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多TE扩散MRI数据集用于探索微结构成像中的综合扩散-放松计方法

Paween Wongkornchaovalit^1,2, Bingchen Shao³, Lingyu Li^1,4

¹College of Biomedical Engineering and Instrument Science, Zhejiang University, Zhejiang, China.

Scientific data

|July 10, 2025

概括

这项研究提供了来自健康受试者的综合多回声时间扩散MRI数据集. 这些数据有助于对大脑微观结构和放松度学的高级分析,克服了传统方法的局限性.

科学领域:

神经成像是一种神经成像.
扩散式核磁共振成像 (MRI)
量化MRI是指数量化的MRI.

背景情况:

与单个TE方法相比,多回声时间 (MTE) 扩散MRI (dMRI) 提供了增强的微观结构和组成分析.
MTE dMRI需要广泛的数据采集和复杂的建模,这对广泛采用构成了挑战.
现有的数据集可能无法完全捕捉MTE dMRI在联合扩散-放松计研究中的潜力.

研究的目的:

介绍和描述一个全面的MTEdMRI数据集,适用于先进的神经成像研究.
提供高质量的数据集,使微结构性质和T2放松计的解成为可能.
为了促进对联合扩散-放松计分析的调查.

主要方法:

在10个回声时间 (TE) 会议中从三名健康受试者获得MTE dMRI数据.
数据采集在两个b值 (700和2000秒/mm2) 和固定的扩散时间 (δ/Δ = 15.2/25.2毫秒).
严格的预处理包括无噪,B0不均,流和运动校正,与b向量对齐.

主要成果:

该数据集包括详细的MTE dMRI数据,在最短和最长的TEs进行重复测量,以进行可靠的分析.
质量评估证实了高信号噪声比 (SNR) 和最小的头部运动.
数据集对计算微结构指标和跨TE的定向分布函数的证明有用性.

结论:

提出的MTE dMRI数据集是神经成像社区的宝贵资源.
它可以进行先进的分析,将扩散特性与T2放松信息结合起来.
这一数据集将刺激扩散放松计和亚细胞组织特征的进一步研究.

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