Proposed neuroimaging criteria for the diagnosis of multiple system atrophy

The potential of phosphorylated α-synuclein as a biomarker for the diagnosis and monitoring of multiple system atrophy

INTRODUCTION

Multiple system atrophy (MSA) is a rapidly progressive neurodegenerative disorder characterized by the presence of glial cytoplasmic inclusions (GCIs) containing aggregated α-synuclein (α-Syn). Accurate diagnosis and monitoring of MSA present significant challenges, which can lead to potential misdiagnosis and inappropriate treatment. Biomarkers play a crucial role in improving the accuracy of MSA diagnosis, and phosphorylated α-synuclein (p-syn) has emerged as a promising biomarker for aiding in diagnosis and disease monitoring.

METHODS

A literature search was conducted on PubMed, Scopus, and Google Scholar using specific keywords and MeSH terms without imposing a time limit. Inclusion criteria comprised various study designs including experimental studies, case-control studies, and cohort studies published only in English, while conference abstracts and unpublished sources were excluded.

RESULTS

Increased levels of p-syn have been observed in various samples from MSA patients, such as red blood cells, cerebrospinal fluid, oral mucosal cells, skin, and colon biopsies, highlighting their diagnostic potential. The α-Syn RT-QuIC assay has shown sensitivity in diagnosing MSA and tracking its progression. Meta-analyses and multicenter investigations have confirmed the diagnostic value of p-syn in cerebrospinal fluid, demonstrating high specificity and sensitivity in distinguishing MSA from other neurodegenerative diseases. Moreover, combining p-syn with other biomarkers has further improved the diagnostic accuracy of MSA.

CONCLUSION

The p-syn stands out as a promising biomarker for MSA. It is found in oligodendrocytes and shows a correlation with disease severity and progression. However, further research and validation studies are necessary to establish p-syn as a reliable biomarker for MSA. If proven, p-syn could significantly contribute to early diagnosis, disease monitoring, and assessing treatment response.

Quantitative cellular changes in multiple system atrophy brains

Multiple system atrophy (MSA) is a neurodegenerative disorder characterised by a combined symptomatology of parkinsonism, cerebellar ataxia, autonomic failure and corticospinal dysfunction. In brains of MSA patients, the hallmark lesion is the aggregation of misfolded alpha-synuclein in oligodendrocytes. Even though the underlying pathological mechanisms remain poorly understood, the evidence suggests that alpha-synuclein aggregation in oligodendrocytes may contribute to the neurodegeneration seen in MSA. The primary aim of this review is to summarise the published stereological data on the total number of neurons and glial cell subtypes (oligodendrocytes, astrocytes and microglia) and volumes in brains from MSA patients. Thus, we include in this review exclusively the reports of unbiased quantitative data from brain regions including the neocortex, nuclei of the cerebrum, the brainstem and the cerebellum. Furthermore, we compare and discuss the stereological results in the context of imaging findings and MSA symptomatology. In general, the stereological results agree with the common neuropathological findings of neurodegeneration and gliosis in brains from MSA patients and support a major loss of nigrostriatal neurons in MSA patients with predominant parkinsonism (MSA-P), as well as olivopontocerebellar atrophy in MSA patients with predominant cerebellar ataxia (MSA-C). Surprisingly, the reports indicate only a minor loss of oligodendrocytes in sub-cortical regions of the cerebrum (glial cells not studied in the cerebellum) and negligible changes in brain volumes. In the past decades, the use of stereological methods has provided a vast amount of accurate information on cell numbers and volumes in the brains of MSA patients. Combining different techniques such as stereology and diagnostic imaging (e.g. MRI, PET and SPECT) with clinical data allows for a more detailed interdisciplinary understanding of the disease and illuminates the relationship between neuropathological changes and MSA symptomatology.

Case report: Atypical Parkinsonism following SARS-CoV-2 infection

A wide range of neurological manifestations have been reported during the COVID-19 pandemic, including a variety of Parkinsonian cases. The association of numerous viruses with the development of persistent or transient Parkinsonism has been well-documented. We observed a patient who developed a levodopa non-responsive Parkinsonian syndrome with dysautonomia during a prolonged stay at home for COVID-19. Although the temporal proximity of the emerging Parkinsonian features with a COVID-19 diagnosis suggested a causal relationship, we considered the possibility of a coincidental occurrence of multiple system atrophy. We discuss the patient's clinical features in relation to the established clinical diagnostic criteria and review differential diagnoses as well as the role of SARS-CoV-2 infection.

Comparative validation of AI and non-AI methods in MRI volumetry to diagnose Parkinsonian syndromes

Automated segmentation and volumetry of brain magnetic resonance imaging (MRI) scans are essential for the diagnosis of Parkinson's disease (PD) and Parkinson's plus syndromes (P-plus). To enhance the diagnostic performance, we adopt deep learning (DL) models in brain MRI segmentation and compared their performance with the gold-standard non-DL method. We collected brain MRI scans of healthy controls ([Formula: see text]) and patients with PD ([Formula: see text]), multiple systemic atrophy ([Formula: see text]), and progressive supranuclear palsy ([Formula: see text]) at Samsung Medical Center from January 2017 to December 2020. Using the gold-standard non-DL model, FreeSurfer (FS), we segmented six brain structures: midbrain, pons, caudate, putamen, pallidum, and third ventricle, and considered them as annotated data for DL models, the representative convolutional neural network (CNN) and vision transformer (ViT)-based models. Dice scores and the area under the curve (AUC) for differentiating normal, PD, and P-plus cases were calculated to determine the measure to which FS performance can be reproduced as-is while increasing speed by the DL approaches. The segmentation times of CNN and ViT for the six brain structures per patient were 51.26 ± 2.50 and 1101.82 ± 22.31 s, respectively, being 14 to 300 times faster than FS (15,735 ± 1.07 s). Dice scores of both DL models were sufficiently high (> 0.85) so their AUCs for disease classification were not inferior to that of FS. For classification of normal vs. P-plus and PD vs. P-plus (except multiple systemic atrophy - Parkinsonian type) based on all brain parts, the DL models and FS showed AUCs above 0.8, demonstrating the clinical value of DL models in addition to FS. DL significantly reduces the analysis time without compromising the performance of brain segmentation and differential diagnosis. Our findings may contribute to the adoption of DL brain MRI segmentation in clinical settings and advance brain research.

