基于磁共振成像的失眠症患者大脑功能研究
- 作者: Borshevetskaya A.A.1, Efimtsev A.Y.1, Trufanov G.E.1, Sviryaev Y.V.1, Amelina V.V.1, Sebelev K.I.1, Filin Y.A.1, Beregovskii D.A.1
-
隶属关系:
- Almazov National Medical Research Centre
- 期: 卷 43, 编号 3 (2024)
- 页面: 261-268
- 栏目: Original articles
- URL: https://journals.rcsi.science/RMMArep/article/view/275794
- DOI: https://doi.org/10.17816/rmmar634084
- ID: 275794
如何引用文章
全文:
详细
BACKGROUND: Insomnia has a significant impact on the quality of life of patients. Despite the progress in understanding the pathophysiological mechanisms of insomnia, the possibilities of its objective diagnosis remain insufficiently studied. This study can contribute to understanding the neural mechanisms of insomnia, contribute to the development of new diagnostic and treatment methods, and personalize therapeutic approaches to improve the quality of life of patients with insomnia disorders.
AIM: to evaluate changes in the brain connectome in patients with psychophysiological and paradoxical insomnia by performing functional magnetic resonance imaging.
MATERIALS AND METHODS: A total of 31 patients were examined who applied for a somnologist appointment at the Federal State Budgetary Institution Almazov National Medical Research Centre of the Ministry of Health of the Russian Federation with diagnosed chronic insomnia. All patients underwent polysomnographic examination using Embla N 7000 (Natus, USA) and SOMNO HD (SOMNOmedics, Germany) for one night with an assessment of the main characteristics of sleep according to the rules of AASM 2.5. Also, all study participants underwent magnetic resonance imaging of the brain on tomographs with a magnetic field induction force of 3.0 Tl at two time points. Statistical analysis of MRI data was performed using MathLab 2023a, CONN v22.a packages. Descriptive statistics, the Kolmogorov–Smirnov criterion were used for processing materials, depending on the characteristics of the data, the Mann–Whitney U-criterion and Pearson Chi-squared were used to analyze demographic data.
DISCUSSION: The study demonstrates the possibilities of functional magnetic resonance imaging in obtaining data on the functional connections of the brain in insomnia. The detected changes in the activity of various brain regions indirectly or directly involved in the regulation of sleep and wakefulness are consistent with the most common pathogenetic models of insomnia, in particular with the theory of hyperactivation and the model of sleep reactivity to stress.
CONCLUSION: The results of the study emphasize the relevance of studying functional changes in the brain in insomnia, opening up new opportunities for more accurate diagnosis and the development of personalized treatment methods.
作者简介
Anastasia A. Borshevetskaya
Almazov National Medical Research Centre
编辑信件的主要联系方式.
Email: borshevetskaya@yandex.ru
ORCID iD: 0000-0003-0613-7385
俄罗斯联邦, St. Petersburg
Alexander Yu. Efimtsev
Almazov National Medical Research Centre
Email: atralf@mail.ru
ORCID iD: 0000-0003-2249-1405
SPIN 代码: 3459-2168
MD, Dr. Sci. (Medicine), Associate Professor at the Department
俄罗斯联邦, St. PetersburgGennady E. Trufanov
Almazov National Medical Research Centre
Email: trufanovge@mail.ru
ORCID iD: 0000-0002-1611-5000
SPIN 代码: 3139-3581
MD, Dr. Sci. (Medicine), Professor
俄罗斯联邦, St. PetersburgYurii V. Sviryaev
Almazov National Medical Research Centre
Email: yusvyr@yandex.ru
