Journal of Shandong University (Health Sciences) ›› 2019, Vol. 57 ›› Issue (4): 42-46.doi: 10.6040/j.issn.1671-7554.0.2018.1341

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Magnetic resonance spectroscopy in patients with vascular cognitive impairment no dementia

ZHANG Xiaoqian, MENG Xiangshui, REN Qingguo, NAN Xiaomin, AN Panpan, SHUAI Xinyan, XIA Xiaona, WANG Xuan   

  1. Department of Radiology, Qilu Hospital of Shandong University, Qingdao 266035, Shandong, China
  • Published:2022-09-27

Abstract: Objective To explore the relevance between metabolic changes in the critical parts of brain and vascular cognitive impairment no dementia(VCIND)by analyzing the metabolite ratios in VCIND patients using magnetic resonance spectroscopy(MRS). Methods A total of 38 VCIND patients(VCIND group)and 44 healthy controls(control group)were involved. The N-acetyl aspartate(NAA), choline(Cho), creatine(Cr), NAA/Cr and Cho/Cr in the frontal lobe, temporal lobe, thalamus, hippocampus, basal ganglia and cingulate gyrus in the two groups were measured with 3.0T MRS. The above parameters in dominant hemisphere of the two groups were compared and statistically analyred. Results Compared with the control group, the VCIND group had significantly reduced NAA in the temporal lobe, hippocampus, thalamus, and cingulate gyrus, and decreased NAA/Cr ratio in the frontal lobe, hippocampus, thalamus and cingulate gyrus (P<0.05). There were no statistical differences in Cho and Cho/Cr in different parts in the dominant hemisphere between two groups(P>0.05). There were no significant differences in all of the parameters between the dominant and non-dominant hemisphere in the VCIND group. Conclusion NAA and NAA/Cr are sensitive indicators to detect VCIND. VCIND patients have extensive cerebral metabolic disorder, but in the dominant hemisphere, the metabolic changes were associated with VCIND in the frontal lobe, temporal lobe, hippocampus, thalamus, and cingulate gyrus. 山 东 大 学 学 报 (医 学 版)57卷4期 -张晓倩,等.磁共振波谱成像对检测非痴呆型血管性认知障碍的探讨 \=-

Key words: Vascular cognitive impairment, Vascular cognitive impairment no dementia, Magnetic resonance spectroscopy, Magnetic resonance imaging, Metabolic disorder

CLC Number: 

