Surface-Based Cortical Thickness for Improved Characterization of Huntington’s Disease Progression
Larson, Kathleen Elizabeth
0000-0002-1997-0248
:
2023-05-17
Abstract
Huntington's disease (HD) is a rare, autosomal dominant, neurodegenerative disorder characterized by severe motor and cognitive decline. Using structural MRI, studies have identified myriad image-based markers related to disease progression, the most significant being volumetric loss in the striatum that corresponds to the severity of motor symptoms. Research has also observed widespread changes in cortical gray matter thickness (CTh) that more closely correlate to cognitive and behavioral symptoms such as processing speed, attention span, and impulsivity. Unfortunately, reports of HD related CTh changes are inconsistent between studies. This is likely due, in part, to the difficulties in quantifying CTh within image data where severe neurodegeneration is present. In this dissertation, we present our work in developing improved image processing techniques to better measure CTh changes. Firstly, we created method to produce ground truth data for accuracy validation the accuracy of both new and existing CTh measurement tools. We then developed a novel, surface-based Laplacian (SBL) thickness mapping for CTh that uses finite difference methods to solve for the Laplacian equation within the cortical GM ribbon. Using our synthetic atrophy method for validation, we demonstrate that our method measures CTh changes with significantly more accuracy than the most widely used too. Lastly, we applied the SBL to measure CTh in the longitudinal, PREDICT-HD dataset to observe patterns between CTh changes and clinical symptom progression. We observed widespread thickness changes across the cortex in agreement with existing literature, but our specific thickness definition rendered these changes far more pronounced than previously found. The work presented has the potential to provide an improved understanding of CTh changes throughout the different stages of disease progression, and how these changes relate to both symptom expression and other forms of HD related neurodegeneration.