Oligodendrocytes Prune Axons Containing α-Synuclein Aggregates In Vivo: Lewy Neurites as Precursors of Glial Cytoplasmic Inclusions in Multiple System Atrophy?

α-Synucleinopathies are spreading neurodegenerative disorders characterized by the intracellular accumulation of insoluble aggregates populated by α-Synuclein (α-Syn) fibrils. In Parkinson's disease (PD) and dementia with Lewy bodies, intraneuronal α-Syn aggregates are referred to as Lewy bodies in the somata and as Lewy neurites in the neuronal processes. In multiple system atrophy (MSA) α-Syn aggregates are also found within mature oligodendrocytes (OLs) where they form Glial Cytoplasmic Inclusions (GCIs). However, the origin of GCIs remains enigmatic: (i) mature OLs do not express α-Syn, precluding the seeding and the buildup of inclusions and (ii) the artificial overexpression of α-Syn in OLs of transgenic mice results in a burden of soluble phosphorylated α-Syn but fails to form α-Syn fibrils. In contrast, mass spectrometry of α-Syn fibrillar aggregates from MSA patients points to the neuronal origin of the proteins intimately associated with the fibrils within the GCIs. This suggests that GCIs are preassembled in neurons and only secondarily incorporated into OLs. Interestingly, we recently isolated a synthetic human α-Syn fibril strain (1B fibrils) capable of seeding a type of neuronal inclusion observed early and specifically during MSA. Our goal was thus to investigate whether the neuronal α-Syn pathology seeded by 1B fibrils could eventually be transmitted to OLs to form GCIs in vivo. After confirming that mature OLs did not express α-Syn to detectable levels in the adult mouse brain, a series of mice received unilateral intra-striatal injections of 1B fibrils. The resulting α-Syn pathology was visualized using phospho-S129 α-Syn immunoreactivity (pSyn). We found that even though 1B fibrils were injected unilaterally, many pSyn-positive neuronal somas were present in layer V of the contralateral perirhinal cortex after 6 weeks. This suggested a fast retrograde spread of the pathology along the axons of crossing cortico-striatal neurons. We thus scrutinized the posterior limb of the anterior commissure, i.e., the myelinated interhemispheric tract containing the axons of these neurons: we indeed observed numerous pSyn-positive linear Lewy Neurites oriented parallel to the commissural axis, corresponding to axonal segments filled with aggregated α-Syn, with no obvious signs of OL α-Syn pathology at this stage. After 6 months however, the commissural Lewy neurites were no longer parallel but fragmented, curled up, sometimes squeezed in-between two consecutive OLs in interfascicular strands, or even engulfed inside OL perikarya, thus forming GCIs. We conclude that the 1B fibril strain can rapidly induce an α-Syn pathology typical of MSA in mice, in which the appearance of GCIs results from the pruning of diseased axonal segments containing aggregated α-Syn.

Imaging in Movement Disorders

OBJECTIVE

This article reviews commonly used imaging modalities in movement disorders, particularly parkinsonism. The review includes the diagnostic utility, role in differential diagnosis, reflection of pathophysiology, and limitations of neuroimaging in the setting of movement disorders. It also introduces promising new imaging modalities and describes the current status of research.

LATEST DEVELOPMENTS

Iron-sensitive MRI sequences and neuromelanin-sensitive MRI can be used to directly assess the integrity of nigral dopaminergic neurons and thus may reflect disease pathology and progression throughout the full range of severity in Parkinson disease (PD). The striatal uptake of presynaptic radiotracers in their terminal axons as currently assessed using clinically approved positron emission tomography (PET) or single-photon emission computed tomography (SPECT) imaging correlates with nigral pathology and disease severity only in early PD. Cholinergic PET, using radiotracers that target the presynaptic vesicular acetylcholine transporter, constitutes a substantial advance and may provide crucial insights into the pathophysiology of clinical symptoms such as dementia, freezing, and falls.

ESSENTIAL POINTS

In the absence of valid, direct, objective biomarkers of intracellular misfolded α-synuclein, PD remains a clinical diagnosis. The clinical utility of PET- or SPECT-based striatal measures is currently limited given their lack of specificity and inability to reflect nigral pathology in moderate to severe PD. These scans may be more sensitive than clinical examination to detect nigrostriatal deficiency that occurs in multiple parkinsonian syndromes and may still be recommended for clinical use in the future to identify prodromal PD if and when disease-modifying treatments become available. Multimodal imaging to evaluate underlying nigral pathology and its functional consequences may hold the key to future advances.

Multiple system atrophy-cerebellar: A case report and literature review

We reported a case of a 48-year-old female patient admitted to the hospital due to balance disorder which progressed rapidly within 1 week. Cerebral magnetic resonance imaging showed significant atrophy and hyperintensities at the middle cerebellar peduncles and the "hot cross bun" sign of the pons. The final diagnosis was probable multiple system atrophy, cerebellar subtype. The clinical and imaging findings will be discussed as well as a brief literature review.

Clinical outcomes and cognitive impairments between progressive supranuclear palsy and multiple system atrophy

BACKGROUND

Both progressive supranuclear palsy (PSP) and multiple system atrophy (MSA) belong to atypical parkinsonian syndromes. It is important to differentiate these diseases accurately. We compared clinical outcomes and cognitive impairments between PSP and MSA.

METHODS

Eighty-five MSA parkinsonism type (MSA-P) patients and 76 PSP patients participated in this research. The Montreal Cognitive Assessment (MoCA) and the mini-mental state examination (MMSE) evaluated cognitive function.

RESULTS

MSA-P patients had a significantly higher incidence of dyskinesia, fall, urinary symptoms, and constipation, whereas patients with PSP had a higher incidence of tremor and salivation. MSA-P patients had higher MMSE and MoCA scores than PSP patients. The MMSE score showed a diagnostic cut-off score of 24.5 in PSP versus MSA-P. The MoCA score showed a diagnostic cut-off score of 20.5 in PSP versus MSA-P.

CONCLUSION

In conclusion, patients with PSP had differences in the clinical outcomes and cognitive impairments compared with MSA-P patients. PSP patients had more severe cognitive deficits. The score of MMSE and MoCA could be used in distinguishing MSA-P from PSP.

