Abstract #4047

Multi-echo NODDI with released intrinsic diffusivity in the healthy human brain tissue

Ezequiel Farrher¹, Kuan-Hung Cho², Richard P. Buschbeck¹, Chia-Wen Chiang³, Sheng-Min Huang⁴, Ming-Jye Chen³, Chang-Hoon Choi¹, Li-Wei Kuo^3,5, and N. Jon Shah^1,6,7,8

¹Institute of Neuroscience and Medicine 4 - Medical Imaging Physics, Forschungszentrum Jülich, Jülich, Germany, ²Department of Electronic Engineering, National United University, Miaoli, Taiwan, ³Institute of Biomedical Engineering and Nanomedicine, National Health Research Institutes, Miaoli, Taiwan, ⁴Department of Pharmacology, National Cheng Kung University, Tainan, Taiwan, ⁵Institute of Medical Device and Imaging, National Taiwan University College of Medicine, Taipei, Taiwan, ⁶Department of Neurology, Faculty of Medicine, RWTH Aachen University, Aachen, Germany, ⁷JARA – BRAIN – Translational Medicine, RWTH Aachen University, Aachen, Germany, ⁸Institute of Neuroscience and Medicine 11, Forschungszentrum Jülich, Jülich, Germany

Synopsis

Keywords: Diffusion Modeling, Diffusion Modeling, NODDI; multi-echo NODDI; transverse relaxation

Motivation: A well-known limitation of NODDI is that the intrinsic diffusivity parameter must be fixed to a brain-wide value to stabilise estimation, which restricts its applicability.

Goal(s): An estimation approach for multi-echo NODDI (MTE-NODDI) with released intrinsic diffusivity recently proposed for the rat brain is applied here to investigate human brain tissue microstructure.

Approach: Parameter estimation was performed via non-linear least-squares with an additional l₂-norm regularisation term to enforce fitting stability.

Results: Estimation of MTE-NODDI parameters with released intrinsic diffusivity was stable over several tissue types. Significant changes in tissue values were observed compared to the conventional approach.

Impact: Incorporating an l₂-norm regularisation term into the estimation of MTE-NODDI parameters allows the intrinsic diffusivity to be released whilst ensuring fitting stability. This opens the possibility of using MTE-NODDI to investigate a great variety of tissue pathologies.

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