Background/Objectives:Connectomics is an evolving branch of neuroscience that determines structural and functional connectivity in the brain. The objective of this prospective imaging study is to evaluate the effect of whole brain radiotherapy (WBRT) on the connectome.Methods:A combination of diffusion tensor imaging (DTI) and functional magnetic resonance imaging (fMRI) was used to study the structural and functional connectivity of the brain, and a machine learning algorithm trained to analyze subject-specific data was applied to create individualized brain maps with 15 neuronal networks for each patient. These brain maps were compared to normal brains from the human connectome project, producing an anomaly matrix. Connectome analysis and multi-dimensional neurocognitive testing on a web-based platform were performed at baseline and 3 months post-WBRT. The change in anomaly frequency was co-related with neurocognitive outcomes.Results:At baseline, connectome analysis revealed that the multiple demand network had the most anomalies (46%). Pre- and post-WBRT comparison revealed increases in proportional anomaly frequency across multiple networks. Pearson correlation showed correlation between neurocognitive domain decline and anomaly changes: learning and memory domain with subcortical network [Verbal recall (Pearson coefficient −0.94;p< 0.01), verbal revision (Pearson coefficient −0.89;p= 0.01), and verbal recognition (Pearson coefficient −0.94;p< 0.01)].Conclusions:This proof-of-concept study integrated data from DTI andfMRI in the form of connectome and revealed significant changes in brain connectivity, with WBRT that also correlated with neurocognitive outcomes. Further studies in a larger cohort are underway, and correlations with white matter changes and tumor locations/numbers will be performed.
背景/目的：连接组学是神经科学中一个不断发展的分支，主要研究大脑的结构与功能连接。本前瞻性影像研究旨在评估全脑放疗对大脑连接组的影响。 方法：研究结合弥散张量成像与功能磁共振成像技术，通过训练机器学习算法分析个体特异性数据，为每位患者构建包含15个神经网络的个性化脑图谱。这些脑图谱与人类连接组计划中的正常大脑进行对比，生成异常矩阵。在基线期及全脑放疗后3个月，通过基于网络平台的连接组分析和多维神经认知测试进行评估，并将异常频率变化与神经认知结局进行关联分析。 结果：基线期连接组分析显示，多重需求网络异常率最高（46%）。全脑放疗前后对比发现，多个网络的异常比例频率均有所增加。皮尔逊相关性分析显示神经认知领域衰退与异常变化存在相关性：学习记忆领域与皮层下网络异常变化呈负相关[言语回忆（皮尔逊系数-0.94；p<0.01）、言语修正（皮尔逊系数-0.89；p=0.01）及言语识别（皮尔逊系数-0.94；p<0.01）]。 结论：这项概念验证研究以连接组形式整合了弥散张量成像与功能磁共振成像数据，揭示了全脑放疗引起的大脑连接显著改变，且这些改变与神经认知结局具有相关性。目前正在开展更大规模队列的深入研究，并将进一步分析其与白质改变及肿瘤位置/数量的关联性。
肿瘤(癌症)患者之家