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动态功能网络连接揭示了肺癌患者化疗后脑功能改变。

Dynamic functional network connectivity reveals the brain functional alterations in lung cancer patients after chemotherapy.

作者信息

Hu Lanyue, Ding Shaohua, Zhang Yujie, You Jia, Shang Song'an, Wang Peng, Yin Xindao, Xia Wenqing, Chen Yu-Chen

机构信息

Department of Radiology, Nanjing First Hospital, Nanjing Medical University, No.68, Changle Road, Nanjing, 210006, China.

Department of Radiology, Taizhou People's Hospital, Fifth Affiliated Hospital of Nantong University, Jiangsu, Taizhou, China.

出版信息

Brain Imaging Behav. 2022 Jun;16(3):1040-1048. doi: 10.1007/s11682-021-00575-9. Epub 2021 Oct 31.

Abstract

This study aimed to investigate alterations of brain functional network connectivity (FNC) in lung cancer patients after chemotherapy and explore links between these FNC differences and cognitive impairment. Twenty-two lung cancer patients receiving chemotherapy and 26 healthy controls (HCs) underwent resting-state functional MRI (rs-fMRI) and neuropsychological testing. Group independent component analysis (GICA) was applied to rs-fMRI data to extract whole-brain resting state networks (RSNs). Static and dynamic FNC (dFNC) were constructed to reveal RSNs connectivity alterations between lung cancer patients and HCs group, and the correlations between the group differences in RSNs and cognitive performance were analyzed. Our findings revealed that chemotherapeutics can produce widespread connectivity abnormalities in RSNs, mainly focused on default mode network (DMN) and executive control network. Furthermore, the dFNC analysis help identify network configurations of each state and capture more chemotherapy-induced disorders of interactions between and within RSNs, which mainly includes sensorimotor network, attentional network and auditory network. In addition, after chemotherapy, the lung cancer patients spend shorter mean dwell time (MDT) in state 2. The decreased dFNC between DMN [independent component 5 (IC5)] and DMN (IC6) in the lung cancer patients after chemotherapy in state 4 was negatively correlated with Montreal Cognitive Assessment (MoCA) scores (r=-0.447, p=0.042). The dFNC analysis enrich our understanding of the neural mechanisms underlying the chemobrain, and suggested that the temporal dynamics of FNC could be a potential effective method to detect cognitive changes in lung cancer patients receiving chemotherapy.

摘要

本研究旨在调查肺癌患者化疗后脑功能网络连接性(FNC)的变化,并探索这些FNC差异与认知障碍之间的联系。22名接受化疗的肺癌患者和26名健康对照者(HCs)接受了静息态功能磁共振成像(rs-fMRI)和神经心理学测试。将组独立成分分析(GICA)应用于rs-fMRI数据,以提取全脑静息态网络(RSNs)。构建静态和动态FNC(dFNC)以揭示肺癌患者和HCs组之间RSNs连接性的变化,并分析RSNs组间差异与认知表现之间的相关性。我们的研究结果显示,化疗药物可在RSNs中产生广泛的连接异常,主要集中在默认模式网络(DMN)和执行控制网络。此外,dFNC分析有助于识别每个状态的网络配置,并捕捉更多化疗引起的RSNs之间及内部相互作用的紊乱,主要包括感觉运动网络、注意力网络和听觉网络。此外,化疗后,肺癌患者在状态2的平均停留时间(MDT)较短。化疗后肺癌患者在状态4时DMN[独立成分5(IC5)]与DMN(IC6)之间dFNC的降低与蒙特利尔认知评估(MoCA)评分呈负相关(r=-0.447,p=0.042)。dFNC分析丰富了我们对化疗脑潜在神经机制的理解,并表明FNC的时间动态可能是检测接受化疗的肺癌患者认知变化的一种潜在有效方法。

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