Novel technologies for timely and equitable dementia diagnosis


There are substantial problems with timeliness, accuracy and equity of dementia diagnosis. Those who are more deprived or from minority ethnic groups tend to be diagnosed later and less accurately. Timely and accurate diagnosis empowers people with cognitive concerns to understand their symptoms, plan for the future and seek appropriate treatments, whether or not they have a diagnosis of dementia. Improved diagnosis will be vital to ensure access to future disease-modifying treatments that might reduce the burden of dementia on individuals and the wider society.

Many people attending memory clinics receive a diagnosis of mild cognitive disorder (MCD) when it is not yet clear whether their symptoms are due to early dementia. Brain MRI and cognitive testing are routinely conducted, but existing cognitive tests are insensitive to early disease and culturally unfair, while human interpretation of brain imaging does not reliably provide a diagnosis until dementia is advanced. Molecular biomarkers to support diagnosis require a lumbar puncture or a PET scan, which are only available in 6% of UK memory services. Currently the only means of establishing the diagnosis is to follow patients up for at least 1-2 years. This follow-up is resource intensive and in many areas is not commissioned.

The East London Memory Clinics serve one of the most deprived and diverse populations in Europe. Around 0.4% of the population have received a diagnosis of dementia compared to the national standard of 1.2%, and of these less than 40% have a clear subtype diagnosis of Alzheimer’s disease (cf national standard 67%). Most patients referred to East London Memory Clinics receive an initial diagnosis of MCD (54% in a recent audit).

A recently awarded NIHR i4i PDA study at QMUL is developing artificial intelligence technology to address these problems using routinely acquired clinical and imaging data (ABATED – Automated Brain Image Analysis for Timely and Equitable Dementia Diagnosis). ABATED will be recruiting patients with MCD from East London Memory Clinics, and gathering demographic, clinical and imaging data to refine and validate the technology. The postdoctoral candidate will have the opportunity to embed their own research within the ABATED study to investigate other novel diagnostic technologies that could improve dementia services in underserved regions.

This research will focus on one or more candidate diagnostic technologies that could be used within existing NHS infrastructure in community settings, including novel methods for analysis of routinely acquired brain imaging, blood-based molecular biomarkers (in collaboration with Prof Jonathan Schott, UCL) and culturally fair, digital cognitive tests (in collaboration with Prof Jason Warren, UCL). The Fellow will have the opportunity to choose and lead on a modality that suits their interests and expertise, while benefiting from the study team infrastructure already in place. This will foster their development of specific research skills and transition towards independence. They will be expected to participate in our ongoing work with patients, the public and organisations including NHSE, NICE and Alzheimer’s Society to support implementation of the research in the design of NHS diagnostic services.

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Partners & Collaborators

Queen Mary, University of London 

Lead Investigator
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