To investigate the effect of cervical spondylosis (CS) in the brain with a combination of advanced neuroimaging techniques.
Twenty-seven patients with CS and 24 age- and gender-matched healthy controls were studied. Disease severity was quantified using the Modified Japanese Orthopaedic Association Scoring System (mJOHA). Magnetic resonance (MR) imaging of the brain and spinal cord, functional MR imaging (fMRI) with a bilateral rest/finger-tapping paradigm, brain diffusion tensor imaging (DTI), voxel-based morphometry (VBM), and MR spectroscopy of the sensorimotor cortex were performed.
A total of 92.3% of patients had more than one herniated disc. In the MRI, 33.33% presented signs of myelopathy. The mJOHA score was 13.03 ± 2.83. Compared with controls, DTI results showed significant lower FA values in Corpus callosum, both corticospinal tracts and middle cerebellar peduncles (p < 0.05 corrected). Only in CS patients fMRI results showed activation in both globus pallidi, caudate nucleus, and left thalamus (p < 0.001). Subject-specific activation of the BOLD signal showed in CS patients lower activation in the sensorimotor cortex and increased activation in both cerebellum hemispheres (p < 0.05 corrected). VBM showed bilateral clusters of gray matter loss in the sensorimotor cortex and pulvinar nucleus (p < 0.05 corrected) of CS patients. NAA/Cr was reduced in the sensorimotor cortex of CS patients (p < 0.05). Linear discriminant and support vector machine analyses were able to classify > 97% of CS patients with parameters obtained from the fMRI, DTI, and MRS results.
CS may lead to distal brain damage affecting the white and gray matter of the sensorimotor cortex causing brain atrophy and functional adaptive changes.
• This study suggests that patients with cervical spondylosis may present anatomical and functional adaptive changes in the brain.
• Cervical spondylosis may lead to white matter damage, gray matter volume loss, and functional adaptive changes in the sensorimotor cortex.
• The results reported in this work may be of value to better understand the effect of prolonged cervical spine compression in the brain.
This is a preview of subscription content, log in to check access.
Buy single article
Instant access to the full article PDF.
Tax calculation will be finalised during checkout.
Subscribe to journal
Immediate online access to all issues from 2019. Subscription will auto renew annually.
Tax calculation will be finalised during checkout.
Cervical spondylosis myelopathy
Diffusion tensor imaging
Functional magnetic resonance imaging
Glutamate and glutamine
Middle cerebellar peduncle
Modified Japanese Orthopaedic Association Scoring System.
Supplementary motor area
Tract-based spatial statistics
Boden SD, McCowin PR, Davis DO, Dina TS, Mark AS, Wiesel S (1990) Abnormal magnetic-resonance scans of the cervical spine in asymptomatic subjects. A prospective investigation. J Bone Joint Surg Am 72:1178–1184
Bakhsheshian J, Mehta VA, Liu JC (2017) Current diagnosis and management of cervical spondylotic myelopathy. Global Spine J 7:572–586. https://doi.org/10.1177/2192568217699208
Tracy JA, Bartleson JD (2010) Cervical spondylotic myelopathy. Neurologist 16:176–187
Lebl DR, Bono CM (2015) Update on the diagnosis and management of cervical spondylotic myelopathy. J Am Acad Orthop Surg 23:648–660
Clarke E, Robinson PK (1956) Cervical myelopathy: a complication of cervical spondylosis. Brain 79:483–510
