Dysfunction of the cerebellum is associated with a wide variety of diseases that have significant morbidity yet inadequate therapy. Strokes, tumors, infection, autoimmune disease, medication side effects, and chronic alcoholism can all affect the cerebellum, as can more specific diseases of the cerebellum such as olivopontine cerebellar degeneration and cerebellar ataxia. Through the study of cerebellar ataxia, which involves pronounced atrophy in distinct patterns associated with specific genetic defects, we will be able to establish precise relationships between patterns of cerebellar atrophy and patterns of motor and cognitive deficits. Eventually, it will become possible to predict the functional impacts of cerebellar degeneration when observed in clinical assessments and thereby to suggest appropriate targeted therapies. Prior research has enabled automated analysis of regional atrophy in the cerebellum, a task that had previously been carried out manually. The proposed research will advance this capability to include joint, automated segmentation and analysis of both white matter and gray matter in cerebellum and nearby regions using multimodal imaging data. Specifically, we will: 1) Implement and optimize gray matter and white matter segmentation methods in the cerebellum and vicinity using multimodal images;2) Develop methods to quantify regional cerebellar shapes in individuals and to define statistical shape variation across populations;3) Carry out a pilot study on gray matter and white matter structure and relate these to motor and cognitive functional performance. Specific hypotheses related to patterns of degeneration and corresponding functional deficits in SCA2, SCA3, and SCA6 will be tested, and a preliminary map of the topography of functional scores on a low- dimensional shape space incorporating normal and ataxia subjects will be produced. This new capability will yield a novel staging chart for cerebellar function for use in diagnosis, prognosis, and treatment assessment. The overall goal of the proposed research is to develop automated image and statistical analysis methods that can analyze the patterns of atrophy and associated motor and cognitive deficits in populations and individuals due to cerebellar dysfunction. Methods that are developed will be made available as open source software within a previously established and very extensive software collection already available on the NITRC website. The statistical atlas of our subjects will also be made available together with software for positioning individuals within this space and for generating new atlases on new data collections. Through our efforts in technology development as well as our pilot study demonstrating utility of this analytic approach, new discoveries related to the cerebellum in diverse diseases carried out by many labs will become possible. Such investigations can then lead to new treatments for cerebellar disease and to targeted therapies in those suffering from ataxia and other diseases with cerebellum involvement.
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