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利用高角度分辨率弥散成像轨迹追踪技术为适合临床人群的连合径路进行勾画和分割的自动化策略。

An automated strategy for the delineation and parcellation of commissural pathways suitable for clinical populations utilising high angular resolution diffusion imaging tractography.

机构信息

Centre for Magnetic Resonance, The University of Queensland, Brisbane, Australia.

出版信息

Neuroimage. 2010 Apr 15;50(3):1044-53. doi: 10.1016/j.neuroimage.2010.01.020. Epub 2010 Jan 14.

Abstract

There is a growing interest in understanding alterations to the interhemispheric transfer of information as a result of brain injury and neurological disease. To facilitate research, we have developed a fully automated method for the accurate extraction of commissural pathways (corpus callosum (CC) and anterior commissure (AC)) and functional parcellation of the CC using a high angular resolution diffusion imaging (HARDI) based probabilistic tractography approach that is applicable to clinical populations. The CC was divided into 33 functional divisions based on its connections to cortical parcellations derived from individual structural images in 8 healthy participants. Probabilistic CC population maps acquired at two different b-values (1000 s mm(-2) and 3000 s mm(-2)) are presented. Topography of the CC was consistent with histology reports. We show that HARDI data acquired at a higher b-value reveals more callosal-temporal connections than low b-value data. With respect to intra-subject precision, data acquired using a higher b-value show superior reproducibility of the delineated CC area on the midsagittal plane (MSP), as well as the total number of callosal streamlines and the number of clustered callosal streamlines. The AC was delineated in all 8 participants using high b-value HARDI tractography. Cortical projections of the AC were analysed and are in agreement with known anatomy. We conclude that, while data acquired at a lower b-value may be used, this is associated with a loss in quality, both in the delineation of commissural pathways and, potentially, the reproducibility of results over time.

摘要

人们越来越关注脑损伤和神经疾病导致的大脑两半球间信息传递变化。为了促进研究,我们开发了一种完全自动化的方法,使用基于高角度分辨率扩散成像(HARDI)的概率追踪技术,准确提取联络束(胼胝体(CC)和前连合(AC))并对 CC 进行功能分区,该方法适用于临床人群。我们根据 8 名健康参与者的个体结构图像,将 CC 分为 33 个功能分区,这些分区与皮质分区有关。呈现了在两个不同 b 值(1000 s mm(-2) 和 3000 s mm(-2))获得的概率 CC 群体图。CC 的拓扑结构与组织学报告一致。我们表明,在更高的 b 值上采集的 HARDI 数据比低 b 值数据揭示了更多的胼胝体-颞部连接。就个体内精度而言,使用更高 b 值采集的数据显示出在中矢状面(MSP)上勾勒出的 CC 区域、总胼胝体流线数量以及聚类胼胝体流线数量的可重复性更好。使用高 b 值 HARDI 追踪技术,在所有 8 名参与者中都描绘了 AC。分析了 AC 的皮质投射,并与已知解剖结构一致。我们得出结论,虽然可以使用在较低 b 值采集的数据,但这与在描绘联络束以及潜在地随着时间推移再现结果的质量方面存在损失有关。

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