MTE-NODDI: Multi-TE NODDI for disentangling non-T2-weighted signal fractions from compartment-specific T2 relaxation times

Ting Gong; Qiqi Tong; Hongjian He; Yi Sun; Jianhui Zhong; Hui Zhang

doi:10.1016/j.neuroimage.2020.116906

MTE-NODDI: Multi-TE NODDI for disentangling non-T2-weighted signal fractions from compartment-specific T2 relaxation times

Neuroimage. 2020 Aug 15:217:116906. doi: 10.1016/j.neuroimage.2020.116906. Epub 2020 May 7.

Authors

Ting Gong¹, Qiqi Tong², Hongjian He³, Yi Sun⁴, Jianhui Zhong⁵, Hui Zhang⁶

Affiliations

¹ Center for Brain Imaging Science and Technology, College of Biomedical Engineering and Instrumental Science, Zhejiang University, Hangzhou, China; Department of Computer Science & Centre for Medical Image Computing, University College London, UK.
² Center for Brain Imaging Science and Technology, College of Biomedical Engineering and Instrumental Science, Zhejiang University, Hangzhou, China.
³ Center for Brain Imaging Science and Technology, College of Biomedical Engineering and Instrumental Science, Zhejiang University, Hangzhou, China. Electronic address: hhezju@zju.edu.cn.
⁴ MR Collaboration, Siemens Healthcare, Shanghai, China.
⁵ Center for Brain Imaging Science and Technology, College of Biomedical Engineering and Instrumental Science, Zhejiang University, Hangzhou, China; Department of Imaging Sciences, University of Rochester, Rochester, NY, United States. Electronic address: jzhong@zju.edu.cn.
⁶ Department of Computer Science & Centre for Medical Image Computing, University College London, UK.

PMID: 32387626
DOI: 10.1016/j.neuroimage.2020.116906

Abstract

Neurite orientation dispersion and density imaging (NODDI) has become a popular diffusion MRI technique for investigating microstructural alternations during brain development, maturation and aging in health and disease. However, the NODDI model of diffusion does not explicitly account for compartment-specific T2 relaxation and its model parameters are usually estimated from data acquired with a single echo time (TE). Thus, the NODDI-derived measures, such as the intra-neurite signal fraction, also known as the neurite density index, could be T2-weighted and TE-dependent. This may confound the interpretation of studies as one cannot disentangle differences in diffusion from those in T2 relaxation. To address this challenge, we propose a multi-TE NODDI (MTE-NODDI) technique, inspired by recent studies exploiting the synergy between diffusion and T2 relaxation. MTE-NODDI could give robust estimates of the non-T2-weighted signal fractions and compartment-specific T2 values, as demonstrated by both simulation and in vivo data experiments. Results showed that the estimated non-T2 weighted intra-neurite fraction and compartment-specific T2 values in white matter were consistent with previous studies. The T2-weighted intra-neurite fractions from the original NODDI were found to be overestimated compared to their non-T2-weighted estimates; the overestimation increases with TE, consistent with the reported intra-neurite T2 being larger than extra-neurite T2. Finally, the inclusion of the free water compartment reduces the estimation error in intra-neurite T2 in the presence of cerebrospinal fluid contamination. With the ability to disentangle non-T2-weighted signal fractions from compartment-specific T2 relaxation, MTE-NODDI could help improve the interpretability of future neuroimaging studies, especially those in brain development, maturation and aging.

Keywords: Aging; Brain development; Brain maturation; Diffusion MRI; NODDI; T2 relaxation.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Aging
Algorithms
Brain / diagnostic imaging
Brain / growth & development
Cerebrospinal Fluid
Computer Simulation
Databases, Factual
Diffusion Magnetic Resonance Imaging / methods*
Humans
Image Interpretation, Computer-Assisted
Image Processing, Computer-Assisted / methods*
Models, Neurological
Neurites / physiology*
Neuroimaging / methods
Reproducibility of Results
White Matter / diagnostic imaging