ORCID iD: 0000-0002-3170-0451
MD, Dr. Sci. (Medicine)
俄罗斯联邦, St. PetersburgValeria V. Amelina
Almazov National Medical Research Centre
Email: v.kemstach@icloud.com
ORCID iD: 0000-0002-0047-3428
MD, Cand. Sci. (Medicine)
俄罗斯联邦, St. PetersburgKonstantin I. Sebelev
Almazov National Medical Research Centre
Email: ki_sebelev@list.ru
ORCID iD: 0000-0003-0075-7807
MD, Dr. Sci. (Medicine), Professor
俄罗斯联邦, St. PetersburgYana A. Filin
Almazov National Medical Research Centre
Email: filin_yana@mail.ru
ORCID iD: 0009-0009-0778-6396
俄罗斯联邦, St. Petersburg
Daniil A. Beregovskii
Almazov National Medical Research Centre
Email: bereg.daniil96@mail.ru
ORCID iD: 0009-0008-7964-7857
俄罗斯联邦, St. Petersburg
参考
- Burchakov DI, Tardov MV. Insomnia: origins, treatment and clinical vignettes. Consilium Medicum. 2020;22(2):75–82. (In Russ.) EDN: CCDHJH doi: 10.26442/20751753.2020.2.200101
- Strygin KN, Poluektov MG. Insomnia. Medical Council. 2017;(S):52–58. (In Russ.) EDN: XUYAWZ doi: 10.21518/2079-701X-2017-0-52-58
- Baymukanov AM, Bulavina IA, Petrova GA, et al. Sleep apnea in patients with atrial fibrillation. Lechebnoye delo. 2022;(2):132–136. (In Russ.) EDN: VTGDHZ doi: 10.24412/2071-5315-2022-12817
- Laugsand LE, Strand LB, Vatten LJ, et al. Insomnia symptoms and risk for unintentional fatal injuries-the HUNT Study. Sleep. 2014;37(11):1777–1786. doi: 10.5665/sleep.4170
- Poluektov MG, Akarachkova ES, Dovgan EV, et al. Management of patients with insomnia and polymorbidity: expert consensus. Zh Nevrol Psikhiatr Im S S Korsakova. 2023;123(5–2): 49–57. (In Russ.) EDN: EVPUSF doi: 10.17116/jnevro202312305249
- Rundo JV, Downey R3rd. Polysomnography. Handbook of Clinical Neurology Volume. 2019;160:381–392. doi: 10.1016/B978-0-444-64032-1.00025-4
- Surikova NA, Glukhova AS. Obstructive sleep apnea syndrome: literature review. CardioSomatics. 2023;14(1):67–76. (In Russ.) EDN: MTMATB doi: 10.17816/CS321374
- Kim SG, Bandettini PA. Principles of BOLD Functional MRI. In: Faro SH, Mohamed FB, Law M, Ulmer JL. Functional Neuroradiology: Principles and Clinical Applications. 2012. P. 293–303. doi: 10.1007/978-1-4419-0345-7_16
- Kim T, Masamoto K, Hendrich K, Kim S-G. Arterial versus total blood volume changes during neural activity-induced cerebral blood flow change: implication for BOLD fMRI. J Cereb Blood Flow Metab. 2007;27(6):1235–1247. doi: 10.1038/sj.jcbfm.9600429
- Eklund A, Nichols T, Andersson M, Knutsson H. Empirically investigating the statistical validity of SPM, FSL and AFNI for single subject fMRI analysis. In: 2015 IEEE12th International Symposium on Biomedical Imaging (ISBI). Brooklyn, NY, USA; 2015. P. 1376–1380. doi: 10.1109/ISBI.2015.7164132
- Zang ZX, Yan CG, Dong ZY, et al. Granger causality analysis implementation on MATLAB: A graphic user interface toolkit for fMRI data processing. Journal of Neuroscience Methods. 2012;203(2): 418–426. doi: 10.1016/j.jneumeth.2011.10.006
- Zigmantovich AS, Sharova EV, Kopachka MМ, et al. Changes in resting fMRI networks in patients with severe traumatic brain injury during therapeutic rhythmic transcranial magnetic stimulation (case report). Obshchaya reanimatologiya. 2022;18(2):53–64. (In Russ.) EDN: INDIYM doi: 10.15360/1813-9779-2022-2-53-64
- Etindele Sosso FA. Measuring sleep health disparities with polysomnography: a systematic review of preliminary findings. Clocks & Sleep. 2022;4(1):80–87. doi: 10.3390/clockssleep4010009
补充文件
