Department of Radiology and Biomedical Research Imaging Center (BRIC) University of North Carolina at Chapel Hill, NC, U.S.A.
Department of Radiology and Biomedical Research Imaging Center (BRIC) University of North Carolina at Chapel Hill, NC, U.S.A.
Med Image Anal. 2020 Jan;59:101543. doi: 10.1016/j.media.2019.101543. Epub 2019 Sep 13.
Diffusion tractography in brain connectomics often involves tracing axonal trajectories across gray-white matter boundaries in gyral blades of complex cortical convolutions. To date, gyral bias is observed in most tractography algorithms with streamlines predominantly terminating at gyral crowns instead of sulcal banks. This work demonstrates that asymmetric fiber orientation distribution functions (AFODFs), computed via a multi-tissue global estimation framework, can mitigate the effects of gyral bias, enabling fiber streamlines at gyral blades to make sharper turns into the cortical gray matter. We use ex-vivo data of an adult rhesus macaque and in-vivo data from the Human Connectome Project (HCP) to show that the fiber streamlines given by AFODFs bend more naturally into the cortex than the conventional symmetric FODFs in typical gyral blades. We demonstrate that AFODF tractography improves cortico-cortical connectivity and provides highly consistent outcomes between two different field strengths (3T and 7T).
脑连接组学中的弥散张量成像通常涉及在复杂皮质脑回的脑回叶的灰白质边界处追踪轴突轨迹。迄今为止,大多数追踪算法都存在脑回偏向性,即流线主要终止于脑回顶部,而不是脑沟底部。本研究表明,通过多组织全局估计框架计算的不对称纤维方向分布函数(AFODFs)可以减轻脑回偏向性的影响,使脑回叶上的纤维流线能够更自然地向皮质灰质急转弯。我们使用成年恒河猴的离体数据和人类连接组计划(HCP)的体内数据,表明与传统的对称 FODFs 相比,AFODFs 给出的纤维流线在典型脑回叶中更自然地弯曲进入皮质。我们证明了 AFODF 追踪可以改善皮质间连接,并在两种不同场强(3T 和 7T)之间提供高度一致的结果。