application for the assessment of subtle or diffuse impairment of the structural tissue integrity. Multiparametric quantitative (q)MRI determines tissue parameters quantitatively, enabling the detection of microstructural processes related to tissue remodeling in aging and neurological diseases. In contrast to measuring tissue atrophy via structural imaging, multiparametric qMRI allows for investigating biologically distinct microstructural processes, which precede changes of the tissue volume. This facilitates a more comprehensive characterization of tissue alterations by revealing early impairment of the microstructural integrity and specific disease-related patterns. So far, qMRI techniques have been employed in a wide range of neurological diseases, including in particular conditions with inflammatory, cerebrovascular and neurodegenerative pathology. Numerous studies suggest that qMRI might add valuable information, including the detection of microstructural tissue damage in areas appearing normal on conventional MRI and unveiling the microstructural correlates of clinical manifestations. This review will give an overview of current qMRI techniques, the most relevant tissue parameters and potential applications in neurological diseases, such as early (differential) diagnosis, monitoring of disease progression, and evaluating effects of therapeutic interventions.

Functional Connectomics and Disease Progression in Drug-Naïve Parkinson's Disease Patients

BACKGROUND

Functional brain connectivity alterations may be detectable even before the occurrence of brain atrophy, indicating their potential as early markers of pathological processes.

OBJECTIVE

We aimed to determine the whole-brain network topologic organization of the functional connectome in a large cohort of drug-naïve Parkinson's disease (PD) patients using resting-state functional magnetic resonance imaging and to explore whether baseline connectivity changes may predict clinical progression.

METHODS

One hundred and forty-seven drug-naïve, cognitively unimpaired PD patients were enrolled in the study at baseline and compared to 38 age- and gender-matched controls. Non-hierarchical cluster analysis using motor and non-motor data was applied to stratify PD patients into two subtypes: 77 early/mild and 70 early/severe. Graph theory analysis and connectomics were used to assess global and local topological network properties and regional functional connectivity at baseline. Stepwise multivariate regression analysis investigated whether baseline functional imaging data were predictors of clinical progression over 2 years.

RESULTS

At baseline, widespread functional connectivity abnormalities were detected in the basal ganglia, sensorimotor, frontal, and occipital networks in PD patients compared to controls. Decreased regional functional connectivity involving mostly striato-frontal, temporal, occipital, and limbic connections differentiated early/mild from early/severe PD patients. Connectivity changes were found to be independent predictors of cognitive progression at 2-year follow-up.

CONCLUSIONS

Our findings revealed that functional reorganization of the brain connectome occurs early in PD and underlies crucial involvement of striatal projections. Connectomic measures may be helpful to identify a specific PD patient subtype, characterized by severe motor and non-motor clinical burden as well as widespread functional connectivity abnormalities. © 2021 International Parkinson and Movement Disorder Society.

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

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

Texture-based markers from structural imaging correlate with motor handicap in Parkinson's disease

There is a growing need for surrogate biomarkers for Parkinson’s disease (PD). Structural analysis using magnetic resonance imaging with T1-weighted sequences has the potential to quantify histopathological changes. Degeneration is typically measured by the volume and shape of morphological changes. However, these changes appear late in the disease, preventing their use as surrogate markers. We investigated texture changes in 108 individuals, divided into three groups, matched in terms of sex and age: (1) healthy controls (n = 32); (2) patients with early-stage PD (n = 39); and (3) patients with late-stage PD and severe L-dopa-related complications (n = 37). All patients were assessed in off-treatment conditions. Statistical analysis of first- and second-order texture features was conducted in the substantia nigra, striatum, thalamus and sub-thalamic nucleus. Regions of interest volumetry and voxel-based morphometry were performed for comparison. Significantly different texture features were observed between the three populations, with some showing a gradual linear progression between the groups. The volumetric changes in the two PD patient groups were not significantly different. Texture features were significantly associated with clinical scores for motor handicap. These results suggest that texture features, measured in the nigrostriatal pathway at PD diagnosis, may be useful in predicting clinical progression of motor handicap.

