Progression of putaminal degeneration in multiple system atrophy: a serial diffusion MR study

White Matter Abnormalities Track Disease Progression in Multiple System Atrophy

BACKGROUND

White matter (WM) abnormalities have been implicated in clinically relevant functional decline in multiple system atrophy (MSA).

OBJECTIVE

To identify the WM and gray matter (GM) abnormalities in MSA and assess the utility of longitudinal structural and diffusion changes as surrogate markers for tracking disease progression in MSA.

METHODS

Twenty-seven participants with early MSA [15 with clinically predominant cerebellar (MSA-C) and 12 with clinically predominant parkinsonian features (MSA-P)] and 14 controls were enrolled as a part of our prospective, longitudinal study of synucleinopathies. Using structural magnetic resonance imaging (MRI) and diffusion MRI (diffusion tensor and neurite orientation and dispersion density imaging), we analyzed whole and regional brain changes in these participants. We also evaluated temporal imaging trajectories based on up to three annual follow-up scans and assessed the impact of baseline diagnosis on these imaging biomarkers using mixed-effect models.

RESULTS

MSA patients exhibited more widespread WM changes than GM, particularly in the cerebellum and brainstem, with greater severity in MSA-C. Structural and diffusion measures in the cerebellum WM and brainstem deteriorated with disease progression. Rates of progression of these abnormalities were similar in both MSA subtypes, reflecting increasing overlap of clinical features over time.

CONCLUSION

WM abnormalities are core features of MSA disease progression and advance at similar rates in clinical MSA subtypes. Multimodal MRI imaging reveals novel insights into the distribution and pattern of brain abnormalities and their progression in MSA. Selected structural and diffusion measures may be useful for tracking disease progression in MSA clinical trials.

Investigating the discrimination ability of 3D convolutional neural networks applied to altered brain MRI parametric maps

Convolutional neural networks (CNNs) are gradually being recognized in the neuroimaging community as a powerful tool for image analysis. Despite their outstanding performances, some aspects of CNN functioning are still not fully understood by human operators. We postulated that the interpretability of CNNs applied to neuroimaging data could be improved by investigating their behavior when they are fed data with known characteristics. We analyzed the ability of 3D CNNs to discriminate between original and altered whole-brain parametric maps derived from diffusion-weighted magnetic resonance imaging. The alteration consisted in linearly changing the voxel intensity of either one (monoregion) or two (biregion) anatomical regions in each brain volume, but without mimicking any neuropathology. Performing ten-fold cross-validation and using a hold-out set for testing, we assessed the CNNs' discrimination ability according to the intensity of the altered regions, comparing the latter's size and relative position. Monoregion CNNs showed that the larger the modified region, the smaller the intensity increase needed to achieve good performances. Biregion CNNs systematically outperformed monoregion CNNs, but could only detect one of the two target regions when tested on the corresponding monoregion images. Exploiting prior information on training data allowed for a better understanding of CNN behavior, especially when altered regions were combined. This can inform about the complexity of CNN pattern retrieval and elucidate misclassified examples, particularly relevant for pathological data. The proposed analytical approach may serve to gain insights into CNN behavior and guide the design of enhanced detection systems exploiting our prior knowledge.

Progressive Brain Atrophy in Multiple System Atrophy: A Longitudinal, Multicenter, Magnetic Resonance Imaging Study

OBJECTIVE

To determine the rates of brain atrophy progression in vivo in patients with multiple system atrophy (MSA).

BACKGROUND

Surrogate biomarkers of disease progression are a major unmet need in MSA. Small-scale longitudinal studies in patients with MSA using magnetic resonance imaging (MRI) to assess progression of brain atrophy have produced inconsistent results. In recent years, novel MRI post-processing methods have been developed enabling reliable quantification of brain atrophy in an automated fashion.

METHODS

Serial 3D-T1-weighted MRI assessments (baseline and after 1 year of follow-up) of 43 patients with MSA were analyzed and compared to a cohort of early-stage Parkinson's disease (PD) patients and healthy controls (HC). FreeSurfer's longitudinal analysis stream was used to determine the brain atrophy rates in an observer-independent fashion.

RESULTS

Mean ages at baseline were 64.4 ± 8.3, 60.0 ± 7.5, and 59.8 ± 9.2 years in MSA, PD patients and HC, respectively. A mean disease duration at baseline of 4.1 ± 2.5 years in MSA patients and 2.3 ± 1.4 years in PD patients was observed. Brain regions chiefly affected by MSA pathology showed progressive atrophy with annual rates of atrophy for the cerebellar cortex, cerebellar white matter, pons, and putamen of -4.24 ± 6.8%, -8.22 ± 8.8%, -4.67 ± 4.9%, and - 4.25 ± 4.9%, respectively. Similar to HC, atrophy rates in PD patients were minimal with values of -0.41% ± 1.8%, -1.47% ± 4.1%, -0.04% ± 1.8%, and -1.54% ± 2.2% for cerebellar cortex, cerebellar white matter, pons, and putamen, respectively.

CONCLUSIONS

Patients with MSA show significant brain volume loss over 12 months, and cerebellar, pontine, and putaminal volumes were the most sensitive to change in mid-stage disease. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Surface-Based Neuroimaging Pattern of Multiple System Atrophy

RATIONALE AND OBJECTIVES

Overlapping parkinsonism, cerebellar ataxia, and pyramidal signs render challenges in the clinical diagnosis of multiple system atrophy (MSA). The neuroimaging pattern is valuable to understand its pathophysiology and improve its diagnostic effect.

MATERIALS AND METHODS

We retrospectively obtained magnetic resonance imaging and susceptibility-weighted imaging in patients with MSA (including parkinsonian type [MSA-P] and cerebellar type [MSA-C]), Parkinson's disease, and normal controls. We quantified neuroimaging features to identify the optimal threshold for diagnosis. Furthermore, we explore neuroimaging patterns of MSA by mapping the subcortical morphological alterations and constructing a diagnostic model.

RESULTS

Compared to controls, normalized putaminal volume significantly decreased in patients with MSA-P (P < .001) and normalized pontine volume significantly decreased in patients with MSA-C (P < .001). The Youden index of the threshold-based clinical prediction model was 0.871-0.928 in patients with MSA. The neuroimaging pattern in patients with MSA was jointly located in the lateral putamen, and the neuroimaging pattern prediction model achieved a classification accuracy of 83.9%-100%.

CONCLUSION

The quantitative neuroimaging features and surface-based morphologic anomalies represent the markers of MSA and open new avenues for personalized clinical diagnosis.

