Resolving bundle-specific intra-axonal T(2) values within a voxel using diffusion-relaxation tract-based estimation.

Resolving bundle-specific intra-axonal T(2) values within a voxel using diffusion-relaxation tract-based estimation.
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DOI:
10.1016/j.neuroimage.2020.117617
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发表时间:
2021-02-15
期刊:
影响因子:
5.7
通讯作者:
Jones DK
Jones DK
中科院分区:
医学1区
文献类型:
--
作者:
Barakovic M;Tax CMW;Rudrapatna U;Chamberland M;Rafael-Patino J;Granziera C;Thiran JP;Daducci A;Canales-Rodríguez EJ;Jones DK

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在人脑 MRI 的典型空间分辨率下,大约 60-90% 的体素包含多个纤维群。因此,量化体素内不同纤维群的微观结构特性具有挑战性,但也是必要的。虽然扩散和 T1 弛豫特性取得了进展,但如何解决体素内 T2 异质性仍然是一个悬而未决的问题。这里提出了一个名为 COMMIT-T2 的新颖框架,该框架使用基于纤维束成像的空间正则化和扩散弛豫数据来估计体素内的多个轴突内 T2 值。与先前提出的基于体素的 T2 估计方法不同,该方法(当应用于白质时)隐式地假设体素中只有一个纤维束或体素中的所有纤维束具有相同的 T2,COMMIT-T2 可以为穿过体素的每个独特纤维群恢复特定的 T2 值。在这种方法中,恢复的唯一 T2 值的数量不是由先验设置的模型参数的数量决定的,而是由穿过体素的纤维束成像重建流线的数量决定的。在计算机和体内提供了概念验证,包括证明即使在胼胝体、弓状束和皮质脊髓束的三向交叉中也可以恢复不同的束特异性 T2 谱。我们证明了 COMMIT-T2 与利用扩散绘制轴突内 T2 的体素方法相比具有良好的性能,包括方向平均方法和 AMICO-T2,AMICO-T2 是先前提出的通过凸优化加速微结构成像 (AMICO) 框架的新扩展。
At the typical spatial resolution of MRI in the human brain, approximately 60–90% of voxels contain multiple fiber populations. Quantifying microstructural properties of distinct fiber populations within a voxel is therefore challenging but necessary. While progress has been made for diffusion and T1-relaxation properties, how to resolve intra-voxel T2 heterogeneity remains an open question. Here a novel framework, named COMMIT-T2, is proposed that uses tractography-based spatial regularization with diffusion-relaxometry data to estimate multiple intra-axonal T2 values within a voxel. Unlike previously-proposed voxel-based T2 estimation methods, which (when applied in white matter) implicitly assume just one fiber bundle in the voxel or the same T2 for all bundles in the voxel, COMMIT-T2 can recover specific T2 values for each unique fiber population passing through the voxel. In this approach, the number of recovered unique T2 values is not determined by a number of model parameters set a priori, but rather by the number of tractography-reconstructed streamlines passing through the voxel. Proof-of-concept is provided in silico and in vivo, including a demonstration that distinct tract-specific T2 profiles can be recovered even in the three-way crossing of the corpus callosum, arcuate fasciculus, and corticospinal tract. We demonstrate the favourable performance of COMMIT-T2 compared to that of voxelwise approaches for mapping intra-axonal T2 exploiting diffusion, including a direction-averaged method and AMICO-T2, a new extension to the previously-proposed Accelerated Microstructure Imaging via Convex Optimization (AMICO) framework.
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