Share:
Share this content in WeChat
X
Clinical Article
Degree centrality of brain network in heroin addicts treated with methadone maintenance: a resting-state functional magnetic resonance imaging study
XUE Jiuhua  CHEN Jiajie  CAI Guanke  SHI Hong  LIU Wei  LIU Yan  MENG Yan  LI Wei  WANG Wei  LI Qiang 

Cite this article as: Xue JH, Chen JJ, Cai GK, et al. Degree centrality of brain network in heroin addicts treated with methadone maintenance: a resting-state functional magnetic resonance imaging study. Chin J Magn Reson Imaging, 2020, 11(11): 961-965. DOI:10.12015/issn.1674-8034.2020.11.001.


[Abstract] Objective: To explore the effect of methadone maintenance treatment on the core nodes of the brain network of heroin addicts.Materials and Methods: Twenty-six heroin addicts during short-term abstinence (HA), 25 heroin addicts during methadone maintenance treatment (MMT) and 42 health controls (HC) were recruited. The resting-state fMRI data of all subjects were collected. Based on the theory of graph theory, the degree centrality (DC) of whole brains of the three groups were compared. The correlations between the DC values and history of heroin addiction and MMT were also analyzed.Results: The DC value of left medial frontal cortex and bilateral inferior parietal lobules in MMT and HC group was significantly lower than that in HA group. The DC value of left anterior precuneus lobe in MMT group was significantly higher than that in HC group. It was found that the DC value of left orbital frontal gyrus and left middle frontal gyrus in HA group and MMT group was significantly higher than that in HC group. The right insular lobe in MMT group was significantly lower than that in HC group and HA group (P<0.001, P<0.05 after Alphasim correction, voxels> 25).Conclusions: The methadone maintenance treatment is beneficial to the recovery of self-awareness, self-monitoring of heroin addicts. However, there are still some abnormalities such as salience, decision-making and inhibitory control, which may take longer or other comprehensive interventions to recover.
[Keywords] methadone maintenance treatment;heroin addiction;degree of centrality;brain network;functional magnetic resonance

XUE Jiuhua Department of Radiology, Tangdu Hospital, Air Force military Medical University, Xi'an 710038, China; Department of Radiology, Xi'an First Hospital, Xi'an 710002, China

CHEN Jiajie Department of Radiology, Tangdu Hospital, Air Force military Medical University, Xi'an 710038, China

CAI Guanke Department of Radiology, Tangdu Hospital, Air Force military Medical University, Xi'an 710038, China

SHI Hong Department of Radiology, Tangdu Hospital, Air Force military Medical University, Xi'an 710038, China; Department of Radiology, Xi'an First Hospital, Xi'an 710002, China

LIU Wei Department of Radiology, Tangdu Hospital, Air Force military Medical University, Xi'an 710038, China; Department of Radiology, Xi'an First Hospital, Xi'an 710002, China

LIU Yan Department of Radiology, Tangdu Hospital, Air Force military Medical University, Xi'an 710038, China

MENG Yan Department of Advertisinng , Shaanxi Youth Vocational College, Xi'an 710068, China

LI Wei Department of Radiology, Tangdu Hospital, Air Force military Medical University, Xi'an 710038, China

WANG Wei Department of Radiology, Tangdu Hospital, Air Force military Medical University, Xi'an 710038, China

LI Qiang* Department of Radiology, Tangdu Hospital, Air Force military Medical University, Xi'an 710038, China

*Correspondence to: Li Q, E-mail: tdqiangqiang@foxmail.com

Conflicts of interest   None.

ACKNOWLEDGMENTS  National Natural Science Foundation of China No. 81671661
Received  2020-06-01
Accepted  2020-09-28
DOI: 10.12015/issn.1674-8034.2020.11.001
Cite this article as: Xue JH, Chen JJ, Cai GK, et al. Degree centrality of brain network in heroin addicts treated with methadone maintenance: a resting-state functional magnetic resonance imaging study. Chin J Magn Reson Imaging, 2020, 11(11): 961-965. DOI:10.12015/issn.1674-8034.2020.11.001.

