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摘要:目前,抑郁症已成为危害人们幸福生活的重大疾病之一。本文对静息态功能磁共振成像技术在抑郁症的诊断中进行讨论,静息态功能磁共振成像技术或成为未来抑郁症诊断的有力工具。
关键词:抑郁症;静息态功能磁共振;功能连接
中图分类号:G4 文献标识码:A
抑郁症
抑郁症是( Major depressive disorder)是一种令人衰弱的精神类疾病,其特征是持续性的情绪低落、兴趣减退、以及认知功能受损和营养不良症状,如睡眠不良或食欲紊乱[1]。抑郁症患者的终身自杀风险约为6%,比一般人群高出20倍[2]。目前对于抑郁症,较主流的诊断依据主要是依靠经验丰富的临床医生根据DSM-5(American Psychiatric Association, 2013)[3]等诊断手册中的标准,结合医生的临床经验,从患者的认知、情绪、意识和行为等方面进行评估诊断。该诊断过程虽被广泛使用,但主要依赖于主观解释。一项荟萃研究报告显示全科医生识别抑郁症患者的正确率为47.3%(95% CI 41.7% to 53.0%),并在病例中记录为抑郁症占33.6%(22.4%-45.7%)。阳性预测值为42.0%(39.6%-44.3%),阴性预测值为85.8%(84.8%-86.7%)[4]。该文献表明全科医生可以正确排除大多数的正常人,然而,在初步诊断过程中抑郁症患病率较低,这意味着误诊的人数多于漏诊人数。诊断延迟可能会对抑郁症的临床病程产生负面影响。因此,在临床诊断中医生迫切需要一种客观工具对患者进行诊断治疗。
功能磁共振成像技术关于抑郁症的发现
近年来,随着脑影像技术的发展,功能磁共振成像(functional magnetic resonance imaging,fMRI)已广泛应用于精神疾病发病机制、治疗效果以及预后评估等方面的研究。功能磁共振成像是基于血氧水平依赖(blood oxygenation level dependent,BOLD )效应并被广泛用于记录大脑神经活动信号的技术[6]。研究大脑不同区域之间BOLD信号的统计关联程度可以反映出大脑的功能连接(functional connectivity,FC)[7]。rfMRI(resting-state functional magnetic resonance imaging, rfMRI)研究的是个体在清醒但不执行任务时的自发脑活动,rfMRI具有设计简单、对被试配合度要求低以及可重复测量的优点[8]。因此近年来越来越多的研究者使用rfMRI技术对抑郁症患者的脑功能网络异常进行研究。rfMRI的研究内容包括局部脑区功能、脑区间联系、多个脑区组成的网络功能,进而推及全脑。rfMRI 能够反映全脑的功能变化,更好地体现抑郁症本身的脑功能变化特点,已用于抑郁症的发病机制、临床诊断、疗效评估、预后预测等方面的研究[9]。基于目前rfMRI研究表明,抑郁个体在广泛分布的脑网络中表现出功能异常,主要表现在默认网络(default mode network, DMN)[10][11]、认知控制网络(cognitive control network, CCN)[12][13]和情緒网络(affective network, AN)[12]等高级脑功能网络内部以及不同网络之间的交互作用[14][15][16]异常。除以上脑网络外,在研究抑郁症的神经影像学报告中也提及了丘脑异常这一现象。在一项使用rfMRI数据研究抑郁症患者的研究中发现丘脑功能连接存在异常,并与核心临床症状相关,可见丘脑功能连接是MDD的神经生物学特征和潜在的生物标志物之一[17]。以与丘脑有关环路为例,不少研究者对其进行了研究。一些早期的磁共振成像研究证实了抑郁症患者的边缘-皮质-纹状体-苍白球-丘脑(LCSPT)网络或边缘-皮质-纹状体-丘脑-皮质(LCSTC)回路存在异常[18]。有许多与自杀相关的研究发现自杀行为与背外侧前额叶皮层(DLPFC)、尾状核和丘脑有关,它们形成了负责执行功能和工作记忆的皮质-纹状体-丘脑-皮层(CSTC)回路。CSTC环路的中断可能导致执行功能障碍和工作记忆障碍,从而导致抑郁症患者的自杀风险增加[19]。在一项难治性抑郁症患者的研究中发现前额叶皮层和丘脑之间出现功能紊乱现象,同时这项研究也表明抑郁症患者的丘脑和亚属扣带连接性增加[22]。一项研究中发现丘脑与主要皮层区域之间功能连接的研究中发现抑郁症患者的内侧丘脑和颞区之间,以及内侧丘脑和体感区之间的连接性显著增加,此外,还发现丘脑-颞叶连接和症状严重程度之间存在着正相关的关系[23]。
总结
由此可见,全科医生对抑郁症进行诊断虽更为常见,但仍存在误诊风险。而rfMRI技术能够为医生提供更为客观的诊断指标,在日后的诊断中,rfMRI技术有望成为一个有力的诊断工具。
[1]Otte, C., Gold, S. M., Penninx, B. W., Pariante, C. M., Etkin, A., Fava, M., ... & Schatzberg, A. F. (2016). Major depressive disorder. Nature reviews Disease primers, 2(1), 1-20.
