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Differential patient responses to spinal manipulative therapy and their relation to spinal degeneration and post-treatment changes in disc diffusion

  • Arnold Y. L. WongEmail author
  • Eric C. Parent
  • Sukhvinder S. Dhillon
  • Narasimha Prasad
  • Dino Samartzis
  • Gregory N. Kawchuk
Original Article

Abstract

Purpose

Our prior study revealed that people with non-specific low back pain (LBP) who self-reported a > 30% improvement in disability after SMT demonstrated significant post-treatment improvements in spinal stiffness, dynamic muscle thickness and disc diffusion, while those not having self-reported improvement did not have these objective changes. The mechanism underlying this differential post-SMT response remains unknown. This exploratory secondary analysis aimed to determine whether persons with non-specific LBP who respond to spinal SMT have unique lumbar magnetic resonance imaging (MRI) findings compared to SMT non-responders.

Methods

Thirty-two participants with non-specific LBP received lumbar MRI before and after SMT on Day 1. Resulting images were assessed for facet degeneration, disc degeneration, Modic changes and apparent diffusion coefficient (ADC). SMT was provided again on Day 4 without imaging. SMT responders were classified as having a ≥ 30% reduction in their modified Oswestry disability index at Day 7. Baseline MRI findings between responders and non-responders were compared. The associations between SMT responder status and the presence/absence of post-SMT increases in ADC values of discs associated with painful/non-painful segments as determined by palpation were calculated. In this secondary analysis, a statistical trend was considered as a P value between 0.05 and 0.10.

Results

Although there was no significant between-group difference in all spinal degenerative features (e.g. Modic changes), SMT responders tended to have a lower prevalence of severely degenerated facets (P = 0.05) and higher baseline ADC values at the L4-5 disc when compared to SMT non-responders (P = 0.09). Post hoc analyses revealed that 180 patients per group should have been recruited to find significant between-group differences in the two features. SMT responders were also characterized by significant increases in post-SMT ADC values at discs associated with painful segments identified by palpation (P < 0.01).

Conclusions

The current secondary analysis suggests that the spines of SMT responders appear to differ from non-responders with respect to degeneration changes in posterior joints and disc diffusion. Although this analysis was preliminary, it provides a new direction to investigate the mechanisms underlying SMT and the existence of discrete forms of treatment-specific LBP.

Graphical abstract

These slides can be retrieved under Electronic Supplementary Material.

Keywords

Spinal manipulative therapy Low back pain Apparent diffusion coefficient Facet joint Degeneration 

Notes

Acknowledgements

The authors would like to thank the Canadian Chiropractic Research Foundation and Alberta Innovates-Health Solutions Graduate Research Allowance for funding this project. Arnold Wong was supported by the Golden Key Graduate Scholar Award. The authors also thank Magnetic Imaging Consultants for providing scan services, and the River Valley Health Clinic for providing professional spinal manipulation and clinical space. The authors also express gratitude to Mr. Karl Brandt and Ms. Carolyn Berendt for assisting the coding and decoding of data files.

Compliance with ethical standards

Conflict of interest

The authors have no potential conflict of interest.

Supplementary material

586_2018_5851_MOESM1_ESM.pptx (1.1 mb)
Supplementary material 1 (PPTX 1075 kb)

