Cerebral Metabolic Patterns In Neurodegeneration

Neurodegenerative disorders comprise a group of conditions, including Parkinson’s and Alzheimer’s disease, in which neurons in specific brain regions deteriorate. Different neurodegenerative diseases exhibit distinct patterns of brain damage. Despite this, they often present with similar features in the beginning, and a ‘typical’ clinical picture can take years to develop. Establishing a diagnosis early in the disease course can be challenging, even for experts. Brain imaging with 18F-FDG PET may offer a solution, as 18F-FDG PET can be used to identify areas with disrupted glucose metabolism caused by the underlying disease process.
In this thesis, several distinguishable disease-related patterns were identified in 18F-FDG PET brain scans using a mathematical model called spatial covariance analysis. This model determines metabolic brain patterns by identifying areas of relative metabolic differences between healthy controls and patients. These patterns can be used to quantify the degree of disease activity in the brain scans of new patients.
We investigated whether this method would be useful at the early stages of neurodegenerative disease. We studied patients with rapid eye movement sleep behavior disorder (RBD), an early stage of Parkinson’s disease. The Parkinson’s disease-related brain pattern was already present in the scans of RBD patients, even though these patients did not yet manifest typical parkinsonian motor symptoms. We also found that mildly cognitively impaired subjects expressed the Alzheimer’s disease-related brain pattern years before developing full-blown dementia.
18F-FDG PET is a widely-available modality which is valuable for the study of neurodegenerative disorders, especially when combined with advanced analytical techniques.