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Prof James Boardman
Dr M E Bastin
No more applications being accepted
Competition Funded PhD Project (European/UK Students Only)
About the Project
Supervisors: Dr James Boardman ( MRC Centre for Reproductive Health), Dr Mark Bastin (Centre for Clinical Brain Sciences), Professor Neil Roberts (Clinical Research Imaging Centre),
Background
Preterm birth affects 9% of pregnancies and is a leading cause of neurocognitive impairment in childhood (1;2). The disturbances to brain structure and function that underlie impairment are poorly understood and this hampers mechanistic and therapeutic studies. Quantitative magnetic resonance (MR) imaging approaches (diffusion tensor imaging and morphometry) show that connectivity of developing neural systems is altered by preterm birth (eg corticothalamic tract) but its effect on tracts that underpin learning, memory, attention and other key functions is unknown (3-5).
MR tractography enables measures of white matter integrity (fractional anisotropy [FA] and mean diffusivity [D]) to be determined within tracts of interest (TOI). To date tractography methods have required users to define start and end points, which is a source of bias. We have developed probabilistic neighbourhood tractography (PNT), which minimises bias by removing the need to define an endpoint or to use arbitrarily thresholded connectivity values.
PNT segments a TOI across a group of subjects by modelling the tract length and shape in comparison to a reference tract. Measures of tract integrity and topology can be extracted to quantify differences between individuals and groups, leading to new insights about ageing and neurodegeneration (6). In a proof of concept study we have shown that PNT can be applied to MR images of the neonatal brain using an adult reference (Anblagan et alISMRM 2013).
Aim
We will test the hypotheses:
1. PNT can be used to extract metrics of tract integrity and topology from 12 TOIs in the developing brain.
2. Optimal performance of PNT is obtained by use of a neonatal reference template.
3. Preterm birth is associated with altered integrity and topology of one or more TOIs.
4. Clinical and biological perinatal variables modulate tract integrity and topology.
Methods
1. We will use images already acquired as part of a wider study of the effects of preterm birth on brain development and eurodevelopmental outcome: 60 preterm infants and 30 controls.
2. Images acquisition: Siemens MAGNETOM Verio 3T, CRIC.
3. 12 TOIs will be identified using PNT (http://www.tractor-mri.org.uk). The resulting tract masks will be applied to each subject's mean diffusivity (D) and fractional anisotropy (FA) volumes, which allows TOI mean values, weighted by the connection probability, to be determined for each tract in every subject. Differences between tract averaged (D) and FA between preterm and control groups will be determined by analysis of variance, and linear regression models will be used to investigate relationships between perinatal variables and MRI measures.
Anticipated outcome
A novel fully-automated method for quantifying volume, shape and diffusion metrics in tracts of interest in the newborn brain.
The Little France Campus
The Medical Research Council Centre for Reproductive Health (CRH) is located on the ground floor of the Queen’s Medical Research Institute on the University of Edinburgh’s Medical Campus at Little France (www.ed.ac.uk/schools-departments/medicine-vet-medicine/about/little-france). The CRH enjoys close collaborative links with the other Centres on the Little France Campus including the MRC Centre for Inflammation Research (MRC-CIR); the British Heart Foundation Centre of Excellence in Cardiovascular Science (BHF-CVS) and the Clinical Research Imaging Centre (CRIC) and the MRC Centre for Regenerative Medicine (CRM). The CRH has a thriving postgraduate community of more than 30 MSc and PhD trainees who are mentored by a postgraduate studies committee.
www.crh.ed.ac.uk
www.cric.ed.ac.uk
www.ccbs.ed.ac.uk
Applicants are expected to have a good honours degree in the sciences (biological, chemical or physical), at least UK level of 2.1 or the equivalent from non-UK universities. A Master’s degree in a relevant subject would be an advantage.
How to Apply
For application, please submit:
• a curriculum vitae
• a 'statement of purpose' outlining your reasons for undertaking this programme of study and how you see it affecting your career plan.
• 3 academic referees should email/send letters on your behalf to [Email Address Removed]
The closing date to apply for these studentships is Monday, 10 March 2014.
Interviews (which may include a short presentation) will be held shortly thereafter.
