Past Projects
Comprehensive Unified Research (CURe)
Funders: West Midlands AHSN (NHS)
Project Supervisors: Professor Theodoros N. Arvanitis, Professor Sudhesh Kumar, Dr Sarah Lim Choi Keung.
Project Researcher: Omar Khan
The objective of the CURe framework and associated web applications is to develop a new approach to get researchers in different specialties to start thinking of prospective studies and what data they need to collect that would be useful to them and their colleagues. Common data elements to all medical areas, as well as specialist requirements can be handled by the framework. The standardisation of data elements to promote interoperability and reuse has been introduced. Semantic Interoperability through coding systems will be supported. For this work a Terminology and Vocabulary Service will be used.
Patient Feedback App - A Rapid Review and Guidance
Funders: West Midlands AHSN (NHS)
Project Supervisors: Professor Theodoros N. Arvanitis, Professor Sudhesh Kumar
Project Researcher: Carolyn Dawson
The aim of this project to provide a rapid review of current Patient Feedback Apps use and evaluate the adoption of such ups in the NHS by researching users’ views for the Apps ease of use, perceived usefulness, attitudes towards adoption and behavioural change. Based on the results of the review, guidelines for the development and adoption for Patient Feedback Apps will be provided, in the context of the NHS in West Midlands.
West Midlands Health Informatics Network
Funder: West Midlands AHSN (NHS)
Project Supervisors: Professor Theodoros N. Arvanitis, Professor Sudhesh Kumar
Project Researchers: Dr Ola Bolanle, Dr Sarah Lim Choi Keung, Martin Roland.
The aim of the network is to support functions in designing, developing, deploying and evaluating health informatics solutions in healthcare within the West Midlands region. Objectives of the network are but not limited to: encourage and support closer working between academics with an interest in health informatics and NHS; enable closer working between IT professionals and clinicians; establish a forum to discuss and disseminate evidence based practice in health informatics; promote research in health informatics; support establishment of health informatics centre of excellence in West Midlands; support designing of health informatics courses.
Query Work Bench for West Midlands Primary Care and Community Care Clinical Studies and Trials
Funder: West Midlands AHSN
Project Supervisors: Professor Theodoros N. Arvanitis, Professor Sudhesh Kumar, Dr Sarah Lim Choi Keung
Project Reseachers: Ali Asadipour, Huseyin Dereli.
The aim of this research is to develop a semantically aware query workbench that will enable easy authoring of distributed searches, using the controlled vocabulary and data standards repository. In order to automatically identify ‘prevalent cases’ for research, the searches will report back counts of eligible subjects in the repositories, flagging the subjects for recruitment and consent by the local clinical care team, in full compliance with data protection legislation and best practice. ‘Incident cases’ will be recruited via the EHR interface during the consultation. Follow up data will be collected directly from the EHR, avoiding double data entry and facilitating rapid identification of adverse events within clinical studies.
Translational Research and Patient Safety in Europe (TRANSFoRm)
Funders: European Commission
Project Supervisors: Professor Theodoros N. Arvanitis, Professor Sudhesh Kumar, Dr Sarah Lim Choi Keung
Project Researchers: Lei Zhao, Christopher Golby, Dr Sarah Lim Choi Keung
The underlying concept of TRANSFoRm is to develop a ‘rapid learning healthcare system’ driven by advanced computational infrastructure that can improve both patient safety and the conduct and volume of clinical research in Europe.The EU policy framework for information society and media, i2010 identifies eHealth as one of the principal areas where advances in ICT can create better quality of life for Europe’s citizens. ICT has important roles in communication, decision-making, monitoring and learning in the healthcare setting. TRANSFoRm recognises the need to advance the underpinning information and computer science to address these issues in a European and international context.
