Improved clinical diffusion MRI reliability using a tensor distribution function compared to a single tensor

Dmitry Y. Isaev; Talia M. Nir; Neda Jahanshad; Julio E. Villalon-Reina; Liang Zhan; Alex D. Leow; Paul M. Thompson

doi:10.1117/12.2257281

26 January 2017 Improved clinical diffusion MRI reliability using a tensor distribution function compared to a single tensor

Dmitry Y. Isaev, Talia M. Nir, Neda Jahanshad, Julio E. Villalon-Reina, Liang Zhan, Alex D. Leow, Paul M. Thompson

Author Affiliations +

Proceedings Volume 10160, 12th International Symposium on Medical Information Processing and Analysis; 101601K (2017) https://doi.org/10.1117/12.2257281
Event: 12th International Symposium on Medical Information Processing and Analysis, 2016, Tandil, Argentina

Abstract

Fractional anisotropy derived from the single-tensor model (FA^DTI) 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 (FA^TDF) 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 FA^TDF and FA^DTI in clinical quality data by computing the intra-class correlation (ICC) between dMRI scans collected 3 months apart. When FA^TDF and FA^DTI were calculated at various angular resolutions, FA^TDF ICC in both the corpus callosum and in a full axial slice were consistently more stable across scans, as compared to FA^DTI.

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Dmitry Y. Isaev, Talia M. Nir, Neda Jahanshad, Julio E. Villalon-Reina, Liang Zhan, Alex D. Leow, and Paul M. Thompson "Improved clinical diffusion MRI reliability using a tensor distribution function compared to a single tensor", Proc. SPIE 10160, 12th International Symposium on Medical Information Processing and Analysis, 101601K (26 January 2017); https://doi.org/10.1117/12.2257281

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