Project description
Personalised surgical strategies for chronic back pain
Chronic back pain, primarily caused by biomechanical factors, can lead to disability. In elderly patients, the biomechanical scenario is complicated by osteoporosis, which makes it necessary to perform surgery to treat instability-related pain and restore the balance of the spine. However, the timing of surgery remains subjective and is based on the surgeon’s experience. Recently, objective image-based criteria have been established to predict the outcome of surgery. The ERC-funded iBack project aims to advance the understanding of instability-related pain and develop personalised surgical strategies for back pain patients. It will improve in vivo imaging and image analysis to create individualised biomechanical models that reveal the underlying pathophysiological process. This will enable personalised treatment planning and prediction of outcomes after spine surgery or conservative treatment.
Objective
Chronic back pain is a major burden and source of disability worldwide. It is primarily attributed to biomechanical factors. In elderly patients, osteoporosis complicates the biomechanical scenario. Surgery is often required to treat instability-related pain and to restore the balance of the spine. However, when and how to perform surgery remains a highly subjective decision based on the surgeon’s experience, with 2/3 of patients experiencing prolonged pain.
We recently established objective, image-based criteria for surgery outcome prediction. As an example, we were able to develop tools for routine density and fracture assessment and demonstrate that screw loosening occurs in >85% of patients with bone mineral density <92 mg/ccm. This directly influences the surgical approach in all spine surgery patients at our institution. Additionally, we improved the prediction of bone strength by advanced image post processing such as scaling indices, finite element and finite cell models.
The high-level objective of iBack is to individualize therapy planning in back pain patients. We will improve in-vivo imaging and image analysis to compute individualized biomechanical models that reveal the underlying pathophysiologic process and allow personalized treatment planning and outcome prediction after spine surgery or conservative treatment.
The main objectives of iBack are: (1) improving computed tomography (CT) and magnetic resonance imaging (MRI) of the spine; (2) combining sagittal balance radiographs, CT and MRI of the spine in one biomechanical multi-body simulation (MBS); (3) creating a statistical model that includes both clinical and biomechanical information to reveal interactions between the two and to predict individual treatment success probability.
The results of iBack will help to better understand instability-related pain and develop personalized surgical strategies which will have major impacts on patients.
Fields of science
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringsignal processingcompressed sensing
- medical and health sciencesclinical medicinesurgery
- engineering and technologymedical engineeringdiagnostic imagingcomputed tomography
- engineering and technologymedical engineeringdiagnostic imagingmagnetic resonance imaging
- natural sciencesmathematicsapplied mathematicsstatistics and probability
Programme(s)
Topic(s)
Funding Scheme
ERC-STG - Starting GrantHost institution
81675 Muenchen
Germany