Comparison of mean diffusivity, R2* relaxation rate and morphometric biomarkers for the clinical differentiation of parkinsonism

INTRODUCTION

Quantitative biomarkers for clinical differentiation of parkinsonian syndromes are still lacking. Our aim was to evaluate the value of combining clinically feasible manual measurements of R2* relaxation rates and mean diffusivity (MD) in subcortical regions and brainstem morphometric measurements to improve the discrimination of parkinsonian syndromes.

METHODS

Twenty-two healthy controls (HC), 25 patients with Parkinson's disease (PD), 19 with progressive supranuclear palsy (PSP) and 27 with multiple system atrophy (MSA, 21 with the parkinsonian variant -MSAp, 6 with the cerebellar variant -MSAc) were recruited. R2*, MD measurements and morphometric biomarkers including the midbrain to pons area ratio and the Magnetic Resonance Parkinsonism Index (MRPI) were compared between groups and their diagnostic performances were assessed.

RESULTS

Morphometric biomarkers discriminated better patients with PSP (ratio: AUC 0.89, MRPI: AUC 0.89) and MSAc (ratio: AUC 0.82, MRPI: AUC 0.75) from other groups. R2* and MD measurements in the posterior putamen performed better in separating patients with MSAp from PD (R2*: AUC 0.89; MD: AUC 0.89). For the three-class classification "MSA vs PD vs PSP", the combination of MD and R2* measurements in the posterior putamen with morphometric biomarkers (AUC: 0.841) outperformed each marker separately. At the individual-level, there were seven discordances between imaging-based prediction and clinical diagnosis involving MSA. Using the new Movement Disorder Society criteria for the diagnosis of MSA, three of these seven patients were clinically reclassified as predicted by quantitative imaging.

CONCLUSION

Combining R2* and MD measurements in the posterior putamen with morphometric biomarkers improves the discrimination of parkinsonism.

Autonomic failure: Clinicopathologic, physiologic, and genetic aspects

Over the past century, generations of neuroscientists, pathologists, and clinicians have elucidated the underlying causes of autonomic failure found in neurodegenerative, inherited, and antibody-mediated autoimmune disorders, each with pathognomonic clinicopathologic features. Autonomic failure affects central autonomic nervous system components in the α-synucleinopathy, multiple system atrophy, characterized clinically by levodopa-unresponsive parkinsonism or cerebellar ataxia, and pathologically by argyrophilic glial cytoplasmic inclusions (GCIs). Two other central neurodegenerative disorders, pure autonomic failure characterized clinically by deficits in norepinephrine synthesis and release from peripheral sympathetic nerve terminals; and Parkinson's disease, with early and widespread autonomic deficits independent of the loss of striatal dopamine terminals, both express Lewy pathology. The rare congenital disorder, hereditary sensory, and autonomic neuropathy type III (or Riley-Day, familial dysautonomia) causes life-threatening autonomic failure due to a genetic mutation that results in loss of functioning baroreceptors, effectively separating afferent mechanosensing neurons from the brain. Autoimmune autonomic ganglionopathy caused by autoantibodies targeting ganglionic α3-acetylcholine receptors instead presents with subacute isolated autonomic failure affecting sympathetic, parasympathetic, and enteric nervous system function in various combinations. This chapter is an overview of these major autonomic disorders with an emphasis on their historical background, neuropathological features, etiopathogenesis, diagnosis, and treatment.

Diffusion Magnetic Resonance Imaging Microstructural Abnormalities in Multiple System Atrophy: A Comprehensive Review

Multiple system atrophy (MSA) is a neurodegenerative disease characterized by autonomic failure, ataxia, and/or parkinsonism. Its prominent pathological alterations can be investigated using diffusion magnetic resonance imaging (dMRI), a technique that exploits the characteristics of water random motion inside brain tissue. The aim of this report was to review currently available literature on the application of dMRI in MSA and to describe microstructural abnormalities, diagnostic applications, and pathophysiological correlates. Sixty-four published studies involving microstructural investigation using dMRI in MSA were included. Widespread microstructural abnormalities of white matter were described, especially in the middle cerebellar peduncle, corticospinal tract, and hemispheric fibers. Gray matter degeneration was identified as well, with diffuse involvement of subcortical structures, especially in the putamina. Diagnostic applications of dMRI were mostly explored for the differential diagnosis between MSA parkinsonism and Parkinson's disease. Recently, machine learning algorithms for image processing and disease classification have demonstrated high diagnostic accuracy, showing potential for translation into clinical practice. To a lesser extent, clinical correlates of microstructural abnormalities have also been investigated, and abnormalities related to motor, ocular, and cognitive impairments were described. dMRI in MSA has contributed to in vivo identification of known pathological abnormalities. Translation into clinical practice of the latest advancements for the differential diagnosis between MSA and other forms of parkinsonism seems feasible. Current limitations involve the possibility of correctly diagnosing MSA in the very early stages, when the clinical diagnosis is most uncertain. Furthermore, pathophysiological correlates of microstructural abnormalities remain understudied. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

The Evaluation Value of Diffusion-Weighted Imaging for Brain Injury in Patients after Deep Hypothermic Circulatory Arrest

Objective

Cerebral complications may occur after surgery with deep hypothermic circulatory arrest (DHCA). Diffusion-weighted imaging (DWI) has shown promising results in detecting early changes of cerebral ischemia. However, studies in human models are limited. Here, we examined the significance of DWI for detecting brain injury in postoperative patients after DHCA.

Methods

Twelve patients who had undergone selective cerebral perfusion with DHCA were enrolled. All patients underwent magnetic resonance imaging (MRI) examinations before and after the operation with T1-weighted phase (T1W) and T2-weighted phase (T2W). Magnetic resonance angiography (3D TOF) was applied to observe intracranial arterial communication situations. DWI was employed to calculate the apparent diffusion coefficient (ADC) values. The neurocognitive function of patients was assessed preoperatively and postoperatively using the Montreal Cognitive Assessment Scale (MoCA), Hamilton Depression Scale (HAMD), and Hamilton Anxiety Scale (HAMA).

Results

The ADC values of the whole brain of patients after surgery were significantly higher than before surgery (P = 0.003). However, no significant difference in the ADC values of other regions before and after the operation was observed. There was no significant effect on the postoperative cognitive function of patients after surgery, but visual-spatial and executive abilities were significantly reduced, while psychological anxiety (P = 0.005) and depression levels (P < 0.05) significantly increased. Correlation analysis revealed a significant association between ADC change values and depression change values (P < 0.05).

Conclusion

DHCA demonstrated no significant effect on the cognitive function of patients but could affect the mood of patients. On the other hand, DWI demonstrated promising efficiency and accuracy in evaluating brain injury after DHCA.