Imaging biomarkers for early multiple system atrophy

OBJECTIVE

To systematically evaluate structural MRI and diffusion MRI features for cross-sectional discrimination and tracking of longitudinal disease progression in early multiple system atrophy (MSA).

METHODS

In a prospective, longitudinal study of synucleinopathies with imaging on 14 controls and 29 MSA patients recruited at an early disease stage (15 predominant cerebellar ataxia subtype or MSA-C and 14 predominant parkinsonism subtype or MSA-P), we computed regional morphometric and diffusion MRI features. We identified morphometric features by ranking them based on their ability to distinguish MSA-C from controls and MSA-P from controls and evaluated diffusion changes in these regions. For the top performing regions, we evaluated their utility for tracking longitudinal disease progression using imaging from 12-month follow-up and computed sample size estimates for a hypothetical clinical trial in MSA. We also computed these selected morphometric features in an independent validation dataset.

RESULTS

We found that morphometric changes in the cerebellar white matter, brainstem, and pons can separate early MSA-C patients from controls both cross-sectionally and longitudinally (p < 0.01). The putamen and striatum, though useful for separating early MSA-P patients from control subjects at baseline, were not useful for tracking MSA disease progression. Cerebellum white matter diffusion changes aided in capturing early disease related degeneration in MSA.

INTERPRETATION

Regardless of clinically predominant features at the time of MSA assessment, brainstem and cerebellar pathways progressively deteriorate with disease progression. Quantitative measurements of these regions are promising biomarkers for MSA diagnosis in early disease stage and potential surrogate markers for future MSA clinical trials.

Multiple system atrophy

Multiple system atrophy (MSA) is a rare neurodegenerative disease that is characterized by neuronal loss and gliosis in multiple areas of the central nervous system including striatonigral, olivopontocerebellar and central autonomic structures. Oligodendroglial cytoplasmic inclusions containing misfolded and aggregated α-synuclein are the histopathological hallmark of MSA. A firm clinical diagnosis requires the presence of autonomic dysfunction in combination with parkinsonism that responds poorly to levodopa and/or cerebellar ataxia. Clinical diagnostic accuracy is suboptimal in early disease because of phenotypic overlaps with Parkinson disease or other types of degenerative parkinsonism as well as with other cerebellar disorders. The symptomatic management of MSA requires a complex multimodal approach to compensate for autonomic failure, alleviate parkinsonism and cerebellar ataxia and associated disabilities. None of the available treatments significantly slows the aggressive course of MSA. Despite several failed trials in the past, a robust pipeline of putative disease-modifying agents, along with progress towards early diagnosis and the development of sensitive diagnostic and progression biomarkers for MSA, offer new hope for patients.

Semiautomated Algorithm for the Diagnosis of Multiple System Atrophy With Predominant Parkinsonism

Objective

Putaminal iron deposition is an important feature that helps differentiate multiple system atrophy with predominant parkinsonism (MSA-p) from Parkinson’s disease (PD). Most previous studies used visual inspection or quantitative methods with manual manipulation to perform this differentiation. We investigated the value of a new semiautomated diagnostic algorithm using 3T-MR susceptibility-weighted imaging for MSA-p.

Methods

This study included 26 MSA-p, 68 PD, and 41 normal control (NC) subjects. The algorithm was developed in 2 steps: 1) determine the image containing the remarkable putaminal margin and 2) calculate the phase-shift values, which reflect the iron concentration. The next step was to identify the best differentiating conditions among several combinations. The highest phase-shift value of each subject was used to assess the most effective diagnostic set.

Results

The raw phase-shift values were present along the lateral margin of the putamen in each group. It demonstrates an anterior-to-posterior gradient that was identified most frequently in MSA-p. The average of anterior 5 phase shift values were used for normalization. The highest area under the receiver operating characteristic curve (0.874, 80.8% sensitivity, and 86.7% specificity) of MSA-p versus PD was obtained under the combination of 3 or 4 vertical pixels and one dominant side when the normalization methods were applied. In the subanalysis for the MSA-p patients with a longer disease duration, the performance of the algorithm improved.

Conclusion

This algorithm detected the putaminal lateral margin well, provided insight into the iron distribution of the putaminal rim of MSA-p, and demonstrated good performance in differentiating MSA-p from PD.

Diagnostic efficacy of the magnetic resonance T1w/T2w ratio for the middle cerebellar peduncle in multiple system atrophy and spinocerebellar ataxia: A preliminary study

BACKGROUND

The standardized T1-weighted/T2-weighted (sT1w/T2w) ratio for the middle cerebellar peduncle (MCP) has been reported to be sensitive for detecting degenerative changes in the cerebellar subtype of multiple system atrophy (MSA-C), even in the early stages. We aimed to investigate the diagnostic value of the MCP sT1w/T2w ratio for differentiating between MSA-C and spinocerebellar ataxia (SCA).

METHODS

We included 32 MSA-C, 8 SCA type 3 (SCA3), 16 SCA type 6 (SCA6) patients, and 17 controls, and the MCP sT1w/T2w ratio was analyzed using a region-of-interest approach. The diagnostic performance of the MCP sT1w/T2w ratio in discriminating among MSA-C, SCA3, and SCA6 was assessed and compared with diagnosis based on visual interpretation of MCP hyperintensities and the "hot cross bun" (HCB) sign.

RESULTS

MCP sT1w/T2w ratio values were markedly lower in patients with MSA-C than in those with SCA3, those with SCA6, and controls (p < 0.001). The MCP sT1w/T2w ratio showed high diagnostic accuracy for distinguishing MSA-C from SCA3 (area under curve = 0.934), SCA6 (area under curve = 0.965), and controls (area under curve = 0.980). The diagnostic accuracy of the MCP sT1w/T2w ratio for differentiating MSA-C from SCA3 or SCA6 (90.0% for MSA-C vs. SCA3, and 91.7% for MSA-C vs. SCA6) was comparable to or superior than that of visual interpretation of MCP hyperintensities (80.0-87.5% in MSA-C vs. SCA3 and 87.6-97.9% in MSA-C vs. SCA6) or the HCB sign (72.5-80.0% in MSA-C vs. SCA3 and 77.1-93.8% in MSA-C vs. SCA6).

CONCLUSIONS

The MCP sT1w/T2w ratio might be a sensitive imaging-based marker for detecting MSA-C-related changes and differentiating MSA-C from SCA3 or SCA6.