[2]Inskip, H., Harris, C., & Barraclough, B. (1998). Lifetime risk of suicide for affective disorder, alcoholism and schizophrenia. The British Journal of Psychiatry, 172(1), 35-37.
[3]American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (DSM-5?). American Psychiatric Pub. [4]Mitchell, A. J., Vaze, A., & Rao, S. (2009). Clinical diagnosis of depression in primary care: a meta-analysis. The Lancet, 374(9690), 609-619.
[5]Ogawa, S. (2012). Finding the BOLD effect in brain images. Neuroimage, 62(2), 608-609.
[6]Greicius, M. D., Krasnow, B., Reiss, A. L., & Menon, V. (2003). Functional connectivity in the resting brain: a network analysis of the default mode hypothesis. Proceedings of the National Academy of Sciences, 100(1), 253-258.
[7]許潇丹, 应福仙, 雷凯凯, 罗跃嘉, & 李至浩. (2019). 抑郁症相关的静息态脑功能网络异常. 中国科学: 生命科学.
[8]王秀丽, 黄晓琦, 龚启勇. 抑郁症静息态脑功能磁共振成像研究进展. 华西医学, 2015, 30(4): 773-778.
[9]Liston, C., Chen, A. C., Zebley, B. D., Drysdale, A. T., Gordon, R., Leuchter, B., ... & Dubin, M. J. (2014). Default mode network mechanisms of transcranial magnetic stimulation in depression. Biological psychiatry, 76(7), 517-526.
[10]Saris, I. M., Penninx, B. W., Dinga, R., van Tol, M. J., Veltman, D. J., van der Wee, N. J., & Aghajani, M. (2020). Default mode network connectivity and social dysfunction in major depressive disorder. Scientific reports, 10(1), 1-11.
[11]Wang, Y. L., Yang, S. Z., Sun, W. L., Shi, Y. Z., & Duan, H. F. (2016). Altered functional interaction hub between affective network and cognitive control network in patients with major depressive disorder. Behavioural brain research, 298, 301-309.
[12]Pan, F., Xu, Y., Zhou, W., Chen, J., Wei, N., Lu, S., ... & Huang, M. (2020). Disrupted intrinsic functional connectivity of the cognitive control network underlies disease severity and executive dysfunction in first-episode, treatment-naive adolescent depression. Journal of affective disorders, 264, 455-463.
[13]Berman, M. G., Peltier, S., Nee, D. E., Kross, E., Deldin, P. J., & Jonides, J. (2011). Depression, rumination and the default network. Social cognitive and affective neuroscience, 6(5), 548-555.
[14]Manoliu, A., Riedl, V., Doll, A., B?uml, J. G., Mühlau, M., Schwerth?ffer, D., ... & Sorg, C. (2013). Insular dysfunction reflects altered between-network connectivity and severity of negative symptoms in schizophrenia during psychotic remission. Frontiers in human neuroscience, 7, 216.
[15]Tang, Y., Kong, L., Wu, F., Womer, F., Jiang, W., Cao, Y., ... & Wang, F. (2013). Decreased functional connectivity between the amygdala and the left ventral prefrontal cortex in treatment-naive patients with major depressive disorder: a resting-state functional magnetic resonance imaging study. Psychological medicine, 43(9), 1921-1927. [16]Kang, L., Zhang, A., Sun, N., Liu, P., Yang, C., Li, G., ... & Zhang, K. (2018). Functional connectivity between the thalamus and the primary somatosensory cortex in major depressive disorder: a resting-state fMRI study. BMC psychiatry, 18(1), 1-8.
