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Proceedings Paper

Improved clinical diffusion MRI reliability using a tensor distribution function compared to a single tensor
Author(s): Dmitry Y. Isaev; Talia M. Nir; Neda Jahanshad; Julio E. Villalon-Reina; Liang Zhan; Alex D. Leow; Paul M. Thompson
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Paper Abstract

Fractional anisotropy derived from the single-tensor model (FADTI) in diffusion MRI (dMRI) is the most widely used metric to characterize white matter (WM) micro-architecture in disease, despite known limitations in regions with extensive fiber crossing. Models such as the tensor distribution function (TDF), which represents the diffusion profile as a probabilistic mixture of tensors, have been proposed to reconstruct multiple underlying fibers. Although complex HARDI acquisition protocols are rare in clinical studies, the TDF and TDF-derived scalar FA metric (FATDF) have been shown to be advantageous even for data with modest angular resolution. However, further evaluation and validation of the metric are necessary. Here we compared the test-retest reliability of FATDF and FADTI in clinical quality data by computing the intra-class correlation (ICC) between dMRI scans collected 3 months apart. When FATDF and FADTI were calculated at various angular resolutions, FATDF ICC in both the corpus callosum and in a full axial slice were consistently more stable across scans, as compared to FADTI.

Paper Details

Date Published: 26 January 2017
PDF: 8 pages
Proc. SPIE 10160, 12th International Symposium on Medical Information Processing and Analysis, 101601K (26 January 2017); doi: 10.1117/12.2257281
Show Author Affiliations
Dmitry Y. Isaev, The Univ. of Southern California (United States)
Talia M. Nir, The Univ. of Southern California (United States)
Neda Jahanshad, The Univ. of Southern California (United States)
Julio E. Villalon-Reina, The Univ. of Southern California (United States)
Liang Zhan, Univ. of Wisconsin-Stout (United States)
Alex D. Leow, Univ. of Illinois (United States)
Paul M. Thompson, The Univ. of Southern California (United States)


Published in SPIE Proceedings Vol. 10160:
12th International Symposium on Medical Information Processing and Analysis
Eduardo Romero; Natasha Lepore; Jorge Brieva; Jorge Brieva; Ignacio Larrabide; , Editor(s)

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