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Proceedings Paper

White matter degeneration in schizophrenia: a comparative diffusion tensor analysis
Author(s): Madhura A. Ingalhalikar; Nancy C. Andreasen; Jinsuh Kim; Andrew L. Alexander; Vincent A. Magnotta
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Paper Abstract

Schizophrenia is a serious and disabling mental disorder. Diffusion tensor imaging (DTI) studies performed on schizophrenia have demonstrated white matter degeneration either due to loss of myelination or deterioration of fiber tracts although the areas where the changes occur are variable across studies. Most of the population based studies analyze the changes in schizophrenia using scalar indices computed from the diffusion tensor such as fractional anisotropy (FA) and relative anisotropy (RA). The scalar measures may not capture the complete information from the diffusion tensor. In this paper we have applied the RADTI method on a group of 9 controls and 9 patients with schizophrenia. The RADTI method converts the tensors to log-Euclidean space where a linear regression model is applied and hypothesis testing is performed between the control and patient groups. Results show that there is a significant difference in the anisotropy between patients and controls especially in the parts of forceps minor, superior corona radiata, anterior limb of internal capsule and genu of corpus callosum. To check if the tensor analysis gives a better idea of the changes in anisotropy, we compared the results with voxelwise FA analysis as well as voxelwise geodesic anisotropy (GA) analysis.

Paper Details

Date Published: 12 March 2010
PDF: 8 pages
Proc. SPIE 7623, Medical Imaging 2010: Image Processing, 762329 (12 March 2010); doi: 10.1117/12.844283
Show Author Affiliations
Madhura A. Ingalhalikar, Univ. of Iowa (United States)
Nancy C. Andreasen, Univ. of Iowa (United States)
Jinsuh Kim, Univ. of Iowa (United States)
Andrew L. Alexander, Univ. of Wisconsin (United States)
Vincent A. Magnotta, Univ. of Iowa (United States)


Published in SPIE Proceedings Vol. 7623:
Medical Imaging 2010: Image Processing
Benoit M. Dawant; David R. Haynor, Editor(s)

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