基于磁共振成像的无先兆偏头痛患者大脑静息状态异常模式研究
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摘要
偏头痛是临床上较为常见的一种原发性头痛类型。当前，随着社会的发展、生活节奏的加快，偏头痛的患病率呈现日益上升的趋势，给病患带来极大的身心痛苦，并给社会公共卫生服务系统造成沉重负担。然而，尽管偏头痛已成为国际上公认的热点研究问题之一，其病因及发病机理尚未完全明确。如何更好地认识了解偏头痛已成为制约其治疗及预防的重要因素。随着影像学技术手段的发展应用，人们对于偏头痛的认识取得了许多突破性进展，发现偏头痛患者大脑中参与痛觉信息加工的区域存在结构和功能异常。现有基于功能核磁共振的偏头痛影像学研究大多采用的是基于任务设计的研究方法，通过比较偏头痛患者和正常人某些脑区在任务中表现出来的不同激活水平揭示偏头痛患者的异常脑区，却很少有人关注偏头痛患者大脑静息状态模式的异常。
本文的主要工作和创新点如下：
首先，虽然有影像学研究证实偏头痛患者静息状态大脑存在局部功能异常和全脑功能连接异常，但目前还没有人将这两者结合起来分析。本研究首先采用低频振荡振幅算法（amplitude of low frequency fluctuation,ALFF）检测偏头痛患者出现功能异常的脑区，然后借助种子点相关方法考察上述脑区在静息状态下与全脑的功能连接异常；与此同时，进一步考察了局部功能异常和网络连接异常与偏头痛病程之间的相关关系。与正常对照组相比：偏头痛患者左侧前喙扣带回皮质（rostral anterior cingulate cortex, rACC）、双侧前额叶皮质（prefrontal cortex, PFC）的活动强度降低，而右侧丘脑（thalamus, TH）的活动强度增高；且左侧前喙扣带回皮质功能异常与偏头痛病程呈现显著的负相关关系。静息状态下出现异常的脑区与全脑的功能连接模式亦出现异常，主要表现为功能连接强度的增加。该研究从局部和整体两个角度考察偏头痛患者大脑静息状态的异常模式，可以帮助我们更好地理解偏头痛对大脑造成的影响。
其次，采用基于数据驱动的独立成分分析方法（independent component analysis,ICA）检测偏头痛患者静息状态固有功能网络连接模式异常。静息状态下，大脑的自发神经活动是由多个具有特定功能的神经网络协调耦合形成，这些网络称为静息状态的固有网络。独立成分分析方法不需要先验模型，只依赖于数据本身，是一种有效提取静息状态功能网络的研究手段。本研究将独立成分分析方法应用于比较偏头痛患者和正常被试的三个静息状态网络连接差异，发现与正常被试相比：无先兆偏头痛患者的执行网络（central executive network, CEN）和凸显网络（salience network, SN）的内部功能连接强度出现异常，表现为执行网络额下回皮质（inferior frontal gyurs, IFG）连接强度增加、凸显网络右侧辅助运动区（rightsupplementary motor area, rSMA）连接强度降低；网络之间的连接模式亦发生改变，表现为默认网络（default mode network, DMN）及右侧执行网络与凸显网络内部右侧前脑岛（right anterior insula, rAI）区域连接强度的增加，进一步的相关分析表明网络间连接强度的增加与偏头痛病程之间存在显著正相关关系。该研究考察了病理条件下无先兆偏头痛患者固有功能网络协同加工模式异常，这些结果可能成为该病临床前期诊断的重要生物学指标。
再次，采用因果分析方法考察静息状态无先兆偏头痛患者大脑核团间有效连接模式。以往大量神经影像学研究表明，大脑复杂活动的完成需要中枢神经多个核团之间协同加工，以脑网络的组织模式进行运作，内外信息的交换主要通过大脑网络的动态交互作用得以实现。本研究采用多变量Granger因果模型，对无先兆偏头痛患者的网络内部核团之间及脑网络之间的信息交互模式进行了分析。发现静息状态下无先兆偏头痛患者和正常被试的右侧额叶脑岛区域（right fronto-insulacortex, rFIC）对默认网络及执行网络起着支配、调控的作用。与正常被试相比，无先兆偏头痛组由凸显网络流向执行网络的因果连接降低，可能为偏头痛伴随的认知、执行能力下降提供神经生理解释。该研究构建了无先兆偏头痛静息状态因果传导通路模型，可以帮助我们加深对无先兆偏头痛神经机制的理解。
最后，探讨了针刺治疗偏头痛的有效性。偏头痛的发病机制比较复杂，临床对该病的治疗也有多种方法。虽然西药对于缓解偏头痛的急性发作具有较好疗效，但存在着一定的毒副作用。中医中药尤其是针刺疗法在预防、治疗偏头痛方面，具有效果显著，毒副作用小，少复发等优点，其疗效得到肯定，在偏头痛的临床应用也较为广泛。功能核磁共振成像（functional magnetic resonance imaging, fMRI）作为一种非侵入、可实时观测大脑功能活动的技术，为探究针刺效应神经调控途径及作用疗效评价提供了全新的研究途径。本部分研究内容采用基于数据驱动的多体素模式分析方法，用以探究大脑对针刺信号的处理与加工。研究结果揭示了针刺不同穴位引起的神经响应大脑空间分布模式显著不同。该研究不仅有助于进一步挖掘穴位相对功能特异性的神经表象，而且有助于为针刺治疗偏头痛的有效性提供理论依据。
总体来说，本文考察了无先兆偏头痛患者静息状态脑功能活动，着重探讨了静息状态下的功能异常，固有功能网络连接模式的改变，网络核团间信息交互模式，最后探讨了针刺治疗偏头痛的可行性。本文的主要发现可以提高我们对偏头痛的认识，为偏头痛的临床诊断和治疗提供帮助。
Migraine is a common, chronic disorder typically characterized by recurrentattacks of disabling headache. Given the heavy burden that migraine disability places onthe individual and society, it is imperative to develop a better understanding of migrainepathophysiology. Neuroimaging has helped to increase our knowledge about neuralmechanisms underlying migraine. Converging evidences of structural and functionalcerebral abnormalities in patients with migraine have been accumulated. All of thesefindings demonstrated that migraine is associated with altered central processing of painstimulus, and recurrent migraine attacks may result in selective damage of brain areasinvolved in pain processing. Despite such progress, migraine remains underdiagnosedand the available therapies underused. By focusing on the neural responses under taskconditions, resting-state analysis has been utilized to investigate the integration level ofneural systems when no explicit task is engaged. Until recently, few studies haveevaluated the abnormalities of the resting state in subjects with migraine.
