A SINAPSE seed fund PhD studentship is available at the University of Aberdeen, in collaboration with the University of Edinburgh and industry partner IXICO.
Dementia is a global public health problem, the importance of which cannot be underestimated. Brain imaging is recommended by UK and international guidelines in the assessment of all patients as part of the diagnostic work up for dementia, both to try to diagnose the likely underlying disease causing dementia, (such as shrinkage of certain regions due to Alzheimer’s pathology and/or evidence of blood vessel disease) and to exclude a potentially surgically treatable abnormality such as a large bleed or tumour, which occurs in a very small proportion of patients. However, at present we cannot diagnose dementia from a scan because of individual differences in how people cope with brain diseases, with some able to overcome disease for some time before developing clinically obvious dementia. Because of these individual differences, often due to variation in brain experience during life, due to education, literacy, occupation, at present we cannot diagnose severity of cognitive impairment or dementia from a scan.
The purpose of this project is to identify the most important life-course factors that influence differences in reserve/resilience and include these in new mathematical methods of analysis of brain magnetic resonance images (MRI) to develop models that can accurately predict dementia risk from a brain scan.
Such “machine learning models” may be able to quantify the disconnect between the amount of disease present (MRI imaging) and cognitive symptoms and relate it to life course determinants. If these models can be developed and are accurate in predicting how impaired a patient is and what the likely underlying pathology is, these approaches will be extremely useful both for clinical trials of new drugs and for early diagnosis of patients with dementia in the NHS. These models could be incorporated into the computer work stations used for routine NHS brain scan reporting, improving accuracy of diagnosis and ultimately improving patient care by allowing early diagnosis, appropriate intervention and care.
Application deadline: 5th August 2016
For more information on the project and how to apply, please visit: https://www.abdn.ac.uk/clsm/graduate/research/cognitive-reserve-1191.php