Dual energy X-Ray absorptiometry (DXA) has attained global acceptance since the early 1990s for the noninvasive diagnosis of osteoporosis as defined by Word Health Organization (WHO). Nevertheless, many factors characterize the relevance of this imaging technology in daily clinical practice. For instance, its low availability and its relatively high costs.Hence, there has been a development of a software tool to extract bone textural information from conventional lumbar spine radiographs. Further, to test it in a subset of postmenopausal women treated for osteoporosis with the fully human monoclonal antibody denosumab. The main aim of this pilot study was to evaluate the clinical applicability of this Osteoporosis Treatment software tool.The development of this innovative Osteoporosis Treatment software is based on the principles of fractal models, using pixel grey-level variations in combination of a specific machine-learning algorithm. The obtained dimensionless parameter, termed bone structure value (BSV), was then tested and compared to bone mineral density (BMD) in a sub-cohort of postmenopausal women with osteoporosis. Those women were treated with the monoclonal antibody denosumab.
Compared to study entry, after 3 years and 8 years of treatment with denosumab, mean lumbar spine BMD as well as mean lumbar BSV were significantly higher (one-way repeated measures ANOVA for DXA: F = 108.2, p < 0.00001; and for BSV: F = 84.3, p < 0.00001). The overall increase in DXA-derived lumbar spine BMD at year 8 was + 42%. The overall increase of BSV was 255%. Altogether, there has been a significant correlation between BMD and BSV (R = 0.51; p < 0.0001).
“Together with its high-resolution QCT substudy, this study provides good evidence that fractal based analysis of conventional radiographs gives us information on structural properties of trabecular bone. Furthermore, this method provides information on treatment-related changes in bone beyond that measured by bone mineral density alone”. – ao.Univ.-Prof. Dr.med.univ. Hans Peter Dimai
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