The details of researches and the main innovations were listed as follows:
Firstly, although previous resting-state studies have reported abnormal functionalcerebral changes in patients with migraine without aura (MwoA), few have focused onthe alterations of regional spontaneous neuronal activity and the corresponding braincircuits’ changes collectively. In the present study, we first investigated alterations ofregional spontaneous neuronal activity during the resting-state in MwoA patients byapplying the amplitude of low-frequency fluctuation (ALFF) approach. Then weextracted the regions with significant ALFF differences between MwoA patients andhealthy controls (HC) as regions of interest (ROIs) for resting-state functionalconnectivity (FC) analysis, which was used to assess the corresponding brain circuits’changes in MwoA. We found that MwoA patients have altered resting-state spontaneousneuronal activity in pain-processing areas, including the left rostral anterior cingulatecortex (rACC), bilateral prefrontal cortex (PFC), and right thalamus (TH), as well asaltered FCs associated with these areas. ROI-based FC analysis also revealed increasedFCs associated with these areas. In addition, the ALFF values of the left rACC werecorrelated with duration of disease in MwoA. Our findings may lead to a betterunderstanding of intrinsic functional architecture of the baseline brain activity in MwoA,providing both regional and the corresponding brain circuits’ spontaneous neuronalactivity properties.
Secondly, numerous neuroimaging studies have defined low-frequency, spatially consistent intrinsic connectivity networks (ICN) in resting-state functional magneticresonance imaging (fMRI) data which reflect functional interactions among distinctbrain areas, in the current study, we applied independent component analysis (ICA) toidentify the group differences of three important networks, i.e., the default modenetwork (DMN), bilateral central executive network (CEN) and salience network (SN)between the MwoA patients and HC. One of the key features of ICA is its ability toperform a spatial-temporal decomposition of the signal without any a priori anatomical(spatial) or neural (temporal) information. Compared with the HC, MwoA patientsshowed greater intra-network connectivity within the right middle frontal gyrus (rMFG)for the right CEN (rCEN) and left inferior frontal gyrus (lIFG) for the left CEN (lCEN),and decreased intra-network connectivity within the right supplementary motor area(rSMA) for the SN. Moreover, MwoA patients demonstrated greater intrinsic DMN andrCEN connectivity to brain regions outside of the classical boundaries of these networks,namely the right anterior insula (rAI). Greater connectivity between both the DMN andrCEN and the insula correlated with duration of migraine. Our findings may haveimplications for understanding brain mechanisms of MwoA, potentially pointingtowards “markers” for disease progression. More broadly, these findings haveimplications for how such complex interplay amongst multiple brain networks can beinfluenced by frequent ongoing migraine attacks.
