Skip to main content

Advertisement

Log in

Altered structural connectivity of pain-related brain network in burning mouth syndrome—investigation by graph analysis of probabilistic tractography

  • Functional Neuroradiology
  • Published:
Neuroradiology Aims and scope Submit manuscript

Abstract

Purpose

Burning mouth syndrome (BMS) is a chronic intraoral pain syndrome featuring idiopathic oral pain and burning discomfort despite clinically normal oral mucosa. The etiology of chronic pain syndrome is unclear, but preliminary neuroimaging research has suggested the alteration of volume, metabolism, blood flow, and diffusion at multiple brain regions. According to the neuromatrix theory of Melzack, pain sense is generated in the brain by the network of multiple pain-related brain regions. Therefore, the alteration of pain-related network is also assumed as an etiology of chronic pain. In this study, we investigated the brain network of BMS brain by using probabilistic tractography and graph analysis.

Methods

Fourteen BMS patients and 14 age-matched healthy controls underwent 1.5T MRI. Structural connectivity was calculated in 83 anatomically defined regions with probabilistic tractography of 60-axis diffusion tensor imaging and 3D T1-weighted imaging. Graph theory network analysis was used to evaluate the brain network at local and global connectivity.

Results

In BMS brain, a significant difference of local brain connectivity was recognized at the bilateral rostral anterior cingulate cortex, right medial orbitofrontal cortex, and left pars orbitalis which belong to the medial pain system; however, no significant difference was recognized at the lateral system including the somatic sensory cortex. A strengthened connection of the anterior cingulate cortex and medial prefrontal cortex with the basal ganglia, thalamus, and brain stem was revealed.

Conclusion

Structural brain network analysis revealed the alteration of the medial system of the pain-related brain network in chronic pain syndrome.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

Abbreviations

BMS:

Burning mouth syndrome

ACC:

Anterior cingulate cortex

PFC:

Prefrontal cortex

References

  1. Headache Classification Committee of the International Headache Society (IHS) (2013) The International Classification of Headache Disorders, 3rd edition (beta version). Cephalalgia 33:629–808. doi:10.1177/0333102413485658

    Article  Google Scholar 

  2. Gao J, Chen L, Zhou J, Peng J (2008) A case-control study on etiological factors involved in patients with burning mouth syndrome. J Oral Pathol Med 38:24–28. doi:10.1111/j.1600-0714.2008.00708.x

    Article  Google Scholar 

  3. Gorsky M, Silverman S, Chinn H (1991) Clinical characteristics and management outcome in the burning mouth syndrome. An open study of 130 patients. Oral Surg Oral Med Oral Pathol 72:192–195

    Article  CAS  PubMed  Google Scholar 

  4. Gurvits GE, Tan A (2013) Burning mouth syndrome. World J Gastroenterol 19:665–672. doi:10.3748/wjg.v19.i5.665

    Article  PubMed  PubMed Central  Google Scholar 

  5. Kohorst JJ, Bruce AJ, Torgerson RR et al (2014) A population-based study of the incidence of burning mouth syndrome. Mayo Clin Proc 89:1545–1552. doi:10.1016/j.mayocp.2014.05.018

    Article  PubMed  PubMed Central  Google Scholar 

  6. Renton T (2011) Burning mouth syndrome. Rev Pain 5:12–17. doi:10.1177/204946371100500403

    PubMed  PubMed Central  Google Scholar 

  7. Adamo D, Celentano A, Ruoppo E et al (2015) The relationship between sociodemographic characteristics and clinical features in burning mouth syndrome. Pain Med 16:2171–2179. doi:10.1111/pme.12808

    Article  PubMed  Google Scholar 

  8. Forssell H, Jääskeläinen S, Tenovuo O, Hinkka S (2002) Sensory dysfunction in burning mouth syndrome. Pain 99:41–47. doi:10.1016/S0304-3959(02)00052-0

