Spatial patterns of asynuclein positive glial cytoplasmic inclusions in multiple system atrophy

In cases of multiple system atrophy (MSA), glial cytoplasmic inclusions (GCI) were distributed randomly or present in large diffuse clusters (>1,600 μm in diameter) in most areas studied. These spatial patterns contrast with those reported for filamentous neuronal inclusions in the tauopathies and α-synucleinopathies. © 2003 Movement Disorder Society.

General features of Multiple System Atrophy

Multiple system atrophy (MSA) is a rare movement disorder and a member of a group of neurodegenerative diseases referred to collectively as the ‘parkinsonian syndromes’. Characteristic of these syndromes is that the patient exhibits symptoms of ‘parkinsonism’, viz., a range of problems involving movement, most typically manifest in Parkinson’s disease (PD) itself1, but also seen in progressive supranuclear palsy (PSP), and to some extent in dementia with Lewy bodies (DLB). MSA is a relatively ‘new’ descriptive term and is derived from three previously described diseases, viz., olivopontocerebellar atrophy, striato-nigral degeneration, and Shy-Drager syndrome. The classical symptoms of MSA include parkinsonism, ataxia, and autonomic dysfunction.6 Ataxia describes a gross lack of coordination of muscle movements while autonomic dysfunction involves a variety of systems that regulate unconscious bodily functions such as heart rate, blood pressure, bladder function, and digestion. Although primarily a neurological disorder, patients with MSA may also develop visual signs and symptoms that could be useful in differential diagnosis. The most important visual signs may include oculomotor dysfunction and problems in pupil reactivity but are less likely to involve aspects of primary vision such as visual acuity, colour vision, and visual fields. In addition, the eye-care practitioner can contribute to the management of the visual problems of MSA and therefore, help to improve quality of life of the patient. Hence, this first article in a two-part series describes the general features of MSA including its prevalence, signs and symptoms, diagnosis, pathology, and possible causes.

Visual signs and symptoms of Multiple System Atrophy

Multiple system atrophy (MSA) is a rare movement disorder and a member of a group of neurodegenerative diseases, which include Parkinson’s disease (PD) and progressive supranuclear palsy (PSP), and referred to as the ‘parkinsonian syndromes’. Although primarily a neurological disorder, patients with MSA may also develop visual signs and symptoms that could be useful in differential diagnosis. In addition, the eye-care practitioner may contribute to the management of visual problems of MSA patients and therefore, help to improve quality of life. This second article in the series considers the visual signs and symptoms of MSA with special reference to those features most useful in differential diagnosis of the parkinsonian syndromes.

Density and spatial pattern of β-amyloid (Aβ) deposits in corticobasal degeneration

Corticobasal degeneration (CBD) is a rare, progressive movement disorder characterized neuropathologically by widespread neuronal and glial pathology including tau-immunoreactive neuronal cytoplasmic inclusions (NCI), oligodendroglial inclusions (GI), and astrocytic plaques (AP). However, ß -amyloid (A ß) deposits have been observed in the cerebral cortex and/or hippocampus in some cases of CBD. To clarify the role of Aß deposition in CBD, the densities and spatial patterns of the Aß deposits were studied in three cases. In two cases, expressing apolipoprotein E (APOE) genotypes 2/3 or 3/3, the densities of the Aß deposits were similar to those in normal elderly brain. In the remaining case, expressing APOE genotype 3/4, Aß deposition was observed throughout the cerebral cortex, sectors CA1 and CA2 of the hippocampus, and the molecular layer of the dentate gyrus. The densities of the Aß deposits in this case were typical of those observed in Alzheimer's disease (AD). In the three cases, clustering of Aß deposits, with clusters ranging in size from 200 to >6400 µm in diameter, was evident in 25/27 (93%) of analyses. In addition, the clusters of Aß deposits were regularly distributed parallel to the tissue boundary in 52% of analyses, a spatial pattern similar to that observed in AD. These results suggest: (1) in some CBD cases, Aß pathology is age-related, (2) more extensive Aß deposition is observed in some cases, the density and spatial patterns of the Aß deposits being similar to AD, and (3) extensive deposition of Aß in CBD may be associated with APOE allele e4.