Normative Data for Brainstem Structures, the Midbrain-to-Pons Ratio, and the Magnetic Resonance Parkinsonism Index

BACKGROUND AND PURPOSE

Imaging biomarkers derived from different brainstem structures are suggested to differentiate among parkinsonian disorders, but clinical implementation requires normative data. The main objective was to establish high-quality, sex-specific data for relevant brainstem structures derived from MR imaging in healthy subjects from the general population in their sixth and seventh decades of life.

MATERIALS AND METHODS

3D T1WI acquired on the same 1.5T scanner of 996 individuals (527 women) between 50 and 66 years of age from a prospective population study was used. The area of the midbrain and pons and the widths of the middle cerebellar peduncles and superior cerebellar peduncles were measured, from which the midbrain-to-pons ratio and Magnetic Resonance Parkinsonism Index [MRPI = (Pons Area / Midbrain Area) × (Middle Cerebellar Peduncles / Superior Cerebellar Peduncles)] were calculated. Sex differences in brainstem measures and correlations to age, height, weight, and body mass index were investigated.

RESULTS

Inter- and intrareliability for measuring the different brainstem structures showed good-to-excellent reliability (intraclass correlation coefficient = 0.785-0.988). There were significant sex differences for the pons area, width of the middle cerebellar peduncles and superior cerebellar peduncles, midbrain-to-pons ratio, and MRPI (all, P <  .001; Cohen D = 0.44-0.98), but not for the midbrain area (P = .985). There were significant very weak-to-weak correlations between several of the brainstem measures and age, height, weight, and body mass index in both sexes. However, no systematic difference in distribution caused by these variables was found, and because age had the highest and most consistent correlations, age-/sex-specific percentiles for the brainstem measures were created.

CONCLUSIONS

We present high-quality, sex-specific data and age-/sex-specific percentiles for the mentioned brainstem measures. These normative data can be implemented in the neuroradiologic work-up of patients with suspected brainstem atrophy to avoid the risk of misdiagnosis.

A Guide for the Differential Diagnosis of Multiple System Atrophy in Clinical Practice

Multiple system atrophy (MSA) is a sporadic and progressive neurodegenerative disorder with a complex differential diagnosis. A range of disorders- also of nondegenerative etiology- can mimic MSA, expanding its differential diagnosis. Both misdiagnosis and diagnostic delays are relatively common in clinical practice. A correct diagnosis is vital for daily clinical practice, in order to facilitate proper counselling and to timely install therapies in treatable disorders that mimic MSA. A correct diagnosis is also essential for including properly classified individuals into research studies that aim to better understand the pathophysiology of MSA, to develop specific biomarkers or to evaluate novel symptomatic or disease-modifying therapies. Here, we offer some practical guidance to support the diagnostic process, by highlighting conditions that may be considered as MSA lookalikes, by emphasizing some key clinical aspects of these mimics, and by discussing several useful ancillary diagnostic tests.

Individual voxel-based morphometry adjusting covariates in multiple system atrophy

INTRODUCTION

This study aimed to evaluate whether novel individual voxel-based morphometry adjusting covariates (iVAC), such as age, sex, and total intracranial volume, could increase the accuracy of a diagnosis of multiple system atrophy (MSA) and enable the differentiation of MSA from Parkinson's disease (PD).

METHODS

We included 53 MSA patients (MSA-C: 33, MSA-P: 20), 53 PD patients, and 189 healthy controls in this study. All participants underwent high-resolution T1-weighted imaging (WI) and T2-WI with a 3.0-T MRI scanner. We evaluated the occurrence of significant atrophic findings in the pons/middle cerebellar peduncle (MCP) and putamen on iVAC and compared these findings with characteristic changes on T2-WI.

RESULTS

On iVAC, abnormal findings were observed in the pons/MCP of 96.2% of MSA patients and in the putamen of 80% of MSA patients; however, on T2-WI, they were both observed at a frequency of 60.4% in MSA patients. On iVAC, all but one MSA-P patient (98.1%) showed significant atrophic changes in the pons/MCP or putamen. By contrast, 69.8% of patients with MSA showed abnormal signal changes in the pons/MCP or putamen on T2-WI. iVAC yielded 95.0% sensitivity and 96.2% specificity for differentiating MSA-P from PD.

CONCLUSION

iVAC enabled us to recognize the morphological characteristics of MSA visually and with high accuracy compared to T2-WI, indicating that iVAC is a potential diagnostic screening tool for MSA.

α-Synuclein in blood exosomes immunoprecipitated using neuronal and oligodendroglial markers distinguishes Parkinson's disease from multiple system atrophy

The diagnosis of Parkinson’s disease (PD) and atypical parkinsonian syndromes is difficult due to the lack of reliable, easily accessible biomarkers. Multiple system atrophy (MSA) is a synucleinopathy whose symptoms often overlap with PD. Exosomes isolated from blood by immunoprecipitation using CNS markers provide a window into the brain’s biochemistry and may assist in distinguishing between PD and MSA. Thus, we asked whether α-synuclein (α-syn) in such exosomes could distinguish among healthy individuals, patients with PD, and patients with MSA. We isolated exosomes from the serum or plasma of these three groups by immunoprecipitation using neuronal and oligodendroglial markers in two independent cohorts and measured α-syn in these exosomes using an electrochemiluminescence ELISA. In both cohorts, α-syn concentrations were significantly lower in the control group and significantly higher in the MSA group compared to the PD group. The ratio between α-syn concentrations in putative oligodendroglial exosomes compared to putative neuronal exosomes was a particularly sensitive biomarker for distinguishing between PD and MSA. Combining this ratio with the α-syn concentration itself and the total exosome concentration, a multinomial logistic model trained on the discovery cohort separated PD from MSA with an AUC = 0.902, corresponding to 89.8% sensitivity and 86.0% specificity when applied to the independent validation cohort. The data demonstrate that a minimally invasive blood test measuring α-syn in blood exosomes immunoprecipitated using CNS markers can distinguish between patients with PD and patients with MSA with high sensitivity and specificity. Future optimization and validation of the data by other groups would allow this strategy to become a viable diagnostic test for synucleinopathies.

