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The logistical complexities of performing multi-site longitudinal diffusion-weighted imaging (DWI) studies requires careful construction of analysis tools and procedures. Proposed clinical trials for therapies in neurodegenerative disease are known to re- quire several hundred subjects, thus mandating multiple site participation to obtain sufficient sample sizes. DWI is an important tool for monitoring diffusivity properties of white matter (WM) in disease progression. The multi-site nature of clinical trials requires new strategies in DWI processing and analysis to reliably measure longitudi- nal WM changes. This work describes the process of developing and validating robust analysis methodologies to process multi-site DWI data in a rare, neurodegenerative disease. Key processing components to accomplish a robust DWI processing system include: DICOM conversion, automated quality control, unbiased atlas construction, fiber tracking, and statistical analysis. Extensive validation studies were performed to characterize methodological results within and across the common confounds inherent in multi-site clinical trials.
The conversion and automated quality control tools optimized for this work both enhanced the ability to reliably obtain repeat diffusion tensor image (DTI) scalar measurements in a reliability analysis of healthy controls scanned at multiple sites using multiple scanner vendors. A DTI scalar analysis performed on focused WM regions showed it was possible to detect significant mean differences of DTI scalars among separate groups of a neurodegenerative disease population. The DTI scalar analysis paved the way for an atlas-based cross-sectional fiber tracking analysis. In the cross-sectional fiber tracking analysis, multi-site data was brought into the same space, making major fiber tracts terminating in the focused WM regions of the scalar analysis from all participants comparable. Significant differences in diffusivity were found throughout each tract among separate groups of the neurodegenerative disease population. In addition, multiple neuropsychological cognitive variables that have a documented ability to track disease progression of the neurodegenerative disease, strongly correlated with many of the DTI scalars in each tract. The findings of the cross-sectional fiber tracking analysis were reinforced by similar findings produced by a longitudinal fiber tracking analysis. Collectively, these findings suggest that cogni- tive deficits seen in the neurodegenerative disease population could be explained by changes in diffusivity of the tracts explored in this work. In addition to the longi- tudinal fiber tracking analysis examining diffusivity, methods for a WM morphology analysis using parallel transport to apply longitudinal volume changes to a template was explored.