肝气郁结证脑深部核团及扣带回的磁共振扩散张量成像
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摘要
目的:研究肝气郁结证患者脑深部神经核团及扣带回微结构损伤的特点。方法:选取2012年5月至2015年5月在北京中医药大学东方医院收治的肝气郁结证患者16例,同时选取正常对照者13例,进行磁共振DTI扫描,原始数据通过后处理计算出部分各向异性分数(FA)图和表观扩散系数(ADC)图。分别测量两侧海马、杏仁核、丘脑、豆状核、尾状核头和扣带回的FA值和ADC值。2组感兴趣区对应测量相同部位。并对2组结果进行统计学比较分析。结果:肝气郁结证组的右侧丘脑、双侧中扣带回FA值明显高于对照组(P=0. 043,0. 004,0. 001),左侧豆状核FA值明显低于对照组(P=0. 033)。肝气郁结证组的左侧前扣带回、双侧后扣带回ADC值明显低于对照组(P=0. 019,0. 039,0. 049)。右中扣带回FA值ROC分析显示,曲线下面积(AUC=0. 87,P=0. 001),最佳诊断界值FA值=0. 383750,灵敏度92. 3%,特异度68. 7%。结论:通过对肝气郁结证患者脑深部核团及扣带回的DTI研究,发现肝气郁结证患者脑深部神经核团及扣带回损伤存在于特定的脑区,其中右中扣带回FA值对鉴别诊断具有重要的意义。
Objective: To study the microstructural damage characteristics of the nerve nuclei and cingulate cortex in the brain of the patients with liver qi stagnation using magnetic resonance diffusion tensor imaging( DTI) technique. Methods: A total of 16 patients with liver qi stagnation syndrome clinically confirmed by Dongfang Hospital,Beijing University of Chinese Medicine from May2012 to May 2015 were selected. Meanwhile,13 normal controls were selected. These subjects were performed by magnetic resonance DTI scanning. After raw data processing,the map of fractional anisotropy( FA) and apparent diffusion coefficient( ADC) were calculated. The FA and ADC values were measured in the bilateral hippocampus,amygdala,thalamus,lentiform nucleus,caudate nucleus and cingulate cortex. Region of interest( ROI) was set at the same brain region. The FA and ADC value of 2 groups were analyzed statistically. Results: The FA values of the right thalamus and bilateral middle cingulate cortex in the disease were significantly higher than that of the control group( P = 0. 043,0. 004,0. 043). The FA value of the left lentiform nucleus was lower than that of the control group significantly( P = 0. 033). The ADC value of the left anterior cingulate cortex( ACC) and bilateral posterior cingulate cortex( PCC) were significantly lower than that of the control group( P = 0. 019,0. 039,0. 049). The FA value of the right middle cingulate cortex was taken as the biomarker,ROC analysis showed the area under the curve( AUC = 0. 87,P = 0. 001),the best diagnostic value FA value was 0. 383750,sensitivity 92. 3%,and the specificity 68. 7%. Conclusion: By the DTI analysis of the deep brain nuclei and cingulate cortex of the patients with liver qi stagnation syndrome,we found that the injury of the patient's deep brain nerve nuclei and cingulate cortex exists in specific brain regions. The FA value of the right middle cingulate cortex played an important role for syndrome differentiation.
Objective: To study the microstructural damage characteristics of the nerve nuclei and cingulate cortex in the brain of the patients with liver qi stagnation using magnetic resonance diffusion tensor imaging( DTI) technique. Methods: A total of 16 patients with liver qi stagnation syndrome clinically confirmed by Dongfang Hospital,Beijing University of Chinese Medicine from May2012 to May 2015 were selected. Meanwhile,13 normal controls were selected. These subjects were performed by magnetic resonance DTI scanning. After raw data processing,the map of fractional anisotropy( FA) and apparent diffusion coefficient( ADC) were calculated. The FA and ADC values were measured in the bilateral hippocampus,amygdala,thalamus,lentiform nucleus,caudate nucleus and cingulate cortex. Region of interest( ROI) was set at the same brain region. The FA and ADC value of 2 groups were analyzed statistically. Results: The FA values of the right thalamus and bilateral middle cingulate cortex in the disease were significantly higher than that of the control group( P = 0. 043,0. 004,0. 043). The FA value of the left lentiform nucleus was lower than that of the control group significantly( P = 0. 033). The ADC value of the left anterior cingulate cortex( ACC) and bilateral posterior cingulate cortex( PCC) were significantly lower than that of the control group( P = 0. 019,0. 039,0. 049). The FA value of the right middle cingulate cortex was taken as the biomarker,ROC analysis showed the area under the curve( AUC = 0. 87,P = 0. 001),the best diagnostic value FA value was 0. 383750,sensitivity 92. 3%,and the specificity 68. 7%. Conclusion: By the DTI analysis of the deep brain nuclei and cingulate cortex of the patients with liver qi stagnation syndrome,we found that the injury of the patient's deep brain nerve nuclei and cingulate cortex exists in specific brain regions. The FA value of the right middle cingulate cortex played an important role for syndrome differentiation.