Differential diagnosis of tremor syndromes using MRI relaxometry

Differential diagnosis of the most common tremor syndromes - essential tremor (ET) and Parkinson's disease (PD) is burdened with high error rate. However, diagnostic MRI biomarkers applicable in this clinically highly relevant scenario remain an unfulfilled objective. The presented study was designed in search for possible candidate MRI protocols relevant for differential diagnostic process in tremor syndromes.10 non-advanced tremor-dominant PD patients meeting diagnostic criteria for clinically established PD, 12 isolated ET patients and 16 healthy controls were enrolled into this study. The study focused on relaxation MRI protocols - T1, T2, adiabatic T1ρ and adiabatic T2ρ due to their relatively low post-processing requirements enabling implementation into routine clinical practice. Compared to ET, PD patients had significantly longer T2 relaxation times in striata with dominant findings in the putamen contralateral to the clinically more affected body side. This difference was driven by alterations in the PD group as confirmed in the complementary comparison with healthy controls. According to the receiver operating characteristic analysis, this region provided a reasonable sensitivity of 0.91 and specificity of 0.89 in the differential diagnosis of PD and ET. In PD patients, we further found prolonged T1ρ in the substantia nigra compared to ET and healthy controls, and shorter T2 and T2ρ in the cerebellum compared to healthy controls. T2 relaxation time in the putamen contralateral to the clinically more affected body side is a plausible candidate diagnostic marker for the differentiation of PD and ET.

Diagnostic Ability of Radiofrequency Ultrasound in Parkinson’s Disease Compared to Conventional Transcranial Sonography and Magnetic Resonance Imaging

We aimed to estimate tissue displacements’ parameters in midbrain using ultrasound radiofrequency (RF) signals and to compare diagnostic ability of this RF transcranial sonography (TCS)-based dynamic features of disease affected tissues with conventional TCS (cTCS) and magnetic resonance imaging (MRI) while differentiating patients with Parkinson’s disease (PD) from healthy controls (HC). US tissue displacement waveform parametrization by RF TCS for endogenous brain tissue motion, standard neurological examination, cTCS and MRI data collection were performed for 20 PD patients and for 20 age- and sex-matched HC in a prospective manner. Three logistic regression models were constructed, and receiver operating characteristic (ROC) curve analyses were applied. The model constructed of RF TCS-based brain tissue displacement parameters—frequency of high-end spectra peak and root mean square—revealed presumably increased anisotropy in the midbrain and demonstrated rather good diagnostic ability in the PD evaluation, although it was not superior to that of the cTCS or MRI. Future studies are needed in order to establish the true place of RF TCS detected tissue displacement parameters for the evaluation of pathologically affected brain tissue.

Methodological Considerations for Neuroimaging in Deep Brain Stimulation of the Subthalamic Nucleus in Parkinson's Disease Patients

Deep brain stimulation (DBS) of the subthalamic nucleus is a neurosurgical intervention for Parkinson's disease patients who no longer appropriately respond to drug treatments. A small fraction of patients will fail to respond to DBS, develop psychiatric and cognitive side-effects, or incur surgery-related complications such as infections and hemorrhagic events. In these cases, DBS may require recalibration, reimplantation, or removal. These negative responses to treatment can partly be attributed to suboptimal pre-operative planning procedures via direct targeting through low-field and low-resolution magnetic resonance imaging (MRI). One solution for increasing the success and efficacy of DBS is to optimize preoperative planning procedures via sophisticated neuroimaging techniques such as high-resolution MRI and higher field strengths to improve visualization of DBS targets and vasculature. We discuss targeting approaches, MRI acquisition, parameters, and post-acquisition analyses. Additionally, we highlight a number of approaches including the use of ultra-high field (UHF) MRI to overcome limitations of standard settings. There is a trade-off between spatial resolution, motion artifacts, and acquisition time, which could potentially be dissolved through the use of UHF-MRI. Image registration, correction, and post-processing techniques may require combined expertise of traditional radiologists, clinicians, and fundamental researchers. The optimization of pre-operative planning with MRI can therefore be best achieved through direct collaboration between researchers and clinicians.

Cerebral blood flow in dystonia due to pantothenate kinase-associated neurodegeneration

BACKGROUND AND PURPOSE

The aim of this study was to look for deviations of cerebral perfusion in patients suffering from pantothenate kinase-associated neurodegeneration, where the globus pallidus is affected by severe accumulation of iron.

