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使用多维 MRI 对扩散频移、张量形状和弛豫进行体内解缠。

In vivo disentanglement of diffusion frequency-dependence, tensor shape, and relaxation using multidimensional MRI.

机构信息

Multiscale Imaging and Integrative Biophysics Unit, National Institute on Aging, NIH, Baltimore, Maryland, USA.

Quantitative Medical Imaging Section, National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Bethesda, Maryland, USA.

出版信息

Hum Brain Mapp. 2024 May;45(7):e26697. doi: 10.1002/hbm.26697.

Abstract

Diffusion MRI with free gradient waveforms, combined with simultaneous relaxation encoding, referred to as multidimensional MRI (MD-MRI), offers microstructural specificity in complex biological tissue. This approach delivers intravoxel information about the microstructure, local chemical composition, and importantly, how these properties are coupled within heterogeneous tissue containing multiple microenvironments. Recent theoretical advances incorporated diffusion time dependency and integrated MD-MRI with concepts from oscillating gradients. This framework probes the diffusion frequency, , in addition to the diffusion tensor, , and relaxation, , , correlations. A clinical imaging protocol was then introduced, with limited brain coverage and 3 mm voxel size, which hinder brain segmentation and future cohort studies. In this study, we introduce an efficient, sparse in vivo MD-MRI acquisition protocol providing whole brain coverage at 2 mm voxel size. We demonstrate its feasibility and robustness using a well-defined phantom and repeated scans of five healthy individuals. Additionally, we test different denoising strategies to address the sparse nature of this protocol, and show that efficient MD-MRI encoding design demands a nuanced denoising approach. The MD-MRI framework provides rich information that allows resolving the diffusion frequency dependence into intravoxel components based on their distribution, enabling the creation of microstructure-specific maps in the human brain. Our results encourage the broader adoption and use of this new imaging approach for characterizing healthy and pathological tissues.

摘要

具有自由梯度波形的扩散 MRI,结合同时的弛豫编码,被称为多维 MRI(MD-MRI),在复杂的生物组织中提供了微观结构的特异性。这种方法提供了关于微观结构、局部化学成分的体素内信息,重要的是,这些特性在包含多个微环境的异质组织中是如何耦合的。最近的理论进展将扩散时间依赖性纳入其中,并将 MD-MRI 与振荡梯度的概念相结合。该框架除了扩散张量 ,还探测扩散频率 ,以及弛豫 、 、 相关性。然后引入了一种临床成像方案,具有有限的大脑覆盖范围和 3mm 体素大小,这阻碍了大脑分割和未来的队列研究。在这项研究中,我们引入了一种高效的、稀疏的体内 MD-MRI 采集方案,在 2mm 体素大小下提供全脑覆盖。我们使用定义明确的体模和五名健康个体的重复扫描来证明其可行性和稳健性。此外,我们测试了不同的去噪策略来解决该方案的稀疏性,并表明高效的 MD-MRI 编码设计需要一种细致入微的去噪方法。MD-MRI 框架提供了丰富的信息,允许根据其分布将扩散频率依赖性解析为体素内分量,从而能够在人脑内创建具有微观结构特异性的图谱。我们的结果鼓励更广泛地采用和使用这种新的成像方法来表征健康和病理组织。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/691a/11082920/eda621032b17/HBM-45-e26697-g006.jpg

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