A toolbox to visually explore cerebellar shape changes in cerebellar disease and dysfunction

S. Mazdak Abulnaga; Zhen Yang; Aaron Carass; Kalyani Kansal; Bruno M. Jedynak; Chiadi U. Onyike; Sarah H. Ying; Jerry L. Prince

doi:10.1117/12.2216584

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24 March 2016 A toolbox to visually explore cerebellar shape changes in cerebellar disease and dysfunction

S. Mazdak Abulnaga, Zhen Yang, Aaron Carass, Kalyani Kansal, Bruno M. Jedynak, Chiadi U. Onyike, Sarah H. Ying, Jerry L. Prince

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Proceedings Volume 9785, Medical Imaging 2016: Computer-Aided Diagnosis; 97852P (2016) https://doi.org/10.1117/12.2216584
Event: SPIE Medical Imaging, 2016, San Diego, California, United States

Abstract

The cerebellum plays an important role in motor control and is also involved in cognitive processes. Cerebellar function is specialized by location, although the exact topographic functional relationship is not fully understood. The spinocerebellar ataxias are a group of neurodegenerative diseases that cause regional atrophy in the cerebellum, yielding distinct motor and cognitive problems. The ability to study the region-specific atrophy patterns can provide insight into the problem of relating cerebellar function to location. In an effort to study these structural change patterns, we developed a toolbox in MATLAB to provide researchers a unique way to visually explore the correlation between cerebellar lobule shape changes and function loss, with a rich set of visualization and analysis modules. In this paper, we outline the functions and highlight the utility of the toolbox. The toolbox takes as input landmark shape representations of subjects’ cerebellar substructures. A principal component analysis is used for dimension reduction. Following this, a linear discriminant analysis and a regression analysis can be performed to find the discriminant direction associated with a specific disease type, or the regression line of a specific functional measure can be generated. The characteristic structural change pattern of a disease type or of a functional score is visualized by sampling points on the discriminant or regression line. The sampled points are used to reconstruct synthetic cerebellar lobule shapes. We showed a few case studies highlighting the utility of the toolbox and we compare the analysis results with the literature.

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S. Mazdak Abulnaga, Zhen Yang, Aaron Carass, Kalyani Kansal, Bruno M. Jedynak, Chiadi U. Onyike, Sarah H. Ying, and Jerry L. Prince "A toolbox to visually explore cerebellar shape changes in cerebellar disease and dysfunction", Proc. SPIE 9785, Medical Imaging 2016: Computer-Aided Diagnosis, 97852P (24 March 2016); https://doi.org/10.1117/12.2216584

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KEYWORDS

Visualization

Cerebellum

Visual analytics

Principal component analysis

Shape analysis

Magnetic resonance imaging

Neodymium

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