MATERIAL AND METHODS

Under resting conditions, cerebral blood flow was measured by the magnetic resonance imaging technique of arterial spin labelling in cortical areas and basal ganglia in eight pantothenate kinase-associated neurodegeneration patients and 14 healthy age-matched control subjects and correlated to T2* time of these areas and - in patients - to clinical parameters.

RESULTS

Despite highly significant differences of T2* time of the globus pallidus (20 vs 39 ms, p < 0.001), perfusion values of this nucleus were nearly identical in both groups (32 ± 3.3 vs 31 ± 4.0 ml/min/100 g) as well as in total brain gray matter (both 62 ± 6.7 resp. ±10.3 ml/min/100 g), putamen (41 ± 5.4 vs 40 ± 6.1 ml/min/100 g), in selected cortical regions, and the cerebellum. Correlations between perfusion and T2* time to clinical data did not reach significance (p > 0.05).

CONCLUSION

The absence of any obvious deviations of perfusion in the group of patients during a resting condition does not support the view that (non-functional) vascular pathology is a major pathogenic factor in pantothenate kinase-associated neurodegeneration in the younger age group. The findings underline the value of the arterial spin technique to measure cerebral blood flow in areas of disturbed susceptibility.

Cohort profile: the Oxford Parkinson's Disease Centre Discovery Cohort MRI substudy (OPDC-MRI)

PURPOSE

The Oxford Parkinson's Disease Centre (OPDC) Discovery Cohort MRI substudy (OPDC-MRI) collects high-quality multimodal brain MRI together with deep longitudinal clinical phenotyping in patients with Parkinson's, at-risk individuals and healthy elderly participants. The primary aim is to detect pathological changes in brain structure and function, and develop, together with the clinical data, biomarkers to stratify, predict and chart progression in early-stage Parkinson's and at-risk individuals.

PARTICIPANTS

Participants are recruited from the OPDC Discovery Cohort, a prospective, longitudinal study. Baseline MRI data are currently available for 290 participants: 119 patients with early idiopathic Parkinson's, 15 Parkinson's patients with pathogenic mutations of the leucine-rich repeat kinase 2 or glucocerebrosidase (GBA) genes, 68 healthy controls and 87 individuals at risk of Parkinson's (asymptomatic carriers of GBA mutation and patients with idiopathic rapid eye movement sleep behaviour disorder-RBD).

FINDINGS TO DATE

Differences in brain structure in early Parkinson's were found to be subtle, with small changes in the shape of the globus pallidus and evidence of alterations in microstructural integrity in the prefrontal cortex that correlated with performance on executive function tests. Brain function, as assayed with resting fMRI yielded more substantial differences, with basal ganglia connectivity reduced in early Parkinson'sand RBD. Imaging of the substantia nigra with the more recent adoption of sequences sensitive to iron and neuromelanin content shows promising results in identifying early signs of Parkinsonian disease.

FUTURE PLANS

Ongoing studies include the integration of multimodal MRI measures to improve discrimination power. Follow-up clinical data are now accumulating and will allow us to correlate baseline imaging measures to clinical disease progression. Follow-up MRI scanning started in 2015 and is currently ongoing, providing the opportunity for future longitudinal imaging analyses with parallel clinical phenotyping.

A Study of the Relationship Between Uric Acid and Substantia Nigra Brain Connectivity in Patients With REM Sleep Behavior Disorder and Parkinson's Disease

Low levels of the natural antioxidant uric acid (UA) and the presence of REM sleep behavior disorder (RBD) are both associated with an increased likelihood of developing Parkinson's disease (PD). RBD and PD are also accompanied by basal ganglia dysfunction including decreased nigrostriatal and nigrocortical resting state functional connectivity. Despite these independent findings, the relationship between UA and substantia nigra (SN) functional connectivity remains unknown. In the present study, voxelwise analysis of covariance was used in a cross-sectional design to explore the relationship between UA and whole-brain SN functional connectivity using the eyes-open resting state fMRI method in controls without RBD, patients with idiopathic RBD, and PD patients with and without RBD. The results showed that controls exhibited a positive relationship between UA and SN functional connectivity with left lingual gyrus. The positive relationship was reduced in patients with RBD and PD with RBD, and the relationship was found to be negative in PD patients. These results are the first to show differential relationships between UA and SN functional connectivity among controls, prodromal, and diagnosed PD patients in a ventral occipital region previously documented to be metabolically and structurally altered in RBD and PD. More investigation, including replication in longitudinal designs with larger samples, is needed to understand the pathophysiological significance of these changes.

