Accuracy in the diagnosis of dementia during life remains suboptimal. While decline in cognition can be reasonably easily identified these days, understanding how this decline relates to the underlying pathology, and therefore the type of dementia, remains fraught with difficulty. This is due, in part, to the number of different pathologies that can cause dementia. It is also related to the fact that many clinical features, such as memory deficits, are present in many syndromic presentations. Historically, memory deficit has been associated with Alzheimer’s disease. However, Professor Olivier Piguet and colleagues demonstrated that disturbance of memory is also found in frontotemporal dementia, a dementia type which is as common as Alzheimer’s disease in people aged < 65 years. In addition, this disturbance is, in some instances, as severe as that seen in Alzheimer’s disease. Importantly, the biological causes for these memory deficits are different in these two dementia syndromes. This study identified the brain regions that are commonly affected in these two types of dementia, as well as those that are affected specifically in one dementia and not the other (Irish, Piguet, Hodges, & Hornberger, 2014). These findings provide a roadmap for the development of future memory tests that can target these brain regions specifically. Inaccurate or delayed diagnosis has important implications for the management of individuals with dementia and the type of interventions (pharmacological and non-pharmacological) that are suitable or relevant.
In addition to providing an early and accurate diagnosis, one of the many challenges in dementia research is to determine the rate of disease progression. One important stream of research in the Memory Program was to develop analysis methods of neuroimaging data to identify patterns of change in the grey and white matter of the brain with disease progression across different dementia syndromes (Landin-Romero, Kumfor, Leyton, Irish, Hodges, & Piguet, 2017). This study is one example of this approach. In the future, we anticipate being able to identify disease specific progression maps related to these different pathologies. Future studies will combine multiple imaging modalities, such as volumetrics, tractography, structural connectivity and functional connectivity, which will provide an integrated landscape of the changes affecting brain networks with dementia, including memory networks. These maps could also used as neuroimaging biomarkers which can potentially be used to measure the efficacy of drug trials or clinical interventions.