Lower limb bones shape variations of a paediatric population

Principal Component Analysis (PCA) is a technique for feature extraction which identify strong patterns in a dataset and emphasize data variation. PCA can be used to characterise bone shape variations in tibia, fibula and femur on a paediatric population. PCA was performed on 64 femurs and 67 tibia/fibula from reconstructed CT scans bones of children aged 5-11. Shape and size variation of femur and tibia/fibula models were captured in 4 components representing between 98-99% of bone variation. Principal Component 1 (PC1) and 2 represented variation in length and width while PC3 accounted for femoral anteversion and tibial torsion differences.