Chamberland Maxime, Scherrer Benoit, Prabhu Sanjay P, Madsen Joseph, Fortin David, Whittingstall Kevin, Descoteaux Maxime, Warfield Simon K
Centre de Recherche CHUS, University of Sherbrooke, Sherbrooke, Canada.
Sherbrooke Connectivity Imaging Lab (SCIL), Computer Science Department, Faculty of Science, University of Sherbrooke, Sherbrooke, Canada.
Hum Brain Mapp. 2017 Jan;38(1):509-527. doi: 10.1002/hbm.23399. Epub 2016 Sep 20.
Streamline tractography algorithms infer connectivity from diffusion MRI (dMRI) by following diffusion directions which are similarly aligned between neighboring voxels. However, not all white matter (WM) fascicles are organized in this manner. For example, Meyer's loop is a highly curved portion of the optic radiation (OR) that exhibits a narrow turn, kissing and crossing pathways, and changes in fascicle dispersion. From a neurosurgical perspective, damage to Meyer's loop carries a potential risk of inducing vision deficits to the patient, especially during temporal lobe resection surgery. To prevent such impairment, achieving an accurate delineation of Meyer's loop with tractography is thus of utmost importance. However, current algorithms tend to under-estimate the full extent of Meyer's loop, mainly attributed to the aforementioned rule for connectivity which requires a direction to be chosen across a field of orientations. In this article, it was demonstrated that MAGNEtic Tractography (MAGNET) can benefit Meyer's loop delineation by incorporating anatomical knowledge of the expected fiber orientation to overcome local ambiguities. A new ROI-mechanism was proposed which supplies additional information to streamline reconstruction algorithms by the means of oriented priors. Their results showed that MAGNET can accurately generate Meyer's loop in all of our 15 child subjects (8 males; mean age 10.2 years ± 3.1). It effectively improved streamline coverage when compared with deterministic tractography, and significantly reduced the distance between the anterior-most portion of Meyer's loop and the temporal pole by 16.7 mm on average, a crucial landmark used for preoperative planning of temporal lobe surgery. Hum Brain Mapp 38:509-527, 2017. © 2016 Wiley Periodicals, Inc.
流线型纤维束成像算法通过追踪相邻体素间扩散方向相似排列的情况,从扩散磁共振成像(dMRI)中推断连接性。然而,并非所有白质(WM)纤维束都是以这种方式组织的。例如,迈耶袢是视辐射(OR)的一个高度弯曲部分,呈现出狭窄的转弯、吻接和交叉路径,以及纤维束分散的变化。从神经外科的角度来看,损伤迈耶袢会给患者带来导致视力缺陷的潜在风险,尤其是在颞叶切除手术期间。为了防止这种损伤,因此用纤维束成像准确描绘迈耶袢至关重要。然而,当前的算法往往低估了迈耶袢的完整范围,这主要归因于上述连接性规则,该规则要求在一个方向场中选择一个方向。在本文中,证明了磁共振纤维束成像(MAGNET)通过纳入预期纤维方向的解剖学知识来克服局部模糊性,从而有助于迈耶袢的描绘。提出了一种新的感兴趣区域(ROI)机制,该机制通过定向先验为简化重建算法提供额外信息。他们的结果表明,MAGNET能够在我们所有15名儿童受试者(8名男性;平均年龄10.2岁±3.1)中准确生成迈耶袢。与确定性纤维束成像相比,它有效提高了流线覆盖范围,并且平均显著缩短了迈耶袢最前部与颞极之间的距离16.7毫米,颞极是颞叶手术术前规划的一个关键标志。《人类脑图谱》38:509 - 527,2017年。© 2016威利期刊公司。