Morishita Y, Naito M, Hymanson H, Miyazaki M, Wu G, Wang JC (2009) The relationship between the cervical spinal canal diameter and the pathological changes in the cervical spine. Eur Spine J 18:877–883
Wada E, Yonenobu K, Suzuki S, Kanazawa A, Ochi T (1999) Can intramedullary signal change on magnetic resonance imaging predict surgical outcome in cervical spondylotic myelopathy? Spine (Phila PA 1976) 24:455–461 discussion 462
Stroman PW, Nance PW, Ryner LN (1999) BOLD MRI of the human cervical spinal cord at 3 tesla. Magn Reson Med 42:571–576
Okada E, Matsumoto M, Fujiwara H, Toyama Y (2011) Disc degeneration of cervical spine on MRI in patients with lumbar disc herniation: comparison study with asymptomatic volunteers. Eur Spine J 20:585–591
Xiangshui M, Xiangjun C, Xiaoming Z et al (2010) 3 T magnetic resonance diffusion tensor imaging and fiber tracking in cervical myelopathy. Clin Radiol 65:465–473
Duggal N, Rabin D, Bartha R et al (2010) Brain reorganization in patients with spinal cord compression evaluated using fMRI. Neurology 74:1048–1054
Holly LT (2009) Management of cervical spondylotic myelopathy with insights from metabolic imaging of the spinal cord and brain. Curr Opin Neurol 22:575–581
Kowalczyk I, Duggal N, Bartha R (2012) Proton magnetic resonance spectroscopy of the motor cortex in cervical myelopathy. Brain. https://doi.org/10.1093/brain/awr328
Zhou FQ, Tan YM, Wu L, Zhuang Y, He LC, Gong HH (2015) Intrinsic functional plasticity of the sensory-motor network in patients with cervical spondylotic myelopathy. Sci Rep 5:1–8. https://doi.org/10.1038/srep09975
Dong Y, Holly LT, Albistegui-Dubois R et al (2008) Compensatory cerebral adaptations before evolving changes after surgical decompression in cervical spondylotic myelopathy. J Neurosurg Spine 9:538–551. https://doi.org/10.3171/SPI.2008.10.0831.Compensatory
Yukawa Y, Kato F, Yoshihara H, Yanase M, Ito K (2007) MR T2 image classification in cervical compression myelopathy. Spine (Phila PA 1976) 32:1675–1678. https://doi.org/10.1097/BRS.0b013e318074d62e
Oishi K, Zilles K, Amunts K et al (2008) Human brain white matter atlas: identification and assignment of common anatomical structures in superficial white matter. Neuroimage 43:447–457. https://doi.org/10.1016/j.neuroimage.2008.07.009
Leemans A, Jeurissen B, Sijbers J, Jones D (2009) ExploreDTI: a graphical toolbox for processing, analyzing, and visualizing diffusion MR data. Proc Intl Soc Mag Reson Med 17:3537
Jones DK, Basser PJ (2004) “Squashing peanuts and smashing pumpkins”: how noise distorts diffusion-weighted MR data. Magn Reson Med 52:979–993. https://doi.org/10.1002/mrm.20283
Basser PJ, Pajevic S, Pierpaoli C, Duda J, Aldroubi A (2000) In vivo fiber tractography using DT-MRI data. Magn Reson Med 44:625–632. https://doi.org/10.1002/1522-2594(200010)44:4<625::AID-MRM17>3.0.CO;2-O
Wakana S, Jiang H, Nagae-Poetscher LM, van Zijl PC, Mori S (2004) Fiber tract-based atlas of human white matter anatomy. Radiology 230:77–87. https://doi.org/10.1148/radiol.2301021640
Papke K, Reimer P, Renger B et al (2000) Optimized activation of the primary sensorimotor cortex for clinical functional MR imaging. AJNR Am J Neuroradiol 21:395–401
Brett M, Anton J-L, Valabregue R, Poline J-B (2002) Region of interest analysis using an SPM toolbox [Internet]. Vol. 16, Presented at the 8th International Conference on Functional Mapping of the Human Brain. [cited 2019 Feb 18]. Available from: https://matthew.dynevor.org/research/abstracts/marsbar/marsbar_abstract.pdf