    Article  PubMed  Google Scholar 

  9. Grushka M, Epstein JB, Gorsky M (2003) Burning mouth syndrome and other oral sensory disorders: a unifying hypothesis. Pain Res Manag 8:133–135

    Article  PubMed  Google Scholar 

  10. Albuquerque RJC, de Leeuw R, Carlson CR et al (2006) Cerebral activation during thermal stimulation of patients who have burning mouth disorder: an fMRI study. Pain 122:223–234. doi:10.1016/j.pain.2006.01.020

    Article  PubMed  Google Scholar 

  11. Forssell H, Jääskeläinen S, List T et al (2015) An update on pathophysiological mechanisms related to idiopathic oro-facial pain conditions with implications for management. J Oral Rehabil 42:300–322. doi:10.1111/joor.12256

    Article  CAS  PubMed  Google Scholar 

  12. Lauria G, Majorana A, Borgna M et al (2005) Trigeminal small-fiber sensory neuropathy causes burning mouth syndrome. Pain 115:332–337. doi:10.1016/j.pain.2005.03.028

    Article  PubMed  Google Scholar 

  13. Yilmaz Z, Renton T, Yiangou Y et al (2007) Burning mouth syndrome as a trigeminal small fibre neuropathy: increased heat and capsaicin receptor TRPV1 in nerve fibres correlates with pain score. J Clin Neurosci 14:864–871. doi:10.1016/j.jocn.2006.09.002

    Article  CAS  PubMed  Google Scholar 

  14. Eliav E, Kamran B, Schaham R et al (2007) Evidence of chorda tympani dysfunction in patients with burning mouth syndrome. J Am Dent Assoc 138:628–633

    Article  PubMed  Google Scholar 

  15. Nasri-Heir C, Gomes J, Heir GM et al (2011) The role of sensory input of the chorda tympani nerve and the number of fungiform papillae in burning mouth syndrome. Oral Surg Oral Med Oral Pathol Oral Radiol Endodontol 112:65–72. doi:10.1016/j.tripleo.2011.02.035

    Article  Google Scholar 

  16. Svensson P, Bjerring P, Arendt-Nielsen L, Kaaber S (1993) Sensory and pain thresholds to orofacial argon laser stimulation in patients with chronic burning mouth syndrome. Clin J Pain 9:207–215

    Article  CAS  PubMed  Google Scholar 

  17. Sinding C, Gransjøen AM, Schlumberger G et al (2016) Grey matter changes of the pain matrix in patients with burning mouth syndrome. Eur J Neurosci 43:997–1005. doi:10.1111/ejn.13156

    Article  PubMed  Google Scholar 

  18. Shinozaki T, Imamura Y, Kohashi R et al (2016) Spatial and temporal brain responses to noxious heat thermal stimuli in burning mouth syndrome. J Dent Res 95:1138–1146. doi:10.1177/0022034516653580

    Article  CAS  PubMed  Google Scholar 

  19. Khan SA, Keaser ML, Meiller TF, Seminowicz DA (2014) Altered structure and function in the hippocampus and medial prefrontal cortex in patients with burning mouth syndrome. Pain 155:1472–1480. doi:10.1016/j.pain.2014.04.022

    Article  PubMed  Google Scholar 

  20. Kupers R, Kehlet H (2006) Brain imaging of clinical pain states: a critical review and strategies for future studies. Lancet Neurol 5:1033–1044. doi:10.1016/S1474-4422(06)70624-X

    Article  PubMed  Google Scholar 

  21. Seifert F, Maihöfner C (2009) Central mechanisms of experimental and chronic neuropathic pain: findings from functional imaging studies. Cell Mol Life Sci 66:375–390. doi:10.1007/s00018-008-8428-0

    Article  CAS  PubMed  Google Scholar 

  22. Price DD (2000) Psychological and neural mechanisms of the affective dimension of pain. Science 288:1769–1772. doi:10.1126/science.288.5472.1769

