Can pathoanatomical pathways of degeneration in lumbar motion segments be identified by clustering MRI findings

BMC Musculoskeletal Disorders

Peter Kent²  Per Kjaer¹  Tue S Jensen²  Rikke K Jensen² 

[1] Institute of Sports Science and Clinical Biomechanics, University of Southern Denmark, Odense, Denmark;Institute of Regional Health Services Research, University of Southern Denmark, Middelfart, Denmark

关键词: Latent Class Analysis;    Subgroup;    Magnetic Resonance Imaging;    Disc degeneration;    Low back pain;   

Others  :  1130377
DOI  :  10.1186/1471-2474-14-198

 received in 2012-09-10, accepted in 2013-06-24,  发布年份 2013

【 摘 要 】

Background

Magnetic Resonance Imaging (MRI) is the gold standard for detailed visualisation of spinal pathological and degenerative processes, but the prevailing view is that such imaging findings have little or no clinical relevance for low back pain. This is because these findings appear to have little association with treatment effects in clinical populations, and mostly a weak association with the presence of pain in the general population.

However, almost all research into these associations is based on the examination of individual MRI findings, despite its being very common for multiple MRI findings to coexist. Therefore, this proof-of-concept study investigated the capacity of a multivariable statistical method to identify clusters of MRI findings and for those clusters to be grouped into pathways of vertebral degeneration.

Methods

This study is a secondary analysis of data from 631 patients, from an outpatient spine clinic, who had been screened for inclusion in a randomised controlled trial. The available data created a total sample pool of 3,155 vertebral motion segments. The mean age of the cohort was 42 years (SD 10.8, range 18–73) and 54% were women.

MRI images were quantitatively coded by an experienced musculoskeletal research radiologist using a detailed and standardised research MRI evaluation protocol that has demonstrated high reproducibility. Comprehensive MRI findings descriptive of the disco-vertebral component of lumbar vertebrae were clustered using Latent Class Analysis. Two pairs of researchers, each containing an experienced MRI researcher, then independently categorised the clusters into hypothetical pathoanatomic pathways based on the known histological changes of discovertebral degeneration.

Results

Twelve clusters of MRI findings were identified, described and grouped into five different hypothetical pathways of degeneration that appear to have face validity.

Conclusions

This study has shown that Latent Class Analysis can be used to identify clusters of MRI findings from people with LBP and that those clusters can be grouped into degenerative pathways that are biologically plausible. If these clusters of MRI findings are reproducible in other datasets of similar patients, they may form a stable platform to investigate the relationship between degenerative pathways and clinically important characteristics such as pain and activity limitation.

【 授权许可】

   
2013 Jensen et al.; licensee BioMed Central Ltd.

【 图 表 】

Figure 1.

Figure 2.

Figure 3.

Figure 4.

Figure 5.

Figure 6.

Figure 7.

Figure 8.

Figure 9.

Figure 10.

Figure 11.

Figure 12.

Figure 13.