[17]Lu, Y., Liang, H., Han, D., Mo, Y., Li, Z., Cheng, Y., ... & Sun, X. (2016). The volumetric and shape changes of the putamen and thalamus in first episode, untreated major depressive disorder. NeuroImage: Clinical, 11, 658-666.
[18]Chattun, M. R., Zhang, S., Chen, Y., Wang, Q., Amdanee, N., Tian, S., ... & Yao, Z. (2020). Caudothalamic dysfunction in drug-free suicidally depressed patients: an MEG study. European Archives of Psychiatry and Clinical Neuroscience, 270(2), 217-227.
[19]Weng, J. C., Chou, Y. S., Tsai, Y. H., Lee, C. T., Hsieh, M. H., & Chen, V. C. H. (2019). Connectome Analysis of Brain Functional Network Alterations in Depressive Patients with Suicidal Attempt. Journal of clinical medicine, 8(11), 1966.
[20]Xue, S. W., Wang, D., Tan, Z., Wang, Y., Lian, Z., Sun, Y., ... & Zhou, X. (2019). Disrupted brain entropy and functional connectivity patterns of thalamic subregions in major depressive disorder. Neuropsychiatric Disease and Treatment, 15, 2629.
[21]Brown, E. C., Clark, D. L., Hassel, S., MacQueen, G., & Ramasubbu, R. (2017). Thalamocortical connectivity in major depressive disorder. Journal of Affective Disorders, 217, 125-131.
[22]Qiu, L., Xia, M., Cheng, B., Yuan, L., Kuang, W., Bi, F., ... & Gong, Q. (2018). Abnormal dynamic functional connectivity of amygdalar subregions in untreated patients with first-episode major depressive disorder. Journal of psychiatry & neuroscience: JPN, 43(4), 262.
[23]Brown, E. C., Clark, D. L., Hassel, S., MacQueen, G., & Ramasubbu, R. (2017). Thalamocortical connectivity in major depressive disorder. Journal of Affective Disorders, 217, 125-131.
作者簡介:潘辰远(1997-)女 汉 浙江杭州 学生 应用心理研究生在读 单位:杭州师范大学教育学院 研究方向:应用心理
关键词:抑郁症;静息态功能磁共振;功能连接
中图分类号:G4 文献标识码:A
抑郁症
抑郁症是( Major depressive disorder)是一种令人衰弱的精神类疾病,其特征是持续性的情绪低落、兴趣减退、以及认知功能受损和营养不良症状,如睡眠不良或食欲紊乱[1]。抑郁症患者的终身自杀风险约为6%,比一般人群高出20倍[2]。目前对于抑郁症,较主流的诊断依据主要是依靠经验丰富的临床医生根据DSM-5(American Psychiatric Association, 2013)[3]等诊断手册中的标准,结合医生的临床经验,从患者的认知、情绪、意识和行为等方面进行评估诊断。该诊断过程虽被广泛使用,但主要依赖于主观解释。一项荟萃研究报告显示全科医生识别抑郁症患者的正确率为47.3%(95% CI 41.7% to 53.0%),并在病例中记录为抑郁症占33.6%(22.4%-45.7%)。阳性预测值为42.0%(39.6%-44.3%),阴性预测值为85.8%(84.8%-86.7%)[4]。该文献表明全科医生可以正确排除大多数的正常人,然而,在初步诊断过程中抑郁症患病率较低,这意味着误诊的人数多于漏诊人数。诊断延迟可能会对抑郁症的临床病程产生负面影响。因此,在临床诊断中医生迫切需要一种客观工具对患者进行诊断治疗。
功能磁共振成像技术关于抑郁症的发现
