Detection of simulated osteoporosis in maxillae using radiographic texture analysis

An effective mass screening tool for detecting osteoporosis is currently lacking. Alveolar bone, routinely examined during periodic dental examinations, may provide a window into the status of systemic bone density. The primary objective of this investigation was to compare the performance of various textural features, computed from dental radiographs, in detecting early simulated osteoporosis of alveolar bone. Five specimens of human maxillary alveolar bone were progressively decalcified and the percentage calcium lost at each decalcification stage quantified. Two radiographs of each specimen, together with an aluminum stepwedge, were exposed at 70 kVp at each stage. The test set of 140 radiographs was digitized, identical bony regions of interest selected from the density-corrected images of each specimen, the regions digitally filtered to reduce film-grain noise, and textural features computed on a line-to-line basis. Correlation analysis identified a set of features whose changes consistently exhibited a moderate-to-strong linear association with bone mineral loss over a wide range of decalcification. Repeated measures analysis of variance was subsequently applied to this set to measure the minimal decalcification that could be detected by each feature under optimal conditions of X-ray beam angulation (0°) and suboptimal conditions (±5°). The best performing features were mean intensity, gradient, Laws´ texture energy measures, and fractal dimension which detected 5.7% bone decalcification at optimal beam angulation and 9.4-12.6% at suboptimal angulation.