    Article  CAS  PubMed  Google Scholar 

  23. Apkarian AV, Bushnell MC, Treede R-D, Zubieta J-K (2005) Human brain mechanisms of pain perception and regulation in health and disease. Eur J Pain 9:463–484. doi:10.1016/j.ejpain.2004.11.001

    Article  PubMed  Google Scholar 

  24. Melzack R (2001) Pain and the neuromatrix in the brain. J Dent Educ 65:1378–1382

    CAS  PubMed  Google Scholar 

  25. Van Dijk KRA, Hedden T, Venkataraman A et al (2010) Intrinsic functional connectivity as a tool for human connectomics: theory, properties, and optimization. J Neurophysiol 103:297–321. doi:10.1152/jn.00783.2009

    Article  PubMed  Google Scholar 

  26. Whitfield-Gabrieli S, Nieto-Castanon A (2012) Conn: a functional connectivity toolbox for correlated and anticorrelated brain networks. Brain Connectivity 2:125–141. doi:10.1089/brain.2012.0073

    Article  PubMed  Google Scholar 

  27. Behrens TEJ, Woolrich MW, Jenkinson M et al (2003) Characterization and propagation of uncertainty in diffusion-weighted MR imaging. Magn Reson Med 50:1077–1088. doi:10.1002/mrm.10609

    Article  CAS  PubMed  Google Scholar 

  28. Nucifora PGP, Verma R, Lee S-K, Melhem ER (2007) Diffusion-tensor MR imaging and tractography: exploring brain microstructure and connectivity. Radiology 245:367–384. doi:10.1148/radiol.2452060445

    Article  PubMed  Google Scholar 

  29. Behrens TEJ, Berg HJ, Jbabdi S et al (2007) Probabilistic diffusion tractography with multiple fibre orientations: what can we gain? NeuroImage 34:144–155. doi:10.1016/j.neuroimage.2006.09.018

    Article  CAS  PubMed  Google Scholar 

  30. Cao Q, Shu N, An L et al (2013) Probabilistic diffusion tractography and graph theory analysis reveal abnormal white matter structural connectivity networks in drug-naive boys with attention deficit/hyperactivity disorder. J Neurosci 33:10676–10687. doi:10.1523/JNEUROSCI.4793-12.2013

    Article  CAS  PubMed  Google Scholar 

  31. Koike K, Shinozaki T, Hara K et al (2014) Immune and endocrine function in patients with burning mouth syndrome. Clin J Pain 30:168–173. doi:10.1097/AJP.0b013e31828c4bf1

    PubMed  Google Scholar 

  32. Yamada H, Abe O, Shizukuishi T et al (2014) Efficacy of distortion correction on diffusion imaging: comparison of FSL eddy and eddy_correct using 30 and 60 directions diffusion encoding. PLoS One. doi:10.1371/journal.pone.0112411.s009

    Google Scholar 

  33. Daducci A, Gerhard S, Griffa A et al (2012) The connectome mapper: an open-source processing pipeline to map connectomes with MRI. PLoS One 7:e48121. doi:10.1371/journal.pone.0048121

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Desikan RS, Ségonne F, Fischl B et al (2006) An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest. NeuroImage 31:968–980. doi:10.1016/j.neuroimage.2006.01.021

    Article  PubMed  Google Scholar 

  35. Rubinov M, Sporns O (2010) Complex network measures of brain connectivity: uses and interpretations. NeuroImage 52:1059–1069. doi:10.1016/j.neuroimage.2009.10.003

    Article  PubMed  Google Scholar 

  36. Rubinov M, Sporns O (2011) Weight-conserving characterization of complex functional brain networks. NeuroImage 56:2068–2079. doi:10.1016/j.neuroimage.2011.03.069

