Structural MRI of the brain is a tool that allows for examination of complex brain structure in increasingly fine detail. The detection of neurodegenerative diseases and quantification of their effects on the brain, using MRI data, remains a challenge. Limited spatial resolution and contrast to noise impose the major boundaries that limit the detection of the earliest stages of neurodegenerative processes. In addition, the complexity of the pattern of subtle structural changes in both normal aging and neurodegeneration, and how these changes are related to clinical measures of cognition and function, impede the construction of meaningful anatomical models that can be used to detect the onset of dementia.
On its own, the image data that MR provides are a highly complex mapping of macroscopic anatomy that cannot be directly related to clinical questions without subjective human interpretation. Automated methods of image processing and analysis provide a route to extracting and analyzing quantitative, accurate and reproducible descriptions of the underlying anatomy, to which formal scientific and mathematical tests can be applied.
This core will build on previous MR image analysis development work carried out at the CIND on lower field MR imaging, to make optimal use of innovative new imaging methods being developed at high field strengths. By combining new imaging techniques with novel image analysis approaches, this component of the research resource proposal will allow the extraction and analysis of key structural features such as changes in cortical gray matter and white matter, which underlie functional changes in aging and neurodegeneration.
In addition to the proposed improvements for extraction of accurate and reproducible anatomical information this core proposes to extend recently developed complexity estimation techniques, which utilize spatial statistical information in anatomical and functional images, to provide sensitive and specific classification of neurodegenerative disease. These techniques should greatly benefit, in terms of improved sensitivity and specificity, from the improved anatomical information generated by the Project 1 of this core, as well as improved functional and metabolic information provided by other cores in this proposal.
This image processing and analysis core consists of two main complementary projects.