Predicting post-stroke dementia from CT neuroimaging and other biomarkers
Project Details - Predicting post-stroke dementia from CT neuroimaging and other biomarkers
|Supervisor(s): Dr Susan D. Shenkin, Dr Dorota Religa, Dr Terry Quinn & Prof Gillian Mead|
|Centre/Institute: Centre for Cognitive Ageing and Cognitive Epidemiology|
Stroke and dementia are among the most feared aspects of ageing. The life-time risk of either is 1:3 for men and 1:2 for women. Post-stroke dementia is dementia temporally related to an incident stroke, affecting ~1/3 stroke survivors. There are currently no biomarkers which accurately predict risk of post stroke dementia1, and would allow targeted therapy. Neuroimaging, including advanced multi-modal imaging, has potential to distinguish dementia types1, but CT imaging is by far the most common neuroimaging in clinical practice globally2: ~93% of stroke patients in Scotland had a CT scan within 24 hours (http://www.strokeaudit.scot.nhs.uk/). CT imaging biomarkers combine the principles of precision medicine with the goal of realistic medicine: to use accessible clinical data to improve patient-centred care3. This will facilitate realistic goal setting, targeting of treatments, and stratifying patients for inclusion in clinical trials of appropriately tailored interventions to reduce the risk of stroke and specifically post-stroke dementia.
This PhD aims to determine CT biomarkers of post-stroke dementia for prognosis, and thus identify targets for future trials of individualized therapies.
The student will perform a systematic review of CT biomarkers of post-stroke dementia, supervised by a multidisciplinary team with links to Cochrane Dementia. If data are available they will perform a meta-analysis including individual participant meta-analysis. The supervising team has close links with the relevant interdisciplinary researchers to facilitate provision of the required data.
The Karolinska Memory Clinical Cohort4 (N~1,000) includes individuals with dementia who have consented to their data use for research. They have detailed phenotyping, including cognitive assessment; CT and MRI neuroimaging, with many aspects already rated, (atrophy, white matter lesions); CSF biomarkers (beta amyloid, tau, p-tau); genetics (ApoE) etc. The student will perform a nested case-control study of matched individuals with and without a documented history of prior stroke, to link their imaging and cognitive data to establish CT biomarkers for post-stroke dementia, taking account of other potential biomarkers/mediators/confounders to develop a prediction model.
Once potential CT biomarkers have been established, the student will identify other cohorts in Scotland, Sweden, and through our international collaborations, world-wide, where data are already available to validate CT biomarkers for post-stroke dementia, and to plan personalized intervention studies. They will compare the results from studies using healthcare associated data, with those collected for research purposes (e.g. R4VaD study).
In particular, they will explore a) the Scottish Stroke Care Audit (http://www.strokeaudit.scot.nhs.uk/) to link CT scan reports – and potentially CT images to measure identified biomarkers - from stroke survivors with subsequent dementia; b) databases of stroke survivors with incident cognitive assessment (e.g. NHS Fife). Post stroke dementia will be ascertained by data linkage to routinely collected data (SMR01, SMR04, cholinesterase inhibitor prescribing, Care Home Census etc). Other healthcare associated data e.g. serum inflammatory markers, sodium, can be included as potential biomarkers/mediators/confounders.
They will find and collate existing consortia, and work with these groups to develop personalized intervention studies to prevent post-stroke dementia.
This project will provide training in Quantitative Skills (statistics for data linkage and prediction using digital health records and neuroimaging). In addition to mandatory teaching, training will be provided at the Karolinska Institute, and in Edinburgh via the Farr institute, Edinburgh Neuroimaging, Edinburgh Data Epidemiology Network, and the Applied Ageing Network. There will be the opportunity to travel to Sweden for part of the training. The project will provide training in Interdisciplinary Skills such as systematic review and meta-analysis through Cochrane Dementia in-house training, and bespoke training around prognostic systematic review, including newly-developed methods of analysis. This will result in an independent researcher in realistic precision medicine, particularly relating to neurovascular and neurodegenerative diseases.
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- The deadline for 18/19 applications is 5pm on Wednesday 10th January 2018.
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