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Updated: Oct 12, 2025

Analysis and Imaging of Osteocytes
Published on: November 29, 2024
Analysis of histomorphometric variables: Proposal and validation of osteon definitions
Christian Crowder1, Victoria M Dominguez2,3,4, Jarred Heinrich5
1Dallas County Medical Examiner's Office, Southwestern Institute of Forensic Sciences, Dallas, Texas, USA.
Abstract:
Histological analysis of bone tissue has been used to explore a variety of questions relating to age-at-death, habitual behaviors, health, and nutritional stress. Identification of intact and fragmentary osteons is of key interest to many researchers in these studies, yet the definitions of these features vary between researchers making cross-study comparisons problematic. Furthermore, histological variable definitions are often ambiguous or require subjective classifications by the observer. As a result, and as indicated by previous studies, observer error and misclassification of certain variables, namely intact and fragmentary osteons, can be significant. This study proposes new definitions for intact and fragmentary osteons that are designed to limit observer subjectivity and also explore efficacy of combining osteon types into one variable. A sample of 30 6th rib cross-sections from a modern forensic population was used to test the validity of the proposed definitions. Observations of intact osteon population density (OPD(I)) and fragmentary osteon population density (OPD(F)) were made by three observers for each cross-section. These observations were used to explore the interobserver error associated with the proposed definitions and determine if combining variables into one variable (OPD) mitigates persisting classification difficulties. Results indicate that the proposed definitions significantly reduce interobserver error and misclassification of intact and fragmentary osteons. However, the interobserver error associated with fragmentary osteons is still high. Evaluation of the variables independently indicates that combining variables has potential to reduce the predictive strength of an age estimation model and the ability to interpret age-related bone remodeling.
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