OBJECTIVE: Computational models are increasingly being used to assess spine biomechanics and the risk of failure of posterior spinal fusion (PSF). Model validation is commonly performed by comparing the model results with analogous experimental or clinical studies. But few studies have reported the validity of the models used or the quantification of their uncertainty. The objective was to validate and establish the credibility of a biomechanical spine model developed to analyze the risk of Proximal Junctional Failure (PJF) after PSF according to ASME V&amp;V40:2018 standard framework.METHODS: A personalized computational multibody model of PSF developed to assess PJF risks was analysed following ASME V&amp;V40:2018 standard framework. To do this, the specific PSF surgery, postoperative erected posture and flexion movements were simulated in two adult subgroups: 1) five cases who did not develop PJF (asymptomatic); 2) six cases who subsequently developed PJF with a junctional subluxation complication.The model validation was designed as a comparative study between the asymptomatic and PJF subgroups.&nbsp; Simulations of the two subgroups were compared against actual outcomes to verify the model’s agreement with the reality of interest. The loads held by the proximal functional spinal unit, the implants, and the rods at the Upper Instrumented Vertebra (UIV) location were compared using Mann-Whitney U statistical test.To quantify the model variability in predicting mechanical factors related to PJF risks, a sensitivity analysis and uncertainty quantification were then performed on the asymptomatic cohort varying the spine stiffness, UIV implant position, vertebra-implant stiffness connection and rod stiffness.RESULTS: The sagittal moment above the upper instrumented vertebra (UIV+1) was significantly higher for the PJF group than the asymptomatic one (15.5 ± 5.0 vs. 8.7 ± 1.3 Nm, p=0.03), which could be interpreted as a predictor of soft tissue failure. The same index also appears to be related to junctional subluxation, as interpreted at the model level by an excessive moment at UIV+1. The other indices were more important for the PJF subgroup, but without statistical difference.&nbsp;The sensitivity analysis demonstrated a moderate correlation for the resulting moment at the UIV+1 vs. spine stiffness (r=0.57). A low correlation was found between the resulting moment at the UIV vs. spine stiffness and implant position (r=0.43 and 0.49 respectively).The uncertainty quantification performed on the control group confirmed that the model predictions were realistic and remained within the physiological range (mean ± STD): pullout implant force (160 ± 187 N), sagittal moment at UIV+1 (8.7 ± 1.9 Nm).CONCLUSION: This study demonstrates the applicability of the ASME V&amp;V40 guidelines for assessing the credibility of a biomechanical model to simulate PSF surgeries and predict PJF risks. We found good agreement between numerical prediction and clinical outcomes by finding higher loads at the proximal junctional segment for the simulated PJF cohort.

Biomechanical Modeling of Proximal Junctional Failure: Credibility Assessment Following Asme V&v40 Standard Framework

Paper Proceedings: https://asmedigitalcollection.asme.org/VVS/VVS2021/volume/84782

ASME 2021 Verification and Validation (VVS2021)

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