Background
Preterm birth affects 9% of pregnancies and is a leading cause of neurocognitive impairment in childhood (1;2). The disturbances to brain structure and function that underlie impairment are poorly understood and this hampers mechanistic and therapeutic studies. Quantitative magnetic resonance (MR) imaging approaches (diffusion tensor imaging and morphometry) show that connectivity of developing neural systems is altered by preterm birth (eg corticothalamic tract) but its effect on tracts that underpin learning, memory, attention and other key functions is unknown (3-5).
MR tractography enables measures of white matter integrity (fractional anisotropy [FA] and mean diffusivity [D]) to be determined within tracts of interest (TOI). To date tractography methods have required users to define start and end points, which is a source of bias. We have developed probabilistic neighbourhood tractography (PNT), which minimises bias by removing the need to define an endpoint or to use arbitrarily thresholded connectivity values.
PNT segments a TOI across a group of subjects by modelling the tract length and shape in comparison to a reference tract. Measures of tract integrity and topology can be extracted to quantify differences between individuals and groups, leading to new insights about ageing and neurodegeneration (6). In a proof of concept study we have shown that PNT can be applied to MR images of the neonatal brain using an adult reference (Anblagan et alISMRM 2013).
Aim
We will test the hypotheses:
1. PNT can be used to extract metrics of tract integrity and topology from 12 TOIs in the developing brain.
2. Optimal performance of PNT is obtained by use of a neonatal reference template.
3. Preterm birth is associated with altered integrity and topology of one or more TOIs.
4. Clinical and biological perinatal variables modulate tract integrity and topology.
Methods
1. We will use images already acquired as part of a wider study of the effects of preterm birth on brain development and eurodevelopmental outcome: 60 preterm infants and 30 controls.
2. Images acquisition: Siemens MAGNETOM Verio 3T, CRIC.
3. 12 TOIs will be identified using PNT (http://www.tractor-mri.org.uk). The resulting tract masks will be applied to each subject's mean diffusivity (D) and fractional anisotropy (FA) volumes, which allows TOI mean values, weighted by the connection probability, to be determined for each tract in every subject. Differences between tract averaged (D) and FA between preterm and control groups will be determined by analysis of variance, and linear regression models will be used to investigate relationships between perinatal variables and MRI measures.
Anticipated outcome
A novel fully-automated method for quantifying volume, shape and diffusion metrics in tracts of interest in the newborn brain.
The Little France Campus
The Medical Research Council Centre for Reproductive Health (CRH) is located on the ground floor of the Queen’s Medical Research Institute on the University of Edinburgh’s Medical Campus at Little France (www.ed.ac.uk/schools-departments/medicine-vet-medicine/about/little-france). The CRH enjoys close collaborative links with the other Centres on the Little France Campus including the MRC Centre for Inflammation Research (MRC-CIR); the British Heart Foundation Centre of Excellence in Cardiovascular Science (BHF-CVS) and the Clinical Research Imaging Centre (CRIC) and the MRC Centre for Regenerative Medicine (CRM). The CRH has a thriving postgraduate community of more than 30 MSc and PhD trainees who are mentored by a postgraduate studies committee.
www.crh.ed.ac.uk
www.cric.ed.ac.uk
www.ccbs.ed.ac.uk
Applicants are expected to have a good honours degree in the sciences (biological, chemical or physical), at least UK level of 2.1 or the equivalent from non-UK universities. A Master’s degree in a relevant subject would be an advantage.
How to Apply
For application, please submit:
• a curriculum vitae
• a 'statement of purpose' outlining your reasons for undertaking this programme of study and how you see it affecting your career plan.
• 3 academic referees should email/send letters on your behalf to [Email Address Removed]
The closing date to apply for these studentships is Monday, 10 March 2014.
Interviews (which may include a short presentation) will be held shortly thereafter.
Funding Notes
Two 3-year PhD Studentships will be available in September 2014 to outstanding science graduates wishing to pursue a career in Reproductive Health Sciences. The studentship will cover tuition fees at the UK/EU rate, a stipend (currently 13,863) with a rise each year to match inflation. This research project is in competition for funding with 6 other projects currently on offer at the Centre for Reproductive Health. Usually the project which receives the best applicant will be awarded the funding. The funding is available to UK and EU nationals who can demonstrate ordinary residence in the European Economic Area.
References
(1) Volpe JJ. Lancet Neurol 2009;8(1):110-24.