Brain MRI Reveals Ascending Atrophy in Parkinson's Disease Across Severity

Models which assess the progression of Lewy pathology in Parkinson's disease have proposed ascending spread in a caudal-rostral pattern. In-vivo human evidence for this theory is limited, in part because there are no biomarkers that allow for direct assessment of Lewy pathology. Here, we measured neurodegeneration via MRI, an outcome which may serve as a proxy for a more direct assessment of ascending models using a combination of (1) MRI-based measures of gray matter density and (2) regions of interest (ROIs) corresponding to cortical and subcortical loci implicated in past MRI and stereological studies of Parkinson's disease. Gray matter density was measured using brain MRI voxel-based morphometry from three cohorts: (1) early Parkinson's disease, (2) more advanced Parkinson's disease and (3) healthy controls. Early Parkinson's disease patients (N = 228, mean age = 61.9 years, mean disease duration = 0.6 years) were newly diagnosed by the Parkinson's Progression Markers Initiative (PPMI). Advanced Parkinson's disease patients (N = 136, mean age = 63.5 years, mean disease duration = 8.0 years) were collected retrospectively from a local cohort undergoing evaluation for functional neurosurgery. Control subjects (N = 103, mean age = 60.2 years) were from PPMI. Comparative analyses focused on gray matter regions ranging from deep gray subcortical structures to the neocortex. ROIs were defined with existing probabilistic cytoarchitectonic brain maps. For subcortical regions of the basal forebrain, amygdala, and entorhinal cortex, advanced Parkinson's disease patients had significantly lower gray matter density when compared to both early Parkinson's disease and healthy controls. No differences were seen in neocortical regions that are "higher" in any proposed ascending pattern. Across early and advanced Parkinson's disease, gray matter density from nearly all subcortical regions significantly decreased with disease duration; no neocortical regions showed this effect. These results demonstrate that atrophy in advanced Parkinson's patients compared to early patients and healthy controls is largely confined to subcortical gray matter structures. The degree of atrophy in subcortical brain regions was linked to overall disease duration, suggesting an organized pattern of atrophy across severity.

Predicting severity and prognosis in Parkinson's disease from brain microstructure and connectivity

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White matter disruption occurs in Parkinson's disease across several brain regions.

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DTI properties could identify clinically distinct subtypes of Parkinson's disease.

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Structural neural disruption can predict clinical outcomes in Parkinson's disease.

Objectives: Investigating biomarkers to demonstrate progression of Parkinson's disease (PD) is of high priority. We investigated the association of brain structural properties with progression of clinical outcomes and their ability to differentiate clinical subtypes of PD.

Methods: A comprehensive set of clinical features was evaluated at baseline and 4.5-year follow-up for 144 de-novo PD patients from the Parkinson's Progression Markers Initiative. We created a global composite outcome (GCO) by combining z-scores of non-motor and motor symptoms, motor signs, overall activities of daily living and global cognition, as a single numeric indicator of prognosis. We classified patients into three subtypes based on multi-domain clinical criteria: ‘mild motor-predominant’, ‘intermediate’ and ‘diffuse-malignant’. We analyzed diffusion-weighted scans at the early drug-naïve stage and extracted fractional anisotropy and mean diffusivity (MD) of basal ganglia and cortical sub-regions. Then, we employed graph theory to calculate network properties and used network-based statistic to investigate our primary hypothesis.

Results: Baseline MD of globus pallidus was associated with worsening of motor severity, cognition, and GCO after 4.5 years of follow-up. Connectivity disruption at baseline was correlated with decline in cognition, and increase in GCO. Baseline MD of nucleus accumbens, globus pallidus and basal-ganglia were linked to clinical subtypes at 4.5-year of follow-up. Disruption in sub-cortical networks associated with being subtyped as ‘diffuse-malignant’ versus ‘mild motor-predominant’ after 4.5 years.

Conclusions: Diffusion imaging analysis at the early de-novo stage of PD was able to differentiate clinical sub-types of PD after 4.5 years and was highly associated with future clinical outcomes of PD.

