%0 Journal Article
%T Osteon shape variation in the femoral diaphysis: A geometric-morphometric approach on human cortical bone microstructure in an elderly sample.
%A Leiss L
%A Ramphaleng T
%A Bacci N
%A Houlton TMR
%A García-Donas JG
%J J Forensic Sci
%V 0
%N 0
%D 2024 Jul 11
%M 38992860
%F 1.717
%R 10.1111/1556-4029.15584
%X Geometric morphometrics (GMM) have been applied to understand morphological variation in biological structures. However, research studying cortical bone through geometric histomorphometrics (GHMM) is scarce. This research aims to develop a landmark-based GHMM protocol to depict osteonal shape variation in the femoral diaphysis, exploring the role of age and biomechanics in bone microstructure. Proximal, midshaft, and distal anatomical segments from the femoral diaphysis of six individuals were assessed, with 864 secondary intact osteons from eight periosteal sampling areas being manually landmarked. Observer error was tested using Procrustes ANOVA. Average osteonal shape and anatomical segment-specific variation were explored using principal component analysis. Osteon shape differences between segments were examined using canonical variate analysis (CVA). Sex differences were assessed through Procrustes ANOVA and discriminant function analysis (DFA). The impact of osteonal size on osteonal shape was investigated. High repeatability and reproducibility in osteon shape landmarking were reported. The average osteon shape captured was an elliptical structure, with PC1 reflecting more circular osteons. Significant differences in osteon shape were observed between proximal and distal segments according to CVA. Osteon shape differed between males and females, with DFA showing 52% cross-validation accuracies. No effect of size on shape was reported. Osteonal shape variation observed in this study might be explained by the elderly nature of the sample as well as biomechanical and physiological mechanisms playing different roles along the femoral diaphysis. Although a larger sample is needed to corroborate these findings, this study contributes to the best of our knowledge on human microanatomy, proposing a novel GHMM approach.