  • R749
[1] Smith EE. Clinical presentations and epidemiology of vascular dementia[J]. Clin Sci(Lond), 2017, 131(11): 1059-1068.
[2] 赵维纳, 韩璎. 血管性认知障碍的影像学研究[J]. 中国卒中杂志, 2018, 13(7): 647-650.
[3] 张晓倩, 孟祥水. 多模态功能MRI对血管性认知障碍的研究进展[J]. 国际医学放射学杂志, 2019, 42(1): 59-61. ZHANG Xiaoqian, MENG Xiangshui. Research progress of multi-modality functional magnetic resonance imaging on vascular cognitive impairment[J]. International Journal of Medical Radiology, 2019, 42(1): 59-61.
[4] Hachinski V, Iadecola C, Petersenrc, et al. National Institute of Neurological Disorders and Stroke-Canadian Stroke Network vascular cognitive impairment harmonization standards[J]. Stroke, 2006, 37(9): 2220-2241.
[5] Zhang C, Zhe Y, Lan T, et al. Study on epidemiology of cognitive dysfunction after stroke in the population over the age of 45 in Inner Mongolia[J]. Int J Neurosci, 2018, 128(7): 654-662.
[6] 孙宇, 韩璎, 戴建平, 等. 血管性认知障碍诊断标准的演变与解读[J]. 中国卒中杂志, 2017, 12(1): 13-17.
[7] Sharma S. Translational multimodality neuroimaging[J]. Curr Drug Targets, 2017, 18(9): 1039-1050.
[8] Joe E, Medina LD, Ringman JM, et al. 1H MRS spectroscopy in preclinical autosomal dominant alzheimer disease[J]. Brain Imaging Behav, 2018, 1: 1-8. doi:10.1007/s11682-018-9913-1.
[9] Boban J, Kozic D, Turkulov V, et al. HIV-associated neurodegeneration and neuroimmunity: multivoxel MR spectroscopy study in drug-naive and treated patients[J]. Eur Radiol, 2017, 27(10): 4218-4236.
[10] Veenith TV, Mada M, Carter E, et al. Comparison of inter subject variability and reproducibility of whole brain proton spectroscopy[J]. PLoS One, 2014, 9(12): e115304. doi:10.1371/journal.pone.0115304.
[11] 黄明明, 曹笑婉, 沈桂权, 等. 应用3.0 T 1H-MRS技术纵向评估血管性认知障碍大鼠脑内代谢物改变[J]. 磁共振成像, 2017, 8(9): 691-696. HUANG Mingming, CAO Xiaowan, SHEN Guiquan, et al. A longitudinal study of changes of brain metabolites in vascular cognitive impairment rats using 3.0 T 1H-MRS[J]. Chinese Journal of Magnetic Resonance Imaging, 2017, 8(9): 691-696.
[12] 刘娟, 李文, 王润榕, 等. 无痴呆型血管性认知障碍患者多体素质子磁共振波谱的诊断价值[J]. 中华神经科杂志, 2010, 43(9): 607-611. LIU Juan, LI Wen, WANG Runrong, et al. A study of multi-voxel 1H-magnetic resonance spectroscopy in patients with vascular cognitive impairment no dementia[J]. Chinese Journal of Neurology, 2010, 43(9): 607-611.
[13] Sullivan MO, Morris RG, Markus HS. Brief cognitive assessment for patients with cerebral small vessel disease[J]. J Neurol Neurosurg Psychiatry, 2005, 76(8): 1140-1145.
[14] Gong L, Hou Z, Wang Z, et al. Disrupted topology of hippocampal connectivity is associated with short-term antidepressant response in major depressive disorder[J]. J Affect Disord, 2018, 225: 539-544. doi: 10.1016/j.jad.2017.08.086.
[15] Ho TC, Sacchet MD, Connolly CG, et al. Inflexible functional connectivity of the dorsal anterior cingulate cortex in adolescent major depressive disorder[J]. Neuropsychopharmacology, 2017, 42(12): 2434-2445.
[16] 陆强彬, 张慧萍, 朱祖福, 等. 血管性认知功能障碍磁共振波谱成像研究[J]. 蚌埠医学院学报, 2016, 41(12): 1673-1675. LU Qiangbin, ZHANG Huiping, ZHU Zufu, et al. Study of the magnetic resonance spectroscopy in patients with vascular cognitive impairment[J]. Journal of Bengbu Medical College, 2016, 41(12): 1673-1675.
[17] Liu YY, Yang ZX, Shen ZW, et al. Magnetic resonance spectroscopy study of amnestic mild cognitive impairment and vascular cognitive impairment with no dementia[J]. Am J Alzheimers Dis Other Demen, 2014, 29(5): 474-481.
[18] Chen SQ, Cai Q, Shen YY, et al. Hydrogen proton magnetic resonance spectroscopy in multidomain amnestic mild cognitive impairment and vascular cognitive impairment without dementia[J]. Am J Alzheimers Dis Other Demen, 2016, 31(5): 422-429.
[19] 郑璐. 不同亚型aMCI的认知行为及脑影像学对比研究[D]. 北京: 北京师范大学, 2011.
[20] Hamoda HM, Makhlouf AT, Fitzsimmons J, et al. Abnormalities in thalamo-cortical connections in patients with first-episode schizophrenia: A two-tensor tractography study[J]. Brain Imaging Behav, 2018: 17. doi: 10.1007/s11682-018-9862-8.
[21] Yan T, Yu JR, Zhang YP, et al. Analysis on correlation of white matter lesion and lacunar infarction with vascular cognitive impairment[J]. Int J Clin Exp Med, 2015, 8(8): 14119-14122.
[22] Thaler A, Kliper E, Maidan I, et al. Cerebral imaging markers of GBA and LRRK2 related parkinsons disease and their first-degree unaffected relatives[J]. Brain Topogr, 2018, 31(6): 1029-1036.
[23] Moreno-Alcázar A, Gonzalvo B, Canales-Rodríguez EJ, et al. Larger gray matter volume in the basal ganglia of heavy cannabis users detected by voxel-based morphometry and subcortical volumetric analysis[J]. Front Psychiatry, 2018, 9: 175. doi: 10.3389/fpsyt.2018. 00175.
[24] 于洋, 尹昌浩. 血管性认知障碍的多模态影像学研究进展[J]. 中国全科医学, 2016, 19(29): 3629-3633. YU Yang, YIN Changhao. Research progress of multi-modality imaging of vascular cognitive disorders [J]. Chinese General Practice, 2016, 19(29): 3629-3633.
[25] Bella R, Cantone M, Lanza G, et al. Cholinergic circuitry functioning in patients with vascular cognitive impairment-no dementia[J]. Brain Stimul, 2016, 9(2): 225-233.
[26] Zhu X, Cao L, Hu X, et al. Brain metabolism assessed via proton magnetic resonance spectroscopy in patients with amnestic or vascular mild cognitive impairment[J]. Clin Neurol Neurosurg, 2015, 130: 80-85. doi: 10.1016/j.clineuro.2014.12.005.
[27] Liu Q, Zhu Z, Teipel SJ, et al. White matter damage in the cholinergic system contributes to cognitive impairment in subcortical vascular cognitive impairment, no dementia[J]. Front Aging Neurosci, 2017, 9(7): 47-56.
[28] 谭子虎, 兰汉超, 杨琼, 等. 非痴呆型血管性认知功能障碍的磁共振波谱分析特点[J]. 临床神经病学杂志, 2013, 26(5): 325-328. TAN Zihu, LAN Hanchao, YANG Qiong, et al. Magnetic resonance spectroscopy features of vascular cognitive impairment with no dementia[J]. Journal of Clinical Neurology, 2013, 26(5): 325-328.
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