Cartilage endplate thickness variation measured by ultrashort echo-time MRI is associated with adjacent disc degeneration
Lippincott Williams & Wilkins
E592 - E600
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Study design: A magnetic resonance imaging study of human cadaver spines. Objective: To investigate associations between cartilage endplate (CEP) thickness and disc degeneration. Summary of background data: Damage to the CEP is associated with spinal injury and back pain. However, CEP morphology and its association with disc degeneration have not been well characterized. Methods: Ten lumbar motion segments with varying degrees of disc degeneration were harvested from six cadaveric spines and scanned with MRI in the sagittal plane using a T2-weighted 2D sequence, a 3D ultrashort echo-time (UTE) imaging sequence, and a 3D T1ρ mapping sequence. CEP thicknesses were calculated from 3D UTE image data using a custom, automated algorithm, and these values were validated against histology measurements. Pfirrmann grades and T1ρ values in the disc were assessed and correlated with CEP thickness. Results: The mean CEP thickness calculated from UTE images was 0.74 ± 0.04 mm. Statistical comparisons between histology and UTE-derived measurements of CEP thickness showed significant agreement, with the mean difference not significantly different from zero (p = 0.32). Within-disc variation of T1ρ (standard deviation) was significantly lower for Pfirrmann grade 4 than Pfirrmann grade 3 (p < 0.05). Within-disc variation of T1ρ and adjacent CEP thickness heterogeneity (coefficient of variation) had a significant negative correlation (r = -0.65, p = 0.04). The standard deviation of T1ρand the mean CEP thickness showed a moderate positive correlation (r = 0.40, p = 0.26). Conclusions: This study demonstrates that quantitative measurements of CEP thickness measured from UTE MRI are associated with disc degeneration. Our results suggest that variability in CEP thickness and T1ρ, rather than their mean values, may serve as valuable diagnostic markers for disc degeneration. Level of evidence: N/A.
Image processing algorithm
Low back pain
Ultrashort echo-time MRI (UTE MRI)