(2) Wood NS et al. N Engl J Med 2000;343(6):378-84.
(3) Boardman JP et al. Neuroimage 2010;52(2):409-14.
(4) Ball G et al. Cortex 2013;49(6):1711-21.
(5) Boardman JP e al. Ann Neurol 2007;62(2):185-92.
(6) Bastin ME et al. Neuroimage 2010;51(1):1-10.
(2) Wood NS et al. N Engl J Med 2000;343(6):378-84.
(3) Boardman JP et al. Neuroimage 2010;52(2):409-14.
(4) Ball G et al. Cortex 2013;49(6):1711-21.
(5) Boardman JP e al. Ann Neurol 2007;62(2):185-92.
(6) Bastin ME et al. Neuroimage 2010;51(1):1-10.
Project supervisors
Career overview
Professor Boardman is a professor of neonatal medicine at the University of Edinburgh. He studied medicine at University College London from 1990 to 1996 and was awarded a PhD from Imperial College London in 2006. Professor Boardman serves as the scientific director of the Jennifer Brown Research Laboratory at the University of Edinburgh and is a UKRI MRC programme grant holder. His research focuses on addressing significant challenges in 21st-century perinatal medicine, particularly in reducing brain injury and restoring learning potential after preterm birth. He employs neuroinformatic approaches to explore the impact of preterm birth on the developing brain and the biological factors that contribute to early life adversity in cerebral development. Professor Boardman has created unique infant cohorts that are phenotyped by various metrics, including brain structure, immune function, DNA methylation, stress axis activation, gut microbiome, medical history, social factors, and behaviour, and has developed tools for integrating multi-scale early life data.
Research interests
Professor Boardman's research focuses on addressing significant challenges in 21st-century perinatal medicine, particularly in reducing brain injury and restoring learning potential following preterm birth. They employ neuroinformatic approaches to investigate the effects of preterm birth on brain development and the biological factors that contribute to early life adversity in cerebral development. Professor Boardman has established unique infant cohorts characterised by various factors, including brain structure (via MRI), biological markers (such as immune function and DNA methylation), medical history, social influences, and behaviour. They have also developed tools for integrating multi-scale early life data.
Neonatal Medicine
Brain Injury
Preterm Birth
Neuroinformatics
Infant Cohorts
Brain MRI
Immune Function
DNA Methylation
Stress Axis Activation
Gut Microbiome
Cognitive Development
Perinatal Medicine
Early Life Adversity
Systemic Inflammation
Neurodevelopment
Cognitive Impairment
Randomised Controlled Trials
Maternal Cortisol
Administrative Datasets
Health Interventions
Career overview
Dr. Mark Bastin is a Reader at the University of Edinburgh, affiliated with the Centre for Clinical Brain Sciences and Edinburgh Imaging. Dr. Bastin's research focuses on the use of diffusion and structural MRI to investigate the connectivity of cerebral white matter and its relationship to cognitive ability in both health and disease. Current research interests include normal ageing, preterm birth, motor neurone disease, multiple sclerosis, schizophrenia, and bipolar disorder. Dr. Bastin collaborates with a range of professionals across the university, including psychologists, psychiatrists, neurologists, neonatologists, and informaticians. The primary research interest lies in the development of MRI acquisition methods and image processing techniques, particularly in relation to white matter studies. Specific areas of focus include diffusion magnetic resonance imaging, magnetization transfer magnetic resonance imaging, and quantitative spin-lattice relaxation measurement, with applications to various neurological conditions.
Research interests
Dr. Bastin's research focuses on using diffusion and structural MRI to investigate the connectivity of cerebral white matter and its relationship to cognitive ability in both health and disease. Current areas of interest include normal ageing, preterm birth, motor neurone disease, multiple sclerosis, schizophrenia, and bipolar disorder. The primary research interest lies in the development of MRI acquisition methods and image processing techniques, with specific areas including diffusion magnetic resonance imaging and tractography, magnetization transfer magnetic resonance imaging, and quantitative spin-lattice relaxation (T1) measurement. The application of these techniques extends to studying conditions such as normal ageing, preterm birth, brain tumours, motor neurone disease, multiple sclerosis, schizophrenia, and bipolar disorder. Collaborations involve psychologists, psychiatrists, neurologists, neonatologists, and informaticians across the University.
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