Study design:

Assessment of sagittal lordosis distribution on mechanical proximal junctional failure-related risks through computer-based biomechanical models.

Objective:

To biomechanically assess how lordosis distribution influences radiographical and biomechanical indices related to Proximal Junctional Failure (PJF). The “optimal” patient-specific targets to restore the sagittal balance in posterior spinal fusion are still not known. Among these, the effect of the lumbar lordosis correction strategy on complications such as PJF remain uncertain.

Methods:

In this computational biomechanical study, five adult spinal deformity patients who underwent posterior spinal fixation were retrospectively reviewed. Their surgery, first erect posture and flexion movement were simulated with a patient-specific multibody model. Three pedicle subtraction osteotomy (PSO) levels (L3, L4, and L5) were simulated, with consistent global lordosis for a given patient and pelvic tilt adjusted accordingly to the actual surgery. Computed loads on the anterior spine and instrumentation were analyzed and compared using Kruskal-Wallis statistical tests and Spearman correlations.

Results:

In these models, no significant correlations were found between the lordosis distribution index (LDI), PSO level and biomechanical PJF-related indices. However, increasing the sagittal vertical axis (SVA) and thoracolumbar junction angle (TLJ) and decreasing the sacral slope (SS) increased the bending moment sustained by the rods at the proximal instrumented level (r = 0.52, 0.57, – 0.56, respectively, p < 0.05). There was a negative correlation between SS and the bending moment held by the adjacent proximal segment (r = - 0.71, p < 0.05).

Conclusion:

Based on these biomechanical simulations, there was no correlation between the lordosis distribution and PJF-associated biomechanical factors. However, increasing SS and flattening the TLJ, as postural adjustment strategies required by a more distal PSO, did decrease such PJF-related factors. Sagittal restoration and PJF risks remain multifactorial, and the use of patient-specific biomechanical models may help to better understand the complex interrelated mechanisms.