References

  1. 1.
    Global Burden of Disease Study 2013 Collaborators (2015) Global, regional, and national incidence, prevalence, and years lived with disability for 301 acute and chronic diseases and injuries in 188 countries, 1990–2013: a systematic analysis for the Global Burden of Disease Study 2013. Lancet 386:743–800.  https://doi.org/10.1016/S0140-6736(15)60692-4 CrossRefPubMedCentralGoogle Scholar
  2. 2.
    Haldeman S, Kopansky-Giles D, Hurwitz EL et al (2012) Advancements in the management of spine disorders. Best Pract Res Clin Rheumatol 26:263–280.  https://doi.org/10.1016/j.berh.2012.03.006 CrossRefPubMedGoogle Scholar
  3. 3.
    Wong AYL, Parent EC, Dhillon SS et al (2015) Do participants with low back pain who respond to spinal manipulative therapy differ biomechanically from nonresponders, untreated controls or asymptomatic controls? Spine 40:1329–1337.  https://doi.org/10.1097/BRS.0000000000000981 CrossRefPubMedGoogle Scholar
  4. 4.
    Fritz JM, Koppenhaver SL, Kawchuk GN et al (2011) Preliminary investigation of the mechanisms underlying the effects of manipulation: exploration of a multi-variate model including spinal stiffness, multifidus recruitment, and clinical findings. Spine 36:1772–1781.  https://doi.org/10.1097/BRS.0b013e318216337d CrossRefPubMedPubMedCentralGoogle Scholar
  5. 5.
    Koppenhaver SL, Fritz JM, Hebert JJ et al (2011) Association between changes in abdominal and lumbar multifidus muscle thickness and clinical improvement after spinal manipulation. J Orthop Sports Phys Ther 41:389–399.  https://doi.org/10.2519/jospt.2011.3632 CrossRefPubMedGoogle Scholar
  6. 6.
    Long A, Donelson R, Fung T (2004) Does it matter which exercise? A randomized control trial of exercise for low back pain. Spine 29:2593–2602CrossRefGoogle Scholar
  7. 7.
    Beneciuk JM, Robinson ME, George SZ (2015) Subgrouping for patients with low back pain: a multidimensional approach incorporating cluster analysis and the STarT Back Screening Tool. J Pain 16:19–30.  https://doi.org/10.1016/j.jpain.2014.10.004 CrossRefPubMedGoogle Scholar
  8. 8.
    Hebert JJ, Koppenhaver SL, Walker BF (2011) Subgrouping patients with low back pain: a treatment-based approach to classification. Sports Health 3:534–542.  https://doi.org/10.1177/1941738111415044 CrossRefPubMedPubMedCentralGoogle Scholar
  9. 9.
    Jensen TS, Karppinen J, Sorensen JS et al (2008) Vertebral endplate signal changes (Modic change): a systematic literature review of prevalence and association with non-specific low back pain. Eur Spine J 17:1407–1422.  https://doi.org/10.1007/s00586-008-0770-2 CrossRefPubMedPubMedCentralGoogle Scholar
  10. 10.
    Kjaer P, Korsholm L, Bendix T et al (2006) Modic changes and their associations with clinical findings. Eur Spine J 15:1312–1319.  https://doi.org/10.1007/s00586-006-0185-x CrossRefPubMedPubMedCentralGoogle Scholar
  11. 11.
    Jensen RK, Leboeuf-Yde C, Wedderkopp N et al (2012) Is the development of Modic changes associated with clinical symptoms? A 14-month cohort study with MRI. Eur Spine J 21:2271–2279.  https://doi.org/10.1007/s00586-012-2309-9 CrossRefPubMedPubMedCentralGoogle Scholar
  12. 12.
    Jensen OK, Nielsen CV, Sørensen JS, Stengaard-Pedersen K (2014) Type 1 Modic changes was a significant risk factor for 1-year outcome in sick-listed low back pain patients: a nested cohort study using magnetic resonance imaging of the lumbar spine. Spine J 14:2568–2581.  https://doi.org/10.1016/j.spinee.2014.02.018 CrossRefPubMedGoogle Scholar
  13. 13.
