Multiple factors determine the mechanical properties of bone including microstructural architecture, porosity, and tissue mineral content. The influence of mineral content on elastic properties can be described through various constitutive relationships from simpler exponential laws [1] to complex multiscale homogenization frameworks [2]. Understanding spatial variations in mineral content across anatomically relevant scales is therefore critical for accurate computational modeling of bone adaptation. However, large-scale, high-resolution experimental studies are limited by imaging constraints. Traditional techniques such as quantitative backscattered electron imaging provide high-resolution mineral quantification but are restricted to small fields of view, capturing local variations rather than regional patterns. We present a large-scale, high-resolution X-ray CT study of mineral content across entire femoral midshaft cortical sections at 11 μm voxel resolution. Our methodology is based on physics-based calibration, converting grey values to attenuation coefficients and subsequently to mineral volume fractions. Regional analysis was performed across anatomical octants (posterior, medial, anterior, lateral, and intermediate positions) and radial positions (periosteal, intracortical, endosteal), enabling simultaneous characterization of both circumferential and through-thickness variations (Figure 1) Preliminary findings show that regional mineral variations across octants and radial positions are more modest than some literature suggests, though anatomically relevant patterns, such as hypermineralization at the linea aspera, are present. The latter aligns with expected mechanical adaptation to high stress related to muscle insertions in this area [3]. To assess mechanical implications, we apply constitutive relationships from literature to convert measured mineral distributions to elastic property predictions. Specifically, we compare empirical exponential relationships [1] with multiscale homogenization approaches [2], revealing how different modeling frameworks propagate mineral heterogeneity into mechanical property variations and how model complexity requirements may depend on the magnitude of observed spatial variations. These findings inform material parameterization in large-scale bone adaptation models, particularly when balancing model complexity against observed spatial variations.