Neuropathology of multiple system atrophy: Kurt Jellinger`s legacy

Multiple System Atrophy (MSA) is a rare, fatal neurodegenerative disorder. Its etiology and exact pathogenesis still remain poorly understood and currently no disease-modifying therapy is available to halt or slow down this detrimental neurodegenerative process. Hallmarks of the disease are α-synuclein rich glial cytoplasmic inclusions (GCIs). Neuropathologically, various degrees of striatonigral degeneration (SND) and olivopontocerebellar atrophy (OPCA) can be observed. Since the original descriptions of this multifaceted disorder, several steps forward have been made to clarify its neuropathological hallmarks and key pathophysiological mechanisms. The Austrian neuropathologist Kurt Jellinger substantially contributed to the understanding of the underlying neuropathology of this disease, to its standardized assessment and to a broad systematical clinic-pathological correlation. On the occasion of his 90th birthday, we reviewed the current state of the art in the field of MSA neuropathology, highlighting Prof. Jellinger’s substantial contribution.

Magnetic resonance imaging abnormalities as a marker of multiple system atrophy in isolated rapid eye movement sleep behavior disorder

STUDY OBJECTIVES

Patients with isolated rapid eye movement (REM) sleep behavior disorder (IRBD) develop Parkinson disease (PD), dementia with Lewy bodies (DLB), or multiple system atrophy (MSA). Magnetic resonance imaging (MRI) is abnormal in MSA showing abnormalities in the putamen, cerebellum, and brainstem. Our objective was to evaluate the usefulness of MRI to detect MRI abnormalities in IRBD and predict development of MSA and not PD and DLB.

METHODS

In IRBD patients that eventually developed PD, DLB, and MSA, we looked for the specific structural MRI abnormalities described in manifest MSA (e.g. hot cross-bun sign, putaminal rim, and cerebellar atrophy). We compared the frequency of these MRI changes among groups of converters (PD, DLB, and MSA) and analyzed their ability to predict development of MSA. The clinical and radiological features of the IRBD patients that eventually converted to MSA are described in detail.

RESULTS

A total of 61 IRBD patients who underwent MRI phenoconverted to PD (n = 30), DLB (n = 26), and MSA (n = 5) after a median follow-up of 2.4 years from neuroimaging. MRI changes typical of MSA were found in four of the five (80%) patients who converted to MSA and in three of the 56 (5.4%) patients who developed PD or DLB. MRI changes of MSA had sensitivity of 80.0%, specificity of 94.6%, positive likelihood ratio of 14.9 (95% CI 4.6-48.8), and negative likelihood ratio of 0.2 (95% CI 0.04-1.2) to predict MSA.

CONCLUSIONS

In IRBD, conventional brain MRI is helpful to predict conversion to MSA. The specific MRI abnormalities of manifest MSA may be detected in its premotor stage.

Imaging Familial and Sporadic Neurodegenerative Disorders Associated with Parkinsonism

In this paper, the structural and functional imaging changes associated with sporadic and genetic Parkinson's disease and atypical Parkinsonian variants are reviewed. The role of imaging for supporting diagnosis and detecting subclinical disease is discussed, and the potential use and drawbacks of using imaging biomarkers for monitoring disease progression is debated. Imaging changes associated with nonmotor complications of PD are presented. The similarities and differences in imaging findings in Lewy body dementia, Parkinson's disease dementia, and Alzheimer's disease are discussed.

Inverted circadian variation of arterial pressure in a geriatric patient: an indicator of autonomic dysfunction

BACKGROUND

Orthostatic hypotension (OH) in geriatric patients frequently involves a component of autonomic failure (AF). The combination of OH with nocturnal hypertension (NHT) is indicative of AF, which is described as pure (PAF), when neurologic symptoms are absent, or as multisystem atrophy (MSA), when combined with motor disturbance (Parkinsonism or Parkinson disease).

CASE PRESENTATION

An 87-year-old man presented with long-lasting OH. He frequently fell, causing several fractures, and he developed heart failure. Blood pressure (BP) registration revealed a reversal of the day-night rhythm with NHT. An 18-FDG PET brain CT scan showed cerebellar hypometabolism, indicating MSA.

CONCLUSIONS

This case demonstrates the use of continuous BP registration in geriatric patients with OH for diagnosing NHT. It illustrates the usefulness of 18-FDG PET brain CT scan to specify the nature of the AF. The case also illustrates the difficulty of managing the combination of OH and NHT.

Magnetic resonance T1w/T2w ratio in the middle cerebellar peduncle might be a sensitive biomarker for multiple system atrophy

OBJECTIVE

We aimed to investigate the use of a myelin-sensitive MRI contrast, the standardized T1-weighted/T2-weighted (sT1w/T2w) ratio, for detecting early changes in the middle cerebellar peduncle (MCP) in cerebellar subtype multiple system atrophy (MSA-C) patients.

METHODS

We included 28 MSA-C patients, including a subset of 17 MSA-C patients within 2 years of disease onset (early MSA-C), and 28 matched healthy controls. T1w and T2w scans were acquired using a 3-T MR system. The sT1w/T2w ratio in MCP was analyzed using SPM12 by utilizing a region-of-interest approach in normalized space. The diagnostic performance of the MCP sT1w/T2w ratio in discriminating MSA-C and the subgroup of early MSA-C from the matched controls was assessed. Correlation analyses were performed to evaluate the relationship between the MCP sT1w/T2w ratio and other clinical parameters including the International Cooperative Ataxia Scale (ICARS) score for quantifying cerebellar ataxia.

RESULTS

Compared to controls, the sT1w/T2w ratio in the MCP was markedly lower in all (p < 0.001) MSA-C patients and 17 early (p < 0.001) MSA-C patients. The MCP sT1w/T2w ratio had high sensitivity (96%) and specificity (100%) to distinguish MSA-C from controls (area under the curve = 0.99), even for the early MSA-C group (area under the curve = 0.99; sensitivity = 94%, specificity = 100%). The MCP sT1w/T2w ratio correlated with the ICARS score in early MSA-C.

CONCLUSIONS

The sT1w/T2w ratio can detect MSA-C-related changes in the MCP, even in the early stages of the disorder, and could be a sensitive biomarker for MSA-C.

KEY POINTS

• The sT1w/T2w ratio can detect MSA-C-related changes in the middle cerebellar peduncle, even in the early stages of the disorder. • The middle cerebellar peduncle sT1w/T2w ratio correlated with a cerebellar ataxia score in early MSA-C patients.