    Antoniou J, Demers CN, Beaudoin G et al (2004) Apparent diffusion coefficient of intervertebral discs related to matrix composition and integrity. Magn Reson Imaging 22:963–972.  https://doi.org/10.1016/j.mri.2004.02.011 CrossRefPubMedGoogle Scholar
  14. 14.
    Huang Y-C, Urban JPG, Luk KDK (2014) Intervertebral disc regeneration: do nutrients lead the way? Nat Rev Rheumatol 10:561–566.  https://doi.org/10.1038/nrrheum.2014.91 CrossRefPubMedGoogle Scholar
  15. 15.
    Flynn T, Fritz J, Whitman J et al (2002) A clinical prediction rule for classifying patients with low back pain who demonstrate short-term improvement with spinal manipulation. Spine 27:2835–2843.  https://doi.org/10.1097/01.BRS.0000035681.33747.8D CrossRefPubMedGoogle Scholar
  16. 16.
    Haneline MT, Young M (2009) A review of intraexaminer and interexaminer reliability of static spinal palpation: a literature synthesis. J Manip Physiol Ther 32:379–386.  https://doi.org/10.1016/j.jmpt.2009.04.010 CrossRefGoogle Scholar
  17. 17.
    Ostelo RWJG, Deyo RA, Stratford P et al (2008) Interpreting change scores for pain and functional status in low back pain: towards international consensus regarding minimal important change. Spine 33:90–94.  https://doi.org/10.1097/BRS.0b013e31815e3a10 CrossRefPubMedGoogle Scholar
  18. 18.
    Suarez-Almazor ME, Kendall C, Johnson JA, Skeith K, Vincent D (2000) Use of health status measures in patients with low back pain in clinical settings. Comparison of specific, generic and preference-based instruments. Rheumatology 39:783–790.  https://doi.org/10.1093/rheumatology/39.7.783 CrossRefPubMedGoogle Scholar
  19. 19.
    Davidson M, Keating JL (2002) A comparison of five low back disability questionnaires: reliability and responsiveness. Phys Ther 82:8–24.  https://doi.org/10.1093/ptj/82.1.8 CrossRefPubMedGoogle Scholar
  20. 20.
    Hagg O, Fritzell P, Nordwall A (2003) The clinical importance of changes in outcome scores after treatment for chronic low back pain. Eur Spine J 12:12–20.  https://doi.org/10.1007/s00586-002-0464-0 CrossRefPubMedGoogle Scholar
  21. 21.
    DePalma MJ, Ketchum JM, Saullo T (2011) What is the source of chronic low back pain and does age play a role? Pain Med 12:224–233.  https://doi.org/10.1111/j.1526-4637.2010.01045.x CrossRefPubMedGoogle Scholar
  22. 22.
    Kjaer P, Leboeuf-Yde C, Korsholm L et al (2005) Magnetic resonance imaging and low back pain in adults: a diagnostic imaging study of 40-year-old men and women. Spine 30:1173–1180.  https://doi.org/10.1097/01.brs.0000162396.97739.76 CrossRefPubMedGoogle Scholar
  23. 23.
    Weishaupt D, Zanetti M, Boos N, Hodler J (1999) MR imaging and CT in osteoarthritis of the lumbar facet joints. Skelet Radiol 28:215–219.  https://doi.org/10.1007/s002560050503 CrossRefGoogle Scholar
  24. 24.
    Kettler A, Wilke HJ (2006) Review of existing grading systems for cervical or lumbar disc and facet joint degeneration. Eur Spine J 15:705–718.  https://doi.org/10.1007/s00586-005-0954-y CrossRefPubMedGoogle Scholar
  25. 25.
    Pfirrmann C, Metzdorf A, Zanetti M et al (2001) Magnetic resonance classification of lumbar intervertebral disc degeneration. Spine 26:1873–1878.  https://doi.org/10.1097/00007632-200109010-00011 CrossRefPubMedGoogle Scholar
  26. 26.
    Jensen TS, Sørensen JS, Kjaer P (2007) Intra- and interobserver reproducibility of vertebral endplate signal (modic) changes in the lumbar spine: the Nordic Modic Consensus Group classification. Acta Radiol 48:748–754.  https://doi.org/10.1080/02841850701422112 CrossRefPubMedGoogle Scholar
  27. 27.
    Modic MT, Steinberg PM, Ross JS et al (1988) Degenerative disk disease: assessment of changes in vertebral body marrow with MR imaging. J Bone Joint Surg Am 166:193–199.  https://doi.org/10.1148/radiology.166.1.3336678 CrossRefGoogle Scholar
