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使用扩散张量成像在胎儿队列中进行特定脑区组分析。

Tract-Specific Group Analysis in Fetal Cohorts Using Diffusion Tensor Imaging.

作者信息

Khan Shadab, Rollins Caitlin K, Ortinau Cynthia M, Afacan Onur, Warfield Simon K, Gholipour Ali

机构信息

Boston Children's Hospital and Harvard Medical School, 360 Longwood Avenue, Boston, MA, USA.

Washington University School of Medicine, St. Louis, MO, USA.

出版信息

Med Image Comput Comput Assist Interv. 2018 Sep;11072:28-35. doi: 10.1007/978-3-030-00931-1_4. Epub 2018 Sep 13.

Abstract

Diffusion tensor imaging (DTI) based group analysis has helped uncover the impact of white matter injuries in a wide range of studies involving subjects from preterm neonates to adults. The application of these methods to fetal cohorts, however, has been hampered by the challenging nature of fetal DTI caused by unconstrained fetal motion, limited scan times, and limited signal-to-noise ratio. We present a framework that addresses these issues to systematically evaluate group differences in fetal cohorts. A motion-robust DTI computation approach with a new unbiased DTI template construction method is unified with kernel-regression in age and tensor-specific registration to normalize DTI volumes in an unbiased space. A robust statistical approach is used to map region-specific group differences to the medial representation of the tracts of interest. The proposed approach was applied and showed, for the first time, differences in local white matter fractional anisotropy based on DTI of fetuses with congenital heart disease and age-matched healthy controls. This paper suggests the need for fetal-specific pipelines to be used for DTI-based group analysis involving fetal cohorts.

摘要

基于扩散张量成像(DTI)的组分析在涉及从早产新生儿到成人等广泛研究对象的众多研究中,有助于揭示白质损伤的影响。然而,由于胎儿不受约束的运动、有限的扫描时间和有限的信噪比所导致的胎儿DTI的挑战性,这些方法在胎儿队列中的应用受到了阻碍。我们提出了一个框架来解决这些问题,以便系统地评估胎儿队列中的组间差异。一种具有新的无偏DTI模板构建方法的运动稳健DTI计算方法,与年龄和张量特定配准中的核回归相结合,以在无偏空间中对DTI体积进行归一化。一种稳健的统计方法用于将特定区域的组间差异映射到感兴趣束的内侧表示。所提出的方法得到了应用,并首次显示了基于先天性心脏病胎儿和年龄匹配的健康对照胎儿的DTI的局部白质分数各向异性差异。本文表明,在涉及胎儿队列的基于DTI的组分析中,需要使用针对胎儿的流程。

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