Endplate lesions in the lumbar spine: a novel MRI-based classification scheme and epidemiology in low back pain patients
Purpose The aims of the study were to introduce a classification scheme for endplate lesions based on T2-weighted magnetic resonance imaging and to detect possible associations between endplate lesions and other variables such as age, sex, disc degeneration and Modic changes in a large population. M...
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Published in | European spine journal Vol. 27; no. 11; pp. 2854 - 2861 |
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Main Authors | , , , , |
Format | Journal Article |
Language | English |
Published |
Berlin/Heidelberg
Springer Berlin Heidelberg
01.11.2018
Springer Nature B.V |
Subjects | |
Online Access | Get full text |
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Summary: | Purpose
The aims of the study were to introduce a classification scheme for endplate lesions based on T2-weighted magnetic resonance imaging and to detect possible associations between endplate lesions and other variables such as age, sex, disc degeneration and Modic changes in a large population.
Methods
MRI images of 996 low back pain patients were collected. All intervertebral spaces were classified as “normal”, “wavy/irregular”, “notched”, “Schmorl’s node” and “fracture”. The associations between endplate lesions and age, sex, disc degeneration and Modic changes were determined in the considered population.
Results
The most common endplate lesions were “notched” and “Schmorl’s nodes”. The prevalence was higher among the male subjects. In most patients (62.8%), no endplate lesions were detected, with a significant difference between male (57.5%) and female subjects (67.9%) (
p
< 0.001). Lesions were found to be associated with intervertebral disc degeneration (relative risk 2.49) and signal alterations (relative risk 3.08). Fleiss kappas of 0.73 and 0.89 were, respectively, assessed for the inter- and intra-observer reliabilities of the new classification system.
Conclusions
Endplate lesions were detected, classified with a novel scheme and analysed in a large population of patients suffering from low back pain based on MRI images. The reliability of the novel classification system was demonstrated.
Graphical abstract
These slides can be retrieved under Electronic Supplementary Material. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 |
ISSN: | 0940-6719 1432-0932 1432-0932 |
DOI: | 10.1007/s00586-018-5787-6 |