Update on neuroimaging for categorization of Parkinson's disease and atypical parkinsonism

PURPOSE OF REVIEW

Differential diagnosis of Parkinsonism may be difficult. The objective of this review is to present the work of the last three years in the field of imaging for diagnostic categorization of parkinsonian syndromes focusing on progressive supranuclear palsy (PSP) and multiple system atrophy (MSA).

RECENT FINDINGS

Two main complementary approaches are being pursued. The first seeks to develop and validate manual qualitative or semi-quantitative imaging markers that can be easily used in clinical practice. The second is based on quantitative measurements of magnetic resonance imaging abnormalities integrated in a multimodal approach and in automatic categorization machine learning tools.

SUMMARY

These two complementary approaches obtained high diagnostic around 90% and above in the classical Richardson form of PSP and probable MSA. Future work will determine if these techniques can improve diagnosis in other PSP variants and early forms of the diseases when all clinical criteria are not fully met.

The Role of Magnetic Resonance Imaging for the Diagnosis of Atypical Parkinsonism

The diagnosis of Parkinson's disease and atypical Parkinsonism remains clinically difficult, especially at the early stage of the disease, since there is a significant overlap of symptoms. Multimodal MRI has significantly improved diagnostic accuracy and understanding of the pathophysiology of Parkinsonian disorders. Structural and quantitative MRI sequences provide biomarkers sensitive to different tissue properties that detect abnormalities specific to each disease and contribute to the diagnosis. Machine learning techniques using these MRI biomarkers can effectively differentiate atypical Parkinsonian syndromes. Such approaches could be implemented in a clinical environment and improve the management of Parkinsonian patients. This review presents different structural and quantitative MRI techniques, their contribution to the differential diagnosis of atypical Parkinsonian disorders and their interest for individual-level diagnosis.

Gray Matter Atrophy in Parkinson's Disease and the Parkinsonian Variant of Multiple System Atrophy: A Combined ROI- and Voxel-Based Morphometric Study

OBJECTIVES

Parkinson's disease (PD) and the parkinsonian variant of multiple system atrophy (MSA-P) are distinct neurodegenerative disorders that share similar clinical features of parkinsonism. The morphological alterations of these diseases have yet to be understood. The purpose of this study was to evaluate gray matter atrophy in PD and MSA-P using regions of interest (ROI)-based measurements and voxel-based morphometry (VBM).

METHODS

We studied 41 patients with PD, 20 patients with MSA-P, and 39 controls matched for age, sex, and handedness using an improved T1-weighted sequence that eased gray matter segmentation. The gray matter volumes were measured using ROI and VBM.

RESULTS

ROI volumetric measurements showed significantly reduced bilateral putamen volumes in MSA-P patients compared with those in PD patients and controls (p<0.05), and the volumes of the bilateral caudate nucleus were significantly reduced in both MSA-P and PD patients compared with those in the controls (p<0.05). VBM analysis revealed multifocal cortical and subcortical atrophy in both MSA-P and PD patients, and the volumes of the cerebellum and temporal lobes were remarkably reduced in MSA-P patients compared with the volumes in PD patients (p<0.05).

CONCLUSIONS

Both PD and MSA-P are associated with gray matter atrophy, which mainly involves the bilateral putamen, caudate nucleus, cerebellum, and temporal lobes. ROI and VBM can be used to identify these morphological alterations, and VBM is more sensitive and repeatable and less time-consuming, which may have potential diagnostic value.

Multiple system atrophy

Multiple system atrophy (MSA) is a sporadic, adult-onset, relentlessly progressive neurodegenerative disorder, clinically characterized by various combinations of autonomic failure, parkinsonism and ataxia. The neuropathological hallmark of MSA are glial cytoplasmic inclusions consisting of misfolded α-synuclein. Selective atrophy and neuronal loss in striatonigral and olivopontocerebellar systems underlie the division into two main motor phenotypes of MSA-parkinsonian type and MSA-cerebellar type. Isolated autonomic failure and REM sleep behavior disorder are common premotor features of MSA. Beyond the core clinical symptoms, MSA manifests with a number of non-motor and motor features. Red flags highly specific for MSA may provide clues for a correct diagnosis, but in general the diagnostic accuracy of the second consensus criteria is suboptimal, particularly in early disease stages. In this chapter, the authors discuss the historical milestones, etiopathogenesis, neuropathological findings, clinical features, red flags, differential diagnosis, diagnostic criteria, imaging and other biomarkers, current treatment, unmet needs and future treatments for MSA.

Multiple System Atrophy: Recent Developments and Future Perspectives

Multiple system atrophy (MSA) is a rare and fatal neurodegenerative disorder characterized by a variable combination of parkinsonism, cerebellar impairment, and autonomic dysfunction. The pathologic hallmark is the accumulation of aggregated α-synuclein in oligodendrocytes, forming glial cytoplasmic inclusions, which qualifies MSA as a synucleinopathy together with Parkinson's disease and dementia with Lewy bodies. The underlying pathogenesis is still not well understood. Some symptomatic treatments are available, whereas neuroprotection remains an urgent unmet treatment need. In this review, we critically appraise significant developments of the past decade with emphasis on pathogenesis, diagnosis, prognosis, and treatment development. We further discuss unsolved questions and highlight some perspectives. © 2019 International Parkinson and Movement Disorder Society.

Quantitative Validation of a Visual Rating Scale for Defining High-Iron Putamen in Patients With Multiple System Atrophy

Objectives: To validate a visual rating scale reflecting sub-regional patterns of putaminal hypointensity in susceptibility-weighted imaging of patients with multiple system atrophy (MSA).

Methods: Using a visual rating scale (from G0 to G3), 2 examiners independently rated putaminal hypointensities of 37 MSA patients and 21 control subjects. To investigate the correlation with the scales, R2^* values and the volume of the entire putamen were measured.

Results: MSA patients with parkinsonian variant had significantly higher scores than those with cerebellar variant. Visual rating scores in MSA were correlated with R2^* values [General estimating equation (GEE), Wald chi-square = 25.89, corrected p < 0.001] and volume (Wald chi-square = 75.44, corrected p < 0.001). They correlated with UPDRS motor scores. Binary logistic regression analyses revealed that the visual rating scale was a significant predictor for discriminating MSA patients from controls [multivariate model adjusted for age and sex, odds ratio 52.722 (corrected p = 0.009)]. Pairwise comparison between areas under the curve (AUCs) revealed that the visual rating scale demonstrated higher accuracy than R2^* values [difference between AUCs; univariate model = 0.247 (corrected p < 0.001); multivariate model = 0.186 (corrected p = 0.003)]. There were no significant differences in clinical characteristics between the high-iron group, defined as putamen with visual rating scale ≥ G2 and R2^* values ≥ third quartile, and the remaining patients.

