中国神经再生研究(英文版)

中国神经再生研究(英文版) ›› 2021, Vol. 16 ›› Issue (2): 338-344.doi: 10.4103/1673-5374.290915

• 原著:脑损伤修复保护与再生 • 上一篇    下一篇

创伤性脑损伤仔猪模型中预测性MRI生物标志物的鉴定

  

  • 出版日期:2021-02-15 发布日期:2020-12-04
  • 基金资助:

    佐治亚大学FDW研究副校长办公室提供了财政支持

Identification of predictive MRI and functional biomarkers in a pediatric piglet traumatic brain injury model 

Hongzhi Wang1, Emily W. Baker2, 3, Abhyuday Mandal1, Ramana M. Pidaparti4, Franklin D. West2, 3, *, Holly A. Kinder2, 3, *   

  1. 1 Department of Statistics, University of Georgia, Athens, GA, USA;  2 Regenerative Bioscience Center, University of Georgia, Athens, GA, USA;  3 Department of Animal and Dairy Science, University of Georgia, Athens, GA, USA;   4 College of Engineering, University of Georgia, Athens, GA, USA 
  • Online:2021-02-15 Published:2020-12-04
  • Contact: Holly A. Kinder, PhD, HollyK17@uga.edu; Franklin D. West, PhD, westf@uga.edu.
  • Supported by:
    Financial support was provided by the University of Georgia Office of the Vice President for Research to FDW.

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摘要：

幼年颅脑外伤会导致长期功能障碍的发生，而最能反映损伤严重程度和功能预后的特异性磁共振成像（MRI）生物标志物仍未确定。实验旨在利用先进的统计学方法来识别临床相关的MRI生物标记物，并预测功能结局。实验建立控制性脑皮质撞击创伤性脑损伤仔猪模型，并在创伤性脑损伤后24h和12周进行了T1加权，T2加权，T2加权液体衰减反转恢复，弥散加权成像和弥散张量成像。创伤性脑损伤后24h和12周使用自动步态垫评估仔猪时空步态参数的变化。结果发现：（1）使用T2W成像获得的病变大小和中线移位的线性组合解释了创伤性脑损伤后24h和12周的多数数据变异性；（2）速度、节奏和步幅长度的线性组合可以解释创伤性脑损伤后24h和12周的多数步态数据变异性；（3）线性回归分析结果显示，MRI检测的病变大小和中线移位均与创伤性脑损伤仔猪步幅和步长的减少显著相关。这项研究结果为确定可预测创伤性脑损伤儿童运动功能结局的MRI生物标志物迈出了重要一步。该研究于2015年12月22日得到乔治亚大学动物保护与使用委员会的批准（AUP：A2015 11-001）批准。

https://orcid.org/0000-0001-8310-7265 (Holly A. Kinder); 

https://orcid.org/0000-0002-0504-7997 (Franklin D. West)

关键词: 创伤性脑损伤, 控制性脑皮质撞击, 步态分析, 线性回归, 磁共振成像, 运动功能, 仔猪模型, 主成分分析

Abstract: Traumatic brain injury (TBI) at a young age can lead to the development of long-term functional impairments. Severity of injury is well demonstrated to have a strong influence on the extent of functional impairments; however, identification of specific magnetic resonance imaging (MRI) biomarkers that are most reflective of injury severity and functional prognosis remain elusive. Therefore, the objective of this study was to utilize advanced statistical approaches to identify clinically relevant MRI biomarkers and predict functional outcomes using MRI metrics in a translational large animal piglet TBI model. TBI was induced via controlled cortical impact and multiparametric MRI was performed at 24 hours and 12 weeks post-TBI using T1-weighted, T2-weighted, T2-weighted fluid attenuated inversion recovery, diffusion-weighted imaging, and diffusion tensor imaging. Changes in spatiotemporal gait parameters were also assessed using an automated gait mat at 24 hours and 12 weeks post-TBI. Principal component analysis was performed to determine the MRI metrics and spatiotemporal gait parameters that explain the largest sources of variation within the datasets. We found that linear combinations of lesion size and midline shift acquired using T2-weighted imaging explained most of the variability of the data at both 24 hours and 12 weeks post-TBI. In addition, linear combinations of velocity, cadence, and stride length were found to explain most of the gait data variability at 24 hours and 12 weeks post-TBI. Linear regression analysis was performed to determine if MRI metrics are predictive of changes in gait. We found that both lesion size and midline shift are significantly correlated with decreases in stride and step length. These results from this study provide an important first step at identifying relevant MRI and functional biomarkers that are predictive of functional outcomes in a clinically relevant piglet TBI model. This study was approved by the University of Georgia Institutional Animal Care and Use Committee (AUP: A2015 11-001) on December 22, 2015. 

Key words: controlled cortical impact, gait analysis, linear regression, magnetic resonance imaging, motor function, pediatric pig model, principal component analysis, traumatic brain injury