Clinical feasibility of using mean apparent propagator (MAP) MRI to characterize brain tissue microstructure.
Clinical feasibility of using mean apparent propagator (MAP) MRI to characterize brain tissue microstructure.
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DOI：
10.1016/j.neuroimage.2015.11.027
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发表时间：
2016-02-15
期刊：
影响因子：
5.7
通讯作者：
Basser PJ
中科院分区：
文献类型：
--
作者：
Avram AV;Sarlls JE;Barnett AS;Özarslan E;Thomas C;Irfanoglu MO;Hutchinson E;Pierpaoli C;Basser PJ
弥散张量成像（Diffusion tensor imaging， DTI）是目前应用最广泛的非侵入性脑组织结构特征表征方法。然而，DTI固有的高斯自旋位移分布的假设削弱了其描述复杂组织微观解剖的能力。因此，微观结构参数的生物学解释，如分数各向异性或平均扩散率往往是模棱两可的。我们评估了用平均表观传播体（MAP） MRI评估脑组织微观结构的临床可行性，这是一个强大的分析框架，可以有效地测量自旋位移的概率密度函数（PDF），并量化该PDF的有用指标，指示复杂微观结构（例如，限制，多隔室）的扩散。从MAP计算的旋转不变量和标量参数显示出神经解剖脑区域的一致变化，与dti衍生的参数相比，具有不同结构和建筑特征的组织的区分能力增强。回归原点概率（RTOP）似乎比MD更好地反映了细胞性和限制，而非高斯性（NG）通过综合量化自旋位移PDF与其高斯近似之间的偏差来衡量扩散非均匀性。RTOP和NG都可以在由扩散张量方向确定的局部解剖框架中进行分解，并显示与DTI互补的附加信息。传播体各向异性（PA）在脑深部核和皮层灰质中显示出较高的组织对比度，在白质中比FA更均匀，在含有交叉纤维的区域明显下降。从MAP MRI序列系数中解析计算的传播体的方向分布允许在白质通路交叉区域分离不同的纤维群，这反过来提高了我们进行全脑纤维束造影的能力。从次采样数据集的重建表明，MAP MRI参数可以从相对较少的高b值和良好信噪比的dwi中计算，临床可实现的扫描时间少于10分钟。健康受试者神经解剖学的一致性和MAP MRI显微结构参数重测实验的可重复性进一步证实了该技术的稳健性和临床可行性。与使用传统扩散MRI技术衍生的显微结构测量相比，MAP MRI指标可能提供更敏感的临床生物标志物，具有更高的病理生理特异性。
Diffusion tensor imaging (DTI) is the most widely used method for characterizing non-invasively structural and architectural features of brain tissues. However, the assumption of a Gaussian spin displacement distribution intrinsic to DTI weakens its ability to describe intricate tissue microanatomy. Consequently, the biological interpretation of microstructural parameters, such as fractional anisotropy or mean diffusivity is often equivocal. We evaluate the clinical feasibility of assessing brain tissue microstructure with mean apparent propagator (MAP) MRI, a powerful analytical framework that efficiently measures the probability density function (PDF) of spin displacements and quantifies useful metrics of this PDF indicative of diffusion in complex microstructure (e.g., restrictions, multiple compartments). Rotation invariant and scalar parameters computed from the MAP show consistent variation across neuroanatomical brain regions and increased ability to differentiate tissues with distinct structural and architectural features compared with DTI-derived parameters. The return-to-origin probability (RTOP) appears to reflect cellularity and restrictions better than MD, while the Non-Gaussianity (NG) measures diffusion heterogeneity by comprehensively quantifying the deviation between the spin displacement PDF and its Gaussian approximation. Both RTOP and NG can be decomposed in the local anatomical frame for reference determined by the orientation of the diffusion tensor and reveal additional information complementary to DTI. The Propagator Anisotropy (PA) shows high tissue contrast even in deep brain nuclei and cortical gray matter and is more uniform in white matter than the FA, which drops significantly in regions containing crossing fibers. Orientational profiles of the propagator computed analytically from the MAP MRI series coefficients allow separation of different fiber populations in regions of crossing white matter pathways, which in turn improves our ability to perform whole brain fiber tractography. Reconstructions from subsampled data sets suggest that MAP MRI parameters can be computed from a relatively small number of DWIs acquired with high b-value and good signal-tonoise ratio in clinically achievable scan durations of less than 10 minutes. The neuroanatomical consistency across healthy subjects and reproducibility in test-retest experiments of MAP MRI microstructural parameters further substantiate the robustness and clinical feasibility of this technique. The MAP MRI metrics could potentially provide more sensitive clinical biomarkers with increased pathophysiological specificity compared to microstructural measures derived using conventional diffusion MRI techniques.