@inproceedings{e97b0ebc85854f6e8c336791d66bfbc8,
title = "Improved clinical diffusion MRI reliability using a tensor distribution function compared to a single tensor",
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.",
keywords = "Diffusion tensor imaging, Fractional anisotropy, Intraclass correlation, Tensor distribution function, Test retest reliability",
author = "Isaev, \{Dmitry Y.\} and Nir, \{Talia M.\} and Neda Jahanshad and Villalon-Reina, \{Julio E.\} and Liang Zhan and Leow, \{Alex D.\} and Thompson, \{Paul M.\}",
note = "Publisher Copyright: {\textcopyright} 2017 SPIE.; 12th International Symposium on Medical Information Processing and Analysis, SIPAIM 2016 ; Conference date: 05-12-2016 Through 07-12-2016",
year = "2017",
doi = "10.1117/12.2257281",
language = "English",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Eduardo Romero and Natasha Lepore and Jorge Brieva and Ignacio Larrabide",
booktitle = "12th International Symposium on Medical Information Processing and Analysis",
address = "United States",
}