Recent Developments in Computer Methods for fMRI Data Processing

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Artificial Neural Networks for Solving Ordinary and Partial Differential Equations

We present a method to solve initial and boundary value problems using artificial neural networks. A trial solution of the differential equation is written as a sum of two parts. The first part satisfies the boundary (or initial) conditions and contains no adjustable parameters. The second part is constructed so as not to affect the boundary conditions. This part involves a feedforward neural network, containing adjustable parameters (the weights). Hence by construction the boundary conditions are satisfied and the network is trained to satisfy the differential equation. The applicability of this approach ranges from single ODE's, to systems of coupled ODE's and also to PDE's. In this article we illustrate the method by solving a variety of model problems and present comparisons with finite elements for several cases of partial differential equations.Comment: LAtex file, 26 pages, 21 figs, submitted to IEEE TN

A six stage approach for the diagnosis of the Alzheimer’s disease based on fMRI data

AbstractThe aim of this work is to present an automated method that assists in the diagnosis of Alzheimer’s disease and also supports the monitoring of the progression of the disease. The method is based on features extracted from the data acquired during an fMRI experiment. It consists of six stages: (a) preprocessing of fMRI data, (b) modeling of fMRI voxel time series using a Generalized Linear Model, (c) feature extraction from the fMRI data, (d) feature selection, (e) classification using classical and improved variations of the Random Forests algorithm and Support Vector Machines, and (f) conversion of the trees, of the Random Forest, to rules which have physical meaning. The method is evaluated using a dataset of 41 subjects. The results of the proposed method indicate the validity of the method in the diagnosis (accuracy 94%) and monitoring of the Alzheimer’s disease (accuracy 97% and 99%)

Spinal cord compression by a solitary metastasis from a low grade leydig cell tumour: a case report and review of the literature

<p>Abstract</p> <p>Background</p> <p>Leydig tumour is rare and there are only three cases with metastatic disease reported.</p> <p>Case presentation</p> <p>A 52 year-old Caucasian male was admitted, on emergency basis to the Orthopaedic Department with six weeks history of increasing midthoracic back pain, change in gait, poor balance, subjective weakness and numbness of the lower trunk and legs. MRI scan showed change in the signal intensity of T4 and T5 vertebral body but their height were maintained. Urgent T4 and T5 corpectomies, decompression of the spinal cord and reconstruction of the vertebral bodies were performed followed by radiotherapy. Neurological status significantly improved with a mild residual numbness over the dorsum of the right foot. The histology of the excised tumour was identical to the primary. At 2 years follow-up visit the patient is neurologically stable and disease free without other organs metastases.</p> <p>Conclusion</p> <p>This is the first case in English literature, which shows that spinal metastases could occur even in the early stage of Leydig cell tumour, without other organs involvement. Aggressive surgical management of spinal metastases combined with post operative radiotherapy can give a better chance for long survivorship.</p

Investigating the feasibility and acceptability of the HOLOBalance system compared with standard care in older adults at risk for falls: study protocol for an assessor blinded pilot randomised controlled study

INTRODUCTION: Approximately one in three of all older adults fall each year, with wide ranging physical, psychosocial and healthcare-related consequences. Exercise-based interventions are the cornerstone for falls prevention programmes, yet these are not consistently provided, do not routinely address all components of the balance system and are often not well attended. The HOLOBalance system provides an evidence-based balance training programme delivered to patients in their home environment using a novel technological approach including an augmented reality virtual physiotherapist, exergames and a remote monitoring system. The aims of this proof-of-concept study are to (1) determine the safety, acceptability and feasibility of providing HOLOBalance to community dwelling older adults at risk for falls and (2) provide data to support sample size estimates for a future trial. METHODS: A single (assessor) blinded pilot randomised controlled proof of concept study. 120 participants will be randomised to receive an 8-week home exercise programme consisting of either: (1) HOLOBalance or (2) The OTAGO Home Exercise Programme. Participants will be required to complete their exercise programme independently under the supervision of a physiotherapist. Participants will have weekly telephone contact with their physiotherapist, and will receive home visits at weeks 0, 3 and 6. Outcome measures of safety, acceptability and feasibility, clinical measures of balance function, disability, balance confidence and cognitive function will be assessed before and immediately after the 8 week intervention. Acceptability and feasibility will be explored using descriptive statistics, and trends for effectiveness will be explored using general linear model analysis of variance. ETHICS AND DISSEMINATION: This study has received institutional ethical approvals in Germany (reference: 265/19), Greece (reference: 9769/24-6-2019) and the UK (reference: 19/LO/1908). Findings from this study will be submitted for peer-reviewed publications. TRIAL REGISTRATION NUMBER: NCT04053829. PROTOCOL VERSION: V.2, 20 January 2020

Multiscale - Patient-Specific Artery and Atherogenesis Models

In this work, we present a platform for the development of multiscale patient-specific artery and atherogenesis models. The platform, called ARTool, integrates technologies of 3-D image reconstruction from various image modalities, blood flow and biological models of mass transfer, plaque characterization, and plaque growth. Patient images are acquired for the development of the 3-D model of the patient specific arteries. Then, blood flow ismodeled within the arterial models for the calculation of the wall shear stress distribution (WSS). WSS is combined with other patient-specific parameters for the development of the plaque progression models. Real-time simulation can be performed for same cases in grid environment. The platform is evaluated using both animal and human data

A huge posteromedial mediastinal cyst complicated with vertebral dislodgment

BACKGROUND: Mediastinal cysts compromise almost 20% of all mediastinal masses with bronchogenic subtype accounting for 60% of all cystic lesions. Although compression of adjoining soft tissues is usual, spinal complications and neurological symptoms are outmost rare and tend to characterize almost exclusively the neuroenteric cysts. CASE PRESENTATION: A young patient with intermittent, dull pain in his back and free medical history presented in the orthopaedic department of our hospital. There, the initial clinical and radiologic evaluation revealed a mediastinal mass and the patient was referred to the thoracic surgery department for further exploration. The following computed tomography (CT) and magnetic resonance imaging (MRI) shown a huge mediastinal cyst compressing the T4-T6 vertebral bodies. The neurological symptoms of the patient were attributed to this specific pathology due to the complete agreement between the location of the cyst and the nervous rule area of the compressed thoracic vertebrae. Despite our strongly suggestions for surgery the patient denied any treatment. CONCLUSION: In controversy with the common faith that the spine plays the role of the natural barrier to the further expansion of cystic lesions, our case clearly indicates that, exceptionally, mediastinal cysts may cause severe vertebral complications. Therefore, early excision should be considered especially in young patients or where close follow up is uncertain