MUSCULOSKELETAL MODELLING OF THE LOWER LIMBS TO INVESTIGATE GAIT OF CHILDREN WITH CEREBRAL PALSY

Abstract

Cerebral palsy (CP) results from an injury to the immature brain; and it leads to progressive musculoskeletal (MS) impairment in most affected patients. Orthopaedic surgery involving muscle-tendon lengthening is a method for managing short muscles in CP patients. Knowledge of muscle length prior to surgery is beneficial to surgical success. However, using common assessment methods like 3D gait analysis or physical examination, accurate pre-surgery estimation of muscle lengths during walking is difficult.

Computer models of the lower limbs, which provide more insight into muscle functioning during walking, have become increasingly important within the research field of CP. MS models are commonly driven by joint kinematics from clinical gait analysis. The most often used MS model in CP related research is based on the geometry of an adult human man with muscles modelled as line segments. This approach might be reasonable for small muscles with well-defined paths; however, for long muscles with multiple attachment points and curved paths, a more realistic 3D muscle model is required.

The aim of this study is the development of a clinical assessment tool for CP patients by incorporating kinematic data from gait analysis into a 3D finite-element MS model of the lower limbs. Ethical approval has been obtained to develop subject-specific MS models of 12 children with CP and 12 control children (age 8 – 12 years) based on magnetic resonance images. Kinematic data from 3D gait analysis is used as input data to transform the bony structures. Soft-tissue muscle deformation is modelled according to a variant of free-form deformation called the Host-Mesh Fitting Technique. So far, MS models of the lower limbs of three control children and of one child with CP were developed. The resulting muscle length changes during walking agree reasonably well with published data. The proposed modelling approach together with the library of 24 MS models will enable us to develop a powerful tool to investigate gait of children with CP.