Jeremy Cosgrove

Cognitive impairment in Parkinson's disease

Cognitive impairment is a significant non-motor symptom of Parkinsons disease (PD). Longitudinal cohort studies have demonstrated that approximately 50% of those with PD develop dementia after 10 years, increasing to over 80% after 20 years. Deficits in cognition can be identified at the time of PD diagnosis in some patients and this mild cognitive impairment (PD-MCI) has been studied extensively over the last decade. Although PD-MCI is a risk factor for developing Parkinsons disease dementia there is evidence to suggest that PD-MCI might consist of distinct subtypes with different pathophysiologies and prognoses. The major pathological correlate of Parkinsons disease dementia is Lewy body deposition in the limbic system and neocortex although Alzheimers related pathology is also an important contributor. Pathological damage causes alteration to neurotransmitter systems within the brain, producing behavioural change. Management of cognitive impairment in PD requires a multidisciplinary approach and accurate communication with patients and relatives is essential.

Myocarditis and diffuse skeletal muscle oedema: new features of neuromyelitis optica spectrum disorder? A case report.

We present a case report of newly diagnosed neuromyelitis optica spectrum disorder (NMOSD) with associated myocarditis and diffuse oedema of the pelvic and anterior compartment thigh muscles on magnetic resonance imaging. Aquaporin 4 antibodies are expressed in skeletal myofibres but involvement of skeletal muscle is rarely reported in NMOSD and myocarditis has not previously been described in this context. This case highlights the need for further research into the involvement of cardiac and skeletal muscle in NMOSD.

Migration of intraocular silicone oil into the brain

A 74-year-old woman gave a 6-month history of predominately right-sided parietal headaches, often worse on waking. Her history included left phthisis bulbi (atrophy and calcification of the eye), resulting from multiple attempted surgical repairs for retinal detachment 20 years previously. She wore a coloured contact lens over her left eye for cosmetic purposes. Neurological examination was normal. An unenhanced CT brain scan of her head demonstrated a high-attenuation abnormality in the left vitreous cavity with posterior extension along the optic nerve. There were further foci of high attenuation in the suprasellar region and in the frontal horn of the right lateral ventricle (figures 1 …

Computational approaches for understanding the diagnosis and treatment of Parkinson's disease

This study describes how the application of evolutionary algorithms (EAs) can be used to study motor function in humans with Parkinsons disease (PD) and in animal models of PD. Human data is obtained using commercially available sensors via a range of non-invasive procedures that follow conventional clinical practice. EAs can then be used to classify human data for a range of uses, including diagnosis and disease monitoring. New results are presented that demonstrate how EAs can also be used to classify fruit flies with and without genetic mutations that cause Parkinsons by using measurements of the proboscis extension reflex. The case is made for a computational approach that can be applied across human and animal studies of PD and lays the way for evaluation of existing and new drug therapies in a truly objective way.

Adult onset Brown-Vialetto-Van Laere syndrome with opsoclonus and a novel heterozygous mutation: a case report.

Brown–Vialetto–Van Laere (BVVL) is a rare neurodegenerative isorder caused by mutations in the human intestinal riboflavin ransporter genes, leading to riboflavin deficiency. It is characerised by bulbar palsy, respiratory insufficiency and sensorineural eafness. Some cases of BVVL have been successfully treated with iboflavin supplementation. Although BVVL is most commonly iagnosed in children it may also present in adults. We describe case of BVVL in a 27-year-old female.

Hemiatrophy and seizures: a case of adult-onset Rasmussen encephalitis

A 21-year-old man with no medical history presented in 2007 with a generalised tonic-clonic seizure. Over the previous 2 months he had experienced intermittent episodes of left-sided paraesthesia. Examination was normal. MR scan of the brain showed right-sided temporal, parietal and occipital lobe abnormalities. Differential diagnoses included infection, inflammation and tumour. Vasculitic and thrombophilia screens were negative, serum ACE level normal. Cerebrospinal fluid (CSF) was unremarkable, with negative results for culture, cytology and oligoclonal bands. Echocardiogram and CT scan of the thorax, abdomen and pelvis were also normal. He started carbamazepine for focal …

Going through directional changes: evolving human movement classifiers using an event based encoding

Directional changes (DC) is an event based encoding for time series data that has become popular in financial analysis, particularly within the evolutionary algorithm community. In this paper, we apply DC to a medical analytics problem, using it to identify and summarise the periods of opposing directional trends present within a set of accelerometry time series recordings. The summarised time series data are then used to train classifiers that can discriminate between different kinds of movement. As a case study, we consider the problem of discriminating the movements of Parkinsons disease patients when they are experiencing a common effect of medication called levodopa-induced dyskinesia. Our results suggest that a DC encoding is competitive against the window-based segmentation and frequency domain encodings that are often used when solving this kind of problem, but offers added benefits in the form of faster training and increased interpretability.

How to use pen and paper tasks to aid tremor diagnosis in the clinic

When a patient presents with tremor, it can be useful to perform a few simple pen and paper tests. In this article, we explain how to maximise the value of handwriting and of drawing Archimedes spirals and straight lines as clinical assessments. These tasks take a matter of seconds to complete but provide a wealth of information that supplements the standard physical examination. They aid the diagnosis of a tremor disorder and can contribute to its longitudinal monitoring. Watching the patient’s upper limb while they write and draw may reveal abnormalities such as bradykinesia, dystonic posturing and distractibility. The finished script and drawings can then be evaluated for frequency, amplitude, direction and symmetry of oscillatory pen movements and for overall scale of penmanship. Essential, dystonic, functional and parkinsonian tremor each has a characteristic pattern of abnormality on these pen and paper tests.

A New Evolutionary Algorithm-Based Home Monitoring Device for Parkinson’s Dyskinesia

Parkinson’s disease (PD) is a neurodegenerative movement disorder. Although there is no cure, symptomatic treatments are available and can significantly improve quality of life. The motor, or movement, features of PD are caused by reduced production of the neurotransmitter dopamine. Dopamine deficiency is most often treated using dopamine replacement therapy. However, this therapy can itself lead to further motor abnormalities referred to as dyskinesia. Dyskinesia consists of involuntary jerking movements and muscle spasms, which can often be violent. To minimise dyskinesia, it is necessary to accurately titrate the amount of medication given and monitor a patient’s movements. In this paper, we describe a new home monitoring device that allows dyskinesia to be measured as a patient goes about their daily activities, providing information that can assist clinicians when making changes to medication regimens. The device uses a predictive model of dyskinesia that was trained by an evolutionary algorithm, and achieves AUC>0.9 when discriminating clinically significant dyskinesia.

A Multi-Objective Approach to Predicting Motor and Cognitive Deficit in Parkinson's Disease Patients

Parkinsons disease (PD) is a chronic neurodegenerative condition. Traditionally categorised as a movement disorder, nowadays it is recognised that PD can also lead to significant cognitive dysfunction including, in many cases, full-blown dementia. Due to the wide range of symptoms, including significant overlap with other neurodegenerative conditions, both diagnosis and prognosis remain challenging. In this paper, we describe our use of a multi-objective evolutionary algorithm to explore trade-offs between polynomial regression models that predict different clinical measures, with the aim of identifying features that are most indicative of motor and cognitive PD variants. Our initial results are promising, showing that polynomial regression models are able to predict clinical measures with good accuracy, and that suitable predictive features can be identified.