PhD Proposal

My department of computing supervisor DR got back to me today and approved my PhD proposal. That means that I can start getting my data a month early, which is a huge bonus. Thanks!

Here’s my proposal in very truncated form. I've had to leave out all the references, study design, methods and technical sections. At least it doesn’t contain all the scary physics and equations of the full document though! I hope it makes it a bit clearer what I’ll be working on for the next three years. Please leave comments (click on the comments hyperlink at the bottom of the text) and feel free to ask any questions or request the whole document.

Yours,
Moc

1. Background
Over the past decade the incidence of low birth weight (infants weighing less than 2500g) has increased steadily, and now represents over 7% of all live births in England and Wales. Over the same period the incidence of very low birth weight (i.e. infants weighing less than 1500 grams) has increased at an even faster rate, now making up over 1% of all births. Although the outcomes for these infants vary widely across different neonatal intensive care units, recent improvements in perinatal care now mean that around 90% of these preterm infants will survive. The improvements in survival have been greatest in the most immature infants but have been accompanied by an increasing awareness of subsequent neurodevelopmental deficits. The immature developing brain is very vulnerable to injury, and many preterm infants suffer long-term morbidity that is more severe with prolonged exposure to the extrauterine environment. Impairments often continue into adolescence, with a high prevalence of behavioural problems documented, including psychiatric and attentional deficit disorders.

Magnetic resonance imaging (MRI) has been increasingly used within the field of neonatology over the past decade. Indeed, most of the recent insights into intrauterine and early extrauterine brain development have been achieved thanks to conventional (T1- and T2-weighted) magnetic resonance imaging techniques. MRI findings correlate with the well-recognised pathologies seen on ultrasound and, in addition, the high spatial resolution and excellent soft tissue contrast also allows the detection of more subtle abnormalities, including increased extracerebral space and diffuse excessive high signal intensity.

Diffusion tensor imaging (DTI) and diffusion weighted imaging (DWI) are magnetic resonance techniques that provide quantitative measures of water diffusion in tissue. By doing so they are able to show brain physiology and microstructure in vivo. The image contrast in DWI and DTI depends on the diffusion characteristics of water molecules, which are restricted by structural barriers including cell membranes and white matter tracts. Values of the apparent diffusion coefficient and fractional anisotropy can be determined from DTI and, by calculating the eigenvalues of the diffusion tensor, diffusion parallel and perpendicular to the white matter tracts can be measured. These are non-subjective measurements and provide information reflecting tissue microstructure. They can therefore be used to assess micro-structural abnormalities in the preterm brain.

Computer-assisted morphometric techniques, including voxel-based morphometry (VBM) and deformation based morphometry (DBM) use image registration and statistical analysis to quantify structural differences between groups To date, there have been no studies applying DBM techniques to diffusion scalar maps (apparent diffusion coefficient, fractional anisotropy and eigenvalue maps) in the preterm brain. However, data from animal and adult studies suggest that combining these two techniques (DBM and DTI) provides information regarding microstructural anomalies that may not be observed using traditional region of interest analysis of DTI data.

In this project I aim to use diffusion tensor imaging and deformation based morphometry to assess microstructural abnormalities in the preterm brain.

2. Hypotheses
i. Deformation based morphometry of diffusion tensor imaging data is able to detect abnormal white matter development in infants who are born prematurely.
ii. Abnormal white matter development is the result of extreme preterm birth and is not associated with other events.


3. Aims
i. To compare diffusion tensor scalar maps of the preterm brain at term equivalent age to those of infants born at term using DBM.
ii. To assess the effect of gestational age at birth on white matter development by acquiring DTI data at three time-points for each preterm infant: within 1 week of birth, at 30 weeks GA and at term equivalent age.
iii. To investigate the effect of other factors on white matter development including antenatal infection, postnatal infection, chronic lung disease, intrauterine growth retardation and gender.