Registration-free analysis of diffusion MRI tractography data across subjects through the human lifespan.
Registration-free analysis of diffusion MRI tractography data across subjects through the human lifespan.
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DOI：
10.1016/j.neuroimage.2020.116703
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发表时间：
2020-07-01
期刊：
影响因子：
5.7
通讯作者：
Yendiki A
中科院分区：
文献类型：
--
作者：
Siless V;Davidow JY;Nielsen J;Fan Q;Hedden T;Hollinshead M;Beam E;Vidal Bustamante CM;Garrad MC;Santillana R;Smith EE;Hamadeh A;Snyder J;Drews MK;Van Dijk KRA;Sheridan M;Somerville LH;Yendiki A
弥散磁共振纤维束成像产生大量的流线集，这些流线集需要聚集成具有解剖学意义的白质束。传统的聚类技术组流线型的基础上，他们在欧几里德空间的接近。我们开发了AnatomiCuts，一种基于相邻解剖结构而不是欧氏空间坐标的无监督纤维束成像流线聚类方法。在这项工作中，我们表明，在AnatomiCuts中使用的解剖相似性度量可以扩展到跨学科和跨半球找到相应的集群，而无需跨学科或跨半球注册。我们提出的方法使组明智的道聚类分析，以及半球不对称的研究。我们对MGH-Harvard-USC Lifespan Human Connectome试点项目的数据进行了评估，结果显示184名8-90岁受试者的束簇对应性得到了改善。当比较具有较大年龄差异的受试者时，我们的方法在相应聚类的重叠中显示出高达38%的改进。这里提出的技术不需要配准到模板，因此可以应用于具有大的受试者间变异性的群体，例如，因为大脑发育衰老或神经系统疾病
Diffusion MRI tractography produces massive sets of streamlines that need to be clustered into anatomically meaningful white-matter bundles. Conventional clustering techniques group streamlines based on their proximity in Euclidean space. We have developed AnatomiCuts, an unsupervised method for clustering tractography streamlines based on their neighboring anatomical structures, rather than their coordinates in Euclidean space. In this work, we show that the anatomical similarity metric used in AnatomiCuts can be extended to find corresponding clusters across subjects and across hemispheres, without inter-subject or inter-hemispheric registration. Our proposed approach enables group-wise tract cluster analysis, as well as studies of hemispheric asymmetry. We evaluate our approach on data from the pilot MGH-Harvard-USC Lifespan Human Connectome project, showing improved correspondence in tract clusters across 184 subjects aged 8–90. Our method shows up to 38% improvement in the overlap of corresponding clusters when comparing subjects with large age differences. The techniques presented here do not require registration to a template and can thus be applied to populations with large inter-subject variability, e.g., due to brain development, aging, or neurological disorders.
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影响因子：
5.7
作者：
de Groot M;Vernooij MW;Klein S;Ikram MA;Vos FM;Smith SM;Niessen WJ;Andersson JL
通讯作者：
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DOI：
10.1073/pnas.1415122111
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