Conclusion: The visual rating scale, which reflects quantitative iron content and atrophy of the putamen as well as motor severities, could be useful for the discrimination and evaluation of patients with MSA.

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.

Imaging markers of disease progression in multiple system atrophy

Different neuroimaging modalities hold potential as surrogate markers of underlying neurodegeneration in multiple system atrophy (MSA) and may reflect cell loss, altered glucose metabolism, microglial proliferation, astroglial activation, and nigrostriatal denervation. Multiple studies have demonstrated that serial structural and functional imaging studies are capable of demonstrating neurodegeneration in MSA patients quantitatively, which allows sample size estimates based on rates of progression of these neuroimaging markers. This review summarizes recent research findings as a tool to assess longitudinal changes of serial neuroimaging-derived parameters in MSA.

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

An update on advances in magnetic resonance imaging of multiple system atrophy

In this review, we describe how different neuroimaging tools have been used to identify novel MSA biomarkers, highlighting their advantages and limitations. First, we describe the main structural MRI changes frequently associated with MSA including the 'hot cross-bun' and 'putaminal rim' signs as well as putaminal, pontine, and middle cerebellar peduncle (MCP) atrophy. We discuss the sensitivity and specificity of different supra- and infratentorial changes in differentiating MSA from other disorders, highlighting those that can improve diagnostic accuracy, including the MCP width and MCP/superior cerebellar peduncle (SCP) ratio on T1-weighted imaging, raised putaminal diffusivity on diffusion-weighted imaging, and increased T2* signal in the putamen, striatum, and substantia nigra on susceptibility-weighted imaging. Second, we focus on recent advances in structural and functional MRI techniques including diffusion tensor imaging (DTI), resting-state functional MRI (fMRI), and arterial spin labelling (ASL) imaging. Finally, we discuss new approaches for MSA research such as multimodal neuroimaging strategies and how such markers may be applied in clinical trials to provide crucial data for accurately selecting patients and to act as secondary outcome measures.

Structural Imaging in Atypical Parkinsonism

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

Clinical and Imaging Features of Multiple System Atrophy: Challenges for an Early and Clinically Definitive Diagnosis

Multiple system atrophy (MSA) is an adult-onset, progressive neurodegenerative disorder. Patients with MSA show various phenotypes during the course of their illness, including parkinsonism, cerebellar ataxia, autonomic failure, and pyramidal signs. Patients with MSA sometimes present with isolated autonomic failure or motor symptoms/ signs. The median duration from onset to the concomitant appearance of motor and autonomic symptoms is approximately 2 years but can range up to 14 years. As the presence of both motor and autonomic symptoms is essential for the current diagnostic criteria, early diagnosis is difficult when patients present with isolated autonomic failure or motor symptoms/signs. In contrast, patients with MSA may show severe autonomic failure and die before the presentation of motor symptoms/signs, which are currently required for the diagnosis of MSA. Recent studies have also revealed that patients with MSA may show nonsupporting features of MSA such as dementia, hallucinations, and vertical gaze palsy. To establish early diagnostic criteria and clinically definitive categorization for the successful development of disease-modifying therapy or symptomatic interventions for MSA, research should focus on the isolated phase and atypical symptoms to develop specific clinical, imaging, and fluid biomarkers that satisfy the requirements for objectivity, for semi- or quantitative measurements, and for uncomplicated, worldwide availability. Several novel techniques, such as automated compartmentalization of the brain into multiple parcels for the quantification of gray and white matter volumes on an individual basis and the visualization of α-synuclein and other candidate serum and cerebrospinal fluid biomarkers, may be promising for the early and clinically definitive diagnosis of MSA.

Spatial correlation and segregation of multimodal MRI abnormalities in multiple system atrophy

OBJECTIVE

The variability of the severity and regional distribution of pathological process in basal ganglia (BG) and brainstem-cerebellar systems results in clinical heterogeneity and represents the motor subtype of multiple system atrophy (MSA). This study aimed to quantify spatial patterns of multimodal MRI abnormalities in BG and stem-CB regions and define structural MRI findings that correlate with clinical characteristics.

METHODS

We simultaneously measured R2*, mean diffusivity (MD), and volume in the subcortical structures (BG, thalamus, brainstem-cerebellar regions) of 39 probable MSA and 22 control subjects. Principal component analysis (PCA) and structural equation modeling (SEM) were performed to show a model consisting of multiple inter-dependencies.

RESULTS

Structural MRI alterations were found to be significantly interrelated within BG as well as brainstem-cerebellar regions in MSA patients. PCA extracted four factors: three factors reflected alterations in R2*, MD and volume of the BG region including the caudate nucleus, putamen, and pallidum, and the remaining one factor represented degenerative changes in MD and volume of stem-CB region. In SEM, a latent variable reflecting brainstem-cerebellar degeneration did not show a significant correlation with the other latent variables associated with BG degeneration. Putaminal MD values and a PCA-driven factor reflecting MD values in the BG showed a significant correlation with UPDRS and UMSARS scores.

CONCLUSION

Multimodal structural MRI abnormalities in MSA appear to be segregated into BG and stem-CB-related factors that can be associated with the clinical phenotype and motor severity.

Multiple System Atrophy: An Oligodendroglioneural Synucleinopathy1

Multiple system atrophy (MSA) is an orphan, fatal, adult-onset neurodegenerative disorder of uncertain etiology that is clinically characterized by various combinations of parkinsonism, cerebellar, autonomic, and motor dysfunction. MSA is an α-synucleinopathy with specific glioneuronal degeneration involving striatonigral, olivopontocerebellar, and autonomic nervous systems but also other parts of the central and peripheral nervous systems. The major clinical variants correlate with the morphologic phenotypes of striatonigral degeneration (MSA-P) and olivopontocerebellar atrophy (MSA-C). While our knowledge of the molecular pathogenesis of this devastating disease is still incomplete, updated consensus criteria and combined fluid and imaging biomarkers have increased its diagnostic accuracy. The neuropathologic hallmark of this unique proteinopathy is the deposition of aberrant α-synuclein in both glia (mainly oligodendroglia) and neurons forming glial and neuronal cytoplasmic inclusions that cause cell dysfunction and demise. In addition, there is widespread demyelination, the pathogenesis of which is not fully understood. The pathogenesis of MSA is characterized by propagation of misfolded α-synuclein from neurons to oligodendroglia and cell-to-cell spreading in a "prion-like" manner, oxidative stress, proteasomal and mitochondrial dysfunction, dysregulation of myelin lipids, decreased neurotrophic factors, neuroinflammation, and energy failure. The combination of these mechanisms finally results in a system-specific pattern of neurodegeneration and a multisystem involvement that are specific for MSA. Despite several pharmacological approaches in MSA models, addressing these pathogenic mechanisms, no effective neuroprotective nor disease-modifying therapeutic strategies are currently available. Multidisciplinary research to elucidate the genetic and molecular background of the deleterious cycle of noxious processes, to develop reliable biomarkers and targets for effective treatment of this hitherto incurable disorder is urgently needed.