Four-angle method for practical ultra-high-resolution magnetic resonance mapping of brain longitudinal relaxation time and apparent proton density

Changes in longitudinal relaxation time (T₁) and proton density (PD) are sensitive indicators of microstructural alterations associated with various central nervous system diseases as well as brain maturation and aging. In this work, we introduce a new approach for rapid and accurate high-resolution (HR) or ultra HR (UHR) mapping of T₁ and apparent PD (APD) of the brain with correction of radiofrequency field, B₁, inhomogeneities. The four-angle method (FAM) uses four spoiled-gradient recalled-echo (SPGR) images acquired at different flip angles (FA) and short repetition times (TRs). The first two SPGR images are acquired at low-spatial resolution and used to accurately map the active B₁⁺ field with the recently introduced steady-state double angle method (SS-DAM). The estimated B₁⁺ map is used in conjunction with the two other SPGR images, acquired at HR or UHR, to map T₁ and APD. The method is evaluated with numerical, phantom, and in-vivo imaging measurements. Furthermore, we investigated imaging acceleration methods to further shorten the acquisition time. Our results indicate that FAM provides an accurate method for simultaneous HR or UHR mapping of T₁ and APD in human brain in clinical high-field MRI. Derived parameter maps without B₁⁺correction suffer from large inaccuracies, but this issue is well-corrected through use of the SS-DAM. Furthermore, the use of SPGR imaging with short TR and phased-array coil acquisition permits substantial imaging acceleration and enables robust HR or UHR T₁ and APD mapping in a clinically acceptable time frame, with whole brain coverage obtained in less than 2 min or 5 min, respectively. The method exhibits high reproducibility and benefits from the use of the conventional SPGR sequence, available in all preclinical and clinical MRI machines, and very simple modeling to address a critical outstanding issue in neuroimaging.

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.

Multimodal MRI evaluation of parkinsonian limbic pathologies

Previous multimodal magnetic resonance imaging (MRI) studies of parkinsonian syndromes have focused primarily on motor-related basal ganglia structures. The present study investigated MRI changes in nonmotor-related limbic structures in 35 Parkinson's disease, 16 multiple system atrophy parkinsonian subtype, 17 progressive supranuclear palsy, and 37 control subjects. Mean diffusivity (MD), fractional anisotropy, transverse relaxation rate (R2*), quantitative susceptibility mapping, and volume measurements were obtained from the amygdala, hippocampus, and nucleus accumbens (NAc) to examine differences between groups and to test for associations with clinical scores. Compared with controls, Parkinson's disease subjects had lower NAc volume; multiple system atrophy parkinsonian subtype subjects had higher NAc transverse relaxation rate; and progressive supranuclear palsy subjects had higher amygdala and hippocampus MD and lower hippocampus fractional anisotropy (p's ≤ 0.008). Among parkinsonian subjects, amygdala and hippocampus MD associated positively with Unified Parkinson's Disease Rating Scale nonmotor and activities of daily living scores (p's ≤ 0.005). Together, these findings support the inclusion of limbic structures in future MRI studies of parkinsonian syndromes.

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.

Automated Subfield Volumetric Analysis of Hippocampus in Patients with Drug-Naïve Nondementia Parkinson's Disease

Several studies used automated segmentation of hippocampal subfield (ASHS) for detailed measurements of anatomic subregions of the hippocampus, especially in the field of neurodegenerative disorders. In this study, we investigated the hippocampal subfield volume of patients with early-stage nondementia PD compared with normal healthy subjects using the ASHS method. A total of 32 subjects were enrolled in this study (sixteen patients with drug naive nondementia PD and sixteen healthy controls). All subjects were scanned with a 1.5 tesla MRI. The volumes of the seven subfields were calculated separately, and then, the whole hippocampal volume was calculated by the summing of CA1, CA2-3, CA4-DG, subiculum, presubiculum, and fimbria, excluding the hippocampal fissure. There were significant diagnosis-by-hemisphere interactive effects on the total hippocampal volume (F = 5.197; p=0.031) and the subfield volume of CA2-3 (F = 7.586; p=0.010) and CA4-DG (F = 7.403; p=0.011). The volumes of CA2-3 (F = 19.911; p < 0.001), CA4-DG (F = 20.273; p < 0.001), and total hippocampus (F = 10.573; p=0.005) in the left hemisphere were reduced compared to the right hemisphere. We suggest that the hippocampal volume asymmetry, especially in CA4-DG and CA2-3, could be observed in drug-naïve PD patients even in the early stage of the disease.

