多模式登记提高儿童创伤性脑损伤的群体歧视。

Emily L Dennis, Faisal Rashid, Julio Villalon-Reina, Gautam Prasad, Joshua Faskowitz, Talin Babikian, Richard Mink, Christopher Babbitt, Jeffrey Johnson, Christopher C Giza, Robert F Asarnow, Paul M Thompson
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引用次数: 0

摘要

创伤性脑损伤(TBI)可以破坏大脑白质(WM)的完整性,导致可能持续数年的功能和认知障碍。患者组内存在相当大的异质性,这使组分析变得复杂。在这里,我们提出了改进的通道识别工作流程,自动多图谱通道提取(自动化),评估改进注册的效果。与标准工作流程相比,使用特定于研究的模板提高了分组分类的准确性。加入多模态配准,包括来自扩散加权成像(DWI)、t1加权成像和流体衰减反演恢复(FLAIR)的信息,进一步提高了分类精度。我们还研究了特定束是否比其他束对群体分类贡献更大。胼胝体的部分贡献最大,双侧束之间存在意想不到的不对称。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Multi-modal Registration Improves Group Discrimination in Pediatric Traumatic Brain Injury.

Multi-modal Registration Improves Group Discrimination in Pediatric Traumatic Brain Injury.

Traumatic brain injury (TBI) can disrupt the white matter (WM) integrity in the brain, leading to functional and cognitive disruptions that may persist for years. There is considerable heterogeneity within the patient group, which complicates group analyses. Here we present improvements to a tract identification workflow, automated multi-atlas tract extraction (autoMATE), evaluating the effects of improved registration. Use of study-specific template improved group classification accuracy over the standard workflow. The addition of a multi-modal registration that includes information from diffusion weighted imaging (DWI), T1-weighted, and Fluid-Attenuated Inversion Recovery (FLAIR) further improved classification accuracy. We also examined whether particular tracts contribute more to group classification than others. Parts of the corpus callosum contributed most, and there were unexpected asymmetries between bilateral tracts.

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