Diffusion-weighted MRI distinguishes Parkinson disease from the parkinsonian variant of multiple system atrophy: A systematic review and meta-analysis

BACKGROUND

Putaminal diffusivity in brain magnetic resonance diffusion-weighted imaging (DWI) is increased in patients with the parkinsonian variant of multiple system atrophy (MSA-P) compared to Parkinson disease (PD) patients.

PURPOSE

We performed a systematic review and meta-analysis to evaluate the diagnostic accuracy of DWI to distinguish MSA-P from PD.

METHODS

Studies on DWI were identified through a systematic PubMed and Clarivate Analytics® Web of Science® Core Collection search. Papers were selected based on stringent inclusion criteria; minimum requirement was the inclusion of MSA-P and PD patients and documented true positive, true negative, false positive and false negative rates or overall sample size and reported sensitivity and specificity. Meta-analysis was performed using the hierarchical summary receiver operating characteristics curve approach.

RESULTS

The database search yielded 1678 results of which 9 studies were deemed relevant. Diagnostic accuracy of putaminal diffusivity measurements were reported in all of these 9 studies, whereas results of other regions of interest were only reported irregularly. Therefore, a meta-analysis could only be performed for putaminal diffusivity measurements: 127 patients with MSA-P, 262 patients with PD and 70 healthy controls were included in the quantitative synthesis. The meta-analysis showed an overall sensitivity of 90% (95% confidence interval (CI): 76.7%-95.8%) and an overall specificity of 93% (95% CI: 80.0%-97.7%) to distinguish MSA-P from PD based on putaminal diffusivity.

CONCLUSION

Putaminal diffusivity yields high sensitivity and specificity to distinguish clinically diagnosed patients with MSA-P from PD. The confidence intervals indicate substantial variability. Further multicenter studies with harmonized protocols are warranted particularly in early disease stages when clinical diagnosis is less certain.

Magnetic resonance imaging for the diagnosis of Parkinson's disease

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

Role of Magnetic Resonance Imaging in the Diagnosis of Multiple System Atrophy

Background

Multiple system atrophy (MSA) is a rapidly progressing neurodegenerative disorder without effective disease-modifying therapies. Because of a lack of reliable diagnostic biomarkers, there has been increasing interest in using magnetic resonance imaging (MRI) to improve the diagnostic accuracy of MSA.

Methods

This review summarizes recent literatures on the role of MRI in the diagnosis of MSA.

Results

Several MRI abnormalities on conventional MRI already are included in the current diagnostic criteria for MSA. Other features on conventional MRI are also used to make a diagnosis of MSA or to rule out alternative diagnoses. On the other hand, some of the MRI findings that were previously considered suggestive of a diagnosis of MSA are now being challenged, because it turned out that they were not as specific to MSA as previously thought. More advanced MRI modalities, including susceptibility-weighted imaging, diffusion-weighted imaging, diffusion tensor imaging, voxel-based morphometry, and cortical thickness analysis, are now used to study the changes in the brains of patients with MSA. Furthermore, studies have produced promising results demonstrating the use of MRI as a tool for monitoring and assessing disease progression in MSA.

Conclusions

MRI is useful and indispensable in the diagnosis of MSA and also possibly for monitoring disease progression. In this regard, well-designed, long-term, prospective studies on large numbers of patients are needed.

Toward disease modification in multiple system atrophy: Pitfalls, bottlenecks, and possible remedies

Multiple system atrophy has recently attracted increased attention in basic and clinical research. Understanding of key pathophysiological mechanismshas improved; and, in the past decade, the first clinical trials aiming at diseasemodification were conducted. However, there is still no established interventional therapy available. In this review, the authors summarize recent advances, discuss bottlenecks and possible pitfalls of previous interventional studies, and suggest future research avenues.

Diffusion tensor imaging in the characterization of multiple system atrophy

PURPOSE

Multiple system atrophy (MSA) is a rare neurodegenerative disease that remains poorly understood, and the diagnosis of MSA continues to be challenging. We endeavored to improve the diagnostic process and understanding of in vivo characteristics of MSA by diffusion tensor imaging (DTI).

MATERIALS AND METHODS

Twenty MSA subjects, ten parkinsonian dominant (MSA-P), ten cerebellar dominant (MSA-C), and 20 healthy volunteer subjects were recruited. Fractional anisotropy, mean diffusivity, radial diffusivity, and axial diffusivity maps were processed using tract-based spatial statistics. Diffusion data were additionally evaluated in the basal ganglia. A support vector machine was used to assess diagnostic utility, leave-one-out cross-validation in the evaluation of classification schemes, and receiver operating characteristic analyses to determine cutoff values.

RESULTS

We detected widespread changes in the brain white matter of MSA subjects; however, no group-wise differences were found between MSA-C and MSA-P subgroups. Altered DTI metrics in the putamen and middle cerebellar peduncles were associated with a positive parkinsonian and cerebellar phenotype, respectively. Concerning clinical applicability, we achieved high classification performance on mean diffusivity data in the combined bilateral putamen and middle cerebellar peduncle (accuracy 90.3%±9%, sensitivity 86.5%±11%, and specificity 99.3%±4%).

CONCLUSION

DTI in the middle cerebellar peduncle and putamen may be used in the diagnosis of MSA with a high degree of accuracy.

Potential of Diffusion Tensor Imaging and Relaxometry for the Detection of Specific Pathological Alterations in Parkinson's Disease (PD)

The purpose of the present study was to evaluate the potential of multimodal MR imaging including mean diffusivity (MD), fractional anisotropy (FA), relaxation rates R2 and R2* to detect disease specific alterations in Parkinson's Disease (PD). We enrolled 82 PD patients (PD-all) with varying disease durations (≤5 years: PD≤5, n = 43; >5 years: PD>5, n = 39) and 38 matched healthy controls (HC), receiving diffusion tensor imaging as well as R2 and R2* relaxometry calculated from multi-echo T2*-weighted and dual-echo TSE imaging, respectively. ROIs were drawn to delineate caudate nucleus (CN), putamen (PU), globus pallidus (GP) and substantia nigra (SN) on the co-registered maps. The SN was divided in 3 descending levels (SL 1–3). The most significant parameters were used for a flexible discrimination analysis (FDA) in a training collective consisting of 25 randomized subjects from each group in order to predict the classification of remaining subjects. PD-all showed significant increases in MD, R2 and R2* within SN and its subregions as well as in MD and R2* within different basal ganglia regions. Compared to the HC group, the PD≤5 and the PD>5 group showed significant MD increases within the SN and its lower two subregions, while the PD≤5 group exhibited significant increases in R2 and R2* within SN and its subregions, and tended to elevation within the basal ganglia. The PD>5 group had significantly increased MD in PU and GP, whereas the PD≤5 group presented normal MD within the basal ganglia. FDA achieved right classification in 84% of study participants. Micro-structural damage affects primarily the SN of PD patients and in later disease stages the basal ganglia. Iron contents of PU, GP and SN are increased at early disease stages of PD.

