Personalized body segment parameters from biplanar low-dose radiography

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 γ-ray scan and dual energy X-ray absorptiometry.