Professor Arvanitis leads the User and Software Services Work Package - This work package will develop the full set of user interfaces and underlying search tools. These will include a generic method for enabling a dynamic interface for data capture and presentation for clinicians during the consultation and a query formulation and generation tool for researchers and a graphical middleware layer for the presentation of results. This work package will also specify and develop tools to assess data accessibility, data quality, and comparability. Finally, a generic method of preserving and examining the provenance of data within the project will be developed and implemented for application in WP3.
http://www.transformproject.eu
Bayesian Spatial Point Process Modelling of Neuroimage Data
Funder: National Institutes of Health
Project Supervisor: Professor Thomas Nichols
Project Partner: University of Michigan
The vast majority of data analysis methods for functional neuroimaging follow a mass univariate approach. While simple and computationally efficient, a mass univariate modelling does not model spatial structure in the data, and in particular cannot make inference on theuncertainty of spatial location of detected effects. This project develops Bayesian statistical models that explicitly address the limitations of the mass univariate approach. Specifically, it develops hierarchical Bayesian spatial point process models to analyse neuroimaging coordinate-level data, binary imaging data (such as that obtained from multiple sclerosis lesions) and hierarchical Bayesian spatial process/spatial point process models for neuroimage voxel-level data (e.g. when the entire contrast or t-statistic image is available on a group of subjects). The developed methods will assist in understanding the development of neuropsychiatric and neurodegenerative disorders, as well as normal brain development, that cannot be answered by current methods/models. This, in turn, will aid in our understanding of the human brain in normal and diseased states.
The Human Brain as a Complex System: Investigating the Relationship between Structural and Functional Networks in the Thalamocortical System
Funders: EPSRC
Project Supervisor: Professor Theo Arvanitis
Project Researcher: Dr Muhammad Naeem
The majority of brain functions are performed not by single regions but by the combined, co-ordinated activity of networks distributed throughout the brain. Several neurological and psychiatric disorders may be caused by a breakdown of the ability of these regions to communicate effectively. While several different methods have been developed to understand how the component regions, or nodes, of a network interact, there is no comprehensive framework for combining the information from different techniques to give an overall picture of network function. Without such a framework, advanced in neuroimaging techniques which allow the characterisation of anatomical and functional connections cannot be fully exploited. The purpose of this project is to develop such a framework, making use of intrinsic brain activity which can define well characterised model networks, thereby providing a natural validation of the results.
The Wellcome Trust Senior Research Fellowship in Basic Biomedical Science - Transforming Statistical Methodology for Neuroimaging Meta-Analysis
Funder: The Wellcome Trust
Project Supervisor: Prof Thomas Nichols
Project Researcher: Dr Camille Maumet
Project Partners: International Neuroinformatics Coordinating facility INCF
This project develops new techniques for sharing Functional Magnetic Resonance Imaging (fMRI) data and analysing that shared data. At present, fMRI researchers only share a tiny fraction of the rich datasets they produce. This is due in part to tradition, but also to the difficulty in sharing the massive datasets and the multitude of details of each imaging experiment. This project will develop software and standards that will make it easy for researchers to share their data, thus allowing more people to access data that, in most cases, is funded by public institutions.
Personalised Medicine through Learning in the Model Space
Funder: EPSRC
Project Supervisors: Professor Thomas Nichols, Dr Michael Chappell
Project Researcher: Dr. Hin (Roland) Wong
Project Partners: University of Birmingham; University of Bristol; Durham University; University College London
Mathematics is playing an ever-increasing role in the area of health and medicine, through the use of predictive modelling, statistics, and virtual simulations. The aim of this project is to be able to ‘guide’ the modeller from the data and to provide personalised models for diagnosis and treatment. Starting from an already existing (partial) explanation of the disease constructed in a mechanistic mathematical way (explanation-based or hypotheses driven), the information should lead the modeller.