Visual signs and symptoms of multiple system atrophy

Multiple system atrophy (MSA) is a rare movement disorder and a member of the 'parkinsonian syndromes', which also include Parkinson's disease (PD), progressive supranuclear palsy (PSP), dementia with Lewy bodies (DLB) and corticobasal degeneration (CBD). Multiple system atrophy is a complex syndrome, in which patients exhibit a variety of signs and symptoms, including parkinsonism, ataxia and autonomic dysfunction. It can be difficult to separate MSA from the other parkinsonian syndromes but if ocular signs and symptoms are present, they may aid differential diagnosis. Typical ocular features of MSA include blepharospasm, excessive square-wave jerks, mild to moderate hypometria of saccades, impaired vestibular-ocular reflex (VOR), nystagmus and impaired event-related evoked potentials. Less typical features include slowing of saccadic eye movements, the presence of vertical gaze palsy, visual hallucinations and an impaired electroretinogram (ERG). Aspects of primary vision such as visual acuity, colour vision or visual fields are usually unaffected. Management of the disease to deal with problems of walking, movement, daily tasks and speech problems is important in MSA. Optometrists can work in collaboration with the patient and health-care providers to identify and manage the patient's visual deficits. A more specific role for the optometrist is to correct vision to prevent falls and to monitor the anterior eye to prevent dry eye and control blepharospasm.

Machine learning for large-scale wearable sensor data in Parkinson disease:concepts, promises, pitfalls, and futures

For the treatment and monitoring of Parkinson's disease (PD) to be scientific, a key requirement is that measurement of disease stages and severity is quantitative, reliable, and repeatable. The last 50 years in PD research have been dominated by qualitative, subjective ratings obtained by human interpretation of the presentation of disease signs and symptoms at clinical visits. More recently, “wearable,” sensor-based, quantitative, objective, and easy-to-use systems for quantifying PD signs for large numbers of participants over extended durations have been developed. This technology has the potential to significantly improve both clinical diagnosis and management in PD and the conduct of clinical studies. However, the large-scale, high-dimensional character of the data captured by these wearable sensors requires sophisticated signal processing and machine-learning algorithms to transform it into scientifically and clinically meaningful information. Such algorithms that “learn” from data have shown remarkable success in making accurate predictions for complex problems in which human skill has been required to date, but they are challenging to evaluate and apply without a basic understanding of the underlying logic on which they are based. This article contains a nontechnical tutorial review of relevant machine-learning algorithms, also describing their limitations and how these can be overcome. It discusses implications of this technology and a practical road map for realizing the full potential of this technology in PD research and practice. © 2016 International Parkinson and Movement Disorder Society.

Technology in Parkinson's disease:challenges and opportunities

The miniaturization, sophistication, proliferation, and accessibility of technologies are enabling the capture of more and previously inaccessible phenomena in Parkinson's disease (PD). However, more information has not translated into a greater understanding of disease complexity to satisfy diagnostic and therapeutic needs. Challenges include noncompatible technology platforms, the need for wide-scale and long-term deployment of sensor technology (among vulnerable elderly patients in particular), and the gap between the "big data" acquired with sensitive measurement technologies and their limited clinical application. Major opportunities could be realized if new technologies are developed as part of open-source and/or open-hardware platforms that enable multichannel data capture sensitive to the broad range of motor and nonmotor problems that characterize PD and are adaptable into self-adjusting, individualized treatment delivery systems. The International Parkinson and Movement Disorders Society Task Force on Technology is entrusted to convene engineers, clinicians, researchers, and patients to promote the development of integrated measurement and closed-loop therapeutic systems with high patient adherence that also serve to (1) encourage the adoption of clinico-pathophysiologic phenotyping and early detection of critical disease milestones, (2) enhance the tailoring of symptomatic therapy, (3) improve subgroup targeting of patients for future testing of disease-modifying treatments, and (4) identify objective biomarkers to improve the longitudinal tracking of impairments in clinical care and research. This article summarizes the work carried out by the task force toward identifying challenges and opportunities in the development of technologies with potential for improving the clinical management and the quality of life of individuals with PD. © 2016 International Parkinson and Movement Disorder Society.

