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Brain Regional Homogeneity Changes in Cirrhotic Patients with or without Hepatic Encephalopathy Revealed by Multi-Frequency Bands Analysis Based on Resting-State Functional MRI

  • Zhang, Gaoyan (Tianjin Key Laboratory of Cognitive Computing and Application, School of Computer Science and Technology, Tianjin University) ;
  • Cheng, Yue (Department of Radiology, Tianjin First Central Hospital) ;
  • Shen, Wen (Department of Radiology, Tianjin First Central Hospital) ;
  • Liu, Baolin (Tianjin Key Laboratory of Cognitive Computing and Application, School of Computer Science and Technology, Tianjin University) ;
  • Huang, Lixiang (Department of Radiology, Tianjin First Central Hospital) ;
  • Xie, Shuangshuang (Department of Radiology, Tianjin First Central Hospital)
  • Received : 2017.05.20
  • Accepted : 2017.11.23
  • Published : 2018.06.01

Abstract

Objective: To investigate brain regional homogeneity (ReHo) changes of multiple sub-frequency bands in cirrhotic patients with or without hepatic encephalopathy using resting-state functional MRI. Materials and Methods: This study recruited 46 cirrhotic patients without clinical hepatic encephalopathy (noHE), 38 cirrhotic patients with clinical hepatic encephalopathy (HE), and 37 healthy volunteers. ReHo differences were analyzed in slow-5 (0.010-0.027 Hz), slow-4 (0.027-0.073 Hz), and slow-3 (0.073-0.198 Hz) bands. Routine analysis of (0.010-0.080 Hz) band was used as a benchmark. Associations of abnormal ReHo values in each frequency band with neuropsychological scores and blood ammonia level were analyzed. Pattern classification analyses were conducted to determine whether ReHo differences in each band could differentiate the three groups of subjects (patients with or without hepatic encephalopathy and healthy controls). Results: Compared to routine analysis, more differences between HE and noHE were observed in slow-5 and slow-4 bands (p < 0.005, cluster > 12, overall corrected p < 0.05). Sub-frequency band analysis also showed that ReHo abnormalities were frequency-dependent (overall corrected p < 0.05). In addition, ReHo abnormalities in each sub-band were correlated with blood ammonia level and neuropsychological scores, especially in the left inferior parietal lobe (overall corrected p < 0.05 for all frequency bands). Pattern classification analysis demonstrated that ReHo differences in lower slow-5 and slow-4 bands (both p < 0.05) and higher slow-3 band could differentiate the three groups (p < 0.05). Compared to routine analysis, ReHo features in slow-4 band obtained better classification accuracy (89%). Conclusion: Cirrhotic patients showed frequency-dependent changes in ReHo. Sub-frequency band analysis is important for understanding HE and clinical monitoring.

