Diffusion tensor distribution function metrics boost power to detect deficits in Alzheimer's disease

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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

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. Due to time constraints and interest in collecting multiple clinical samples and MRI scan types, complex HARDI acquisition protocols are rare in clinical population dMRI studies. Under such constraints, the tensor distribution function (TDF) can still be used to reconstruct multiple underlying fibers by representing the diffusion profile as a probabilistic mixture of tensors. Here we set out to better profile WM deficits in Alzheimer's disease (AD) by comparing the standard FADTI and TDF-derived FA (FATDF) in (1) WM network connectivity and voxel-based analyses of diagnostic differences, and (2) for picking up associations with clinical cognitive ratings and hippocampal volume. Ultimately, the TDF approach may be more sensitive and accurate than corresponding DTI-derived measures.

Original languageEnglish (US)
Title of host publication2016 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2016 - Proceedings
PublisherIEEE Computer Society
Pages1088-1092
Number of pages5
Volume2016-June
ISBN (Electronic)9781479923502
DOIs
StatePublished - Jun 15 2016
Event2016 IEEE 13th International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2016 - Prague, Czech Republic
Duration: Apr 13 2016Apr 16 2016

Other

Other2016 IEEE 13th International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2016
CountryCzech Republic
CityPrague
Period4/13/164/16/16

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Keywords

  • Alzheimer's disease
  • diffusion imaging
  • fractional anisotropy
  • TDF
  • white matter

ASJC Scopus subject areas

  • Biomedical Engineering
  • Radiology Nuclear Medicine and imaging

Cite this

Nir, T. M., Zavaliangos-Petropulu, A., Jahanshad, N., Villalon-Reina, J. E., Zhan, L., Leow, A. D., Bernstein, M. A., Jack, C. R. J., Weiner, M. W., & Thompson, P. M. (2016). Diffusion tensor distribution function metrics boost power to detect deficits in Alzheimer's disease. In 2016 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2016 - Proceedings (Vol. 2016-June, pp. 1088-1092). [7493455] IEEE Computer Society. https://doi.org/10.1109/ISBI.2016.7493455