arrow
Return

Multi-TE Diffusion MRI Dataset for Exploring Combined Diffusion-Relaxometry Methods in Microstructure Imaging

delete2025-07-10
delete0
delete
OA
AI
P
Paween Wongkornchaovalit
B
Bingchen Shao
L
Lingyu Li
Y
Yahong Chen
何宏建 (Hongjian He) *
J
Jianhui Zhong
T
Ting Gong *
DOI:10.1038/s41597-025-05544-1delete
deleteOriginal
deleteOriginal request for help
deleteShare
deleteSave
Abstract

Abstract

En 中文
Multi-echo-time (MTE) diffusion MRI (dMRI) offers several advantages over conventional single TE dMRI, including disentanglement of microstructural and compositional differences, reduction of bias in microstructural properties, and addition of sub-cellular T2 measures. However, MTE methods require additional data acquisition and complex model fitting. In this work, we share a comprehensive MTE dMRI dataset acquired from three healthy subjects in ten TE sessions (each with eight TEs: 62-132 ms and repeated measures at the shortest and longest TEs). The dataset includes two b-values (700 and 2000 s/mm2) with 30 gradient directions for each b-value and four b = 0 images, with diffusion times fixed (δ/Δ = 15.2/25.2 ms) across b-values and TEs. Preprocessing steps include denoising, corrections for B0 inhomogeneity, eddy current and motion correction, and aligning the DWIs and b-vectors to the first TE session. The dataset quality is validated by SNR and head motion assessments. The usage of the dataset is shown with microstructure metrics and orientation distribution functions across TE sessions, which may facilitate investigation in combined diffusion-relaxometry.

Journal

Scientific Data cover
Scientific Data
IF:
6.9
Papers:
3.5K
Citations:
3.8W

Organization

D
Department of Imaging Sciences
Scholars:
9
Papers: 6
Citations: 0
A
Athinoula A Martinos Center for Biomedical Imaging
Scholars:
7
Papers: 5
Citations: 4.5K
S
School of Physics
Scholars:
1.6K
Papers: 632
Citations: 18
researcher View more organizations