Multimodal MRI assessment of nigro-striatal pathway in multiple system atrophy and Parkinson disease

BACKGROUND

Parkinson's disease (PD) and multiple system atrophy (MSA) are two neurodegenerative alpha-synucleinopathies characterized by severe impairment of the nigro-striatal pathway. Based on T1-, T2*-, and diffusion-weighted magnetic resonance imaging (MRI), macro-structural and micro-structural abnormalities in these diseases can be detected.

OBJECTIVE

This study was undertaken to compare the nigro-striatal changes that occur in patients with PD with those in patients with both variants of MSA (the parkinsonian variant, MSA-P, and the cerebellar variant, MSA-C), and to explore correlations between different MRI parameters and clinical data.

METHODS

We simultaneously measured volume, T2* relaxation rates, and mean diffusivity in nigro-striatal structures (substantia nigra, caudate nucleus, and putamen) of 26 patients with PD and 29 patients with MSA (16 with MSA-P and 13 with MSA-C).

RESULTS

Significant changes in the putamina in patients with MSA were observed compared with patients with PD. Patients with MSA-P had higher mean diffusivity values in their putamina than did patients with PD or MSA-C. The putamina of both subgroups of MSA had higher T2* relaxation rates values than PD. Remarkably, discriminant analysis showed that using two measurements of microstructural damage (T2* relaxation rates and mean diffusivity in the putamen) allowed 96% accuracy to distinguish patients with PD from those with MSA-P. Correlation analyses between MRI findings and clinical variables revealed that patients with PD showed significant correlations only at the nigra. In patients with MSA, clinical variables correlated with MRI findings in both the nigra and striatum.

CONCLUSIONS

Multimodal MRI reveals different pattern of nigro-striatal involvement in patients with PD and patients with MSA.

Potential Interactions between the Autonomic Nervous System and Higher Level Functions in Neurological and Neuropsychiatric Conditions

The autonomic nervous system (ANS) maintains the internal homeostasis by continuously interacting with other brain structures. Its failure is commonly observed in many neurological and neuropsychiatric disorders, including neurodegenerative and vascular brain diseases, spinal cord injury, and peripheral neuropathies. Despite the different underlying pathophysiological mechanisms, ANS failure associates with various forms of higher level dysfunctions, and may also negatively impact on patients’ clinical outcome. In this review, we will discuss potential relationships between ANS and higher level dysfunctions in a selection of neurological and neuropsychiatric disorders. In particular, we will focus on the effect of a documented fall in blood pressure fulfilling the criteria for orthostatic hypotension and/or autonomic-reflex impairment on cognitive performances. Some evidence supports the hypothesis that cardiovascular autonomic failure may play a negative prognostic role in most neurological disorders. Despite a clear causal relationship between ANS involvement and higher level dysfunctions that is still controversial, this might have implications for neuro-rehabilitation strategies aimed at improving patients’ clinical outcome.

White matter differences between multiple system atrophy (parkinsonian type) and Parkinson's disease: A diffusion tensor image study

The clinical differential diagnosis between the Parkinson variant of multiple system atrophy (MSA-P) and Parkinson's disease (PD) is difficult in early stages. To identify objective markers for differential diagnosis, we combined the novel tract-based spatial statistics (TBSS) and region of interest (ROI) analyses for the first time to investigate three groups (15 MSA-P, 20 PD patients and 20 controls) with diffusion tensor imaging data. By TBSS, we performed pairwise comparisons of fractional anisotropy (FA), mean diffusivity, radial diffusivity (RD) and axial diffusivity maps. The clusters with significant differences between MSA-P and PD were used as ROIs for further analyses. FA/RD values in bilateral corticospinal tract (CST) and left anterior thalamic radiation (ATR) in MSA-P were significantly different from PD or controls, and significantly correlated with clinical data. These findings indicated that the abnormalities of left ATR and bilateral CST were specific for MSA-P relative to PD or controls, and seemed to be promising for differential diagnosis. Furthermore, it may be useful for severity assessment of MSA-P.

Progression of subcortical atrophy and iron deposition in multiple system atrophy: a comparison between clinical subtypes

Magnetic resonance imaging (MRI) can be useful not only for the diagnosis of multiple system atrophy (MSA) itself, but also to distinguish between different clinical subtypes. This study aimed to investigate whether there are differences in the progression of subcortical atrophy and iron deposition between two variants of MSA. Two serial MRIs at baseline and follow-up were analyzed in eight patients with the parkinsonian variant MSA (MSA-P), nine patients with cerebellar variant MSA (MSA-C), and fifteen patients with Parkinson's disease (PD). The R2* values and volumes were calculated for the selected subcortical structures (caudate nucleus, putamen, globus pallidus, and thalamus) using an automated region-based analysis. In both volume and R2*, a higher rate of progression was identified in MSA-P patients. Volumetric analysis showed significantly more rapid progression of putamen and caudate nucleus in MSA-P than in MSA-C. With regard to R2* changes, a significant increase at follow-up and a higher rate of progression were identified in the putamen of MSA-P group compared to MSA-C and PD groups. This longitudinal study revealed different progression rates of MRI markers between MSA-P and MSA-C. Iron-related degeneration in the putamen may be more specific for MSA-P.

Progression of microstructural damage in spinocerebellar ataxia type 2: a longitudinal DTI study

BACKGROUND AND PURPOSE

The ability of DTI to track the progression of microstructural damage in patients with inherited ataxias has not been explored so far. We performed a longitudinal DTI study in patients with spinocerebellar ataxia type 2.

MATERIALS AND METHODS

Ten patients with spinocerebellar ataxia type 2 and 16 healthy age-matched controls were examined twice with DTI (mean time between scans, 3.6 years [patients] and 3.3 years [controls]) on the same 1.5T MR scanner. Using tract-based spatial statistics, we analyzed changes in DTI-derived indices: mean diffusivity, axial diffusivity, radial diffusivity, fractional anisotropy, and mode of anisotropy.

