Improved tractography using asymmetric fibre orientation distributions.
Improved tractography using asymmetric fibre orientation distributions.
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DOI：
10.1016/j.neuroimage.2017.06.050
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发表时间：
2017-09
期刊：
影响因子：
5.7
通讯作者：
Sotiropoulos SN
中科院分区：
文献类型：
--
作者：
Bastiani M;Cottaar M;Dikranian K;Ghosh A;Zhang H;Alexander DC;Behrens TE;Jbabdi S;Sotiropoulos SN
扩散MRI使我们能够通过将水扩散映射到白色物质微观结构来推断大脑的结构组织。然而，这样的映射通常是不明确的;例如，扩散测量是反足对称的（沿沿着x和-x的扩散是相等的），而体素内的纤维取向的分布通常是不对称的。因此，不同的子体素模式，如交叉，扇形或急剧弯曲，不能通过拟合逐体素模型的信号来区分。然而，一旦考虑到来自相邻体素的空间信息，就可以潜在地区分非对称纤维图案。我们提出了一种邻域约束的球面反卷积方法，能够推断非对称纤维取向分布（A-FODS）。重要的是，我们进一步设计和实现了一个纤维束成像算法，利用估计的A-fod，因为常用的流线纤维束成像范式不能直接利用新的信息。我们使用超高分辨率的组织学数据来评估性能，在这些数据中，我们可以将真实的取向分布与从下采样数据中估计的子体素纤维模式进行比较。最后，我们探讨的好处A-fods为基础的纤维束成像使用在体内的数据，通过评估协议的纤维束成像预测与连接估计使用不同的体内模式。所提出的方法可以可靠地估计复杂的纤维模式，如急剧弯曲和扇形，体素方式的方法不能估计。此外，基于组织学的和体内的结果表明，新的框架允许更准确的纤维束成像和量化（对称和不对称）纤维复杂性的地图重建。非对称fod估计和纤维束成像的综合框架。扩展经典CSD方法适用于单壳和多壳数据。使用来自组织学的解剖学相关纤维模式进行验证。正确重建子体素扇形极性和急弯。
Diffusion MRI allows us to make inferences on the structural organisation of the brain by mapping water diffusion to white matter microstructure. However, such a mapping is generally ill-defined; for instance, diffusion measurements are antipodally symmetric (diffusion along x and –x are equal), whereas the distribution of fibre orientations within a voxel is generally not symmetric. Therefore, different sub-voxel patterns such as crossing, fanning, or sharp bending, cannot be distinguished by fitting a voxel-wise model to the signal. However, asymmetric fibre patterns can potentially be distinguished once spatial information from neighbouring voxels is taken into account. We propose a neighbourhood-constrained spherical deconvolution approach that is capable of inferring asymmetric fibre orientation distributions (A-fods). Importantly, we further design and implement a tractography algorithm that utilises the estimated A-fods, since the commonly used streamline tractography paradigm cannot directly take advantage of the new information. We assess performance using ultra-high resolution histology data where we can compare true orientation distributions against sub-voxel fibre patterns estimated from down-sampled data. Finally, we explore the benefits of A-fods-based tractography using in vivo data by evaluating agreement of tractography predictions with connectivity estimates made using different in-vivo modalities. The proposed approach can reliably estimate complex fibre patterns such as sharp bending and fanning, which voxel-wise approaches cannot estimate. Moreover, histology-based and in-vivo results show that the new framework allows more accurate tractography and reconstruction of maps quantifying (symmetric and asymmetric) fibre complexity. A new comprehensive framework for both asymmetric fod estimation and tractography. Extension of classical CSD approaches applicable to single and multi-shell data. Validation using anatomically relevant fibre patterns derived from histology. Correct reconstruction of sub-voxel fanning polarities and sharp bends.
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