引文
[1]滕晶,王玉来,刘子旺.肝气郁结证的研究总结与未来发展探讨[J].中医药学刊,2006,24(12):2220-2221.
[2]毛海燕,叶林,叶向荣.肝郁证大鼠中枢神经递质变化的观察[J].福建中医药,2002,33(2):17-18.
[3]孛立甲,金光亮.肝郁证模型大鼠海马内差异表达片段生物信息学分析[J].吉林中医药,2012,32(5):507-509.
[4]苏娜娜,郭承伟.肝郁证大鼠外侧膝状体NMDAR1基因表达的实验研究[J].山东中医药大学学报,2013,37(4):327-329.
[5]滕晶,王玉来,姚斌,等.肝气郁结证患者脑电非线性分析的研究[J].山东中医药大学学报,2008,31(5):378-382.
[6]刘明,刘子旺,赵晶,等.肝郁症与正常人群欣赏欢快音乐的脑功能激活模式研究[J].世界中医药,2016,11(9):1909-1912.
[7]王爱成,王玉来,李柏,等.肝气郁结证相关脑区的正电子发射断层成像[J].中华中医药杂志,2005,20(8):479-481.
[8]曲淼,唐启盛.抑郁症与中医“郁证”的关系探讨[J].北京中医药大学学报,2004,27(1):111-113.
[9]赵燕,王天芳,于春光,等.抑郁症中医证候及证候要素分布特点的文献研究[J].中医杂志,2006,47(9):691-693.
[10]金卫东.肝郁与抑郁症关系探讨[J].中医研究,2009,22(11):1-3.
[11]Zhao K,Liu H,Yan R,et al. Cortical thickness and subcortical structure volume abnormalities in patients with major depression with and without anxious symptoms[J]. Brain Behav,2017,7(8):e00754.
[12]Li L,Li B,Bai Y,et al. Abnormal resting state effective connectivity within the default mode network in major depressive disorder:A spectral dynamic causal modeling study[J]. Brain Behav,2017,7(7):e00732.
[13]Lois G,Wessa M. Differential association of default mode network connectivity and rumination in healthy individuals and remitted MDD patients[J]. Soc Cogn Affect Neurosci,2016,11(11):1792-1801.
[14]Bora E,Harrison BJ,Davey CG,et al. Meta-analysis of volumetric abnormalities in cortico-striatal-pallidal-thalamic circuits in major depressive disorder[J]. Psychol Med,2012,42(4):671-681.
[15]Liu J,Xu X,Luo Q,et al. Brain grey matter volume alterations associated with antidepressant response in major depressive disorder[J].Sci Rep,2017,7(1):10464.
[16]Bora E,Fornito A,Pantelis C,et al. Gray matter abnormalities in Major Depressive Disorder:a meta-analysis of voxel based morphometry studies[J]. J Affect Disord,2012,138(1-2):9-18.
[17]Dillon DG,Gonenc A,Belleau E,et al. Depression is associated with dimensional and categorical effects on white matter pathways[J].Depress Anxiety,2018,35(5):440-447.
[18]Jaworska N,Mac Master FP,Yang XR,et al. Influence of age of onset on limbic and paralimbic structures in depression[J]. Psychiatry Clin Neurosci,2014,68(12):812-820.
[19]窦社伟,付畅,轩昂,等.首发抑郁症患者脑葡萄糖代谢与脑功能局部一致性的关系[J].中华核医学与分子影像杂志,2015,35(1):27-31.
