PDF(Pubmed)
Abstract：
Traumatic brain injury (TBI), a significant global health issue, is affecting ∼69 million annually. To better understand TBI\'s impact on brain function and assess the efficacy of treatments, this study uses a novel temporal-spatial cross-group approach with a porcine model, integrating resting-state functional magnetic resonance imaging (rs-fMRI) for temporal and arterial spin labeling for spatial information. Our research used 18 four-week-old pigs divided into three groups: TBI treated with saline (SLN, n = 6), TBI treated with fecal microbial transplant (FMT, n = 6), and a sham group (sham, n = 6) with only craniectomy surgery as the baseline. By applying machine learning techniques-specifically, independent component analysis and sparse dictionary learning-across seven identified resting-state networks, we assessed the temporal and spatial correlations indicative of treatment efficacy. Both temporal and spatial analyses revealed a consistent increase of correlation between the FMT and sham groups in the executive control and salience networks. Our results are further evidenced by a simulation study designed to mimic the progression of TBI severity through the introduction of variable Gaussian noise to an independent rs-fMRI dataset. The results demonstrate a decreasing temporal correlation between the sham and TBI groups with increasing injury severity, consistent with the experimental results. This study underscores the effectiveness of the methodology in evaluating post-TBI treatments such as the FMT. By presenting comprehensive experimental and simulated data, our research contributes significantly to the field and opens new paths for future investigations into TBI treatment evaluations.
摘要：
创伤性脑损伤（TBI），一个重大的全球健康问题，每年影响6900万。为了更好地了解TBI对脑功能的影响并评估治疗的疗效，这项研究使用了一种新的时空交叉群方法与猪模型，整合静息状态功能磁共振成像（rs-fMRI），以时空和动脉自旋标记为空间信息。我们的研究使用了18只四周龄的猪，分为三组：用盐水处理的TBI（SLN，n=6),用粪便微生物移植治疗的TBI(FMT，n=6),和一个假小组(假，n=6），仅以开颅手术为基线。通过具体应用机器学习技术，独立分量分析和稀疏字典学习-跨七个已识别的静息状态网络，我们评估了指示治疗疗效的时间和空间相关性.时间和空间分析均显示，在执行控制和显著性网络中，FMT和假手术组之间的相关性持续增加。通过将可变高斯噪声引入独立的rs-fMRI数据集，旨在模拟TBI严重程度的进展的模拟研究进一步证明了我们的结果。结果表明，假手术组和TBI组之间的时间相关性随着损伤严重程度的增加而降低，与实验结果一致。这项研究强调了该方法在评估TBI后治疗如FMT中的有效性。通过提供全面的实验和模拟数据，我们的研究为该领域做出了重要贡献,并为未来对TBI治疗评价的研究开辟了新的途径.
