Kammen Alexandra, Law Meng, Tjan Bosco S, Toga Arthur W, Shi Yonggang
Laboratory of Neuro Imaging, USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA 90032, USA; Department of Radiology, Keck School of Medicine, University of Southern California, Los Angeles, CA 90032, USA.
Department of Radiology, Keck School of Medicine, University of Southern California, Los Angeles, CA 90032, USA.
Neuroimage. 2016 Jan 15;125:767-779. doi: 10.1016/j.neuroimage.2015.11.005. Epub 2015 Nov 6.
Diffusion MRI tractography provides a non-invasive modality to examine the human retinofugal projection, which consists of the optic nerves, optic chiasm, optic tracts, the lateral geniculate nuclei (LGN) and the optic radiations. However, the pathway has several anatomic features that make it particularly challenging to study with tractography, including its location near blood vessels and bone-air interface at the base of the cerebrum, crossing fibers at the chiasm, somewhat-tortuous course around the temporal horn via Meyer's Loop, and multiple closely neighboring fiber bundles. To date, these unique complexities of the visual pathway have impeded the development of a robust and automated reconstruction method using tractography. To overcome these challenges, we develop a novel, fully automated system to reconstruct the retinofugal visual pathway from high-resolution diffusion imaging data. Using multi-shell, high angular resolution diffusion imaging (HARDI) data, we reconstruct precise fiber orientation distributions (FODs) with high order spherical harmonics (SPHARM) to resolve fiber crossings, which allows the tractography algorithm to successfully navigate the complicated anatomy surrounding the retinofugal pathway. We also develop automated algorithms for the identification of ROIs used for fiber bundle reconstruction. In particular, we develop a novel approach to extract the LGN region of interest (ROI) based on intrinsic shape analysis of a fiber bundle computed from a seed region at the optic chiasm to a target at the primary visual cortex. By combining automatically identified ROIs and FOD-based tractography, we obtain a fully automated system to compute the main components of the retinofugal pathway, including the optic tract and the optic radiation. We apply our method to the multi-shell HARDI data of 215 subjects from the Human Connectome Project (HCP). Through comparisons with post-mortem dissection measurements, we demonstrate the retinotopic organization of the optic radiation including a successful reconstruction of Meyer's loop. Then, using the reconstructed optic radiation bundle from the HCP cohort, we construct a probabilistic atlas and demonstrate its consistency with a post-mortem atlas. Finally, we generate a shape-based representation of the optic radiation for morphometry analysis.
扩散张量磁共振成像纤维束示踪技术提供了一种非侵入性方法来研究人类视网膜神经纤维投射,该投射由视神经、视交叉、视束、外侧膝状体核(LGN)和视辐射组成。然而,该通路具有一些解剖学特征,使得使用纤维束示踪技术进行研究极具挑战性,包括其在大脑底部靠近血管和骨 - 空气界面的位置、视交叉处的交叉纤维、通过迈耶环在颞叶角周围略显曲折的路径以及多个紧密相邻的纤维束。迄今为止,视觉通路的这些独特复杂性阻碍了使用纤维束示踪技术开发强大且自动化的重建方法。为了克服这些挑战,我们开发了一种新颖的全自动系统,用于从高分辨率扩散成像数据重建视网膜神经纤维视觉通路。使用多壳、高角分辨率扩散成像(HARDI)数据,我们用高阶球谐函数(SPHARM)重建精确的纤维方向分布(FODs)以解决纤维交叉问题,这使得纤维束示踪算法能够成功地在围绕视网膜神经纤维通路的复杂解剖结构中导航。我们还开发了用于识别纤维束重建所用感兴趣区域(ROI)的自动化算法。特别是,我们基于从视交叉处的种子区域到初级视觉皮层的目标计算出的纤维束的固有形状分析,开发了一种新颖的方法来提取外侧膝状体核感兴趣区域(ROI)。通过结合自动识别的ROI和基于FOD的纤维束示踪技术,我们获得了一个全自动系统来计算视网膜神经纤维通路的主要组成部分,包括视束和视辐射。我们将我们的方法应用于人类连接组计划(HCP)中215名受试者的多壳HARDI数据。通过与尸检测量结果进行比较,我们展示了视辐射的视网膜拓扑组织,包括成功重建迈耶环。然后,使用从HCP队列重建的视辐射束,我们构建了一个概率图谱,并证明了其与尸检图谱的一致性。最后,我们生成视辐射的基于形状的表示用于形态计量分析。