Department of Computer Science, Centre for Medical Image Computing, University College of London, Gower Street, London WC1E 6BT, United Kingdom.
Champalimaud Neuroscience Programme, Champalimaud Centre for the Unknown, Av. Brasilia, 1400-038 Lisbon, Portugal.
Neuroimage. 2018 Nov 15;182:97-116. doi: 10.1016/j.neuroimage.2017.11.028. Epub 2017 Nov 16.
Many developmental processes, such as plasticity and aging, or pathological processes such as neurological diseases are characterized by modulations of specific cellular types and their microstructures. Diffusion-weighted Magnetic Resonance Imaging (DW-MRI) is a powerful technique for probing microstructure, yet its information arises from the ubiquitous, non-specific water signal. By contrast, diffusion-weighted Magnetic Resonance Spectroscopy (DW-MRS) allows specific characterizations of tissues such as brain and muscle in vivo by quantifying the diffusion properties of MR-observable metabolites. Many brain metabolites are predominantly intracellular, and some of them are preferentially localized in specific brain cell populations, e.g., neurons and glia. Given the microstructural sensitivity of diffusion-encoding filters, investigation of metabolite diffusion properties using DW-MRS can thus provide exclusive cell and compartment-specific information. Furthermore, since many models and assumptions are used for quantification of water diffusion, metabolite diffusion may serve to generate a-priori information for model selection in DW-MRI. However, DW-MRS measurements are extremely challenging, from the acquisition to the accurate and correct analysis and quantification stages. In this review, we survey the state-of-the-art methods that have been developed for the robust acquisition, quantification and analysis of DW-MRS data and discuss the potential relevance of DW-MRS for elucidating brain microstructure in vivo. The review highlights that when accurate data on the diffusion of multiple metabolites is combined with accurate computational and geometrical modeling, DW-MRS can provide unique cell-specific information on the intracellular structure of brain tissue, in health and disease, which could serve as incentives for further application in vivo in human research and clinical MRI.
许多发育过程,如可塑性和衰老,或病理性过程,如神经疾病,其特征是特定细胞类型及其微结构的调制。扩散加权磁共振成像(DW-MRI)是一种强大的探测微结构的技术,但它的信息来自无处不在的、非特异性的水信号。相比之下,扩散加权磁共振波谱(DW-MRS)通过量化可观察代谢物的扩散特性,允许对大脑和肌肉等组织进行特定的特征描述。许多脑代谢物主要是细胞内的,其中一些优先定位于特定的脑细胞群体,例如神经元和神经胶质。鉴于扩散编码滤波器的微结构敏感性,使用 DW-MRS 研究代谢物扩散特性可以提供细胞和特定隔室的独特信息。此外,由于许多模型和假设用于量化水扩散,代谢物扩散可能有助于在 DW-MRI 中选择模型。然而,DW-MRS 测量从采集到准确和正确的分析和量化阶段都极具挑战性。在这篇综述中,我们调查了为稳健采集、量化和分析 DW-MRS 数据而开发的最新方法,并讨论了 DW-MRS 在阐明体内脑微结构方面的潜在相关性。该综述强调,当结合准确的多代谢物扩散数据和准确的计算和几何建模时,DW-MRS 可以提供关于组织内细胞结构的独特的细胞特异性信息,无论是在健康还是疾病状态下,这可能会激励进一步在人类研究和临床 MRI 中进行体内应用。