[1]
Fazel S, Yoon IA, Hayes AJ. Substance use disorders in prisoners: an updated systematic review and meta-regression analysis in recently incarcerated men and women. Addiction, 2017, 112(10): 1725-1739. DOI: 10.1111/add.13877
[2]
Volkow ND, Koroshetz WJ. The role of neurologists in tackling the opioid epidemic. Nature reviews. Neurology, 2019, 15(5): 301-305. DOI: 10.1038/s41582-019-0146-8
[3]
Malta M, Varatharajan T, Russell C, et al. Opioid-related treatment, interventions, and outcomes among incarcerated persons: a systematic review. PLoS Med, 2019, 16 (12): e1003002. DOI: 10.1371/journal.pmed.1003002
[4]
江桂华,汪天悦,邱迎伟,等.美沙酮对海洛因成瘾患者脑功能影响的静息态功能磁共振成像研究.功能与分子医学影像学(电子版), 2014,3 (4): 498-502. DOI: 10.3969/j.issn.2095-2252.2014.04.002
[5]
Stone AC, Carroll JJ, Rich JD, et al. Methadone maintenance treatment among patients exposed to illicit fentanyl in Rhode Island: Safety, dose, retention, and relapse at 6 months. Drug Alcoh Depend, 2018, 192(11): 94-97. DOI: 10.1016/j.drugalcdep.2018.07.019
[6]
Zhou K, Zhuang G. Retention in methadone maintenance treatment in mainland China, 2004-2012: a literature review. Addictive behaviors, 2014, 39(1): 22-29. DOI: 10.1016/j.addbeh.2013.09.001
[7]
Zhou K, Li H, Wei X, et al. Relationships between perceived social support and retention among patients in methadone maintenance treatment in mainland China. Psychol health Med, 2017, 22 (4): 493-500. DOI: 10.1080/13548506.2016.1164873
[8]
Corre J, van Zessen R, Loureiro M, et al. Dopamine neurons projecting to medial shell of the nucleus accumbens drive heroin reinforcement. eLife, 2018, 30(10): e39945. DOI: 10.7554/eLife.39945
[9]
Yuan K, Cao L, Xue YX, et al. Basolateral amygdala is required for reconsolidation updating of heroin-associated memory after prolonged withdrawal. Addict Biol, 2019: e12793. DOI: 10.1111/adb.12793
[10]
Teklezgi BG, Pamreddy A, Baijnath S, et al. Time-dependent regional brain distribution of methadone and naltrexone in the treatment of opioid addiction. Addict Biol, 2019, 24 (3): 438-446. DOI: 10.1111/adb.12609
[11]
Baler RD, Volkow ND. Drug addiction: the neurobiology of disrupted self-control. Trends Mol Med, 2006, 12 (12): 559-566. DOI: 10.1016/j.molmed.2006.10.005
[12]
Li Q, Li Z, Li W, et al. Disrupted default mode network and basal craving in male heroin-dependent individuals: a resting-state fMRI study. J Clin Psychiatry, 2016, 77(10): e1211-e1217. DOI: 10.4088/JCP.15m09965
[13]
Li Q, Liu J, Wang W, et al. Disrupted coupling of large-scale networks is associated with relapse behaviour in heroin-dependent men. J Psychiatry Neurosci, 2018, 43(1): 48-57. DOI: 10.1503/jpn.170011
[14]
Stam CJ. Modern network science of neurological disorders. Nature reviews. Neuroscience, 2014, 15 (10): 683-695. DOI: 10.1038/nrn3801
[15]
Luo X, Guo L, Dai XJ, et al. Abnormal intrinsic functional hubs in alcohol dependence: evidence from a voxelwise degree centrality analysis. Neuropsychiatr Dis treat, 2017, 13(7): 2011-2020. DOI: 10.2147/NDT.S142742
