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球谐平均单扩散编码 MRI 中微观各向异性的估计误差。

Microscopic anisotropy misestimation in spherical-mean single diffusion encoding MRI.

机构信息

Champalimaud Neuroscience Programme, Champalimaud Centre for the Unknown, Lisbon, Portugal.

Center of Functionally Integrative Neuroscience (CFIN) and MINDLab, Clinical Institute, Aarhus University, Aarhus, Denmark.

出版信息

Magn Reson Med. 2019 May;81(5):3245-3261. doi: 10.1002/mrm.27606. Epub 2019 Jan 16.

Abstract

PURPOSE

Microscopic fractional anisotropy (µFA) can disentangle microstructural information from orientation dispersion. While double diffusion encoding (DDE) MRI methods are widely used to extract accurate µFA, it has only recently been proposed that powder-averaged single diffusion encoding (SDE) signals, when coupled with the diffusion standard model (SM) and a set of constraints, could be used for µFA estimation. This study aims to evaluate µFA as derived from the spherical mean technique (SMT) set of constraints, as well as more generally for powder-averaged SM signals.

METHODS

SDE experiments were performed at 16.4 T on an ex vivo mouse brain (Δ/δ = 12/1.5 ms). The µFA maps obtained from powder-averaged SDE signals were then compared to maps obtained from DDE-MRI experiments (Δ/τ/δ = 12/12/1.5 ms), which allow a model-free estimation of µFA. Theory and simulations that consider different types of heterogeneity are presented for corroborating the experimental findings.

RESULTS

µFA, as well as other estimates derived from powder-averaged SDE signals produced large deviations from the ground truth in both gray and white matter. Simulations revealed that these misestimations are likely a consequence of factors not considered by the underlying microstructural models (such as intercomponent and intracompartmental kurtosis).

CONCLUSION

Powder-averaged SMT and (2-component) SM are unable to accurately report µFA and other microstructural parameters in ex vivo tissues. Improper model assumptions and constraints can significantly compromise parameter specificity. Further developments and validations are required prior to implementation of these models in clinical or preclinical research.

摘要

目的

微观分数各向异性(µFA)可以从方向分散中分离出微观结构信息。虽然双扩散编码(DDE)MRI 方法广泛用于提取准确的µFA,但最近才有人提出,当粉末平均单扩散编码(SDE)信号与扩散标准模型(SM)和一组约束条件结合使用时,也可以用于µFA 估计。本研究旨在评估基于球平均技术(SMT)约束条件的µFA,以及更普遍地评估粉末平均 SM 信号的µFA。

方法

在 16.4T 的离体鼠脑上进行 SDE 实验(Δ/δ = 12/1.5ms)。然后,将从粉末平均 SDE 信号获得的µFA 图与从 DDE-MRI 实验(Δ/τ/δ = 12/12/1.5ms)获得的µFA 图进行比较,DDE-MRI 实验可以进行无模型µFA 估计。提出了考虑不同类型异质性的理论和模拟,以验证实验结果。

结果

µFA 以及从粉末平均 SDE 信号得出的其他估计值,在灰质和白质中均与真实值存在较大偏差。模拟表明,这些估计错误很可能是微观结构模型未考虑的因素(如组件间和组件内的峰度)造成的。

结论

粉末平均 SMT 和(2 分量)SM 无法准确报告离体组织中的µFA 和其他微观结构参数。不合适的模型假设和约束条件会显著影响参数的特异性。在将这些模型应用于临床或临床前研究之前,需要进一步开发和验证。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/def2/6519215/789a2a81200e/MRM-81-3245-g001.jpg

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