Thirdly, we applied multivariate Granger causality analysis (mGCA) to directlyassess the causal interactions of specific nodes within and among the intrinsic networks.One distinguishing feature of the human brain is the amount of cognitive controlavailable for selecting, switching, and attending to salient events in the environments.Recent researches have suggested that the human brain is intrinsically organized intodistinct functional networks that support these processes. We used mGCA to examinethe interaction between the DMN, CEN, and SN. Our findings emphaszied a key rolefor the rFIC in the hierarchical initiation of control signals, specifically with respect toactivation and deactivation in the CEN and DMN, and the dynamics of switchingbetween these two networks. Compared with the HC, the SN did have a weaker causalinfluence on the CEN in MwoA patients. This might be related to cognitive impairmentin migraine patients.
Finally, we discussed potential acupuncture effectiveness for treatment of migraine.The pathogenesis of migraine is complex, and there are various clinical treatments ofthe disease. In terms of acute treatment, migraine can be managed effectively withwestern medicine. However, the western medicine oftern have side effects that limit their utility. The Traditional Chinese Medicine (TCM), especially acupuncture therapy,has proven to be effective in treatment of migraine; and it has been widely used in theclinical treatment of the disease. The fMRI technique, with its non-invasive and higherresolution characterstics, has been widely applied in the detection of the brainactivations evoked by acupunture stimuli. In the current study, we introduced adata-driven based multivariate approach namely support vector machine (SVM) toexplore the spatial neural response patterns evoked by acupuncture at two differentacupoints. The results showed that acupuncture at the acupoints can evoke distinctneural response patterns. Our findings may suggest potentially selective efficacy-relatedneural actions in response to acupuncture at different acupoints, which might provide atheoretical basis for clinical application of acupuncture in treatment of migraine.
In summary, these resting-state functional abnormalities in MwoA patientsprovided additional evidence for abnormal brain function in MwoA patients. Thesefindings may be beneficial for understanding migraine, as well as providing potentialdiagnostic information and treatment strategies.
本文的主要工作和创新点如下：
首先，虽然有影像学研究证实偏头痛患者静息状态大脑存在局部功能异常和全脑功能连接异常，但目前还没有人将这两者结合起来分析。本研究首先采用低频振荡振幅算法（amplitude of low frequency fluctuation,ALFF）检测偏头痛患者出现功能异常的脑区，然后借助种子点相关方法考察上述脑区在静息状态下与全脑的功能连接异常；与此同时，进一步考察了局部功能异常和网络连接异常与偏头痛病程之间的相关关系。与正常对照组相比：偏头痛患者左侧前喙扣带回皮质（rostral anterior cingulate cortex, rACC）、双侧前额叶皮质（prefrontal cortex, PFC）的活动强度降低，而右侧丘脑（thalamus, TH）的活动强度增高；且左侧前喙扣带回皮质功能异常与偏头痛病程呈现显著的负相关关系。静息状态下出现异常的脑区与全脑的功能连接模式亦出现异常，主要表现为功能连接强度的增加。该研究从局部和整体两个角度考察偏头痛患者大脑静息状态的异常模式，可以帮助我们更好地理解偏头痛对大脑造成的影响。
