A predictive model for creep deformation following vertebral compression fractures.
Bone
; 141: 115595, 2020 12.
Article
em En
| MEDLINE
| ID: mdl-32814126
ABSTRACT
Many vertebral compression fractures continue to collapse over time, resulting in spinal deformity and chronic back pain. Currently, there is no adequate screening strategy to identify patients at risk of progressive vertebral collapse. This study developed a mathematical model to describe the quantitative relationship between initial bone damage and progressive ("creep") deformation in human vertebrae. The model uses creep rate before damage, and the degree of vertebral bone damage, to predict creep rate of a fractured vertebra following bone damage. Mechanical testing data were obtained from 27 vertebral trabeculae samples, and 38 motion segments, from 26 human spines. These were analysed to evaluate bone damage intensity, and creep rates before and after damage, in order to estimate the model parameter, p, which represents how bone damage affects the change of creep rate after damage. Results of the model showed that p was 1.38 (R2â¯=â¯0.72, pâ¯<â¯0.001) for vertebral trabeculae, and 1.48 for motion segments (R2â¯=â¯0.22, pâ¯=â¯0.003). These values were not significantly different from each other (Pâ¯>â¯0.05). Further analyses revealed that p was not significantly influenced by cortical bone damage, endplate damage, disc degeneration, vertebral size, or vertebral areal bone mineral density (aBMD) (Pâ¯>â¯0.05). The key determinant of creep deformation following vertebral compression fracture was the degree of trabecular bone damage. The proposed model could be used to identify the measures of bone damage on routine MR images that are associated with creep deformation so that a screening tool can be developed to predict progressive vertebral collapse following compression fracture.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Fraturas da Coluna Vertebral
/
Fraturas por Compressão
Tipo de estudo:
Prognostic_studies
/
Risk_factors_studies
Limite:
Humans
Idioma:
En
Ano de publicação:
2020
Tipo de documento:
Article