Axial T1ρ MRI as a diagnostic imaging modality to quantify proteoglycan concentration in degenerative disc disease
- PMID: 25236594
- PMCID: PMC5603078
- DOI: 10.1007/s00586-014-3582-6
Axial T1ρ MRI as a diagnostic imaging modality to quantify proteoglycan concentration in degenerative disc disease
Abstract
Purpose: The aim of the study was to investigate if axial T1ρ MR images had similar accuracy as established sagittal T1ρ MRI for the assessment of proteoglycan concentration and content in intervertebral degenerated discs (IDDs).
Methods: T1ρ and T2-weighted MR images of 12 intervertebral discs (IVDs) from 3 harvested human lumbar spines (levels L1-L2 to L5-S1) were grouped across their degenerative grade (Pfirrmann scores) and analyzed using a 3T MRI scanner in the axial and sagittal views. Post-processing of axial T1ρ-weighted images was performed using a Wiener filter. Median axial T1ρ values for traced regions of interest (ROIs) on color maps were compared against ROIs in the corresponding location in the sagittal plane of each disc. Assessment of sulfated glycosaminoglycans (GAGs) content was also performed.
Results: Comparison of post Wiener filtered mid-axial T1ρ values in the NP with corresponding mid-sagittal values revealed no statistical difference (P > 0.05). Higher axial T1ρ and biochemically measured GAGs content corresponded to a lower Pfirrmann grading of the IVDs. A strong association between the T1ρ values and the GAG contents was observed (r = 0.85, P = 0.0002).
Conclusions: The axial T1ρ methodology was validated against sagittal T1ρ providing an augmented spatial representation of IVD and can facilitate localization of focal degeneration within IVDs. T1ρ values provided a better granularity assessment of degenerative disc disease as it correlated with proteoglycan concentration. Thus, Wiener filtering is an effective tool for removing noise from T1ρ-weighted axial MR images.
Keywords: Axial T1ρ magnetic resonance imaging (MRI); Intervertebral disc (IVD); Pfirrmann grade; Proteoglycan; Wiener filtering.
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