Biomarkers of Parkinson's disease: Striatal sub-regional structural morphometry and diffusion MRI

Parkinson's disease (PD) is a progressive neurological disorder that has no reliable biomarkers. The aim of this study was to explore the potential of semi-automated sub-regional analysis of the striatum with magnetic resonance imaging (MRI) to distinguish PD patients from controls (i.e., as a diagnostic biomarker) and to compare PD patients at different stages of disease.

With 3 Tesla MRI, diffusion- and T1-weighted scans were obtained on two occasions in 24 PD patients and 18 age-matched, healthy controls. PD patients completed one session on and the other session off dopaminergic medication. The striatum was parcellated into seven functionally disparate sub-regions. The segmentation was guided by reciprocal connections to distinct cortical regions. Volume, surface-based morphometry, and integrity of white matter connections were calculated for each striatal sub-region.

Test-retest reliability of our volume, morphometry, and white matter integrity measures across scans was high, with correlations ranging from r = 0.452, p < 0.05 and r = 0.985, p < 0.001. Global measures of striatum such as total striatum, nucleus accumbens, caudate nuclei, and putamen were not significantly different between PD patients and controls, indicating poor sensitivity of these measures, which average across sub-regions that are functionally heterogeneous and differentially affected by PD, to act as diagnostic biomarkers. Further, these measures did not correlate significantly with disease severity, challenging their potential to serve as progression biomarkers. In contrast, a) decreased volume and b) inward surface displacement of caudal-motor striatum—the region first and most dopamine depleted in PD—distinguished PD patients from controls. Integrity of white matter cortico-striatal connections in caudal-motor and adjacent striatal sub-regions (i.e., executive and temporal striatum) was reduced for PD patients relative to controls. Finally, volume of limbic striatum, the only striatal sub-region innervated by the later-degenerating ventral tegmental area in PD, was reduced in later-stage compared to early stage PD patients a potential progression biomarker.

Segmenting striatum based on distinct cortical connectivity provided highly sensitive MRI measures for diagnosing and staging PD.

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Using 3T structural and diffusion tensor MRI, we explored potential biomarkers in PD.

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Striatum was parcellated into 7 functional sub-regions based on cortical connectivity.

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Volume of caudal-motor region was significantly smaller in PDs compared to controls.

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Volume of limbic region was sensitive to PD disease progression.

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Striatal sub-regions provided sensitive measures of the presence and progression of PD.

Biomarkers in Neurodegenerative Diseases

The past decade has seen tremendous efforts in biomarker discovery and validation for neurodegenerative diseases. The source and type of biomarkers has continued to grow for central nervous system diseases, from biofluid-based biomarkers (blood or cerebrospinal fluid (CSF)), to nucleic acids, tissue, and imaging. While DNA remains a predominant biomarker used to identify familial forms of neurodegenerative diseases, various types of RNA have more recently been linked to familial and sporadic forms of neurodegenerative diseases during the past few years. Imaging approaches continue to evolve and are making major contributions to target engagement and early diagnostic biomarkers. Incorporation of biomarkers into drug development and clinical trials for neurodegenerative diseases promises to aid in the development and demonstration of target engagement and drug efficacy for neurologic disorders. This review will focus on recent advancements in developing biomarkers for clinical utility in Alzheimer's disease (AD), Parkinson's disease (PD), and amyotrophic lateral sclerosis (ALS).

Recent Advances in Biomarkers for Parkinson's Disease

Parkinson's disease (PD) is one of the common progressive neurodegenerative disorders with several motor and non-motor symptoms. Most of the motor symptoms may appear at a late stage where most of the dopaminergic neurons have been already damaged. In order to provide better clinical intervention and treatment at the onset of disease, it is imperative to find accurate biomarkers for early diagnosis, including prodromal diagnosis and preclinical diagnosis. At the same time, these reliable biomarkers can also be utilized to monitor the progress of the disease. In this review article, we will discuss recent advances in the development of PD biomarkers from different aspects, including clinical, biochemical, neuroimaging and genetic aspects. Although various biomarkers for PD have been developed so far, their specificity and sensitivity are not ideal when applied individually. So, the combination of multimodal biomarkers will greatly improve the diagnostic accuracy and facilitate the implementation of personalized medicine.