RESULTS

At baseline, the patients with spinocerebellar ataxia type 2, as compared with controls, showed numerous WM tracts with significantly increased mean diffusivity, axial diffusivity, and radial diffusivity and decreased fractional anisotropy and mode of anisotropy in the brain stem, cerebellar peduncles, cerebellum, cerebral hemisphere WM, corpus callosum, and thalami. Longitudinal analysis revealed changes in axial diffusivity and mode of anisotropy in patients with spinocerebellar ataxia type 2 that were significantly different than those in the controls. In patients with spinocerebellar ataxia type 2, axial diffusivity was increased in WM tracts of the right cerebral hemisphere and the corpus callosum, and the mode of anisotropy was extensively decreased in hemispheric cerebral WM, corpus callosum, internal capsules, cerebral peduncles, pons and left cerebellar peduncles, and WM of the left paramedian vermis. There was no correlation between the progression of changes in DTI-derived indices and clinical deterioration.

CONCLUSIONS

DTI can reveal the progression of microstructural damage of WM fibers in the brains of patients with spinocerebellar ataxia type 2, and mode of anisotropy seems particularly sensitive to such changes. These results support the potential of DTI-derived indices as biomarkers of disease progression.

Differentiating multiple-system atrophy from Parkinson's disease

The purpose of this review is to illustrate the differentiating features of multiple-system atrophy from Parkinson's disease at MRI. The various MRI sequences helpful in the differentiation will be discussed, including newer methods, such as diffusion tensor imaging, MR spectroscopy, and nuclear imaging.

Multiple system atrophy as emerging template for accelerated drug discovery in α-synucleinopathies

There is evidence that the α-synucleinopathies Parkinson's disease (PD) and the Parkinson variant of multiple system atrophy (MSA-P) overlap at multiple levels. Both disorders are characterized by deposition of abnormally phosphorylated fibrillar α-synuclein within the central nervous system suggesting shared pathophysiological mechanisms. Despite the considerable clinical overlap in the early disease stages, MSA-P, in contrast to PD, is fatal and rapidly progressive. Moreover recent clinical studies have shown that surrogate markers of disease progression can be quantified easily and may reliably depict the rapid course of MSA. We therefore posit that, MSA-P may be exploited as a filter barrier in the development of disease-modifying therapeutic strategies targeting common pathophysiological mechanisms of α-synucleinopathies. This approach might reduce the number of negative phase III clinical trials, and, in turn, shift the available resources to earlier development stages, thereby increasing the number of candidate compounds validated.

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α-synucleinopathies overlap at multiple levels.

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α-synucleinopathies are characterized by an abnormal deposition of α-synuclein.

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Validated surrogate markers in MSA reliably monitor disease progression.

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MSA may serve as a template disease for other α-synucleinopathies.

The value of novel MRI techniques in Parkinson-plus syndromes: diffusion tensor imaging and anatomical connectivity studies

Conventional MRI is a well-described, highly useful tool for the differential diagnosis of degenerative parkinsonian syndromes. Nevertheless, the observed abnormalities may only appear in late-stage disease. Diffusion tensor imaging (DTI) can identify microstructural changes in brain tissue integrity and connectivity. The technique has proven value in the differential diagnosis of multiple system atrophy (MSA), progressive supranuclear palsy (PSP) and Parkinson's disease (PD). Here, we performed a systematic review of the literature on the main corticosubcortical DTI abnormalities identified to date in the context of the diagnosis of MSA and PSP with diffusion-weighted imaging, diffusion tensor imaging and anatomical connectivity studies. In good agreement with the histological data, increased diffusivity in the putamen (in MSA and PSP), in the middle cerebellar peduncles (in MSA) and in the upper cerebellar peduncles (in PSP) has been reported. Motor pathway involvement is characterized by low fraction anisotropy (FA) in the primary motor cortex in MSA-P and PSP, a high apparent diffusion coefficient (ADC) and low FA in the supplementary motor area in PSP. We then outline the value of these techniques in differential diagnosis (especially with respect to PD). Anatomical connectivity studies have revealed a lower number of fibers in the corticospinal tract in MSA and PSP (relative to PD and controls) and fewer tracked cortical projection fibers in patients with PSP or late-stage MSA (relative to patients with early MSA or PD and controls). Lastly, we report the main literature data concerning the value of DTI parameters in monitoring disease progression. The observed correlations between DTI parameters on one hand and clinical scores and/or disease duration on the other constitute strong evidence of the value of DTI in monitoring disease progression. In MSA, the ataxia score was correlated with ADC values in the pons and the upper cerebellar peduncles, whereas both the motor score and the disease duration were correlated with putaminal ADC values. In conclusion, DTI and connectivity studies constitute promising tools for differentiating between "Parkinson-plus" syndromes.

Neuroimaging of rapidly progressive dementias, part 1: neurodegenerative etiologies

Most dementias begin insidiously, developing slowly and generally occurring in the elderly age group. The so-called rapidly progressive dementias constitute a different, diverse collection of conditions, many of which are reversible or treatable. For this reason, prompt identification and assessment of acute and subacute forms of dementia are critical to effective treatment. Numerous other entities within this category of presenile rapid-onset dementias are untreatable such as the prion-related diseases. Neuroimaging aids in the diagnosis and evaluation of many of these rapidly progressive dementias, which include myriad conditions ranging from variations of more common neurodegenerative dementias, such as Alzheimer disease, dementia with Lewy bodies, and frontotemporal dementia; infectious-related dementias such as acquired immune deficiency syndrome dementia; autoimmune and malignancy-related conditions; to toxic and metabolic forms of encephalopathy. This first of a 2-part review will specifically address the ability of MR imaging and ancillary neuroimaging strategies to support the diagnostic evaluation of rapidly progressive dementias due to neurodegenerative causes.

The value of GRE, ADC and routine MRI in distinguishing Parkinsonian disorders

OBJECTIVES

To study different radiological signs and sequences including apparent diffusion coefficient (ADC) and gradient echo (GRE) to differentiate degenerative parkinsonian syndromes.

BACKGROUND

Multiple system atrophy (MSA), Parkinson's disease (PD), progressive supranuclear palsy (PSP) and corticobasal degeneration (CbD) differ in the pattern of neurodegeneration and cellular damage. Measuring the ADC, GRE sequences for paramagnetic substances and simple anatomical assessments have been reported individually to assist in separating some of these disorders, but have not been compared.

METHODS

brain MRIs from May 2002 to February 2008 were retrospectively evaluated by raters blinded to the clinical diagnosis for predefined MRI signs on T1, T2 and GRE sequences. ADC values were quantitatively measured. Medical records were objectively analyzed using standard clinical criteria for different parkinsonian syndromes.

