Personalized body segment parameters from biplanar low-dose radiography.

Abstract

Body segment parameters are essential data in biomechanics. They are usually computed with population-specific predictive equations from literature. Recently, medical imaging and video-based methods were also reported for personalized computation. However, these methods present limitations: some of them provide only two-dimensional measurements or external measurements, others require a lot of tomographic images for a three-dimensional (3-D) reconstruction. Therefore, an original method is proposed to compute personalized body segment parameters from biplanar radiography. Simultaneous low-dose frontal and sagittal radiographs were obtained with EOS system. The upper leg segments of eight young males and eight young females were studied. The personalized parameters computed from the biplanar radiographic 3-D reconstructions were compared to literature. The biplanar radiographic method was consistent with predictive equations based on gamma-ray scan and dual energy X-ray absorptiometry.