In vivo prediction of intervertebral disc strains and segmental kinematics from clinical MRI during lumbar extension

Excessive intervertebral disc (IVD) strains and vertebral body motions are associated with lower back pain (LBP). Quantifying these strains and motions may aid in predicting the success of candidate LBP treatments and enable better prediction of pre-operative instability and post-operative implant failure, but cannot currently be obtained in routine clinical assessment. Thus, the aim of this study was to evaluate the feasibility of utilising clinical measures of spinal alignment, IVD geometry, and disc degeneration to predict in vivo IVD strains and vertebral translations.

Fifteen participants presenting no LBP were subjected to one unloaded and one supine extension-loaded MRI scan. MRI-based digital volume correlation (DVC) was used to quantify the principal and shear strains of lumbar IVDs and anterior-posterior, cranial-caudal, and total translation of the vertebral bodies (L1-S1). IVD height, anterior-posterior IVD height ratio, segmental lordosis, lumbar lordosis, lumbar height, sacral angle, and Pfirrmann grade were evaluated using the reference MR images. Multivariate linear regression was used to predict level-wise strains and translations.

IVD strains and vertebral translations were successfully predicted from clinical measures of spinal alignment and disc degeneration, but only at the L4-L5 and L5-S1 levels. Specifically, greater minimum principal IVD strains and vertebral anterolisthesis were associated with a reduced anterior-posterior IVD height ratio at L4-L5 (p < 0.01). Greater peak minimum principal strains and anterolisthesis were associated with taller IVDs in the L5-S1 segment (p < 0.05). In the same segment, increased sacral angle was associated with greater peak minimum principal strains (p < 0.05) but lower anterolisthesis (p < 0.01).

This study demonstrates the potential of utilising radiographic variables to predict the biomechanical behaviour at the segmental level, giving rise to future exploration of complex loading patterns in patient cohorts with specific spinal pathologies.