其次，采用基于数据驱动的独立成分分析方法（independent component analysis,ICA）检测偏头痛患者静息状态固有功能网络连接模式异常。静息状态下，大脑的自发神经活动是由多个具有特定功能的神经网络协调耦合形成，这些网络称为静息状态的固有网络。独立成分分析方法不需要先验模型，只依赖于数据本身，是一种有效提取静息状态功能网络的研究手段。本研究将独立成分分析方法应用于比较偏头痛患者和正常被试的三个静息状态网络连接差异，发现与正常被试相比：无先兆偏头痛患者的执行网络（central executive network, CEN）和凸显网络（salience network, SN）的内部功能连接强度出现异常，表现为执行网络额下回皮质（inferior frontal gyurs, IFG）连接强度增加、凸显网络右侧辅助运动区（rightsupplementary motor area, rSMA）连接强度降低；网络之间的连接模式亦发生改变，表现为默认网络（default mode network, DMN）及右侧执行网络与凸显网络内部右侧前脑岛（right anterior insula, rAI）区域连接强度的增加，进一步的相关分析表明网络间连接强度的增加与偏头痛病程之间存在显著正相关关系。该研究考察了病理条件下无先兆偏头痛患者固有功能网络协同加工模式异常，这些结果可能成为该病临床前期诊断的重要生物学指标。
再次，采用因果分析方法考察静息状态无先兆偏头痛患者大脑核团间有效连接模式。以往大量神经影像学研究表明，大脑复杂活动的完成需要中枢神经多个核团之间协同加工，以脑网络的组织模式进行运作，内外信息的交换主要通过大脑网络的动态交互作用得以实现。本研究采用多变量Granger因果模型，对无先兆偏头痛患者的网络内部核团之间及脑网络之间的信息交互模式进行了分析。发现静息状态下无先兆偏头痛患者和正常被试的右侧额叶脑岛区域（right fronto-insulacortex, rFIC）对默认网络及执行网络起着支配、调控的作用。与正常被试相比，无先兆偏头痛组由凸显网络流向执行网络的因果连接降低，可能为偏头痛伴随的认知、执行能力下降提供神经生理解释。该研究构建了无先兆偏头痛静息状态因果传导通路模型，可以帮助我们加深对无先兆偏头痛神经机制的理解。
最后，探讨了针刺治疗偏头痛的有效性。偏头痛的发病机制比较复杂，临床对该病的治疗也有多种方法。虽然西药对于缓解偏头痛的急性发作具有较好疗效，但存在着一定的毒副作用。中医中药尤其是针刺疗法在预防、治疗偏头痛方面，具有效果显著，毒副作用小，少复发等优点，其疗效得到肯定，在偏头痛的临床应用也较为广泛。功能核磁共振成像（functional magnetic resonance imaging, fMRI）作为一种非侵入、可实时观测大脑功能活动的技术，为探究针刺效应神经调控途径及作用疗效评价提供了全新的研究途径。本部分研究内容采用基于数据驱动的多体素模式分析方法，用以探究大脑对针刺信号的处理与加工。研究结果揭示了针刺不同穴位引起的神经响应大脑空间分布模式显著不同。该研究不仅有助于进一步挖掘穴位相对功能特异性的神经表象，而且有助于为针刺治疗偏头痛的有效性提供理论依据。
总体来说，本文考察了无先兆偏头痛患者静息状态脑功能活动，着重探讨了静息状态下的功能异常，固有功能网络连接模式的改变，网络核团间信息交互模式，最后探讨了针刺治疗偏头痛的可行性。本文的主要发现可以提高我们对偏头痛的认识，为偏头痛的临床诊断和治疗提供帮助。
Migraine is a common, chronic disorder typically characterized by recurrentattacks of disabling headache. Given the heavy burden that migraine disability places onthe individual and society, it is imperative to develop a better understanding of migrainepathophysiology. Neuroimaging has helped to increase our knowledge about neuralmechanisms underlying migraine. Converging evidences of structural and functionalcerebral abnormalities in patients with migraine have been accumulated. All of thesefindings demonstrated that migraine is associated with altered central processing of painstimulus, and recurrent migraine attacks may result in selective damage of brain areasinvolved in pain processing. Despite such progress, migraine remains underdiagnosedand the available therapies underused. By focusing on the neural responses under taskconditions, resting-state analysis has been utilized to investigate the integration level ofneural systems when no explicit task is engaged. Until recently, few studies haveevaluated the abnormalities of the resting state in subjects with migraine.