【 参考文献 】

• [1]Hancock MJ, Maher CG, Laslett M, Hay E, Koes B: Discussion paper: what happened to the ‘bio’ in the bio-psycho-social model of low back pain. Eur Spine J 2011, 20:2105-2110.
• [2]Deyo RA, Rainville J, Kent DL: What can the history and physical examination tell us about low back pain? JAMA 1992, 268:760-765.
• [3]Kent P, Keating J: Do primary-care clinicians think that nonspecific low back pain is one condition. Spine (Phila Pa 1976) 2004, 29:1022-1031.
• [4]Fairbank J, Gwilym SE, France JC, Daffner SD, Dettori J, Hermsmeyer J, Andersson G: The role of classification of chronic low back pain. Spine (Phila Pa 1976) 2011, 36:S19-S42.
• [5]Kent P, Kjaer P: The efficacy of targeted interventions for modifiable psychosocial risk factors of persistent nonspecific low back pain - A systematic review. Man Ther 2012, 17:385-401.
• [6]Donelson R, Aprill C, Medcalf R, Grant W: A prospective study of centralization of lumbar and referred pain. A predictor of symptomatic discs and anular competence. Spine (Phila Pa 1976) 1997, 22:1115-1122.
• [7]Long A, Donelson R, Fung T: Does it matter which exercise? A randomized control trial of exercise for low back pain. Spine (Phila Pa 1976) 2004, 29:2593-2602.
• [8]Boden SD, Davis DO, Dina TS, Patronas NJ, Wiesel SW: Abnormal magnetic-resonance scans of the lumbar spine in asymptomatic subjects. A prospective investigation. J Bone Joint Surg Am 1990, 72:403-408.
• [9]Jarvik JJ, Hollingworth W, Heagerty P, Haynor DR, Deyo RA: The Longitudinal Assessment of Imaging and Disability of the Back (LAIDBack) Study: baseline data. Spine (Phila Pa 1976) 2001, 26:1158-1166.
• [10]Jensen MC, Brant-Zawadzki MN, Obuchowski N, Modic MT, Malkasian D, Ross JS: Magnetic resonance imaging of the lumbar spine in people without back pain. N Engl J Med 1994, 331:69-73.
• [11]Jarvik JG, Hollingworth W, Martin B, Emerson SS, Gray DT, Overman S, Robinson D, Staiger T, Wessbecher F, Sullivan SD, Kreuter W, Deyo RA: Rapid magnetic resonance imaging vs radiographs for patients with low back pain: a randomized controlled trial. JAMA 2003, 289:2810-2818.
• [12]Chou D, Samartzis D, Bellabarba C, Patel A, Luk KD, Kisser JM, Skelly AC: Degenerative magnetic resonance imaging changes in patients with chronic low back pain: a systematic review. Spine (Phila Pa 1976) 2011, 36:S43-S53.
• [13]Boos N, Weissbach S, Rohrbach H, Weiler C, Spratt KF, Nerlich AG: Classification of age-related changes in lumbar intervertebral discs: 2002 Volvo Award in basic science. Spine (Phila Pa 1976) 2002, 27:2631-2644.
• [14]Wang Y, Videman T, Battie MC: ISSLS Prize Winner: Lumbar Vertebral Endplate Lesions: Associations With Disc Degeneration and Back Pain History. Spine (Phila Pa 1976) 2012, 37:1490-1496.
• [15]Lusins JO, Cicoria AD, Goldsmith SJ: SPECT and lumbar MRI in back pain with emphasis on changes in end plates in association with disc degeneration. J Neuroimaging 1998, 8:78-82.
• [16]Schmid G, Witteler A, Willburger R, Kuhnen C, Jergas M, Koester O: Lumbar disk herniation: correlation of histologic findings with marrow signal intensity changes in vertebral endplates at MR imaging. Radiology 2004, 231:352-358.
• [17]van Dieen JH, Weinans H, Toussaint HM: Fractures of the lumbar vertebral endplate in the etiology of low back pain: a hypothesis on the causative role of spinal compression in aspecific low back pain. Med Hypotheses 1999, 53:246-252.
• [18]Cheung KM, Karppinen J, Chan D, Ho DW, Song YQ, Sham P, Cheah KS, Leong JC, Luk KD: Prevalence and pattern of lumbar magnetic resonance imaging changes in a population study of one thousand forty-three individuals. Spine (Phila Pa 1976) 2009, 34:934-940.