    Article  PubMed  Google Scholar 

  37. Boccaletti S, Latora V, Moreno Y, Chavez M (2006) Complex networks: structure and dynamics. Phys Rep 424:175–308. doi:10.1016/j.physrep.2005.10.009

    Article  Google Scholar 

  38. Albert R, Barabási A-L (2002) Statistical mechanics of complex networks. Rev Mod Phys 74:47–97. doi:10.1103/RevModPhys.74.47

    Article  Google Scholar 

  39. Borgatti SP, Mehra A, Brass DJ, Labianca G (2009) Network analysis in the social sciences. Science 323:892–895. doi:10.1126/science.1165821

    Article  CAS  PubMed  Google Scholar 

  40. Newman M (2003) The structure and function of complex networks. SIAM Rev 45:167–256

    Article  Google Scholar 

  41. Bullmore E, Sporns O (2009) Complex brain networks: graph theoretical analysis of structural and functional systems. Nat Rev Neurosci 10:186–198. doi:10.1038/nrn2575

    Article  CAS  PubMed  Google Scholar 

  42. Achard S (2006) A resilient, low-frequency, small-world human brain functional network with highly connected association cortical hubs. J Neurosci 26:63–72. doi:10.1523/JNEUROSCI.3874-05.2006

    Article  CAS  PubMed  Google Scholar 

  43. Watts DJ, Strogatz SH (1998) Collective dynamics of small-world networks. Nature 393:440–442. doi:10.1038/30918

    Article  CAS  PubMed  Google Scholar 

  44. Woolf CJ (2010) What is this thing called pain? J Clin Invest 120:3742. doi:10.1172/JCI45178

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Chen J (2011) History of pain theories. Neurosci Bull 27:343–350. doi:10.1007/s12264-011-0139-0

    Article  PubMed  Google Scholar 

  46. May A (2007) Neuroimaging: visualising the brain in pain. Neurol Sci 28:S101–S107. doi:10.1007/s10072-007-0760-x

    Article  PubMed  Google Scholar 

  47. Moisset X, Bouhassira D (2007) Brain imaging of neuropathic pain. NeuroImage 37(Suppl 1):S80–S88. doi:10.1016/j.neuroimage.2007.03.054

    Article  PubMed  Google Scholar 

  48. Luo C, Kuner T, Kuner R (2014) Synaptic plasticity in pathological pain. Trends Neurosci 37:343–355. doi:10.1016/j.tins.2014.04.002

    Article  CAS  PubMed  Google Scholar 

  49. Borsook D, Moulton EA, Schmidt KF, Becerra LR (2007) Neuroimaging revolutionizes therapeutic approaches to chronic pain. Mol Pain 3:1. doi:10.1186/1744-8069-3-25

    Google Scholar 

  50. Rainville P (1997) Pain affect encoded in human anterior cingulate but not somatosensory cortex. Science 277:968–971. doi:10.1126/science.277.5328.968

    Article  CAS  PubMed  Google Scholar 

  51. Peyron R, Laurent B, García-Larrea L (2000) Functional imaging of brain responses to pain. A review and meta-analysis (2000). Neurophysiol Clin 30:263–288

    Article  CAS  PubMed  Google Scholar 

  52. Ghatan PH, Hsieh JC, Wirsen-Meurling A et al (1995) Brain activation induced by the perceptual maze test: a PET study of cognitive performance. NeuroImage 2:112–124. doi:10.1006/nimg.1995.1014

    Article  CAS  PubMed  Google Scholar 

  53. Wager TD (2004) Placebo-induced changes in fMRI in the anticipation and experience of pain. Science 303:1162–1167. doi:10.1126/science.1093065

    Article  CAS  PubMed  Google Scholar 

  54. Amodio DM, Frith CD (2006) Meeting of minds: the medial frontal cortex and social cognition. Nat Rev Neurosci 7:268–277. doi:10.1038/nrn1884

