RESUMEN
Standard microarchitectural analysis of bone using micro-computed tomography produces a large number of parameters that quantify the structure of the trabecular network. Analyses that perform statistical tests on many parameters are at elevated risk of making Type I errors. However, when multiple testing correction procedures are applied, the risk of Type II errors is elevated if the parameters being tested are strongly correlated. In this article, we argue that four commonly used trabecular microarchitectural parameters (thickness, separation, number, and bone volume fraction) are interdependent and describe only two independent properties of the trabecular network. We first derive theoretical relationships between the parameters based on their geometric definitions. Then, we analyze these relationships with an aggregated in vivo dataset with 2987 images from 1434 participants and a synthetically generated dataset with 144 images using principal component analysis (PCA) and linear regression analysis. With PCA, when trabecular thickness, separation, number, and bone volume fraction are combined, we find that 92 % to 97 % of the total variance in the data is explained by the first two principal components. With linear regressions, we find high coefficients of determination (0.827-0.994) and fitted coefficients within expected ranges. These findings suggest that to maximize statistical power in future studies, only two of trabecular thickness, separation, number and bone volume fraction should be used for statistical testing.
Asunto(s)
Hueso Esponjoso , Análisis de Componente Principal , Microtomografía por Rayos X , Microtomografía por Rayos X/métodos , Humanos , Hueso Esponjoso/diagnóstico por imagen , Femenino , Masculino , Modelos LinealesRESUMEN
INTRODUCTION: High resolution peripheral quantitative computed tomography (HR-pQCT) imaging protocol requires defining where to position the â¼1 cm thick scan along the bone length. Discrepancies between the use of two positioning methods, the relative and fixed offset, may be problematic in the comparison between studies and participants. This study investigated how bone landmarks scale linearly with length and how this scaling affects both positioning methods aimed at providing a consistent anatomical location for scan acquisition. METHODS: Using CT images of the radius (Nâ¯=â¯25) and tibia (Nâ¯=â¯42), 10 anatomical landmarks were selected along the bone length. The location of these landmarks was converted to a percent length along the bone, and the variation in their location was evaluated across the dataset. The absolute location of the HR-pQCT scan position using both offset methods was identified for all bones and converted to a percent length position relative to the HR-pQCT reference line for comparison. A secondary analysis of the location of the scan region specifically within the metaphysis was explored at the tibia. RESULTS: The location of landmarks deviated from a linear relationship across the dataset, with a range of 3.6â¯% at the radius sites, and 4.5â¯% at the tibia sites. The consequent variation of the position of the scan at the radius was 0.6â¯% and 0.3â¯%, and at the tibia 2.4â¯% and 0.5â¯%, for the fixed and relative offset, respectively. The position of the metaphyseal junction with the epiphysis relative to the scan position was poorly correlated to bone length, with R2â¯=â¯0.06 and 0.37, for the fixed and relative offset respectively. CONCLUSION: The variation of the scan position by either method is negated by the intrinsic variation of the bone anatomy with respect both to total bone length as well as the metaphyseal region. Therefore, there is no clear benefit of either offset method. However, the lack of difference due to the inherent variation in the underlying anatomy implies that it is reasonable to compare studies even if they are using different positioning methods.