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

Parkinson's disease: Cause factors, measurable indicators, and early diagnosis

Parkinson's disease (PD) is a neurodegenerative disease of the central nervous system caused due to the loss of dopaminergic neurons. It is classified under movement disorder as patients with PD present with tremor, rigidity, postural changes, and a decrease in spontaneous movements. Comorbidities including anxiety, depression, fatigue, and sleep disorders are observed prior to the diagnosis of PD. Gene mutations, exposure to toxic substances, and aging are considered as the causative factors of PD even though its genesis is unknown. This paper reviews PD etiologies, progression, and in particular measurable indicators of PD such as neuroimaging and electrophysiology modalities. In addition to gene therapy, neuroprotective, pharmacological, and neural transplantation treatments, researchers are actively aiming at identifying biological markers of PD with the goal of early diagnosis. Neuroimaging modalities used together with advanced machine learning techniques offer a promising path for the early detection and intervention in PD patients.

Iron deposition quantification: Applications in the brain and liver

Iron has long been implicated in many neurological and other organ diseases. It is known that over and above the normal increases in iron with age, in certain diseases there is an excessive iron accumulation in the brain and liver. MRI is a noninvasive means by which to image the various structures in the brain in three dimensions and quantify iron over the volume of the object of interest. The quantification of iron can provide information about the severity of iron-related diseases as well as quantify changes in iron for patient follow-up and treatment monitoring. This article provides an overview of current MRI-based methods for iron quantification, specifically for the brain and liver, including: signal intensity ratio, R₂ , R2*, R2', phase, susceptibility weighted imaging and quantitative susceptibility mapping (QSM). Although there are numerous approaches to measuring iron, R₂ and R2* are currently preferred methods in imaging the liver and QSM has become the preferred approach for imaging iron in the brain.

LEVEL OF EVIDENCE

5 Technical Efficacy: Stage 5 J. Magn. Reson. Imaging 2018. J. MAGN. RESON. IMAGING 2018;48:301-317.

The Aging of Iron Man

Brain iron is tightly regulated by a multitude of proteins to ensure homeostasis. Iron dyshomeostasis has become a molecular signature associated with aging which is accompanied by progressive decline in cognitive processes. A common theme in neurodegenerative diseases where age is the major risk factor, iron dyshomeostasis coincides with neuroinflammation, abnormal protein aggregation, neurodegeneration, and neurobehavioral deficits. There is a great need to determine the mechanisms governing perturbations in iron metabolism, in particular to distinguish between physiological and pathological aging to generate fruitful therapeutic targets for neurodegenerative diseases. The aim of the present review is to focus on the age-related alterations in brain iron metabolism from a cellular and molecular biology perspective, alongside genetics, and neuroimaging aspects in man and rodent models, with respect to normal aging and neurodegeneration. In particular, the relationship between iron dyshomeostasis and neuroinflammation will be evaluated, as well as the effects of systemic iron overload on the brain. Based on the evidence discussed here, we suggest a synergistic use of iron-chelators and anti-inflammatories as putative anti-brain aging therapies to counteract pathological aging in neurodegenerative diseases.

New Progress on the Role of Glia in Iron Metabolism and Iron-Induced Degeneration of Dopamine Neurons in Parkinson's Disease

It is now increasingly appreciated that glial cells play a critical role in the regulation of iron homeostasis. Impairment of these properties might lead to dysfunction of iron metabolism and neurodegeneration of neurons. We have previously shown that dysfunction of glia could cause iron deposit and enhance iron-induced degeneration of dopamine (DA) neurons in Parkinson’s disease (PD). There also has been a substantial growth of knowledge regarding the iron metabolism of glia and their effects on iron accumulation and degeneration of DA neurons in PD in recent years. Here, we attempt to describe the role of iron metabolism of glia and the effect of glia on iron accumulation and degeneration of DA neurons in the substantia nigra of PD. This could provide evidence to reveal the mechanisms underlying nigral iron accumulation of DA neurons in PD and provide the basis for discovering new potential therapeutic targets for PD.