Annulus fibrosus functional extrafibrillar and fibrous mechanical behaviour: experimental and computational characterisation

• Main Authors: Marlène Mengoni, Oluwasegun Kayode, Sebastien N. F. Sikora, Fernando Y. Zapata-Cornelio, Diane E. Gregory, Ruth K. Wilcox
• Format: Article
• Language: English
• Published: The Royal Society 2017-01-01
• Series: Royal Society Open Science
• Subjects: intervertebral disc; annulus fibrosus; pre-strain; reverse engineering; direct-controlled calibration
• Online Access: https://royalsocietypublishing.org/doi/pdf/10.1098/rsos.170807

The development of current surgical treatments for intervertebral disc damage could benefit from virtual environment accounting for population variations. For such models to be reliable, a relevant description of the mechanical properties of the different tissues and their role in the functional mechanics of the disc is of major importance. The aims of this work were first to assess the physiological hoop strain in the annulus fibrosus in fresh conditions (n = 5) in order to extract a functional behaviour of the extrafibrillar matrix; then to reverse-engineer the annulus fibrosus fibrillar behaviour (n = 6). This was achieved by performing both direct and global controlled calibration of material parameters, accounting for the whole process of experimental design and in silico model methodology. Direct-controlled models are specimen-specific models representing controlled experimental conditions that can be replicated and directly comparing measurements. Validation was performed on another six specimens and a sensitivity study was performed. Hoop strains were measured as 17 ± 3% after 10 min relaxation and 21 ± 4% after 20–25 min relaxation, with no significant difference between the two measurements. The extrafibrillar matrix functional moduli were measured as 1.5 ± 0.7 MPa. Fibre-related material parameters showed large variability, with a variance above 0.28. Direct-controlled calibration and validation provides confidence that the model development methodology can capture the measurable variation within the population of tested specimens.