Evaluating the Consistency, Repeatability, and Reproducibility of Osteometric Data on Dry Bone Surfaces, Scanned Dry Bone Surfaces, and Scanned Bone Surfaces Obtained from Living Individuals

Abstract

Applying dry bone osteometrics to virtual bone surfaces obtained via medical imaging raises the question of consistency between the variables. Variables obtained from virtual bone surfaces also need to be sufficiently repeatable and reproducible to be valid for anthropological studies. This is also true for the landmarks defining these variables and for their acquisition. The consistency between variables taken directly from dry bones and from the virtual surfaces of dry bones was tested on 40 clavicles. 30 virtual surfaces of iliae, fifth lumbar vertebrae, and clavicles reconstructed from computed tomography scans of living individuals were used to test the repeatability and reproducibility of 16 landmarks and 19 variables. Statistical tests, graphical and quantitative error evaluations, and intraclass correlation coefficients were applied. The differences between all variables taken on dry and virtual clavicles were less than ±1 mm. Bland–Altman plots showed more than 95% reliability between variables obtained on dry bone and their virtually reconstructed surfaces, confirming their consistency and thus validating their use in osteometric studies independently of the medium of study. Although not all landmarks were repeatable and reproducible, most variables were. To assess intra- or inter-observer errors, graphical representations or coefficients are more precise and accurate than statistical tests. These two evaluation methods should be given priority to test the repeatability and reproducibility of osteometric variables.

Integrating Growth Variability of the Ilium, Fifth Lumbar Vertebra, and Clavicle with Multivariate Adaptive Regression Splines Models for Subadult Age Estimation

“…The four variables measured on the ilia, the five variables measured on the clavicles, and two of the ten lumbar variables (AVH and UVW) are well‐known anthropological and/or osteological measurements defined by several authors on adult bones. Matching measurements taken on subadult and/or fetal bones were also defined or used in previous works by different authors . Six of the ten biometric variables measured on the fifth lumbar vertebra were used in a geometric medical and anthropometric study of CT scan slices of adult lumbar vertebrae and a morphometric study of dissected subadult lumbar vertebrae .…”

“…Unidimensional variables were obtained by calculating the Euclidian distance between two landmarks placed directly on the bone surfaces in Avizo ® (Fig. ), using the formula for vector length or by geometric construction using the ImageJ ® Software . Bidimensional variables were calculated as the product of two unidimensional variables (e.g., IM) or obtained by geometric construction (e.g., IA).…”

Error measurement in craniometrics: The comparative performance of four popular assessment methods using 2000 simulated cranial length datasets (g-op)

“…As part of anthropometry research practice or forensic casework, it is crucial for the measurement error to be determined and explicitly documented to communicate the trustworthiness of the data [10][11][12]. The statistics used to describe the measurement error should thereby be carefully chosen so that they clearly communicate the amount of error present in an easy to appreciate manner.…”

“…Error statistics that cryptically encode the data or encourage misleading interpretations should be avoided. Four commonly used statistics to report error in anthropometry and craniofacial identification are: Pearson's product-moment correlation coefficients (r), P-value results from statistical significance tests (commonly Student's t-test), intraclass correlation coefficients (ICC), and technical error of measurement (TEM) [11,[13][14][15][16]].…”

Estimativa da ancestralidade em Antropologia Forense por meio do software \"AncesTrees\" em medidas cranianas de uma amostra brasileira

“…Aferir erros de medição é crucial para atestar a repetibilidade e reprodutibilidade do método testado e assim assegurar a confiabilidade dos resultados obtidos (CORRON et. al., 2017) (LINS et al, 2011;QUEIROZ et al, 2013;PENA et al, 2009), e outros contrários a essa ligação (PARRA et al, 2003;PIMENTA et al, 2006 WRIGHT, R. Detection of likely ancestry using CRANID.…”