RESULTS

195 cases comprising of 61 PD, 15 MSA-P, 7 MSA-C, 21 PSP, 6 Corticobasal syndrome, 21 not fitting criteria and 64 controls were evaluated. 73% of patients with MSA-P had hypointensity of the putamen (compared to the pallidum) on GRE. The specificity of this sign to diagnose MSA-P was 90% versus PD and 76% versus PSP. When GRE hypointensity was combined with atrophy of the putamen the specificity improved to 98% (versus PD) and 95% (versus PSP) without altering the sensitivity. The ADC values were significantly higher in the middle cerebellar peduncle in cases with MSA-C versus controls, PD and PSP (p<0.001).

CONCLUSIONS

The combination of hypointensity and atrophy of the putamen on GRE is useful in differentiating MSA-P from other parkinsonian syndromes.

The value of putaminal diffusion imaging versus 18-fluorodeoxyglucose positron emission tomography for the differential diagnosis of the Parkinson variant of multiple system atrophy

Differentiating the Parkinson variant of multiple system atrophy (MSA-P) from idiopathic Parkinson's disease (PD) and other forms of atypical parkinsonism can be difficult because symptoms overlap considerably. 18-Fluorodeoxyglucose positron emission tomography (FDG-PET) is a powerful imaging technique that can assist in the diagnosis of MSA-P via detection of putaminal and cerebellar hypometabolism. Recent studies suggest that diffusion-weighted imaging (DWI) might be of similar diagnostic value, as it can detect microstructural damage in the putamen by means of an increased mean diffusivity (MD). The aim of this study was a direct comparison of DWI and FDG-PET by using both methods on the same subject cohort. To this end, combined DWI and FDG-PET were employed in patients with MSA-P (n = 11), PD (n = 13), progressive supranuclear palsy (n = 8), and in 6 control subjects. MD values and FDG uptake ratios were derived from volumetric parcellations of the putamen and subjected to further analysis of covariance (ANCOVA) and receiver operating characteristics analyses. MSA-P was found to be associated with an increased posterior putaminal MD (P < 0.001 in all subgroup comparisons) that correlated strongly with local reductions in FDG uptake (r = -0.85, P = 0.002). DWI discriminated patients with MSA-P from other subgroups nearly as accurately as FDG-PET (area under the curve = 0.89 vs 0.95, P = 0.27 [pooled data]). Our data suggest a close association between the amount of putaminal microstructural damage and a reduced energy metabolism in patients with MSA-P. The clinical use of DWI for the differential diagnosis of MSA-P is encouraged.

Longitudinal quantitative MRI in multiple system atrophy and progressive supranuclear palsy

OBJECTIVE

MRI has been used in parkinsonism to assess atrophy, tissue water diffusivity, and mineral deposition but usually at a single time-point. However, multiple system atrophy (MSA) and progressive supranuclear palsy (PSP) are progressive diseases. This study assessed the value of longitudinal MRI in characterizing the time course of the degenerative process.

METHODS

Two serial MRIs (mean 23 months apart) were retrospectively analyzed in 12 MSA, 6 PSP, and 18 age and sex matched controls. Assessment included selected cross-sectional areas, regional apparent diffusion coefficient (ADC) and gradient echo (GRE) intensity ratios of the lateral ventricles, caudate, putamen, middle cerebellar peduncle, pons and midbrain.

RESULTS

On follow-up imaging, there was a larger ADC increase in the putamen in PSP over time compared to controls (p = 0.02). In MSA there was greater volume loss in the pons over time compared to controls (p = 0.002). In MSA the changes in middle cerebellar peduncle ADC were correlated with motor symptom severity according to the Unified Parkinson's Disease Rating Scale Part III (p = 0.005).

CONCLUSIONS

Evidence of progressive neurodegeneration can be observed on MRI in MSA and PSP within two years consisting of increasing putaminal ADC in PSP and pontine atrophy in MSA.

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

Differentiating Parkinson's disease (PD) from other types of neurodegenerative atypical parkinsonism (AP) can be challenging, especially in early disease stages. Routine brain magnetic resonance imaging (MRI) can show atrophy or signal changes in several parts of the brain with fairly high specificity for particular forms of AP, but the overall diagnostic value of routine brain MRI is limited. In recent years, various advanced MRI sequences have become available, including diffusion weighted imaging (DWI) and diffusion tensor imaging (DTI). Here, we review available literature on the value of diffusion MRI for identifying and quantifying different patterns of neurodegeneration in PD and AP, in relation to what is known of underlying histopathologic changes and clinical presentation of these diseases. Next, we evaluate the value of diffusion MRI to differentiate between PD and AP and the potential value of serial diffusion MRI to monitor disease progression. We conclude that diffusion MRI may quantify patterns of neurodegeneration which could be of additional value in clinical use. Future prospective clinical cohort studies are warranted to assess the added diagnostic value of diffusion MRI.

Assessment of global and regional diffusion changes along white matter tracts in parkinsonian disorders by MR tractography

Purpose

The aim of the study was to determine the usefulness of diffusion tensor tractography (DTT) in parkinsonian disorders using a recently developed method for normalization of diffusion data and tract size along white matter tracts. Furthermore, the use of DTT in selected white matter tracts for differential diagnosis was assessed.

Methods

We quantified global and regional diffusion parameters in major white matter tracts in patients with multiple system atrophy (MSA), progressive nuclear palsy (PSP), idiopathic Parkinson’s disease (IPD) and healthy controls). Diffusion tensor imaging data sets with whole brain coverage were acquired at 3 T using 48 diffusion encoding directions and a voxel size of 2×2×2 mm³. DTT of the corpus callosum (CC), cingulum (CG), corticospinal tract (CST) and middle cerebellar peduncles (MCP) was performed using multiple regions of interest. Regional evaluation comprised projection of fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD) and the apparent area coefficient (AAC) onto a calculated mean tract and extraction of their values along each structure.

Results

There were significant changes of global DTT parameters in the CST (MSA and PSP), CC (PSP) and CG (PSP). Consistent tract-specific variations in DTT parameters could be seen along each tract in the different patient groups and controls. Regional analysis demonstrated significant changes in the anterior CC (MD, RD and FA), CST (MD) and CG (AAC) of patients with PSP compared to controls. Increased MD in CC and CST, as well as decreased AAC in CG, was correlated with a diagnosis of PSP compared to IPD.

Conclusions

DTT can be used for demonstrating disease-specific regional white matter changes in parkinsonian disorders. The anterior portion of the CC was identified as a promising region for detection of neurodegenerative changes in patients with PSP, as well as for differential diagnosis between PSP and IPD.