Naressi A, Couturier C, Devos JM et al (2001) Java-based graphical user interface for the MRUI quantitation package. MAGMA 12:141–152
Bernabeu A, Alfaro A, García M, Fernández E (2009) Proton magnetic resonance spectroscopy (1H-MRS) reveals the presence of elevated myo-inositol in the occipital cortex of blind subjects. Neuroimage 47:1172–1176. https://doi.org/10.1016/j.neuroimage.2009.04.080
Cano M, Martínez-Zalacaín I, Bernabéu-Sanz Á et al (2017) Brain volumetric and metabolic correlates of electroconvulsive therapy for treatment-resistant depression: a longitudinal neuroimaging study. Transl Psychiatry 7:e1023. https://doi.org/10.1038/tp.2016.267
Poveda MJ, Bernabeu Á, Concepción L et al (2010) Brain edema dynamics in patients with overt hepatic encephalopathy. A magnetic resonance imaging study. Neuroimage 52:481–487. https://doi.org/10.1016/j.neuroimage.2010.04.260
Morales S, Bernabeu-Sanz A, López-Mir F, González P, Luna L, Naranjo V (2017) BRAIM: a computer-aided diagnosis system for neurodegenerative diseases and brain lesion monitoring from volumetric analyses. Comput Methods Programs Biomed 145:167–179. https://doi.org/10.1016/j.cmpb.2017.04.006
Pedregosa F, Varoquaux G, Gramfort A et al (2011) Scikit-learn: machine learning in Python. J Mach Learn Res 12. Available from: http://scikit-learn.org
Schott GD (1993) Penfield’s homunculus: a note on cerebral cartography. J Neurol Neurosurg Psychiatry 56:329–333
Ijima Y, Furuya T, Koda M et al (2017) Experimental rat model for cervical compressive myelopathy. Neuroreport 28:1239–1245. https://doi.org/10.1097/WNR.0000000000000907
Lee JW, Kim JH, Bin PJ et al (2011) Diffusion tensor imaging and fiber tractography in cervical compressive myelopathy: preliminary results. Skeletal Radiol 40:1543–1551. https://doi.org/10.1007/s00256-011-1161-z
Jang SH (2014) The corticospinal tract from the viewpoint of brain rehabilitation. J Rehabil Med 46:193–199. https://doi.org/10.2340/16501977-1782
Fabri M, Pierpaoli C, Barbaresi P, Polonara G (2014) Functional topography of the corpus callosum investigated by DTI and fMRI. World J Radiol 6:895–906. https://doi.org/10.4329/wjr.v6.i12.895
Zhou F, Gong H, Liu X, Wu L, Luk KD, Hu Y (2014) Increased low-frequency oscillation amplitude of sensorimotor cortex associated with the severity of structural impairment in cervical myelopathy. PLoS One. https://doi.org/10.1371/journal.pone.0104442
Zhou F, Wu L, Liu X, Gong H, Luk KD, Hu Y (2015) Characterizing thalamocortical disturbances in cervical spondylotic myelopathy : revealed by functional connectivity under two slow frequency bands. PLoS One https://doi.org/10.1371/journal.pone.0125913
Tan Y, Zhou F, Wu L et al (2015) Alteration of Regional homogeneity within the sensorimotor network after spinal cord decompression in cervical spondylotic myelopathy: a resting-state fMRI study. Biomed Res Int 647958. https://doi.org/10.1155/2015/647958
Bruehlmeier M, Dietz V, Leenders KL, Roelcke U, Missimer J, Curt A (1998) How does the human brain deal with a spinal cord injury? Eur J Neurosci 10:3918–3922. https://doi.org/10.1046/j.1460-9568.1998.00454.x
Cramer SC, Lastra L, Lacourse MG, Cohen MJ (2005) Brain motor system function after chronic, complete spinal cord injury. Brain 128:2941–2950. https://doi.org/10.1093/brain/awh648
Bunday KL, Tazoe T, Rothwell JC, Perez MA (2014) Subcortical control of precision grip after human spinal cord injury. J Neurosci 34:7341–7350. https://doi.org/10.1523/JNEUROSCI.0390-14.2014