    Article  CAS  PubMed  Google Scholar 

  55. May A (2008) Chronic pain may change the structure of the brain. Pain 137:7–15. doi:10.1016/j.pain.2008.02.034

    Article  PubMed  Google Scholar 

  56. Baliki MN, Geha PY, Jabakhanji R et al (2008) A preliminary fMRI study of analgesic treatment in chronic back pain and knee osteoarthritis. Mol Pain 4:47. doi:10.1186/1744-8069-4-47

    Article  PubMed  PubMed Central  Google Scholar 

  57. Apkarian AV, Sosa Y, Sonty S et al (2004) Chronic back pain is associated with decreased prefrontal and thalamic gray matter density. J Neurosci 24:10410–10415. doi:10.1523/JNEUROSCI.2541-04.2004

    Article  CAS  PubMed  Google Scholar 

  58. Grushka M (1987) Clinical features of burning mouth syndrome. Oral Surg Oral Med Oral Pathol 63:30–36. doi:10.1016/0030-4220(87)90336-7

    Article  CAS  PubMed  Google Scholar 

  59. Kong J, Jensen K, Loiotile R et al (2013) Functional connectivity of the frontoparietal network predicts cognitive modulation of pain. Pain 154:459–467. doi:10.1016/j.pain.2012.12.004

    Article  PubMed  Google Scholar 

  60. Bushnell MC, Čeko M, Low LA (2013) Cognitive and emotional control of pain and its disruption in chronic pain. Nat Rev Neurosci 14:502–511. doi:10.1038/nrn3516

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Catani M, Thiebaut de Schotten M, Slater D, Dell’Acqua F (2013) Connectomic approaches before the connectome. NeuroImage 80:2–13. doi:10.1016/j.neuroimage.2013.05.109

    Article  CAS  PubMed  Google Scholar 

  62. Talbot JD, Marrett S, Evans AC et al (1991) Multiple representations of pain in human cerebral cortex. Science 251:1355–1358

    Article  CAS  PubMed  Google Scholar 

  63. Apkarian VA (1995) Functional imaging of pain: new insights regarding the role of the cerebral cortex in human pain perception. Semin Neurosci 7:279–293. doi:10.1006/smns.1995.0031

    Article  Google Scholar 

  64. Hsieh J-C, Ståhle-Bäckdahl M, Hägermark Ö et al (1996) Traumatic nociceptive pain activates the hypothalamus and the periaqueductal gray: a positron emission tomography study. Pain 64:303–314. doi:10.1016/0304-3959(95)00129-8

    Article  CAS  PubMed  Google Scholar 

  65. Forss N, Raij TT, Seppä M, Hari R (2005) Common cortical network for first and second pain. NeuroImage 24:132–142. doi:10.1016/j.neuroimage.2004.09.032

    Article  PubMed  Google Scholar 

  66. Mullins P, Rowland L, Jung R, Sibbittjr W (2005) A novel technique to study the brain’s response to pain: proton magnetic resonance spectroscopy. NeuroImage 26:642–646. doi:10.1016/j.neuroimage.2005.02.001

    Article  PubMed  Google Scholar 

  67. Petrovic P, Ingvar M (2002) Imaging cognitive modulation of pain processing. Pain 95:1–5

    Article  PubMed  Google Scholar 

  68. Gracely RH, Geisser ME, Giesecke T et al (2004) Pain catastrophizing and neural responses to pain among persons with fibromyalgia. Brain 127:835–843. doi:10.1093/brain/awh098

    Article  CAS  PubMed  Google Scholar 

  69. Schweinhardt P, Bushnell MC (2010) Pain imaging in health and disease—how far have we come? J Clin Invest 120:3788. doi:10.1172/JCI43498

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  70. Fields H (2004) State-dependent opioid control of pain. Nat Rev Neurosci 5:565–575. doi:10.1038/nrn1431