近年来,随着脑影像技术的发展,功能磁共振成像(functional magnetic resonance imaging,fMRI)已广泛应用于精神疾病发病机制、治疗效果以及预后评估等方面的研究。功能磁共振成像是基于血氧水平依赖(blood oxygenation level dependent,BOLD )效应并被广泛用于记录大脑神经活动信号的技术[6]。研究大脑不同区域之间BOLD信号的统计关联程度可以反映出大脑的功能连接(functional connectivity,FC)[7]。rfMRI(resting-state functional magnetic resonance imaging, rfMRI)研究的是个体在清醒但不执行任务时的自发脑活动,rfMRI具有设计简单、对被试配合度要求低以及可重复测量的优点[8]。因此近年来越来越多的研究者使用rfMRI技术对抑郁症患者的脑功能网络异常进行研究。rfMRI的研究内容包括局部脑区功能、脑区间联系、多个脑区组成的网络功能,进而推及全脑。rfMRI 能够反映全脑的功能变化,更好地体现抑郁症本身的脑功能变化特点,已用于抑郁症的发病机制、临床诊断、疗效评估、预后预测等方面的研究[9]。基于目前rfMRI研究表明,抑郁个体在广泛分布的脑网络中表现出功能异常,主要表现在默认网络(default mode network, DMN)[10][11]、认知控制网络(cognitive control network, CCN)[12][13]和情緒网络(affective network, AN)[12]等高级脑功能网络内部以及不同网络之间的交互作用[14][15][16]异常。除以上脑网络外,在研究抑郁症的神经影像学报告中也提及了丘脑异常这一现象。在一项使用rfMRI数据研究抑郁症患者的研究中发现丘脑功能连接存在异常,并与核心临床症状相关,可见丘脑功能连接是MDD的神经生物学特征和潜在的生物标志物之一[17]。以与丘脑有关环路为例,不少研究者对其进行了研究。一些早期的磁共振成像研究证实了抑郁症患者的边缘-皮质-纹状体-苍白球-丘脑(LCSPT)网络或边缘-皮质-纹状体-丘脑-皮质(LCSTC)回路存在异常[18]。有许多与自杀相关的研究发现自杀行为与背外侧前额叶皮层(DLPFC)、尾状核和丘脑有关,它们形成了负责执行功能和工作记忆的皮质-纹状体-丘脑-皮层(CSTC)回路。CSTC环路的中断可能导致执行功能障碍和工作记忆障碍,从而导致抑郁症患者的自杀风险增加[19]。在一项难治性抑郁症患者的研究中发现前额叶皮层和丘脑之间出现功能紊乱现象,同时这项研究也表明抑郁症患者的丘脑和亚属扣带连接性增加[22]。一项研究中发现丘脑与主要皮层区域之间功能连接的研究中发现抑郁症患者的内侧丘脑和颞区之间,以及内侧丘脑和体感区之间的连接性显著增加,此外,还发现丘脑-颞叶连接和症状严重程度之间存在着正相关的关系[23]。
总结
由此可见,全科医生对抑郁症进行诊断虽更为常见,但仍存在误诊风险。而rfMRI技术能够为医生提供更为客观的诊断指标,在日后的诊断中,rfMRI技术有望成为一个有力的诊断工具。
[1]Otte, C., Gold, S. M., Penninx, B. W., Pariante, C. M., Etkin, A., Fava, M., ... & Schatzberg, A. F. (2016). Major depressive disorder. Nature reviews Disease primers, 2(1), 1-20.
[2]Inskip, H., Harris, C., & Barraclough, B. (1998). Lifetime risk of suicide for affective disorder, alcoholism and schizophrenia. The British Journal of Psychiatry, 172(1), 35-37.
[3]American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (DSM-5?). American Psychiatric Pub. [4]Mitchell, A. J., Vaze, A., & Rao, S. (2009). Clinical diagnosis of depression in primary care: a meta-analysis. The Lancet, 374(9690), 609-619.
[5]Ogawa, S. (2012). Finding the BOLD effect in brain images. Neuroimage, 62(2), 608-609.
[6]Greicius, M. D., Krasnow, B., Reiss, A. L., & Menon, V. (2003). Functional connectivity in the resting brain: a network analysis of the default mode hypothesis. Proceedings of the National Academy of Sciences, 100(1), 253-258.
[7]許潇丹, 应福仙, 雷凯凯, 罗跃嘉, & 李至浩. (2019). 抑郁症相关的静息态脑功能网络异常. 中国科学: 生命科学.
[8]王秀丽, 黄晓琦, 龚启勇. 抑郁症静息态脑功能磁共振成像研究进展. 华西医学, 2015, 30(4): 773-778.
[9]Liston, C., Chen, A. C., Zebley, B. D., Drysdale, A. T., Gordon, R., Leuchter, B., ... & Dubin, M. J. (2014). Default mode network mechanisms of transcranial magnetic stimulation in depression. Biological psychiatry, 76(7), 517-526.