Dobkin BH (2000) Spinal and supraspinal plasticity after incomplete spinal cord injury: correlations between functional magnetic resonance imaging and engaged locomotor networks. Prog Brain Res 128:99–111. https://doi.org/10.1016/S0079-6123(00)28010-2
Curt A, Alkadhi H, Crelier GR, Boendermaker SH, Hepp-Reymond MC, Kollias SS (2002) Changes of non-affected upper limb cortical representation in paraplegic patients as assessed by fMRI. Brain 125:2567–2578. https://doi.org/10.1093/brain/awf250
Holly LT, Dong Y, Albistegui-DuBois R, Marehbian J, Dobkin B (2014) Cortical reorganization in patients with cervical spondylotic myelopathy. J Neurosurg Spine 6:544–551. https://doi.org/10.3171/spi.2007.6.6.5.Cortical
Henderson LA, Gustin SM, Macey PM, Wrigley PJ, Siddall PJ (2011) Functional reorganization of the brain in humans following spinal cord injury: evidence for underlying changes in cortical anatomy. J Neurosci 31:2630–2637. https://doi.org/10.1523/JNEUROSCI.2717-10.2011
Wurster CD, Graf H, Ackermann H, Groth K, Kassubek J, Riecker A (2015) Neural correlates of rate-dependent finger-tapping in Parkinson’s disease. Brain Struct Funct 220:1637–1648. https://doi.org/10.1007/s00429-014-0749-1
Nikolaidis I, Fouyas IP, Sandercock PA, Statham PF (2010) Surgery for cervical radiculopathy or myelopathy. Cochrane Database Syst Rev CD001466. https://doi.org/10.1002/14651858.CD001466.pub3
Dhillon RS, Parker J, Syed YA et al (2016) Axonal plasticity underpins the functional recovery following surgical decompression in a rat model of cervical spondylotic myelopathy. Acta Neuropathol Commun 4:89. https://doi.org/10.1186/s40478-016-0359-7
Martin AR, Aleksanderek I, Cohen-Adad J et al (2016) Translating state-of-the-art spinal cord MRI techniques to clinical use: a systematic review of clinical studies utilizing DTI, MT, MWF, MRS, and fMRI. Neuroimage Clin 10:192–238. https://doi.org/10.1016/j.nicl.2015.11.019
The authors would like to thank the following people: our subjects for their time and help. Our MR technologists Mr. David González García, Miss. Patricia Lucena Ibáñez, Ms. Evelyn Teruel Sanchez, and Ms. Maria Vicenta Picazo Panadero for their outstanding technical support during the acquisition of the studies. Mr. Mikel Val for his invaluable help and advice in the SVM analysis. We would also like to show our gratitude to the anonymous reviewers who provided insight and expertise that greatly improved the manuscript.
This work was supported in part by Grant No. RTI2018-098969-B-100 from the Spanish Government and by the Bidons Egara Research Chair.
The scientific guarantor of this publication is Dr. Ángela Bernabeu-Sanz.
Conflict of interest
The authors of this manuscript declare no relationships with any companies, whose products or services may be related to the subject matter of the article.
Statistics and biometry
No complex statistical methods were necessary for this paper.
Written informed consent was obtained from all subjects (patients) in this study.
Institutional Review Board approval was obtained.
• case-control study
• performed at one institution
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Electronic supplementary material
About this article
Cite this article
Bernabéu-Sanz, Á., Mollá-Torró, J.V., López-Celada, S. et al. MRI evidence of brain atrophy, white matter damage, and functional adaptive changes in patients with cervical spondylosis and prolonged spinal cord compression. Eur Radiol 30, 357–369 (2020). https://doi.org/10.1007/s00330-019-06352-z
- Neural plasticity