[20]Shen Z,Jiang L,Yang S,et al. Identify changes of brain regional homogeneity in early and later adult onset patients with first-episode depression using resting-state f MRI[J]. PLo S One,2017,12(9):e0184712.
[21]Pan PM,Sato JR,Salum GA,et al. Ventral Striatum Functional Connectivity as a Predictor of Adolescent Depressive Disorder in a Longitudinal Community-Based Sample[J]. Am J Psychiatry,2017,174(11):1112-1119.
[2]毛海燕,叶林,叶向荣.肝郁证大鼠中枢神经递质变化的观察[J].福建中医药,2002,33(2):17-18.
[3]孛立甲,金光亮.肝郁证模型大鼠海马内差异表达片段生物信息学分析[J].吉林中医药,2012,32(5):507-509.
[4]苏娜娜,郭承伟.肝郁证大鼠外侧膝状体NMDAR1基因表达的实验研究[J].山东中医药大学学报,2013,37(4):327-329.
[5]滕晶,王玉来,姚斌,等.肝气郁结证患者脑电非线性分析的研究[J].山东中医药大学学报,2008,31(5):378-382.
[6]刘明,刘子旺,赵晶,等.肝郁症与正常人群欣赏欢快音乐的脑功能激活模式研究[J].世界中医药,2016,11(9):1909-1912.
[7]王爱成,王玉来,李柏,等.肝气郁结证相关脑区的正电子发射断层成像[J].中华中医药杂志,2005,20(8):479-481.
[8]曲淼,唐启盛.抑郁症与中医“郁证”的关系探讨[J].北京中医药大学学报,2004,27(1):111-113.
[9]赵燕,王天芳,于春光,等.抑郁症中医证候及证候要素分布特点的文献研究[J].中医杂志,2006,47(9):691-693.
[10]金卫东.肝郁与抑郁症关系探讨[J].中医研究,2009,22(11):1-3.
[11]Zhao K,Liu H,Yan R,et al. Cortical thickness and subcortical structure volume abnormalities in patients with major depression with and without anxious symptoms[J]. Brain Behav,2017,7(8):e00754.
[12]Li L,Li B,Bai Y,et al. Abnormal resting state effective connectivity within the default mode network in major depressive disorder:A spectral dynamic causal modeling study[J]. Brain Behav,2017,7(7):e00732.
[13]Lois G,Wessa M. Differential association of default mode network connectivity and rumination in healthy individuals and remitted MDD patients[J]. Soc Cogn Affect Neurosci,2016,11(11):1792-1801.
[14]Bora E,Harrison BJ,Davey CG,et al. Meta-analysis of volumetric abnormalities in cortico-striatal-pallidal-thalamic circuits in major depressive disorder[J]. Psychol Med,2012,42(4):671-681.
[15]Liu J,Xu X,Luo Q,et al. Brain grey matter volume alterations associated with antidepressant response in major depressive disorder[J].Sci Rep,2017,7(1):10464.
[16]Bora E,Fornito A,Pantelis C,et al. Gray matter abnormalities in Major Depressive Disorder:a meta-analysis of voxel based morphometry studies[J]. J Affect Disord,2012,138(1-2):9-18.
[17]Dillon DG,Gonenc A,Belleau E,et al. Depression is associated with dimensional and categorical effects on white matter pathways[J].Depress Anxiety,2018,35(5):440-447.
[18]Jaworska N,Mac Master FP,Yang XR,et al. Influence of age of onset on limbic and paralimbic structures in depression[J]. Psychiatry Clin Neurosci,2014,68(12):812-820.
[19]窦社伟,付畅,轩昂,等.首发抑郁症患者脑葡萄糖代谢与脑功能局部一致性的关系[J].中华核医学与分子影像杂志,2015,35(1):27-31.
[20]Shen Z,Jiang L,Yang S,et al. Identify changes of brain regional homogeneity in early and later adult onset patients with first-episode depression using resting-state f MRI[J]. PLo S One,2017,12(9):e0184712.
[21]Pan PM,Sato JR,Salum GA,et al. Ventral Striatum Functional Connectivity as a Predictor of Adolescent Depressive Disorder in a Longitudinal Community-Based Sample[J]. Am J Psychiatry,2017,174(11):1112-1119.