MR approaches in neurodegenerative disorders

Abstract

Neurodegenerative disease is the umbrella term which refers to a range of clinical conditions causing degeneration of neurons within the central nervous system leading to loss of brain function and eventual death. The most prevalent of these is Alzheimer’s disease (AD), which affects approximately 50 million people worldwide and is predicted to reach 75 million by 2030. Neurodegenerative diseases can only be fully diagnosed at post mortem by neuropathological assessment of the type and distribution of protein deposits which characterise each different condition, but there is a clear role for imaging technologies in aiding patient diagnoses in life. Magnetic resonance imaging (MRI) and spectroscopy (MRS) techniques have been applied to study these conditions for many years. In this review, we consider the range of MR-based measurements and describe the findings in AD, but also contrast these with the second most common dementia, dementia with Lewy bodies (DLB).

The most definitive observation is the major structural brain changes seen in AD using conventional T1-weighted (T1w) MRI, where medial temporal lobe structures are notably atrophied in most symptomatic patients with AD, but often preserved in DLB. Indeed these findings are sufficiently robust to have been incorporated into clinical diagnostic criteria. Diffusion tensor imaging (DTI) reveals widespread changes in tissue microstructure, with increased mean diffusivity and decreased fractional anisotropy reflecting the degeneration of the white matter structures. There are suggestions that there are subtle differences between AD and DLB populations. At the metabolic level, atrophy-corrected MRS demonstrates reduced density of healthy neurons in brain areas with altered perfusion and in regions known to show higher deposits of pathogenic proteins.

As studies have moved from patients with advanced disease and clear dysfunction to patients with earlier presentation such as with mild cognitive impairment (MCI), which in some represents the first signs of their ensuing dementia, the ability of MRI to detect differences has been weaker and further work is still required, ideally in much larger cohorts than previously studied.

The vast majority of imaging research in dementia populations has been univariate with respect to the MR-derived parameters considered. To date, none of these measurements has uniquely replicated the patterns of tissue involvement seen by neuropathology, and the ability of MR techniques to deliver a non-invasive diagnosis eludes us. Future opportunities may lie in combining MR and nuclear medicine approaches (position emission tomography, PET) to provide a more complete view of structural and metabolic changes. Such developments will require multi-variate analyses, possibly combined with artificial intelligence or deep learning algorithms, to enhance our ability to combine the array of image-derived information, genetic, gender and lifestyle factors.