Positron Emission Tomography (PET) and Neuroimaging in the Personalized Approach to Neurodegenerative Causes of Dementia

Generally, dementia should be considered an acquired syndrome, with multiple possible causes, rather than a specific disease in itself. The leading causes of dementia are neurodegenerative and non-neurodegenerative alterations. Nevertheless, the neurodegenerative group of diseases that lead to cognitive impairment and dementia includes multiple possibilities or mixed pathologies with personalized treatment management for each cause, even if Alzheimer's disease is the most common pathology. Therefore, an accurate differential diagnosis is mandatory in order to select the most appropriate therapy approach. The role of personalized assessment in the treatment of dementia is rapidly growing. Neuroimaging is an essential tool for differential diagnosis of multiple causes of dementia and allows a personalized diagnostic and therapeutic protocol based on risk factors that may improve treatment management, especially in early diagnosis during the prodromal stage. The utility of structural and functional imaging could be increased by standardization of acquisition and analysis methods and by the development of algorithms for automated assessment. The aim of this review is to focus on the most commonly used tracers for differential diagnosis in the dementia field. Particularly, we aim to explore ¹⁸F Fluorodeoxyglucose (FDG) and amyloid positron emission tomography (PET) imaging in Alzheimer's disease and in other neurodegenerative causes of dementia.

Diagnosing multiple system atrophy at the prodromal stage

Identifying individuals at the earliest disease stage becomes crucial as we aim to develop disease-modifying treatments for neurodegenerative disorders. Prodromal diagnostic criteria were recently developed for Parkinson's disease (PD) and are forthcoming for dementia with Lewy bodies (DLB). The latest 2008 version of diagnostic criteria for multiple system atrophy (MSA) have improved diagnostic accuracy in early disease stages compared to previous criteria, but we do not yet have formal criteria for prodromal MSA. Building on similar approaches as for PD and DLB, we can identify features on history-taking, clinical examination, and ancillary clinical testing that can predict the likelihood of an individual developing MSA, while also distinguishing it from PD and DLB. The main clinical hallmarks of MSA are REM sleep behavior disorder (RBD) and autonomic dysfunction (particularly orthostatic hypotension and urogenital symptoms), and may be the primary means by which patients with potential prodromal MSA are identified. Preserved olfaction, absence of significant cognitive deficits, urinary retention, and respiratory symptoms such as stridor and respiratory insufficiency can be clinical features that help distinguish MSA from PD and DLB. Finally, ancillary test results including neuroimaging as well as serological and cerebrospinal fluid (CSF) biomarkers may lend further weight to quantifying the likelihood of phenoconversion into MSA. For prodromal criteria, the primary challenges are MSA's lower prevalence, shorter lead time to diagnosis, and strong overlap with other synucleinopathies. Future prodromal criteria may need to first embed the diagnosis into a general umbrella of prodromal alpha-synucleinopathies, followed by identification of features that suggest prodromal MSA as the specific cause.

Differential value of brain magnetic resonance imaging in multiple system atrophy cerebellar phenotype and spinocerebellar ataxias

Clinically differentiating multiple system atrophy cerebellar (MSA-C) phenotype and spinocerebellar ataxias (SCAs) is challenging especially in the early stage. We assessed diagnostic value of brain magnetic resonance imaging (MRI) in differentiating MSA-C and SCAs based at different disease stages (<3, 3–7, and >7 years of disease duration). Overall, 186 patients with probable MSA-C and 117 with genetically confirmed SCAs were included. Hot cross bun (HCB) signs and middle cerebellar peduncle (MCP) hyperintensities were exclusively prevalent in MSA-C compared to SCAs at <3 years (HCB, 44.6% versus 0.9%; MCP hyperintensities, 38.3% versus 0.9%, respectively). Sensitivity, specificity, and positive predictive value (PPV) for HCB signs to differentiate MSA-C from SCAs were 45%, 99%, and 99% and those for MCP hyperintensities were 68%, 99%, and 99%, respectively; considering both HCB signs and MCP hyperintensities, specificity and PPV were 100%. However, the differential value of MRI signs decreased over time. MCP widths were smaller and showed more significant decrease in MSA-C than in SCAs. In conclusion, pontine and MCP changes were exclusively prominent in early stage MSA-C rather than in SCAs. Therefore, we should consider disease duration when interpreting pontine and MCP changes in brain MRIs, which will help better differentiate MSA-C and SCAs.

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.

How to approach a patient with parkinsonism - red flags for atypical parkinsonism

Parkinsonism is a clinical syndrome defined by bradykinesia plus rigidity or tremor. Though most commonly encountered in the setting of idiopathic Parkinson's disease, a number of neurodegenerative, structural, metabolic and toxic neurological disorders can result in parkinsonism. Accurately diagnosing the underlying cause of parkinsonism is of both therapeutic and prognostic relevance, especially as we enter the era of disease-modifying treatment trials for neurodegenerative disorders. Being aware of the wide array of potential causes of parkinsonism is of paramount importance for clinicians. In this chapter, we present a pragmatic clinical approach to patients with parkinsonism, specifically focusing on 'red flags', which should alert one to consider diagnoses other than idiopathic Parkinson's disease.

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.

Altered structural connectivity of the motor subnetwork in multiple system atrophy with cerebellar features

OBJECTIVES

To investigate the structural connectivity of the motor subnetwork in multiple system atrophy with cerebellar features (MSA-C), a distinct subtype of MSA, characterized by predominant cerebellar symptoms.

METHODS

Twenty-three patients with MSA-C and 25 age- and gender-matched healthy controls were recruited for the study. Disease severity was quantified using the Unified Multiple System Atrophy Rating Scale (UMSARS). Diffusion MRI images were acquired and used to compute the structural connectomes (SCs) using probabilistic fiber tracking. The motor network with 12 brain regions and 26 cerebellar regions was extracted and was compared between the groups using analysis of variance at a global (network-wide), nodal (at each node), and edge (at each connection) levels, and was corrected for multiple comparisons. In addition, the acquired connectivity measures were correlated with duration of illness, total Unified MSA Rating Scale (UMSARS), and the motor component score.

RESULTS

Significantly lower global network metrics-global density, transitivity, clustering coefficient, and characteristic path length-were observed in MSA-C (corrected p < 0.05). Reduced nodal strength was observed in the bilateral ventral diencephalon, the left thalamus, and several cerebellar regions. Network-based statistics revealed significant abnormal edge-wise connectivity in 40 connections (corrected p < 0.01), with majority of deficits observed in the cerebellum. Finally, significant negative correlations were observed between UMSARS scores and thalamic and cerebellar connectivity (p < 0.05) as well as between duration of illness and cerebellar connectivity.