    Article  CAS  PubMed  Google Scholar 

  71. Tracey I (2005) Nociceptive processing in the human brain. Curr Opin Neurobiol 15:478–487. doi:10.1016/j.conb.2005.06.010

    Article  CAS  PubMed  Google Scholar 

  72. Hadjipavlou G, Dunckley P, Behrens TE, Tracey I (2006) Determining anatomical connectivities between cortical and brainstem pain processing regions in humans: a diffusion tensor imaging study in healthy controls. Pain 123:169–178. doi:10.1016/j.pain.2006.02.027

    Article  PubMed  Google Scholar 

  73. Tracey I, Mantyh PW (2007) The cerebral signature for pain perception and its modulation. Neuron 55:377–391. doi:10.1016/j.neuron.2007.07.012

    Article  CAS  PubMed  Google Scholar 

  74. Koch MA, Norris DG, Hund-Georgiadis M (2002) An investigation of functional and anatomical connectivity using magnetic resonance imaging. NeuroImage 16:241–250. doi:10.1006/nimg.2001.1052

    Article  PubMed  Google Scholar 

  75. Camchong J, MacDonald AW, Bell C et al (2011) Altered functional and anatomical connectivity in schizophrenia. Schizophr Bull 37:640–650. doi:10.1093/schbul/sbp131

    Article  PubMed  Google Scholar 

  76. Damoiseaux JS, Greicius MD (2009) Greater than the sum of its parts: a review of studies combining structural connectivity and resting-state functional connectivity. Brain Struct Funct 213:525–533. doi:10.1007/s00429-009-0208-6

    Article  PubMed  Google Scholar 

  77. Messé A, Rudrauf D, Benali H, Marrelec G (2014) Relating structure and function in the human brain: relative contributions of anatomy, stationary dynamics, and non-stationarities. PLoS Comp Biol 10:e1003530. doi:10.1371/journal.pcbi.1003530

    Article  Google Scholar 

  78. Greicius MD, Supekar K, Menon V, Dougherty RF (2008) Resting-state functional connectivity reflects structural connectivity in the default mode network. Cereb Cortex 19:72–78. doi:10.1093/cercor/bhn059

    Article  PubMed  PubMed Central  Google Scholar 

  79. Xiao H, Yang Y, Xi J-H, Chen Z-Q (2015) Structural and functional connectivity in traumatic brain injury. Neural Regen Res 10:2062–2071. doi:10.4103/1673-5374.172328

    Article  PubMed  PubMed Central  Google Scholar 

  80. Ray S, Miller M, Karalunas S et al (2014) Structural and functional connectivity of the human brain in autism spectrum disorders and attention-deficit/hyperactivity disorder: a rich club-organization study. Hum Brain Mapp 35:6032–6048. doi:10.1002/hbm.22603

    Article  PubMed  PubMed Central  Google Scholar 

  81. Betzel RF, Byrge L, He Y et al (2014) Changes in structural and functional connectivity among resting-state networks across the human lifespan. NeuroImage 102(Pt 2):345–357. doi:10.1016/j.neuroimage.2014.07.067

    Article  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Akihiko Wada.

Ethics declarations

Funding

This study was funded by a Japan Society for the Promotion of Science Grant-in-Aid for Scientific Research to OA (grant number 16K10330), Grants-in-Aid for Scientific Research to YI (grant number 15K11326), a Uemura Fund Research Grant to YI and Grants-in-Aid for Scientific Research to TS (grant number 16K11897).

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the Nihon University Hospitals’ Joint Institutional Review Board and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed consent

Informed consent was obtained from all individual participants included in the study.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wada, A., Shizukuishi, T., Kikuta, J. et al. Altered structural connectivity of pain-related brain network in burning mouth syndrome—investigation by graph analysis of probabilistic tractography. Neuroradiology 59, 525–532 (2017). https://doi.org/10.1007/s00234-017-1830-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00234-017-1830-2

Keywords

Navigation