Assessing the health of ageing blood vessels in the brain using fMRI: experimental design, modelling and analysis
Lead Research Organisation:
CARDIFF UNIVERSITY
Department Name: School of Physics and Astronomy
Abstract
In an ageing population, neurological problems related to control of brain blood flow are increasing and are a contributing factor in conditions associated with ageing, such as Alzheimer's disease and other forms of dementia. If the smooth muscle around small arteries in the brain is not functioning well, too little blood may be supplied, causing problems for neurological function. Currently, we are developing pragmatic functional magnetic resonance imaging (fMRI) tools to assess the health of the brain's blood vessels.
The objective of this PhD project is to develop novel fMRI imaging techniques and computational software to improve measures of brain vessel health. The utility of these clinical techniques will then be assessed in a suitable patient population. Initially, the student will acquire MR data during carbon dioxide challenges that stress the brain's blood vessels. Since this type of challenge can often be confused in software as head motion, a motion tracking camera system will be used in tandem as a gold standard. Quantification of motion confounds and data feature extraction methods will be developed to increase the reliability of vessel health measures obtained from this data. The second approach will take advantage of existing large scale imaging databases to derive new measure of vessel health by developing novel signal processing techniques. Current noise correction methods discard the information we are interested in and so this will require an inversion of the employed logic. In this section of the PhD, the student will develop algorithms to deal with large data. Finally, practical improvements to the way physiological challenges are administered will be sought by engineering more comfortable, patient- friendly MR compatible setups and by simultaneously improving related processing pipelines. A lower body negative pressure chamber that minimises motion in the scanner will be developed. The objective is to increase the repeatability of related vessel health measures in a medium sized patient cohort.
The objective of this PhD project is to develop novel fMRI imaging techniques and computational software to improve measures of brain vessel health. The utility of these clinical techniques will then be assessed in a suitable patient population. Initially, the student will acquire MR data during carbon dioxide challenges that stress the brain's blood vessels. Since this type of challenge can often be confused in software as head motion, a motion tracking camera system will be used in tandem as a gold standard. Quantification of motion confounds and data feature extraction methods will be developed to increase the reliability of vessel health measures obtained from this data. The second approach will take advantage of existing large scale imaging databases to derive new measure of vessel health by developing novel signal processing techniques. Current noise correction methods discard the information we are interested in and so this will require an inversion of the employed logic. In this section of the PhD, the student will develop algorithms to deal with large data. Finally, practical improvements to the way physiological challenges are administered will be sought by engineering more comfortable, patient- friendly MR compatible setups and by simultaneously improving related processing pipelines. A lower body negative pressure chamber that minimises motion in the scanner will be developed. The objective is to increase the repeatability of related vessel health measures in a medium sized patient cohort.
Organisations
People |
ORCID iD |
Kevin Murphy (Primary Supervisor) | |
Ryan Beckerleg (Student) |
Publications
Duffy D
(2023)
Lifting, Loading, and Buckling in Conical Shells
Duffy D
(2023)
Lifting, Loading, and Buckling in Conical Shells
in Physical Review Letters
Duffy D
(2023)
Lifting, Loading, and Buckling in Conical Shells.
Studentship Projects
Project Reference | Relationship | Related To | Start | End | Student Name |
---|---|---|---|---|---|
EP/R513003/1 | 30/09/2018 | 29/09/2023 | |||
2105369 | Studentship | EP/R513003/1 | 30/09/2018 | 30/03/2022 | Ryan Beckerleg |