Fractional anisotropy derived from the diffusion tensor distribution function boosts power to detect Alzheimer's disease deficits

Talia M. Nir, Neda Jahanshad, Julio E. Villalon-Reina, Dmitry Isaev, Artemis Zavaliangos-Petropulu, Liang Zhan, Alex D. Leow, Clifford R Jr. Jack, Michael W. Weiner, Paul M. Thompson

Research output: Contribution to journalArticle

9 Citations (Scopus)

Abstract

Purpose: In diffusion MRI (dMRI), fractional anisotropy derived from the single-tensor model (FADTI) is the most widely used metric to characterize white matter (WM) microarchitecture, despite known limitations in regions with crossing fibers. Due to time constraints when scanning patients in clinical settings, high angular resolution diffusion imaging acquisition protocols, often used to overcome these limitations, are still rare in clinical population studies. However, the tensor distribution function (TDF) may be used to model multiple underlying fibers by representing the diffusion profile as a probabilistic mixture of tensors. Methods: We compared the ability of standard FADTI and TDF-derived FA (FATDF), calculated from a range of dMRI angular resolutions (41, 30, 15, and 7 gradient directions), to profile WM deficits in 251 individuals from the Alzheimer's Disease Neuroimaging Initiative and to detect associations with 1) Alzheimer's disease diagnosis, 2) Clinical Dementia Rating scores, and 3) average hippocampal volume. Results: Across angular resolutions and statistical tests, FATDF showed larger effect sizes than FADTI, particularly in regions preferentially affected by Alzheimer's disease, and was less susceptible to crossing fiber anomalies. Conclusion: The TDF "corrected" form of FA may be a more sensitive and accurate alternative to the commonly used FADTI, even in clinical quality dMRI data.

Original languageEnglish (US)
JournalMagnetic Resonance in Medicine
DOIs
StateAccepted/In press - 2017

Fingerprint

Diffusion Magnetic Resonance Imaging
Anisotropy
Alzheimer Disease
Aptitude
Neuroimaging
Dementia
Population
Power (Psychology)
White Matter

Keywords

  • Alzheimer's disease
  • Diffusion-weighted imaging
  • Fractional anisotropy
  • Tensor distribution function
  • White matter

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging

Cite this

Nir, T. M., Jahanshad, N., Villalon-Reina, J. E., Isaev, D., Zavaliangos-Petropulu, A., Zhan, L., ... Thompson, P. M. (Accepted/In press). Fractional anisotropy derived from the diffusion tensor distribution function boosts power to detect Alzheimer's disease deficits. Magnetic Resonance in Medicine. https://doi.org/10.1002/mrm.26623

Fractional anisotropy derived from the diffusion tensor distribution function boosts power to detect Alzheimer's disease deficits. / Nir, Talia M.; Jahanshad, Neda; Villalon-Reina, Julio E.; Isaev, Dmitry; Zavaliangos-Petropulu, Artemis; Zhan, Liang; Leow, Alex D.; Jack, Clifford R Jr.; Weiner, Michael W.; Thompson, Paul M.

In: Magnetic Resonance in Medicine, 2017.

Research output: Contribution to journalArticle

Nir, TM, Jahanshad, N, Villalon-Reina, JE, Isaev, D, Zavaliangos-Petropulu, A, Zhan, L, Leow, AD, Jack, CRJ, Weiner, MW & Thompson, PM 2017, 'Fractional anisotropy derived from the diffusion tensor distribution function boosts power to detect Alzheimer's disease deficits', Magnetic Resonance in Medicine. https://doi.org/10.1002/mrm.26623
Nir, Talia M. ; Jahanshad, Neda ; Villalon-Reina, Julio E. ; Isaev, Dmitry ; Zavaliangos-Petropulu, Artemis ; Zhan, Liang ; Leow, Alex D. ; Jack, Clifford R Jr. ; Weiner, Michael W. ; Thompson, Paul M. / Fractional anisotropy derived from the diffusion tensor distribution function boosts power to detect Alzheimer's disease deficits. In: Magnetic Resonance in Medicine. 2017.
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