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相关张量磁共振成像。

Correlation tensor magnetic resonance imaging.

机构信息

Champalimaud Research, Champalimaud Centre for the Unknown, Lisbon, Portugal.

Center of Functionally Integrative Neuroscience (CFIN) and MINDLab, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark; Department of Physics and Astronomy, Aarhus University, Aarhus, Denmark.

出版信息

Neuroimage. 2020 May 1;211:116605. doi: 10.1016/j.neuroimage.2020.116605. Epub 2020 Feb 8.

Abstract

Diffusional Kurtosis Magnetic Resonance Imaging (DKI) quantifies the extent of non-Gaussian water diffusion, which has been shown to be a sensitive biomarker for microstructure in health and disease. However, DKI is not specific to any microstructural property per se since kurtosis may emerge from several different sources. Q-space trajectory encoding schemes have been proposed for decoupling kurtosis arising from the variance of mean diffusivities (isotropic kurtosis) from kurtosis driven by microscopic anisotropy (anisotropic kurtosis). Still, these methods assume that the system is comprised of multiple Gaussian diffusion components with vanishing intra-compartmental kurtosis (associated with restricted diffusion). Here, we develop a more general framework for resolving the underlying kurtosis sources without relying on the multiple Gaussian diffusion approximation. We introduce Correlation Tensor MRI (CTI) - an approach harnessing the versatility of double diffusion encoding (DDE) and its sensitivity to displacement correlation tensors capable of explicitly decoupling isotropic and anisotropic kurtosis components from intra-compartmental kurtosis effects arising from restricted (and time-dependent) diffusion. Additionally, we show that, by subtracting these isotropic and anisotropic kurtosis components from the total diffusional kurtosis, CTI provides an index that is potentially sensitive to intra-compartmental kurtosis. The theoretical foundations of CTI, as well as the first proof-of-concept CTI experiments in ex vivo mouse brains at ultrahigh field of 16.4 T, are presented. We find that anisotropic and isotropic kurtosis can decouple microscopic anisotropy from substantial partial volume effects between tissue and free water. Our intra-compartmental kurtosis index exhibited positive values in both white and grey matter tissues. Simulations in different synthetic microenvironments show, however, that our current CTI protocol for estimating intra-compartmental kurtosis is limited by higher order terms that were not taken into account in this study. CTI measurements were then extended to in vivo settings and used to map heathy rat brains at 9.4 T. These in vivo CTI results were found to be consistent with our ex vivo findings. Although future studies are still required to assess and mitigate the higher order effects on the intra-compartmental kurtosis index, our results show that CTI's more general estimates of anisotropic and isotropic kurtosis contributions are already ripe for future in vivo studies, which can have significant impact our understanding of the mechanisms underlying diffusion metrics extracted in health and disease.

摘要

扩散峰度磁共振成像(DKI)量化了非高斯水分子扩散的程度,该技术已被证明是健康和疾病中微观结构的敏感生物标志物。然而,DKI 本身并不是针对任何微观结构特性的,因为峰度可能来自多个不同的来源。已经提出了 Q 空间轨迹编码方案,用于将源于平均扩散率方差的峰度(各向同性峰度)与由微观各向异性引起的峰度(各向异性峰度)解耦。尽管如此,这些方法假设系统由具有零腔内峰度(与受限扩散相关)的多个高斯扩散分量组成。在这里,我们开发了一种更通用的框架,用于在不依赖于多个高斯扩散逼近的情况下解析潜在的峰度源。我们引入了相关张量磁共振成像(CTI)-一种利用双扩散编码(DDE)的多功能性及其对能够明确将各向同性和各向异性峰度分量与受限(和时变)扩散引起的腔内峰度效应解耦的位移相关张量的灵敏度的方法。此外,我们表明,通过从总扩散峰度中减去这些各向同性和各向异性峰度分量,CTI 提供了一个可能对腔内峰度敏感的指标。介绍了 CTI 的理论基础,以及在 16.4T 超高场的离体小鼠脑中进行的首次 CTI 实验的初步结果。我们发现各向异性和各向同性峰度可以将微观各向异性与组织和游离水之间的大量部分容积效应解耦。我们的腔内峰度指数在白质和灰质组织中均表现出正值。然而,在不同的合成微环境中的模拟表明,我们当前用于估计腔内峰度的 CTI 方案受到在这项研究中未考虑的高阶项的限制。CTI 测量随后扩展到体内设置,并用于在 9.4T 下绘制健康大鼠的大脑。发现这些体内 CTI 结果与我们的离体结果一致。尽管仍需要进行未来的研究来评估和减轻腔内峰度指数的高阶效应,但我们的结果表明,CTI 对各向异性和各向同性峰度贡献的更一般估计已经为未来的体内研究做好了准备,这可能对我们在健康和疾病中提取扩散指标的机制的理解产生重大影响。

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