Eye movement analysis in congenital nystagmus:concise parameters estimation

Along with other diseases that can affect binocular vision, reducing the visual quality of a subject, Congenital Nystagmus (CN) is of peculiar interest. CN is an ocular-motor disorder characterized by involuntary, conjugated ocular oscillations and, while identified more than forty years ago, its pathogenesis is still under investigation. This kind of nystagmus is termed congenital (or infantile) since it could be present at birth or it can arise in the first months of life. The majority of CN patients show a considerable decrease of their visual acuity: image fixation on the retina is disturbed by nystagmus continuous oscillations, mainly horizontal. However, the image of a given target can still be stable during short periods in which eye velocity slows down while the target image is placed onto the fovea (called foveation intervals). To quantify the extent of nystagmus, eye movement recordings are routinely employed, allowing physicians to extract and analyze nystagmus main features such as waveform shape, amplitude and frequency. Use of eye movement recording, opportunely processed, allows computing "estimated visual acuity" predictors, which are analytical functions that estimate expected visual acuity using signal features such as foveation time and foveation position variability. Hence, it is fundamental to develop robust and accurate methods to measure both those parameters in order to obtain reliable values from the predictors. In this chapter the current methods to record eye movements in subjects with congenital nystagmus will be discussed and the present techniques to accurately compute foveation time and eye position will be presented. This study aims to disclose new methodologies in congenital nystagmus eye movements analysis, in order to identify nystagmus cycles and to evaluate foveation time, reducing the influence of repositioning saccades and data noise on the critical parameters of the estimation functions. Use of those functions extends the information acquired with typical visual acuity measurement (e.g., Landolt C test) and could be a support for treatment planning or therapy monitoring. © 2010 by Nova Science Publishers, Inc. All rights reserved.

Characterisation of baseline oscillation in congenital nystagmus eye movement recordings

Congenital nystagmus is an ocular-motor disorder that develops in the first few months of life; its pathogenesis is still unknown. Patients affected by congenital nystagmus show continuous, involuntary, rhythmical oscillations of the eyes. Monitoring eye movements, nystagmus main features such as shape, amplitude and frequency, can be extracted and analysed. Previous studies highlighted, in some cases, a much slower and smaller oscillation, which appears added up to the ordinary nystagmus waveform. This sort of baseline oscillation, or slow nystagmus, hinder precise cycle-to-cycle image placement onto the fovea. Such variability of the position may reduce patient visual acuity. This study aims to analyse more extensively eye movements recording including the baseline oscillation and investigate possible relationships between these slow oscillations and nystagmus. Almost 100 eye movement recordings (either infrared-oculographic or electrooculographic), relative to different gaze positions, belonging to 32 congenital nystagmus patients were analysed. The baseline oscillation was assumed sinusoidal; its amplitude and frequency were computed and compared with those of the nystagmus by means of a linear regression analysis. The results showed that baseline oscillations were characterised by an average frequency of 0.36 Hz (SD 0.11 Hz) and an average amplitude of 2.1° (SD 1.6°). It also resulted in a considerable correlation (R2 scored 0.78) between nystagmus amplitude and baseline oscillation amplitude; the latter, on average, resulted to be about one-half of the correspondent nystagmus amplitude. © 2009 Elsevier Ltd. All rights reserved.