Keywords

Acknowledgement

Supported by : Tianjin University, National Natural Science Foundation of China

References

  1. Hsu TW, Wu CW, Cheng YF, Chen HL, Lu CH, Cho KH, et al. Impaired small-world network efficiency and dynamic functional distribution in patients with cirrhosis. PLoS One 2012;7:e35266 https://doi.org/10.1371/journal.pone.0035266
  2. Alonso J, Cordoba J, Rovira A. Brain magnetic resonance in hepatic encephalopathy. Semin Ultrasound CT MR 2014;35:136-152 https://doi.org/10.1053/j.sult.2013.09.008
  3. Cheng Y, Zhang G, Shen W, Huang LX, Zhang L, Xie SS, et al. Impact of previous episodes of hepatic encephalopathy on short-term brain function recovery after liver transplantation: a functional connectivity strength study. Metab Brain Dis 2018;33:237-249 https://doi.org/10.1007/s11011-017-0155-5
  4. McPhail MJ, Patel NR, Taylor-Robinson SD. Brain imaging and hepatic encephalopathy. Clin Liver Dis 2012;16:57-72 https://doi.org/10.1016/j.cld.2011.12.001
  5. Park SH, Han PK, Choi SH. Physiological and functional magnetic resonance imaging using balanced steady-state free precession. Korean J Radiol 2015;16:550-559 https://doi.org/10.3348/kjr.2015.16.3.550
  6. Lv XF, Ye M, Han LJ, Zhang XL, Cai PQ, Jiang GH, et al. Abnormal baseline brain activity in patients with HBV-related cirrhosis without overt hepatic encephalopathy revealed by resting-state functional MRI. Metab Brain Dis 2013;28:485-492 https://doi.org/10.1007/s11011-013-9420-4
  7. Chen HJ, Zhu XQ, Jiao Y, Li PC, Wang Y, Teng GJ. Abnormal baseline brain activity in low-grade hepatic encephalopathy: a resting-state fMRI study. J Neurol Sci 2012;318:140-145 https://doi.org/10.1016/j.jns.2012.02.019
  8. Zhang G, Cheng Y, Shen W, Liu B, Huang L, Xie S. The shortterm effect of liver transplantation on the low-frequency fluctuation of brain activity in cirrhotic patients with and without overt hepatic encephalopathy. Brain Imaging Behav 2017;11:1849-1861 https://doi.org/10.1007/s11682-016-9659-6
  9. Zhang G, Cheng Y, Liu B. Abnormalities of voxel-based wholebrain functional connectivity patterns predict the progression of hepatic encephalopathy. Brain Imaging Behav 2017;11:784-796 https://doi.org/10.1007/s11682-016-9553-2
  10. Chen HJ, Zhu XQ, Shu H, Yang M, Zhang Y, Ding J, et al. Structural and functional cerebral impairments in cirrhotic patients with a history of overt hepatic encephalopathy. Eur J Radiol 2012;81:2463-2469 https://doi.org/10.1016/j.ejrad.2011.10.008
  11. Lv XF, Qiu YW, Tian JZ, Xie CM, Han LJ, Su HH, et al. Abnormal regional homogeneity of resting-state brain activity in patients with HBV-related cirrhosis without overt hepatic encephalopathy. Liver Int 2013;33:375-383 https://doi.org/10.1111/liv.12096
  12. Lin WC, Hsu TW, Chen CL, Lu CH, Chen HL, Cheng YF. Resting state-fMRI with ReHo analysis as a non-invasive modality for the prognosis of cirrhotic patients with overt hepatic encephalopathy. PLoS One 2015;10:e0126834 https://doi.org/10.1371/journal.pone.0126834
  13. Song X, Zhou S, Zhang Y, Liu Y, Zhu H, Gao JH. Frequencydependent modulation of regional synchrony in the human brain by eyes open and eyes closed resting-states. PLoS One 2015;10:e0141507 https://doi.org/10.1371/journal.pone.0141507
  14. Qian L, Zhang Y, Zheng L, Shang Y, Gao JH, Liu Y. Frequency dependent topological patterns of resting-state brain networks. PLoS One 2015;10:e0124681 https://doi.org/10.1371/journal.pone.0124681
  15. Zuo XN, Di Martino A, Kelly C, Shehzad ZE, Gee DG, Klein DF, et al. The oscillating brain: complex and reliable. Neuroimage 2010;49:1432-1445 https://doi.org/10.1016/j.neuroimage.2009.09.037
  16. He BJ, Zempel JM, Snyder AZ, Raichle ME. The temporal structures and functional significance of scale-free brain activity. Neuron 2010;66:353-369 https://doi.org/10.1016/j.neuron.2010.04.020
  17. Baria AT, Baliki MN, Parrish T, Apkarian AV. Anatomical and functional assemblies of brain BOLD oscillations. J Neurosci 2011;31:7910-7919 https://doi.org/10.1523/JNEUROSCI.1296-11.2011
  18. Wang P, Li R, Yu J, Huang Z, Li J. Frequency-dependent brain regional homogeneity alterations in patients with mild cognitive impairment during working memory state relative to resting state. Front Aging Neurosci 2016;8:60
  19. Buzsaki G, Draguhn A. Neuronal oscillations in cortical networks. Science 2004;304:1926-1929 https://doi.org/10.1126/science.1099745
  20. Pugh RN, Murray-Lyon IM, Dawson JL, Pietroni MC, Williams R. Transection of the oesophagus for bleeding oesophageal varices. Br J Surg 1973;60:646-649 https://doi.org/10.1002/bjs.1800600817
  21. Atterbury CE, Maddrey WC, Conn HO. Neomycin-sorbitol and lactulose in the treatment of acute portal-systemic encephalopathy. A controlled, double-blind clinical trial. Am J Dig Dis 1978;23:398-406 https://doi.org/10.1007/BF01072921
  22. Cheng Y, Huang L, Zhang X, Zhong J, Ji Q, Xie S, et al. Liver transplantation nearly normalizes brain spontaneous activity and cognitive function at 1 month: a resting-state functional MRI study. Metab Brain Dis 2015;30:979-988 https://doi.org/10.1007/s11011-015-9657-1
  23. Yan CG, Wang XD, Zuo XN, Zang YF. DPABI: data processing & analysis for (resting-state) brain imaging. Neuroinformatics 2016;14:339-351 https://doi.org/10.1007/s12021-016-9299-4
  24. Jenkinson M, Bannister P, Brady M, Smith S. Improved optimization for the robust and accurate linear registration and motion correction of brain images. Neuroimage 2002;17:825-841 https://doi.org/10.1006/nimg.2002.1132
  25. Song X, Zhang Y, Liu Y. Frequency specificity of regional homogeneity in the resting-state human brain. PLoS One 2014;9:e86818 https://doi.org/10.1371/journal.pone.0086818
  26. Zang Y, Jiang T, Lu Y, He Y, Tian L. Regional homogeneity approach to fMRI data analysis. Neuroimage 2004;22:394-400 https://doi.org/10.1016/j.neuroimage.2003.12.030
  27. Qi R, Zhang LJ, Chen HJ, Zhong J, Luo S, Ke J, et al. Role of local and distant functional connectivity density in the development of minimal hepatic encephalopathy. Sci Rep 2015;5:13720 https://doi.org/10.1038/srep13720
  28. Silk TJ, Bellgrove MA, Wrafter P, Mattingley JB, Cunnington R. Spatial working memory and spatial attention rely on common neural processes in the intraparietal sulcus. Neuroimage 2010;53:718-724 https://doi.org/10.1016/j.neuroimage.2010.06.068

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