[16]
Hua K, Wang T, Li C, et al. Abnormal degree centrality in chronic users of codeine-containing cough syrups: a resting-state functional magnetic resonance imaging study. NeuroImage. Clinical, 2018, 19(6): 775-781. DOI: 10.1016/j.nicl.2018.06.003
[17]
Yan CG, Wang XD, Zuo XN, et al. DPABI: data processing & analysis for (resting-state) brain imaging. Neuroinformatics, 2016, 14 (3): 339-351. DOI: 10.1007/s12021-016-9299-4
[18]
Takeuchi H, Taki Y, Nouchi R, et al. Degree centrality and fractional amplitude of low-frequency oscillations associated with stroop interference. NeuroImage, 2015, 119(10): 197-209. DOI: 10.1016/j.neuroimage.2015.06.058
[19]
Zuo XN, Ehmke R, Mennes M, et al. Network centrality in the human functional connectome. Cerebral cortex, 2012, 22 (8): 1862-1875. DOI: 10.1093/cercor/bhr269
[20]
Murphy K, Birn RM, Handwerker DA, et al. The impact of global signal regression on resting state correlations: are anti-correlated networks introduced? NeuroImage, 2009, 44 (3): 893-905. DOI: 10.1016/j.neuroimage.2008.09.036
[21]
Kuo LW, Lin PS, Lin SY, et al. Functional correlates of resting-state connectivity in the default mode network of heroin users on methadone treatment and medication-free therapeutic community program. Front Psychiatry, 2019, 10(6): 381. DOI: 10.3389/fpsyt.2019.00381
[22]
Ma X, Qiu Y, Tian J, et al. Aberrant default-mode functional and structural connectivity in heroin-dependent individuals. PloS One, 2015, 10(4): e0120861. DOI: 10.1371/journal.pone.0120861
[23]
Ma N, Liu Y, Fu XM, et al. Abnormal brain default-mode network functional connectivity in drug addicts. PloS One, 2011, 6(1): e16560. DOI: 10.1371/journal.pone.0016560
[24]
刘彬,黄飚,王卫卫,等.全臂丛损伤后脑网络度中心度改变的fMRI研究.临床放射学杂志, 2017, 36 (12): 1736-1739. DOI: 10.13437/j.cnki.jcr.2017.12.002
[25]
Schoenbaum G, Shaham Y. The role of orbitofrontal cortex in drug addiction: a review of preclinical studies. Biological psychiatry, 2008, 63(3): 256-262. DOI: 10.1016/j.biopsych.2007.06.003
[26]
Zhang R, Jiang G, Tian J, et al. Abnormal white matter structural networks characterize heroin-dependent individuals: a network analysis. Addiction biology, 2016, 21(3): 667-678. DOI: 10.1111/adb.12234
[27]
任其欢,董玲萍,刘薇薇,等.美沙酮维持治疗对海洛因依赖者冲动决策的影响.中国药物依赖性杂志, 2019, 28 (5): 366-370. DOI: 10.13936/j.cnki.cjdd1992.2019.05.008
[28]
Chang H, Li W, Li Q, et al. Regional homogeneity changes between heroin relapse and non-relapse patients under methadone maintenance treatment: a resting-state fMRI study. BMC Neurol, 2016, 16 (1): 145. DOI: 10.1186/s12883-016-0659-3
[29]
Yarkoni T, Poldrack RA, Nichols TE, et al. Large-scale automated synthesis of human functional neuroimaging data. Nature methods, 2011, 8(8): 665-670. DOI: 10.1038/nmeth.1635

PREV Advances in clinical research of radiomics in bone tumors
NEXT Amplitude of low-frequency fluctuations of resting-state functional MRI in multiple system atrophy patients with depression
  



Tel & Fax: +8610-67113815    E-mail: editor@cjmri.cn