Mapping the Human Connectome: Structure, Function and Heritability
Funder: National Institutes of Health
Project Supervisor: Professor Thomas Nichols
Project Partners: Washington University; University of Minnesota; University of Oxford; Indiana University; Saint Louis University; University d’Annunzio; Ernst Strungmann Institute; Radboud University; Advanced MRI Technologies
This project seeks to characterise adult human brain circuitry, including its variability and its relation to behaviour and genetics. This multi-institutional consortium is led by Dr David van Essen of Washington University at St. Louis, and is acquiring cutting-edge neuroimaging
data in 1,200 healthy adult humans along with behavioural performance data and blood samples for genotyping. The sample is population-based and is based on families with twins plus non-twin siblings, a strategy that enables powerful analyses of heritability and genetic
underpinnings of specific brain circuits. Dr Nichols is responsible for developing and evaluating methods for voxel-wise heritability estimation for structural and functional FMRI data, as well as supporting the interaction between the genetics team and the core HCP imaging investigators.
USEFIL: Unobtrusive Smart Environments for Independent Living
Funders: European Commission
Project Supervisors: Professor Christopher James, Professor Ala Szczepura
Project Researchers: Dr James Amor; Dr Vijayalakshmi Ahanathapillai, Josh Elliott
The USEFIL project aims to address the gap between technological research advances and the practical needs of elderly people by developing advanced but affordable in-home unobtrusive monitoring and web communication solutions. Morespecifically, USEFIL intends to use low-cost off-the-shelf technology to develop immediately applicable services that will assist the elderly in maintaining their independence and daily activities. Installation of the USEFIL system will not require retrofitting in a person's residence and will be almost invisible once installed.
SOLAR-Eclipse computational tools for imaging genetics
Funders: National Institutes of Health
Project Supervisor: Professor Thomas Nichols
Project Partners: University of Maryland
This project will provide urgently needed analysis methods to the emerging field of imaging genetics. Our focus is to create SOLAR-Eclipse imaging genetics tools for classical genetic and epigenetic epidemiological analyses such as heritability, pleiotropy, quantitative trait loci (QTL) and genome-wide association (GWAS), gene expression, and methylation analyses using traits derived from structural and functional brain imaging (AIM 1). We will also develop intelligent correction for multiple testing that meets both genetic and imaging requirements (AIM 2).
Knowledge Transfer Partnership with Heart of England NHS Foundation Trust Project
Funder: Technology Strategy Board
Project Supervisors: Professor Christopher James; Dr James Harte
Project Researcher: Christopher Golby
Project Partner: Heart of England NHS Foundation Trust
The aim of this project is to develop an integrated system for examination of chest wall by accurately measuring volume variations of entire thoracic abdominal wall and various compartments. The system developed as part of this research needs to measure the various thoracic parameters including current volume, vital capacity, respiratory frequency, duration of the phases of inspiration and exhalation, the average inspiration and exhalation flux and the volume variations at the end of exhalation. The system is oriented to evaluate lung function in order to improve diagnosis, decision making and treatment outcomes in patients with diseases affecting the chest.
Integrated Multimodal Brain Imaging for Neuroscience Research and Clinical Practice
Funders: The Wellcome Trust
Project Supervisor: Professor Thomas Nichols
Project Partners: University of Oxford
Advances in neuroimaging have given unprecedented access to in vivo measurements of brain function, structure and connectivity, but the full potential is not being realised due to a lack of suitable analysis tools to explore relationships between, and integrate across, modalities.
Our overall goal is to bring multimodal imaging to the forefront of neuroscience and clinical research in order to provide new biomarkers and insights into disease mechanisms, explore ageing and developmental processes, increase the scope for large neuroimaging studies and improve clinical decision-support for patients.
Linear and Non-Linear brain changes over the transition to psychosis
Funders: MRC
Project Supervisor: Professor Thomas Nichols
The course of schizophrenia is associated with significant brain changes. Exactly when these changes occur is a matter of some debate, with significant evidence now available for progressive volumetric declines in the early period of the illness (the first 12-24 months after onset). However, there is additional evidence for the decline beginning prior to that, during the prodromal period. What remains unclear is how this decline occurs, whether it is reversible, and to what extent it represents a core feature of the disorder (i.e. it precedes the worsening of symptoms), is an endogenous response to the experience of a psychotic disorder (i.e. it is a reaction to the onset of the illness) and/or is iatrogenic (i.e. it is a result of treatment).