Improving Diagnosis And Measurement Of Progression In Dementia: Longitudinal Clinical And MRI Studies
Lead Research Organisation:
University College London
Department Name: Institute of Neurology
Abstract
In the UK there are already 700,000 people with dementia and this number is set to double in the next 20 years. Alzheimer‘s disease is the commonest of many causes. These diseases are difficult to diagnose at an early stage. Magnetic resonance scans provide detailed pictures of the brain. The amount and pattern of brain loss (atrophy) on the scan can help make a diagnosis. Unfortunately visual assessment is not good at distinguishing disease from age-related change; new measures are needed. I have developed methods of scanning using computers to measure changes on brain scans. I will use and improve these techniques to measure how fast brain tissue is being lost and from where. I will assess how these changes relate to clinical symptoms and cognitive decline. I will also compare atrophy measure to other markers, including scans for amyloid (a protein that accumulates in AD brains). This will help us diagnose the diseases that cause dementia and understand how they progress. Importantly these techniques are now also being used in trials to assess therapies. Ultimately I hope these methods will help identify effective treatments for these devastating conditions and enable them to be provided as early as possible through earlier improved diagnosis.
Technical Summary
Aims/objectives
Achieve earlier and more precise diagnosis in Alzheimer‘s disease (AD) and related disorders, including pre-clinical detection of disease;
Improve understanding of the pathophysiological evolution of neurodegenerative diseases and the relationships between imaging and clinical manifestations;
Measure disease progression, and assess its correlates and influences;
Evaluate symptomatic and potentially disease-modifying therapies.
Design/methods
Measures of cerebral change will be improved by optimising MRI acquisition reproducibility and post-acquisition artefact correction. Optimised protocols and artefact correction will be developed for 3T phased array acquisitions for 3D T2-weighted as well as T1-weighted volumetric studies. Linear and non-linear registration will be used to match imaging studies across modality and over time.
Registration-based measures of atrophy rates will be further developed - and different approaches critically compared and the topography of progression will be assessed. The precision of measures will be improved with multiple time point imaging. Registration and quantification techniques will be developed that fully incorporate multiple time point studies, fitting the time series rather than each pair of scans independently. I will determine the minimum scan-interval needed for serial MRI to a) detect and b) distinguish neurodegenerative disorders. I will pursue the potential for reduced sample sizes in trials by reducing within-subject variability in atrophy rate measures and investigating run-in designs.
I will further develop registration-based methods for quantifying progression of regional and global atrophy and parenchymal change and for measurement of cortical thickness changes: for these aims I will investigate combined serial 3D T2-weighted and T1-weighted imaging.
I will combine and correlate atrophy measures with CSF markers and amyloid imaging (C11-PIB- PET) to determine the topography and association between amyloid deposition and neuronal loss. I will also correlate imaging changes with neuropsychometry to understand the temporal and topographical association between neuronal loss, amyloid deposition and cognition.
I will apply these techniques to well-characterised clinical cohorts with established disease and also to individuals at risk of familial AD, prion, Huntington‘s and fronto-temporal dementia. These cohorts offer a unique opportunity to study pre-symptomatic disease. Additionally I will study mild cognitive impairment (MCI) and subjects who have amnestic complaints but do have a sufficient memory deficit to fulfil criteria for MCI (which may represent a pre-MCI stage).
This programme of research offers clinical as well as scientific opportunities in the dementias but should also have relevance to other disorders where precise and yet easily applicable measurements of cerebral changes are important.
Achieve earlier and more precise diagnosis in Alzheimer‘s disease (AD) and related disorders, including pre-clinical detection of disease;
Improve understanding of the pathophysiological evolution of neurodegenerative diseases and the relationships between imaging and clinical manifestations;
Measure disease progression, and assess its correlates and influences;
Evaluate symptomatic and potentially disease-modifying therapies.
Design/methods
Measures of cerebral change will be improved by optimising MRI acquisition reproducibility and post-acquisition artefact correction. Optimised protocols and artefact correction will be developed for 3T phased array acquisitions for 3D T2-weighted as well as T1-weighted volumetric studies. Linear and non-linear registration will be used to match imaging studies across modality and over time.
Registration-based measures of atrophy rates will be further developed - and different approaches critically compared and the topography of progression will be assessed. The precision of measures will be improved with multiple time point imaging. Registration and quantification techniques will be developed that fully incorporate multiple time point studies, fitting the time series rather than each pair of scans independently. I will determine the minimum scan-interval needed for serial MRI to a) detect and b) distinguish neurodegenerative disorders. I will pursue the potential for reduced sample sizes in trials by reducing within-subject variability in atrophy rate measures and investigating run-in designs.
I will further develop registration-based methods for quantifying progression of regional and global atrophy and parenchymal change and for measurement of cortical thickness changes: for these aims I will investigate combined serial 3D T2-weighted and T1-weighted imaging.
I will combine and correlate atrophy measures with CSF markers and amyloid imaging (C11-PIB- PET) to determine the topography and association between amyloid deposition and neuronal loss. I will also correlate imaging changes with neuropsychometry to understand the temporal and topographical association between neuronal loss, amyloid deposition and cognition.
I will apply these techniques to well-characterised clinical cohorts with established disease and also to individuals at risk of familial AD, prion, Huntington‘s and fronto-temporal dementia. These cohorts offer a unique opportunity to study pre-symptomatic disease. Additionally I will study mild cognitive impairment (MCI) and subjects who have amnestic complaints but do have a sufficient memory deficit to fulfil criteria for MCI (which may represent a pre-MCI stage).
This programme of research offers clinical as well as scientific opportunities in the dementias but should also have relevance to other disorders where precise and yet easily applicable measurements of cerebral changes are important.