Using brain network modules to improve diagnostic accuracy of behavioural variant of frontotemporal dementia and Alzheimer’s disease and predicting determinants of treatment response to LMTM

Alzheimer’s disease (AD) and behavioural variant of frontotemporal dementia (bvFTD) are two brain diseases that can cause dementia. Both diseases cause progressive loss of thinking abilities and behavioural problems to greater or lesser extents. There are no current treatments for ether disease that stops or reverses disease progression. Both can cause similar symptoms and it is difficult to diagnose either condition or to distinguish them, especially in their early stages when new treatments are likely to be most valuable. This project will make early, specific diagnosis more accurate by detecting information from brain scans using a new approach. Using information about patterns of loss of brain tissue across different parts of the brain, we will develop new ways of assessing brain scans, patient symptoms and test results so that these methods combine to give us more accurate ways of making a diagnosis. In particular, the methods we develop will help future accurate diagnosis of different causes of dementia. These new methods will be designed to be used in routine NHS practice in future, to increase clinical accuracy and confidence. They will also be valuable in selecting patients for future clinical trials of new drugs and deciding whether the drugs are working or not.