Using MRI-Derived Spinal Geometry to Compute Back Compressive Stress (BCS): a New Measure of Low Back Pain Risk

Abstract

Back compressive force (BCF) is a commonly used surrogate for the risk of developing low back pain. Point force estimates of spinal loading have been shown to predict low back pain in epidemiological studies. However, they are an imperfect measure and can over- or under-estimate risk, particularly for very large or small individuals. A logical means to normalize risk over a varied population is to convert these forces to stresses (force/unit area). To achieve this, Magnetic Resonance Imaging (MRI) scans were used to provide area measurements for the intervertebral discs and vertebral bodies of the lumbar region (L3/L4, L4/L5, & L5/S1 segments). Various regression models were explored based on individual subject gross anthropometry. These models allow for the estimation of intervertebral disc (IVD) size using easily measured anthropometric characteristics such as height and gender. Converting the BCF to a back compressive stress (BCS) normalizes and personalizes risk estimates for subjects of varying sizes. Back compressive force data from a previous study was converted to back compressive stress to determine if risk estimates could be improved. Using peak BCF with a cut point of 3400 N (~770 lbs) yielded an odds ratio of 2.76 (1.2-6.6) to predict jobs with injuries and discomfort. Using BCS with a cut point of 280 N/cm2, which corresponds to 3400 N load applied to a 50th percentile female L5/S1 IVD area, improved the odds ratio to 5.78 (1.8-18.4). Normalizing for the size of a subject’s IVD shows great promise for improving the predictive abilities of biomechanical assessment methods.

Keywords: Low Back Pain, Risk, Modeling, Intervertebral Disc (IVD), Back Compressive Force (BCF), Back Compressive Stress (BCS)

DOI: 10.54941/ahfe100407