Can Quantitative Magnetic Resonance Imaging Predict Mechanical Behavior of Human Intervertebral Disks with Different Grades of Degeneration?

Introduction The dramatic changes in morphology, composition, and structure that occur in the intervertebral disk (IVD) with aging and degeneration are accompanied by specific changes in mechanical properties of the disk material. 1,2 Evaluation of these changes in the IVD hinges on the ability to objectively and noninvasively assess the IVD matrix composition and integrity. Different studies on human IVDs have correlated IVD matrix composition and integrity to the longitudinal magnetization recovery T1, the transverse magnetization decay T2, the magnetization transfer ratio (MTR), and apparent diffusion coefficient (ADC). 3,4 Correlations and multiple linear regressions have been also identified between quantitative magnetic resonance imaging (qMRI) parameters, biochemical, and mechanical parameters of targeted enzyme matrix denaturation and buffer-treated bovine IVDs. To this end, qMRI analysis can be used to correlate MRI signal to the mechanical properties of NP and AF tissue in order to predict structural changes in IVDs with degeneration. The aim of the present study was to determine how quantitative MRI parameters can predict biomechanical properties in human IVDs with different grades of degeneration. Materials and Methods Experimental Groups Ten whole lumbar spine specimens, 5 disks per spine, were obtained through organ donations via Héma-Québec within 24 hours after death. Age of donors was from 32 to 77 years. The samples were vacuum sealed in plastic bags for MRI to maintain hydration. MRI Procedure The MRI examinations were carried out in a 1.5T whole-body Siemens’ Avanto system using the standard circularly polarized head coil. The samples were placed in a sagittal orientation and T1, T2, MTR, and ADC were measured as previously described. 1 All disks ( n = 50) were then graded from T2-weighted images according to the classification system described by Pfirrmann. Numerical analysis of quantitative MRI was performed using a custom code written in MATLAB (MathWorks, Natick, MA, USA) allowing the selection of the regions of interest (ROI) and the calculation of average signal intensities from all images. ROI were traced manually as polygonal shapes with no contact with the endplate tissues and were reproduced identically on all T1, T2, Ms/Mo ratio, and diffusion images. Mechanical Testing Procedure Confined compression tests were performed on 5-mm-diameter cylindrical plugs of tissue using a custom built axial testing machine. Material parameters (aggregate modulus HA and permeability k) were obtained from a linear biphasic fit. Dynamic shear testing was carried out using a rheometer (TA Instruments). Steady-state dynamic shear modulus and phase angle were calculated at each point of the frequency and strain sweeps and fitted with exponential functions. Statistical Methods Correlations between qMRI and mechanical parameters were investigated using Pearson test performed on GraphPad Prism software (GraphPad Software, La Jolla, CA, USA). Correlation between a mechanical parameter and an MR parameter in the same region of the disk was considered significant with p. Results Significant correlations for the NP tissue were found between T2 and shear modulus |G*| ( r = −0.465, p = 0.022), and between diffusion ADC and α δ ( r = 0.4, p = 0.047) (Fig. 1). Significant correlations for the AF tissue were found between T1 and α δ ( r = 0.372, p = 0.047) and between T1 and permeability k ( r = −0.468, p = 0.043) (Fig. 2). No correlations were found between MTR and any mechanical parameters for both AF and NP tissues. Conclusion The results of the present study are consistent with our previous studies in bovine model and indicate sensitivity to distinct changes at varying levels of degeneration. In the AF, permeability and phase angle were predicted by T1 while in the NP tissue, T2 was a stronger determinant of the tissue integrity (reflected by shear modulus). This may relate to the fact that T1 has been predominantly correlated to water content, while T2 is influenced by tissue anisotropy (orientation of collagen fibers), collagen concentration, and water content in tissues. These results prove that it is possible to develop correlations and multiple linear regressions in human IVDs which are essential for developing quantitative MRI as a diagnostic tool in determining the functional state of the disk. I confirm having declared any potential conflict of interest for all authors listed on this abstract Yes Disclosure of Interest None declared Mwale F, et al. Journal of Magnetic Resonance Imaging 2008; 27:563–573 Iatridis J, et al. Journal of Biomechanics 1998; 31:535–544 Antoniou, J. et al. Magnetic Resonance in Medicine1998; 40(6):900–907 Antoniou, J. et al. Journal of Magnetic Resonance Imaging 2004; 22:963–972

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