• [19]Pfirrmann CW, Metzdorf A, Zanetti M, Hodler J, Boos N: Magnetic resonance classification of lumbar intervertebral disc degeneration. Spine (Phila Pa 1976) 2001, 26:1873-1878.
• [20]Jensen RK, Leboeuf-Yde C, Wedderkopp N, Sorensen JS, Manniche C: Rest versus exercise as treatment for patients with low back pain and Modic changes. A randomized controlled clinical trial. BMC Med 2012, 10:22. BioMed Central Full Text
• [21]Jensen TS, Sorensen JS, Kjaer P: Intra- and interobserver reproducibility of vertebral endplate signal (modic) changes in the lumbar spine: the Nordic Modic Consensus Group classification. Acta Radiol 2007, 48:748-754.
• [22]Solgaard SJ, Kjaer P, Jensen ST, Andersen P: Low-field magnetic resonance imaging of the lumbar spine: reliability of qualitative evaluation of disc and muscle parameters. Acta Radiol 2006, 47:947-953.
• [23]Meyerding HW: Low back ache and sciatic pain associated with spondylolisthesis and protruded intervertebral disc. J Bone Joint Surg Am 1941, 23:461.
• [24]Magidson J, Vermunt JK: Latent class models for clustering: A comparison with K-means. Canadian Journal of Marketing Research 2002, 20:37-44.
• [25]Wallace CS, Dowe DL: Intrinsic classification by MML - the SNOB program. Armidale NSW, Australia: World Scientific; 1994:37-44. [Proc 7th Australian Joint Conference on Artificial Intelligence]
• [26]Wallace CS: Statistical and inductive inference by minimum message length. New York, USA: Springer; 2005.
• [27]Takatalo J, Karppinen J, Niinimaki J, Taimela S, Nayha S, Mutanen P, Sequeiros RB, Kyllönen E, Tervonen O: Does lumbar disc degeneration on magnetic resonance imaging associate with low back symptom severity in young Finnish adults. Spine (Phila Pa 1976) 2011, 36:2180-2189.
• [28]Takatalo J, Karppinen J, Niinimaki J, Taimela S, Mutanen P, Sequeiros RB, Näyhä S, Järvelin MR, Kyllönen E, Tervonen O: Association of Modic Changes, Schmorl’s Nodes, Spondylolytic Defects, High-Intensity Zone Lesions, Disc Herniations, and Radial Tears With Low Back Symptom Severity Among Young Finnish Adults. Spine (Phila Pa 1976) 2012, 37:1231-1239.
• [29]Prust M, Wang J, Morizono H, Messing A, Brenner M, Gordon E, Hartka T, Sokohl A, Schiffmann R, Gordish-Dressman H, Albin R, Amartino H, Brockman K, Dinopoulos A, Dotti MT, Fain D, Fernandez R, Ferreira J, Fleming J, Gill D, Griebel M, Heilstedt H, Kaplan P, Lewis D, Nakagawa M, Pedersen R, Reddy A, Sawaishi Y, Schneider M, Sherr E, Takiyama Y, Wakabayashi K, Gorospe JR, Vanderver A: GFAP mutations, age at onset, and clinical subtypes in Alexander disease. Neurology 2011, 77:1287-1294.
• [30]Wolz R, Julkunen V, Koikkalainen J, Niskanen E, Zhang DP, Rueckert D, Soininen H, Lötjönen J: Alzheimer’s Disease Neuroimaging Initiative: Multi-method analysis of MRI images in early diagnostics of Alzheimer’s disease. PLoS One 2011, 6:e25446.
• [31]Yoon JH, Tamir D, Minzenberg MJ, Ragland JD, Ursu S, Carter CS: Multivariate pattern analysis of functional magnetic resonance imaging data reveals deficits in distributed representations in schizophrenia. Biol Psychiatry 2008, 64:1035-1041.
• [32]Zwemmer JN, Berkhof J, Castelijns JA, Barkhof F, Polman CH, Uitdehaag BM: Classification of multiple sclerosis patients by latent class analysis of magnetic resonance imaging characteristics. Mult Scler 2006, 12:565-572.
• [33]Thompson JP, Pearce RH, Schechter MT, Adams ME, Tsang IK, Bishop PB: Preliminary evaluation of a scheme for grading the gross morphology of the human intervertebral disc. Spine (Phila Pa 1976) 1990, 15:411-415.