De Alwis, Manori1,2(Poster presenter), Wood, Emily1,3, Reich, Daniel1,4,5
1Translational Neuroradiology Unit, NIB, NINDS, NIH; 2Cornell University; Departments of 3Neuroscience, 4Neurology and 5Radiology, Johns Hopkins University School of Medicine.
Neuro-axonal degeneration is a major contributor to clinical disability in MS. Diffusion tensor spectroscopy (DTS) blends features of both diffusion weighted imaging and magnetic resonance spectroscopy, allowing measurement of the diffusion properties of intracellular metabolites such as N-acetylaspartate (NAA). As NAA is found primarily within axons in WM, DTS measurements of decreased NAA parallel diffusivity (PD) may confirm the presence of axonopathy in the face of overall increased intra- and extracellular water diffusion. Preliminary studies support this possibility by a finding of a correlation between clinical status and NAA PD (but not water PD), since disability is more closely related to neuroaxonal pathology than to inflammation.
Further work is required to establish the reliability of DTS and its sensitivity to detect changes in tissue microstructure over time. In order to examine the responsiveness of DTS measures to a range of disease severity in a longitudinal continuation study, data analysis and modeling procedures must be developed. The goal of this work was to establish an automated data analysis “pipeline” for post-processing of anatomical images related to the DTS acquisition. Multiple 3D brain volumes, including MPRAGE (T1-weighted), FLAIR (T2-weighted), and Diffusion Tensor Imaging, were co-registered, corrected for magnetic field inhomogeneities, and segmented into brain regions with the Java Imaging Science Toolbox (JIST) and MATLAB.
Last updated December 14, 2012