Augmentation of musculoskeletal soft tissue morphology within low back pain patients may suggest the presence of physiological stress shielding: An in vivo study.

INTRODUCTION: The pathomechanism of low back pain (LBP) remains unknown. However, changes to mechanical properties of soft tissues affected by LBP may indicate the presence of stress shielding, which may manifest via tissue remodeling. This study investigates the potential for physiological stress shielding within the lumbar spine by examining differences within lumbar soft tissue morphology between control and LBP subjects. METHODS: Through MRI, the total and functional cross-sectional area (tCSA, fCSA) and fatty infiltration (FI) of the lumbar multifidus (MF), erector spinae (ES), quadratus lumborum (QL), psoas major (PM), and thoracolumbar fascia (TLF) were measured from the L1/L2 to L5/S1 intervertebral disc levels of 69 subjects (36 LBP and 33 control subjects). Statistical analysis was conducted using Mann-Whitney U. P < 0.05 denoted significance. RESULTS: Comparison of male LBP patients and male healthy controls yielded an increase in tCSA and fCSA within the L4/L5 PM (p < 0.01), and the L4/L5 ES (p = 0.02) and PM (p < 0.01), respectively, of LBP patients. Female LBP patients' FI compared to female controls increased within the L1/L2 MF (p = 0.03), L3/L4 MF (p = 0.04) and ES (p = 0.02), and L4/L5 QL (p = 0.01). The L3/L4 TLF also demonstrated an 8% increase in LBP subjects. CONCLUSION: Male patients' results suggest elevated tissue loading during motion yielding hypertrophy in the L4/L5 ES and PM fCSA, and PM tCSA. Female LBP patients' MF, ES, and PM at L3/L4 demonstrating elevated FI coupled with TLF tCSA hypertrophy may suggest irregular stress distributions and lay the foundation for stress shielding within musculoskeletal soft tissues.

System identification and simulation of soft tissue force feedback in a spine surgical simulator.

Surgical simulators are being introduced as training modalities for surgeons. This paper aims to evaluate dynamic models used to convey force feedback from puncturing the soft tissue during a spine surgical simulation. The force feedback of the tissue is treated as a dynamic system. This is done by performing classical system identification across a bandwidth of frequencies on a tissue analogue and fitting that behaviour to dynamic viscoelastic models. The models that are tested are an inverted linear model, the Maxwell model, the Kelvin-Boltzmann (KB) model, and a higher-order blackbox (HO) model. Several error metrics such as percent variance accounted for (%VAF) are determined to measure solution accuracy. The force feedback models are programmed into a surgical simulator and tested with study participants who rated them based on how well the identified models match the behaviour of the rubber tissue analogue. The highest %VAF is 82.64% when the tissue is modelled as the HO model. Statistically significant differences (p < 0.05) are found between all model ratings from participants except between the HO model and the KB model. However, the HO model has the highest percentage (37.8%) of participants who rank its performance as the closest to the tissue analogue compared to the other force feedback models. The more accurately the dynamic behaviour resembles the tissue analogue, the higher the model was rated by study participants. This study highlights the importance of utilizing dynamic signals to generate dynamic models of soft tissue for spine surgical simulators.