ESR 7: Spine Inverse Modelling for Scoliosis Brace Design

Early Stage Researcher: Christos Koutras
Host institution
: Universidad Rey Juan Carlos (URJC, ES)
Supervisor: Prof. Miguel Otaduy, URJC
Co-supervisor: Benjamin Gilles, Chief Scientific Officer, AnatoScope (FR)
Clinical expertise: Dr. Aurélien Courvoisier, Centre Hospitalier Universitaire du Montpellier, FR 


Scoliosis impacts 1% to 4% of children between 6 and 14. While braces are commonly used to prevent or delay surgery, their design lacks precision since their effect on spine is indirect and hard to predict, as it occurs through soft tissue and the rib cage, and depends on material parameters of bones, ligaments and connective tissue, which cannot be measure in-vivo. The goal of this project is to identify these parameters to improve brace design. The scientific challenge is to produce a novel Inverse Method to compute these using imaging of the patient in different postures: bi-planar radiographs, optical scans, videos. A Finite Element model of the patient will be computed based on available CT or MRI imaging. The method will then compute the most appropriate material parameters to match the imaging produced in different poses.

Expected Results

An imaging protocol for spine mechanical characterization (type of images, number of necessary poses, etc.). Inverse methods to identify spine material parameters from optical images. A validation study to compare predicted vs. measured spine configuration, in patients wearing a scoliosis brace.

Planned research stays

  • URJC (6 months): Training on computer simulation
  • AnatoScope (4 months) secondment: data collection, medical training. Finite Element model construction.
  • URJC (8 months): Training on computer simulation. Development of inverse methods.
  • AnatoScope (3 months) Secondment: Validation study.
  • URJC (8 months): Training on computer simulation. Development of inverse methods.
  • AnatoScope (3 months): allow integration with ESR9
  • URJC (4 months): finalize developments, thesis writing.

Further information about the project at URJC lab website.