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Age and disc degeneration in low back pain: automated analysis enables a magnetic resonance imaging comparison of large cross-sectional cohorts of symptomatic and asymptomatic subjects

Abstract:
Objectives We aimed to improve understanding of the role of imaging in diagnosis of low back pain by determining the prevalence of age-related disc degeneration in asymptomatic and symptomatic subjects. Spinal MRIs of symptomatic and asymptomatic subjects were re-annotated onto the same objective grading system and prevalence of degenerative changes compared.
 
Methods In an exploratory cross-sectional study, we compared the prevalence of disc degeneration between two large groups of anonymised females, 30-80yrs, viz a symptomatic group with chronic back pain (724) and an asymptomatic (701) group. We used a verified automated MRI annotation system to re-annotate their spinal MRIs and report degeneration on the Pfirrmann (1-5) scale, and other degenerative changes (herniation, endplate defects, marrow signs, spinal stenosis) as binary present/absent.
 
Results Severe degenerative changes were significantly more prevalent in discs of symptomatics than asymptomatics in the lower (L4-S1) but not the upper (L1-L3) lumbar discs in subjects <60years. We found high co-existence of several degenerative features in both populations. Degeneration was minimal in around 30% of symptomatics < 50years.
 
Conclusions Automated MRI provides a valuable means of rapidly comparing large MRI datasets. Here, through directly comparing MRI annotations on the same objective scales it enabled us to detect significant age and spinal-level related differences in the prevalence of degenerative features between asymptomatic and symptomatic populations. By distinguishing between symptomatics whose discs have structural defects, and symptomatics with minimal degenerative changes, MRI could provide a means of clinical stratification, and provide a useful pathway to investigate possible pain sources.
Publication status:
Published
Peer review status:
Not peer reviewed

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Preprint server copy:
10.1101/2021.11.08.21265571

Authors

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Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author
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Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Oxford college:
Brasenose College
Role:
Author
ORCID:
0000-0002-8945-8573
More by this author
Role:
Author
ORCID:
0000-0002-2998-2744


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Funder identifier:
https://ror.org/0439y7842
Grant:
EP/M013774/1


Preprint server:
medRxiv
Publication date:
2021-11-08
DOI:


Language:
English
Pubs id:
1585996
Local pid:
pubs:1585996
Deposit date:
2024-06-14
ARK identifier:

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