BACKGROUND: Finite element models of augmented vertebral bodies require a realistic modelling of the cement infiltrated region. Most methods published so far used idealized cement shapes or oversimplified material models for the augmented region. In this study, an improved, anatomy-specific, homogenized finite element method was developed and validated to predict the apparent as well as the local mechanical behavior of augmented vertebral bodies. METHODS: Forty-nine human vertebral body sections were prepared by removing the cortical endplates and scanned with high-resolution peripheral quantitative CT before and after injection of a standard and a low-modulus bone cement. Forty-one specimens were tested in compression to measure stiffness, strength and contact pressure distributions between specimens and loading-plates. From the remaining eight, fourteen cylindrical specimens were extracted from the augmented region and tested in compression to obtain material properties. Anatomy-specific finite element models were generated from the CT data. The models featured element-specific, density-fabric-based material properties, damage accumulation, real cement distributions and experimentally determined material properties for the augmented region. Apparent stiffness and strength as well as contact pressure distributions at the loading plates were compared between simulations and experiments. FINDINGS: The finite element models were able to predict apparent stiffness (R(2)>0.86) and apparent strength (R(2)>0.92) very well. Also, the numerically obtained pressure distributions were in reasonable quantitative (R(2)>0.48) and qualitative agreement with the experiments. INTERPRETATION: The proposed finite element models have proven to be an accurate tool for studying the apparent as well as the local mechanical behavior of augmented vertebral bodies.
BACKGROUND: Finite element models of augmented vertebral bodies require a realistic modelling of the cement infiltrated region. Most methods published so far used idealized cement shapes or oversimplified material models for the augmented region. In this study, an improved, anatomy-specific, homogenized finite element method was developed and validated to predict the apparent as well as the local mechanical behavior of augmented vertebral bodies. METHODS: Forty-nine human vertebral body sections were prepared by removing the cortical endplates and scanned with high-resolution peripheral quantitative CT before and after injection of a standard and a low-modulus bone cement. Forty-one specimens were tested in compression to measure stiffness, strength and contact pressure distributions between specimens and loading-plates. From the remaining eight, fourteen cylindrical specimens were extracted from the augmented region and tested in compression to obtain material properties. Anatomy-specific finite element models were generated from the CT data. The models featured element-specific, density-fabric-based material properties, damage accumulation, real cement distributions and experimentally determined material properties for the augmented region. Apparent stiffness and strength as well as contact pressure distributions at the loading plates were compared between simulations and experiments. FINDINGS: The finite element models were able to predict apparent stiffness (R(2)>0.86) and apparent strength (R(2)>0.92) very well. Also, the numerically obtained pressure distributions were in reasonable quantitative (R(2)>0.48) and qualitative agreement with the experiments. INTERPRETATION: The proposed finite element models have proven to be an accurate tool for studying the apparent as well as the local mechanical behavior of augmented vertebral bodies.
Authors: Fernando Y Zapata-Cornelio; Gavin A Day; Ruth H Coe; Sebastien N F Sikora; Vithanage N Wijayathunga; Sami M Tarsuslugil; Marlène Mengoni; Ruth K Wilcox Journal: Ann Biomed Eng Date: 2017-07-25 Impact factor: 3.934
Authors: Sairam Gajavelli; Aaron Gee; Z Shaghayegh Bagheri; Emil H Schemitsch; Christopher S Bailey; Parham Rasoulinejad; Radovan Zdero Journal: Biomed Res Int Date: 2022-09-21 Impact factor: 3.246