  28. 28.
    Maataoui A, Vogl TJ, Khan MF (2015) Magnetic resonance imaging-based interpretation of degenerative changes in the lower lumbar segments and therapeutic consequences. World J Radiol 7:194–197.  https://doi.org/10.4329/wjr.v7.i8.194 CrossRefPubMedPubMedCentralGoogle Scholar
  29. 29.
    Määttä JH, Karppinen JI, Luk KDK et al (2015) Phenotype profiling of Modic changes of the lumbar spine and its association with other MRI phenotypes: a large-scale population-based study. Spine J 15:1933–1942.  https://doi.org/10.1016/j.spinee.2015.06.056 CrossRefPubMedGoogle Scholar
  30. 30.
    Gjorup T (1988) The kappa coefficient and the prevalence of a diagnosis. Methods Inf Med 27:184–186CrossRefGoogle Scholar
  31. 31.
    Kovacs FM, Arana E, Royuela A et al (2014) Disc degeneration and chronic low back pain: an association which becomes nonsignificant when endplate changes and disc contour are taken into account. Neuroradiology 56:25–33.  https://doi.org/10.1007/s00234-013-1294-y CrossRefPubMedGoogle Scholar
  32. 32.
    Kalichman L, Hodges P, Li L et al (2010) Changes in paraspinal muscles and their association with low back pain and spinal degeneration: CT study. Eur Spine J 19:1136–1144.  https://doi.org/10.1007/s00586-009-1257-5 CrossRefPubMedGoogle Scholar
  33. 33.
    Landis JR, Koch GG (1977) The measurement of observer agreement for categorical data. Biometrics 33:159–174.  https://doi.org/10.2307/2529310 CrossRefPubMedGoogle Scholar
  34. 34.
    Portney LG, Watkins MP (2009) Foundations of clinical research applications to practice, 3rd edn. Pearson Education Inc, New JerseyGoogle Scholar
  35. 35.
    Fritz CO, Morris PE, Richler JJ (2012) Effect size estimates: current use, calculations, and interpretation. J Exp Psychol Gen 141:2–18.  https://doi.org/10.1037/a0024338 CrossRefPubMedGoogle Scholar
  36. 36.
    Fluss R, Faraggi D, Reiser B (2005) Estimation of the Youden index and its associated cutoff point. Biom J 47:458–472.  https://doi.org/10.1002/bimj.200410135 CrossRefPubMedGoogle Scholar
  37. 37.
    Eliasziw M, Young SL, Woodbury MG, Fryday-Field K (1994) Statistical methodology for the concurrent assessment of interrater and intrarater reliability: using goniometric measurements as an example. Phys Ther 74:777–788CrossRefGoogle Scholar
  38. 38.
    Healey JF (2007) The essentials of statistics: a tool for social research. Nelson Education, Toronto.  https://doi.org/10.1179/107735201800339434 CrossRefGoogle Scholar
  39. 39.
    Erdfelder E, Faul F, Buchner A (1996) GPower: a general power analysis program. Behav Res Methods Instrum Comput 1996(28):1–11.  https://doi.org/10.3758/BF03203630 CrossRefGoogle Scholar
  40. 40.
    Teraguchi M, Yoshimura N, Hashizume H et al (2014) Prevalence and distribution of intervertebral disc degeneration over the entire spine in a population-based cohort: the Wakayama Spine Study. Osteoarthr Cartil 22:104–110.  https://doi.org/10.1016/j.joca.2013.10.019 CrossRefPubMedGoogle Scholar
  41. 41.
    Yu HJ, Bahri S, Gardner V, Muftuler LT (2015) In vivo quantification of lumbar disc degeneration: assessment of ADC value using a degenerative scoring system based on Pfirrmann framework. Eur Spine J 24(11):2442–2448.  https://doi.org/10.1007/s00586-014-3721-0 CrossRefPubMedGoogle Scholar
  42. 42.
    Weiler C, Lopez-Ramos M, Mayer HM et al (2011) Histological analysis of surgical lumbar intervertebral disc tissue provides evidence for an association between disc degeneration and increased body mass index. BMC Res Notes 4(1):497.  https://doi.org/10.1186/1756-0500-4-497 CrossRefPubMedPubMedCentralGoogle Scholar
