The purpose of this study is to determine the correlation between texture features of Diffraction Enhanced Imaging (DEI) images and trabecular properties of human wrist bone in the assessment of osteoporosis. Osteoporosis is a metabolic bone disorder that is characterized by reduced bone mass and a deterioration of bone structure which results in an increased fracture risk. Since the disease is preventable, diagnostic techniques are of major importance. Bone micro-architecture and Bone mineral density (BMD) are two main factors related to osteoporotic fractures. Trabecular properties like bone volume (BV), trabecular number (Tb.N), trabecular thickness (Tb.Th), bone surface (BS), and other properties of bone, characterizes the bone architecture. Currently, however, BMD is the only measurement carried out to assess osteoporosis. Researchers suggest that bone micro-architecture and texture analysis of bone images along with BMD can provide more accuracy in the assessment.
We have applied texture analysis on DEI images and extracted texture features. In our study, we used fractal analysis, gray level co-occurrence matrix (GLCM), texture feature coding method (TFCM), and local binary patterns (LBP) as texture analysis methods to extract texture features. 3D Micro-CT trabecular properties were extracted using SkyScanTM CTAN software. Then, we determined the correlation between texture features and trabecular properties. GLCM energy feature of DEI images explained more than 39% of variance in bone surface by volume ratio (BS/BV), 38% of variance in percent bone volume (BV/TV), and 37% of variance in trabecular number (Tb.N). TFCM homogeneity feature of DEI images explained more than 42% of variance in bone surface (BS) parameter. LBP operator - LBP 11 of DEI images explained more than 34% of variance in bone surface (BS) and 30% of variance in bone surface density (BS/TV). Fractal dimension parameter of DEI images explained more than 47% of variance in bone surface (BS) and 32% of variance in bone volume (BV). This study will facilitate in the quantification of osteoporosis beyond conventional BMD.