Project Team Leader
Dr Julie Choisne (UoA)
A/Prof Justin Fernandez (UoA)
Mr Peter Robertson (Auckland City Hospital)
Mr Rowan Schouten (UoO Christchurch)
Dr Ju Zhang (Formus Labs ltd)
Degenerative spinal disc disorder (DDD) can lead to chronic low back pain which is one of the main musculoskeletal disorders with major disability. DDD causes the disc between two vertebrae to lose its damping function and results in flat back and pain for the patient. Surgical treatment consists of replacing the degenerative disc with a fusion implant. Incorrect placement of the implant and inability of restoring the natural lumbar spine curvature (lordosis) can lead to patients continuing to experience significant pain and/or failure of the adjacent discs due to changes in the axial loading of the spine. In both cases further expensive surgery is required. Spinal fusion has a relatively high failure rate (reportedly up to 40%), although only 25% of failures may be revised. Patients with unrevised failed surgery face long term health issue, with associated economic burdens.
Computational modelling has the ability to predict clinical and functional outcomes but is highly dependent on the complex geometry of the musculoskeletal system and the ability to describe patient-specific loads and boundary conditions. We propose to develop a web-based tool to plan spinal fusion surgery for improved clinical outcomes using 1) patient’s frontal and sagittal X-rays to generate patient-specific 3 dimensional bone geometry and 2) a computational model to compute stress distribution in the spine based on implant placement and calculate the optimal lumbar lordosis angle to be restored.