This preprint explores whether finite element analysis (FEA) applied to patient-specific, post-operative computed tomography (CT) data can provide clinically relevant information about stresses in instrumented lumbar spinal fusion constructs. The authors developed FEA models from post-operative CT scans of three patients who had previously undergone spinal fusion and used those models to compare mechanical performance of different implant materials across multiple fusion levels. The study frames FEA as a potential tool for both pre-operative planning and post-operative assessment of instrumentation and bone stresses.
The investigators segmented the spine from post-operative CT image data to build patient-specific finite element models representing the post-surgery anatomy. These models were intended to reflect the actual instrumented state after lumbar fusion in each patient. The report indicates that biomechanical analyses were completed for all three patients, though detailed model parameters (for example mesh density, element types, and exact boundary conditions) are not reported in the abstract and summary provided here.
Using the post-operative models, the study simulated a range of biomechanical loading conditions relevant to spinal mechanics, including compression, flexion, bending and extension. Within these simulations, the team tested pedicle-screw constructs manufactured from different materials to compare how material selection influenced stress distributions in both the instrumentation and the instrumented vertebrae. The materials explicitly compared in the summary are polyetheretherketone (PEEK) and titanium.
Across the cohort, PEEK constructs typically demonstrated lower peak implant stress when compared with titanium constructs for all spinal fusion levels examined. The authors report that material choice influenced stresses in both the instrumentation and the adjacent bone. For the 2-level fusion case specifically, the report notes comparable stress levels in the bone regardless of whether PEEK or titanium instrumentation was modelled. Exact numerical stress values, statistical comparisons, and case-by-case breakdowns are not included in the abstract summary available here.
The analysis indicated that increasing the number of fused levels resulted in significant differences in maximum von Mises stress within both the bone and the instrumentation. This suggests that construct length is an important variable affecting mechanical loading and that interactions between fusion level and implant material may alter stress distributions. The summary does not include detailed quantitative thresholds or clinically validated stress limits.
The authors propose two main clinical utilities for patient-specific FEA using post-operative CT-derived models:
Pre-operative planning: FEA could potentially inform selection of implant material and construct design by predicting implant and bone stresses under physiologic loads.
Post-operative assessment: FEA applied to post-operative imaging might help assess stress concentrations in instrumentation and instrumented vertebrae that could be relevant for predicting mechanical complications or guiding follow-up.
In this pilot cohort, differences between PEEK and titanium constructs in peak implant stress and in how fusion level altered stress distributions support the concept that material choice and construct length are relevant mechanical factors that FEA can evaluate.
This work is presented as a preprint and has not undergone peer review. The report represents a small, retrospective pilot using three patients; details such as patient demographics, numerical stress results, modelling specifics (mesh, material property values, contact definitions), and the statistical handling of results are not provided in the abstract and summary. The authors declare no competing interests. Funding sources listed include the European Research Council (RESTORE), Taighde Éireann - Research Ireland, and a Health Research Board Summer Student Scholarship. Because this is a preliminary report, the findings should be interpreted cautiously and would require full peer review and further validation before clinical adoption.