[10]Saris, I. M., Penninx, B. W., Dinga, R., van Tol, M. J., Veltman, D. J., van der Wee, N. J., & Aghajani, M. (2020). Default mode network connectivity and social dysfunction in major depressive disorder. Scientific reports, 10(1), 1-11.
[11]Wang, Y. L., Yang, S. Z., Sun, W. L., Shi, Y. Z., & Duan, H. F. (2016). Altered functional interaction hub between affective network and cognitive control network in patients with major depressive disorder. Behavioural brain research, 298, 301-309.
[12]Pan, F., Xu, Y., Zhou, W., Chen, J., Wei, N., Lu, S., ... & Huang, M. (2020). Disrupted intrinsic functional connectivity of the cognitive control network underlies disease severity and executive dysfunction in first-episode, treatment-naive adolescent depression. Journal of affective disorders, 264, 455-463.
[13]Berman, M. G., Peltier, S., Nee, D. E., Kross, E., Deldin, P. J., & Jonides, J. (2011). Depression, rumination and the default network. Social cognitive and affective neuroscience, 6(5), 548-555.
[14]Manoliu, A., Riedl, V., Doll, A., B?uml, J. G., Mühlau, M., Schwerth?ffer, D., ... & Sorg, C. (2013). Insular dysfunction reflects altered between-network connectivity and severity of negative symptoms in schizophrenia during psychotic remission. Frontiers in human neuroscience, 7, 216.
[15]Tang, Y., Kong, L., Wu, F., Womer, F., Jiang, W., Cao, Y., ... & Wang, F. (2013). Decreased functional connectivity between the amygdala and the left ventral prefrontal cortex in treatment-naive patients with major depressive disorder: a resting-state functional magnetic resonance imaging study. Psychological medicine, 43(9), 1921-1927. [16]Kang, L., Zhang, A., Sun, N., Liu, P., Yang, C., Li, G., ... & Zhang, K. (2018). Functional connectivity between the thalamus and the primary somatosensory cortex in major depressive disorder: a resting-state fMRI study. BMC psychiatry, 18(1), 1-8.
[17]Lu, Y., Liang, H., Han, D., Mo, Y., Li, Z., Cheng, Y., ... & Sun, X. (2016). The volumetric and shape changes of the putamen and thalamus in first episode, untreated major depressive disorder. NeuroImage: Clinical, 11, 658-666.
[18]Chattun, M. R., Zhang, S., Chen, Y., Wang, Q., Amdanee, N., Tian, S., ... & Yao, Z. (2020). Caudothalamic dysfunction in drug-free suicidally depressed patients: an MEG study. European Archives of Psychiatry and Clinical Neuroscience, 270(2), 217-227.
[19]Weng, J. C., Chou, Y. S., Tsai, Y. H., Lee, C. T., Hsieh, M. H., & Chen, V. C. H. (2019). Connectome Analysis of Brain Functional Network Alterations in Depressive Patients with Suicidal Attempt. Journal of clinical medicine, 8(11), 1966.
[20]Xue, S. W., Wang, D., Tan, Z., Wang, Y., Lian, Z., Sun, Y., ... & Zhou, X. (2019). Disrupted brain entropy and functional connectivity patterns of thalamic subregions in major depressive disorder. Neuropsychiatric Disease and Treatment, 15, 2629.
[21]Brown, E. C., Clark, D. L., Hassel, S., MacQueen, G., & Ramasubbu, R. (2017). Thalamocortical connectivity in major depressive disorder. Journal of Affective Disorders, 217, 125-131.
[22]Qiu, L., Xia, M., Cheng, B., Yuan, L., Kuang, W., Bi, F., ... & Gong, Q. (2018). Abnormal dynamic functional connectivity of amygdalar subregions in untreated patients with first-episode major depressive disorder. Journal of psychiatry & neuroscience: JPN, 43(4), 262.
[23]Brown, E. C., Clark, D. L., Hassel, S., MacQueen, G., & Ramasubbu, R. (2017). Thalamocortical connectivity in major depressive disorder. Journal of Affective Disorders, 217, 125-131.
作者簡介:潘辰远(1997-)女 汉 浙江杭州 学生 应用心理研究生在读 单位:杭州师范大学教育学院 研究方向:应用心理