CONCLUSIONS

Abnormal connectivity of the basal ganglia and cerebellar network may be causally implicated for the motor features observed in MSA-C.

KEY POINTS

• Structural connectivity of the motor subnetwork was explored in patients with multiple system atrophy with cerebellar features (MSA-C) using probabilistic tractography. • The motor subnetwork in MSA-C has significant alterations in both basal ganglia and cerebellar connectivity, with a higher extent of abnormality in the cerebellum. • These findings may be causally implicated for the motor features of cerebellar dysfunction and parkinsonism observed in MSA-C.

Olfaction and Colour Vision: What Can They Tell Us about Parkinson’s Disease?

Parkinson’s disease is a neurodegenerative disorder with the pathological accumulation of alpha synuclein in the brain and peripheral nerve tissue. Early stages of synucleinopathies, often present clinically with rapid eye movement (REM) sleep disorder (RBD). Clinical markers that indicate early progression from RBD to manifest synucleinopathies include abnormal dopamine transporter (DAT) imaging, motor and non-motor symptoms. Despite the high diagnostic strength of DAT imaging and motor abnormalities, they are not the earliest biomarkers. Non-motor signs of neurodegeneration such as colour vision and olfaction abnormalities are detectable by clinical examination as early as 20 years before disease onset. Detailed analysis of olfactory and colour vision dysfunction can provide valuable information regarding brain pathologies, further specifying clinical phenotypes, and giving clues to underlying pathophysiological mechanisms in Parkinson’s disease and related disorders.

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.

Diagnosis of multiple system atrophy

Multiple system atrophy (MSA) may be difficult to distinguish clinically from other disorders, particularly in the early stages of the disease. An autonomic-only presentation can be indistinguishable from pure autonomic failure. Patients presenting with parkinsonism may be misdiagnosed as having Parkinson disease. Patients presenting with the cerebellar phenotype of MSA can mimic other adult-onset ataxias due to alcohol, chemotherapeutic agents, lead, lithium, and toluene, or vitamin E deficiency, as well as paraneoplastic, autoimmune, or genetic ataxias. A careful medical history and meticulous neurological examination remain the cornerstone for the accurate diagnosis of MSA. Ancillary investigations are helpful to support the diagnosis, rule out potential mimics, and define therapeutic strategies. This review summarizes diagnostic investigations useful in the differential diagnosis of patients with suspected MSA. Currently used techniques include structural and functional brain imaging, cardiac sympathetic imaging, cardiovascular autonomic testing, olfactory testing, sleep study, urological evaluation, and dysphagia and cognitive assessments. Despite advances in the diagnostic tools for MSA in recent years and the availability of consensus criteria for clinical diagnosis, the diagnostic accuracy of MSA remains sub-optimal. As other diagnostic tools emerge, including skin biopsy, retinal biomarkers, blood and cerebrospinal fluid biomarkers, and advanced genetic testing, a more accurate and earlier recognition of MSA should be possible, even in the prodromal stages. This has important implications as misdiagnosis can result in inappropriate treatment, patient and family distress, and erroneous eligibility for clinical trials of disease-modifying drugs.

Clinical Neurology and Epidemiology of the Major Neurodegenerative Diseases

Neurodegenerative diseases are a common cause of morbidity and cognitive impairment in older adults. Most clinicians who care for the elderly are not trained to diagnose these conditions, perhaps other than typical Alzheimer's disease (AD). Each of these disorders has varied epidemiology, clinical symptomatology, laboratory and neuroimaging features, neuropathology, and management. Thus, it is important that clinicians be able to differentiate and diagnose these conditions accurately. This review summarizes and highlights clinical aspects of several of the most commonly encountered neurodegenerative diseases, including AD, frontotemporal dementia (FTD) and its variants, progressive supranuclear palsy (PSP), corticobasal degeneration (CBD), Parkinson's disease (PD), dementia with Lewy bodies (DLB), multiple system atrophy (MSA), and Huntington's disease (HD). For each condition, we provide a brief overview of the epidemiology, defining clinical symptoms and diagnostic criteria, relevant imaging and laboratory features, genetics, pathology, treatments, and differential diagnosis.

as-PSOCT: Volumetric microscopic imaging of human brain architecture and connectivity

Polarization sensitive optical coherence tomography (PSOCT) with serial sectioning has enabled the investigation of 3D structures in mouse and human brain tissue samples. By using intrinsic optical properties of back-scattering and birefringence, PSOCT reliably images cytoarchitecture, myeloarchitecture and fiber orientations. In this study, we developed a fully automatic serial sectioning polarization sensitive optical coherence tomography (as-PSOCT) system to enable volumetric reconstruction of human brain samples with unprecedented sample size and resolution. The 3.5 μm in-plane resolution and 50 μm through-plane voxel size allow inspection of cortical layers that are a single-cell in width, as well as small crossing fibers. We show the abilities of as-PSOCT in quantifying layer thicknesses of the cerebellar cortex and creating microscopic tractography of intricate fiber networks in the subcortical nuclei and internal capsule regions, all based on volumetric reconstructions. as-PSOCT provides a viable tool for studying quantitative cytoarchitecture and myeloarchitecture and mapping connectivity with microscopic resolution in the human brain.

Hyperconnective and hypoconnective cortical and subcortical functional networks in multiple system atrophy

INTRODUCTION

In multiple system atrophy (MSA), the organization of the functional brain connectivity within cortical and subcortical networks and its clinical correlates remains to be investigated.

METHODS

Whole-brain based 'resting-state' fMRI data were obtained from 22 MSA patients (11 MSA-C, 11 MSA-P) and 22 matched healthy controls, together with standardized clinical assessment and video-oculographic recordings (EyeLink^®).

RESULTS

MSA patients vs. controls showed significantly higher ponto-cerebellar functional connectivity and lower default mode network connectivity (p < .05, corrected). No differences were observed in the motor network and in the control network. The higher the ponto-cerebellar network functional connectivity was, the more pronounced was smooth pursuit impairment.