The details of researches and the main innovations were listed as follows:
Firstly, although previous resting-state studies have reported abnormal functionalcerebral changes in patients with migraine without aura (MwoA), few have focused onthe alterations of regional spontaneous neuronal activity and the corresponding braincircuits’ changes collectively. In the present study, we first investigated alterations ofregional spontaneous neuronal activity during the resting-state in MwoA patients byapplying the amplitude of low-frequency fluctuation (ALFF) approach. Then weextracted the regions with significant ALFF differences between MwoA patients andhealthy controls (HC) as regions of interest (ROIs) for resting-state functionalconnectivity (FC) analysis, which was used to assess the corresponding brain circuits’changes in MwoA. We found that MwoA patients have altered resting-state spontaneousneuronal activity in pain-processing areas, including the left rostral anterior cingulatecortex (rACC), bilateral prefrontal cortex (PFC), and right thalamus (TH), as well asaltered FCs associated with these areas. ROI-based FC analysis also revealed increasedFCs associated with these areas. In addition, the ALFF values of the left rACC werecorrelated with duration of disease in MwoA. Our findings may lead to a betterunderstanding of intrinsic functional architecture of the baseline brain activity in MwoA,providing both regional and the corresponding brain circuits’ spontaneous neuronalactivity properties.
Secondly, numerous neuroimaging studies have defined low-frequency, spatially consistent intrinsic connectivity networks (ICN) in resting-state functional magneticresonance imaging (fMRI) data which reflect functional interactions among distinctbrain areas, in the current study, we applied independent component analysis (ICA) toidentify the group differences of three important networks, i.e., the default modenetwork (DMN), bilateral central executive network (CEN) and salience network (SN)between the MwoA patients and HC. One of the key features of ICA is its ability toperform a spatial-temporal decomposition of the signal without any a priori anatomical(spatial) or neural (temporal) information. Compared with the HC, MwoA patientsshowed greater intra-network connectivity within the right middle frontal gyrus (rMFG)for the right CEN (rCEN) and left inferior frontal gyrus (lIFG) for the left CEN (lCEN),and decreased intra-network connectivity within the right supplementary motor area(rSMA) for the SN. Moreover, MwoA patients demonstrated greater intrinsic DMN andrCEN connectivity to brain regions outside of the classical boundaries of these networks,namely the right anterior insula (rAI). Greater connectivity between both the DMN andrCEN and the insula correlated with duration of migraine. Our findings may haveimplications for understanding brain mechanisms of MwoA, potentially pointingtowards “markers” for disease progression. More broadly, these findings haveimplications for how such complex interplay amongst multiple brain networks can beinfluenced by frequent ongoing migraine attacks.
Thirdly, we applied multivariate Granger causality analysis (mGCA) to directlyassess the causal interactions of specific nodes within and among the intrinsic networks.One distinguishing feature of the human brain is the amount of cognitive controlavailable for selecting, switching, and attending to salient events in the environments.Recent researches have suggested that the human brain is intrinsically organized intodistinct functional networks that support these processes. We used mGCA to examinethe interaction between the DMN, CEN, and SN. Our findings emphaszied a key rolefor the rFIC in the hierarchical initiation of control signals, specifically with respect toactivation and deactivation in the CEN and DMN, and the dynamics of switchingbetween these two networks. Compared with the HC, the SN did have a weaker causalinfluence on the CEN in MwoA patients. This might be related to cognitive impairmentin migraine patients.
Finally, we discussed potential acupuncture effectiveness for treatment of migraine.The pathogenesis of migraine is complex, and there are various clinical treatments ofthe disease. In terms of acute treatment, migraine can be managed effectively withwestern medicine. However, the western medicine oftern have side effects that limit their utility. The Traditional Chinese Medicine (TCM), especially acupuncture therapy,has proven to be effective in treatment of migraine; and it has been widely used in theclinical treatment of the disease. The fMRI technique, with its non-invasive and higherresolution characterstics, has been widely applied in the detection of the brainactivations evoked by acupunture stimuli. In the current study, we introduced adata-driven based multivariate approach namely support vector machine (SVM) toexplore the spatial neural response patterns evoked by acupuncture at two differentacupoints. The results showed that acupuncture at the acupoints can evoke distinctneural response patterns. Our findings may suggest potentially selective efficacy-relatedneural actions in response to acupuncture at different acupoints, which might provide atheoretical basis for clinical application of acupuncture in treatment of migraine.
In summary, these resting-state functional abnormalities in MwoA patientsprovided additional evidence for abnormal brain function in MwoA patients. Thesefindings may be beneficial for understanding migraine, as well as providing potentialdiagnostic information and treatment strategies.
引文
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