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在9.4特斯拉的衰老老鼠大脑的放松-扩散MRI数据集

Baoxing Ren^1,2, Ye Wu³, Yan Liu^1,2

¹School of Biomedical Engineering, Southern Medical University, Guangzhou, 510515, China.

Scientific data

|November 17, 2025

概括

这项研究提出了一个新的放松-扩散MRI (rdMRI) 老化小鼠大脑的数据集. 这种宝贵的资源有助于开发先进的MRI技术,用于临床前研究和理解大脑衰老.

科学领域:

神经成像是一种神经成像.
生物医学工程生物医学工程
老年学是一门学科.

背景情况:

放松-扩散MRI (rdMRI) 通过分离放松和扩散效应,为组织微观结构提供了先进的洞察力.
在临床前小鼠模型中rdMRI数据集的有限可用性阻碍了对复杂生物过程和衰老的研究.

研究的目的:

为了呈现一个新的,高质量的老鼠大脑的体内rdMRI数据集.
促进在临床前环境中对rdMRI技术的验证和优化.
为研究与年龄有关的结构性大脑变化提供资源.

主要方法:

使用9.4T超高场MRI扫描仪从五个年龄组的小鼠 (每组n=6) 获取rdMRI数据.
在5个回声时间 (TE) 收集数据,在每个TE进行多扩散扫描.
通过专业管道进行严格的数据处理,并有系统的质量控制.

主要成果:

创建一个全面的,高质量的老化老鼠大脑的体内rdMRI数据集.
通过精心处理和质量控制措施,确保数据的可靠性.

结论:

本文所介绍的数据集是推进rdMRI方法学的基础资源.
这一数据集将加速对老鼠大脑中与年龄相关的结构变化的研究,支持临床前研究.

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Magnetic Resonance Imaging

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