CONCLUSION

This functional connectivity analysis supports a network-dependent combination of hyper- and hypoconnectivity states in MSA, in agreement with adaptive compensatory responses (hyperconnectivity) and a function disconnection syndrome (hypoconnectivity) that may occur in a consecutive sequence.

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.

Recommendations of the Global Multiple System Atrophy Research Roadmap Meeting

Multiple system atrophy (MSA) is a rare neurodegenerative disorder with substantial knowledge gaps despite recent gains in basic and clinical research. In order to make further advances, concerted international collaboration is vital. In 2014, an international meeting involving leaders in the field and MSA advocacy groups was convened in Las Vegas, Nevada, to identify critical research areas where consensus and progress was needed to improve understanding, diagnosis, and treatment of the disease. Eight topic areas were defined: pathogenesis, preclinical modeling, target identification, endophenotyping, clinical measures, imaging biomarkers, nonimaging biomarkers, treatments/trial designs, and patient advocacy. For each topic area, an expert served as a working group chair and each working group developed priority-ranked research recommendations with associated timelines and pathways to reach the intended goals. In this report, each groups' recommendations are provided.

Merging Clinical and Imaging Biomarkers to Tackle Parkinson's Disease

Background

In Parkinson's disease, biomarkers represent tools that are potentially suitable for either clinical or research settings and are useful in predicting onset, confirming diagnosis, detecting progression, and evaluating response to potential disease-modifying treatments. The range of available biomarkers in Parkinson's disease is fast expanding and includes an increasing amount of laboratory, clinical, and imaging data. Indeed, the latter 2 represent the cornerstones of the diagnostic criteria for Parkinson's disease recently proposed by the International Parkinson and Movement Disorders Society Task Force on the definition of Parkinson's disease.

Methods and Results

In this review, we describe current knowledge and emerging findings on clinical (with emphasis on nonmotor symptoms) and imaging biomarkers for Parkinson's disease, with a focus on prodromal, diagnostic, and middle/advanced phases.

Conclusion

An increasing body of evidence suggests that merging clinical and imaging biomarkers through disease stages may be the best, fastest track to tackle Parkinson's disease.

Multiple System Atrophy: Many Lessons from the Transcriptome

Multiple system atrophy (MSA) is a complex, multifactorial, debilitating neurodegenerative disease that is often misdiagnosed and misunderstood. MSA has two subclasses, MSA-P and MSA-C, defined by the dominance of parkinsonism or cerebellar dysfunction in the earlier stages of disease, coupled with dysautonomia. This distinction between subclasses becomes largely redundant as the disease progresses. Aggregation of α-synuclein is a clinical marker used to confirm MSA diagnoses, which can only be performed postmortem. Transcriptome profiling provides in-depth information about the diseased state and can contribute to further understanding of MSA, enabling easier and more rapid diagnosis as well as contributing to improving the quality of life of people with MSA. Currently, there is no method of diagnosing MSA with certainty, and there is no cure for this disease. This review provides an update on current advances in investigations of molecular pathology of MSA with particular focus on perturbation of individual gene expression and MSA transcriptome.

Nonmotor fluctuations: phenotypes, pathophysiology, management, and open issues

Parkinson's disease (PD) is a neurodegenerative multisystem disorder characterized by progressive motor symptoms such as bradykinesia, tremor and muscle rigidity. Over the course of the disease, numerous non-motor symptoms, sometimes preceding the onset of motor symptoms, significantly impair patients' quality of life. The significance of non-motor symptoms may outweigh the burden through progressive motor incapacity, especially in later stages of the disease. The advanced stage of the disease is characterized by motor complications such as fluctuations and dyskinesias induced by the long-term application of levodopa therapy. In recent years, it became evident that various non-motor symptoms such as psychiatric symptoms, fatigue and pain also show fluctuations after chronic levodopa therapy (named non-motor fluctuations or NMFs). Although NMFs have moved into the focus of interest, current national guidelines on the treatment of PD may refer to non-motor symptoms and their management, but do not mention NMF, and do not contain recommendations on their management. The present article summarizes major issues related to NMF including clinical phenomenology and pathophysiology, and outlines a number of open issues and topics for future research.

Magnetic Resonance Parkinsonism Index: diagnostic accuracy of a fully automated algorithm in comparison with the manual measurement in a large Italian multicentre study in patients with progressive supranuclear palsy

OBJECTIVES

To investigate the reliability of a new in-house automatic algorithm for calculating the Magnetic Resonance Parkinsonism Index (MRPI), in a large multicentre study population of patients affected by progressive supranuclear palsy (PSP) or Parkinson's disease (PD), and healthy controls (HC), and to compare the diagnostic accuracy of the automatic and manual MRPI values.

METHODS

The study included 88 PSP patients, 234 PD patients and 117 controls. MRI was performed using both 3T and 1.5T scanners. Automatic and manual MRPI values were evaluated, and accuracy of both methods in distinguishing PSP from PD and controls was calculated.

RESULTS

No statistical differences were found between automated and manual MRPI values in all groups. The automatic MRPI values differentiated PSP from PD with an accuracy of 95 % (manual MRPI accuracy 96 %) and 97 % (manual MRPI accuracy 100 %) for 1.5T and 3T scanners, respectively.

CONCLUSION

Our study showed that the new in-house automated method for MRPI calculation was highly accurate in distinguishing PSP from PD. Our automatic approach allows a widespread use of MRPI in clinical practice and in longitudinal research studies.

KEY POINTS

• A new automatic method for calculating the MRPI is presented. • Automatic MRPI values are in good agreement with manual values. • Automatic MRPI can distinguish patients with PSP from patients with PD. • The automatic method overcomes MRPI application limitations in routine practice. • The automatic method may allow a more widespread use of MRPI.

Recognizing Atypical Parkinsonisms: "Red Flags" and Therapeutic Approaches

The overlap of signs and symptoms between Parkinson's disease and the atypical parkinsonian syndromes, such as progressive supranuclear palsy, multiple system atrophy, corticobasal syndrome and dementia with Lewy bodies, can render clinical diagnoses challenging. The continued evolution of diagnostic criteria to reflect the increasingly recognized heterogeneous presentations of these diseases further complicates timely recognition and diagnosis. In this review, we provide a diagnostic approach to the classic atypical parkinsonian syndromes, with an emphasis on the key clinical and pathological features of each and the recognition of “red flags” in the setting of recent advances in diagnosis and treatment.