  43. 43.
    Colloca CJ, Gunzburg R, Freeman BJ et al (2012) Biomechancial quantification of pathologic manipulable spinal lesions: an in vivo ovine model of spondylolysis and intervertebral disc degeneration. J Manip Physiol Ther 35:354–366.  https://doi.org/10.1016/j.jmpt.2012.04.018 CrossRefGoogle Scholar
  44. 44.
    Vietra-Peltenz F, Olivia-Pascual-Vaca A, Rodriguez-Blanco C et al (2014) Short-term effect of spinal manipulation on pain perception, spinal mobility, and full height recovery in male subjects with degenerative disk disease: a randomized controlled trial. Arch Phys Med Rehabil 95:1613–1619.  https://doi.org/10.1016/j.apmr.2014.05.002 CrossRefGoogle Scholar
  45. 45.
    Albert HB, Lambert P, Rollason J et al (2013) Does nuclear tissue infected with bacteria following disc herniations lead to Modic changes in the adjacent vertebrae? Eur Spine J 22:690–696.  https://doi.org/10.1007/s00586-013-2674-z CrossRefPubMedPubMedCentralGoogle Scholar
  46. 46.
    Samartzis D, Liebenberg EC, Fong DY (2014) Innervation of pathologies in the lumbar vertebral end plate and intervertebral disc. Spine J 14:513–521.  https://doi.org/10.1016/j.spinee.2013.06.075 CrossRefGoogle Scholar
  47. 47.
    Dankaerts W, O’Sullivan PB, Straker LM et al (2006) The inter-examiner reliability of a classification method for non-specific chronic low back pain patients with motor control impairment. Man Ther 11:28–39.  https://doi.org/10.1016/j.math.2005.02.001 CrossRefPubMedGoogle Scholar
  48. 48.
    Delitto A (2005) Research in low back pain: time to stop seeking the elusive “magic bullet”. Phys Ther 85:206–208PubMedGoogle Scholar
  49. 49.
    McCarthy CJ, Arnall FA, Strimpakos N et al (2013) The biopsychosocial classification of non-specific low back pain: a systematic review. Phys Ther Rev 9:17–30.  https://doi.org/10.1179/108331904225003955 CrossRefGoogle Scholar
  50. 50.
    O’Sullivan P (2005) Diagnosis and classification of chronic low back pain disorders: maladaptive movement and motor control impairments as underlying mechanism. Man Ther 10:242–255.  https://doi.org/10.1016/j.math.2005.07.001 CrossRefPubMedGoogle Scholar
  51. 51.
    McKenzie RA, May S (2003) Mechanical diagnosis and therapy: the lumbar spine, 2nd edn. Spinal Publications, Waikanae.  https://doi.org/10.2519/jospt.2004.34.3.105 CrossRefGoogle Scholar
  52. 52.
    Waddell G, Newton M, Henderson I et al (1993) A Fear-Avoidance Beliefs Questionnaire (FABQ) and the role of fear-avoidance beliefs in chronic low back pain and disability. Pain 52:157–168CrossRefGoogle Scholar
  53. 53.
    Mondloch M (2001) Does how you do depend on how you think you’ll do? A systematic review of the evidence for a relation between patients” recovery expectations and health outcomes. CMAJ 165:174–179PubMedPubMedCentralGoogle Scholar
  54. 54.
    Bialosky JE, Bishop MD, Price DD et al (2009) The mechanisms of manual therapy in the treatment of musculoskeletal pain: a comprehensive model. Man Ther 14:531–538.  https://doi.org/10.1016/j.math.2008.09.001 CrossRefPubMedGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Physical TherapyUniversity of AlbertaEdmontonCanada
  2. 2.Department of Rehabilitation SciencesThe Hong Kong Polytechnic UniversityHung HomChina
  3. 3.Department of RadiologyUniversity of AlbertaEdmontonCanada
  4. 4.Department of Mathematical and Statistical SciencesUniversity of Alberta HospitalEdmontonCanada
  5. 5.Department of Orthopaedic SurgeryRush University Medical CenterChicagoUSA

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