OBJECTIVES: Osteoporosis results in loss of bone mass and microarchitectural deterioration. Dental radiographs potentially offer a means of screening for osteoporosis as they are commonly made on adults. Spatial frequency analyses are well suited to detect subtle changes in image patterns. We hypothesize that individuals with osteoporosis exhibit an altered radiographic trabecular pattern that can be detected by spatial frequency and strut analysis. STUDY DESIGN: Maxillary and mandibular periapical radiographs of 26 women with osteoporosis and 23 controls were examined using one-dimensional discrete Fourier and wavelet analyses in both jaws to measure the spatial frequency distributions of trabecular structures. A strut analysis was also performed. RESULTS: Individuals with osteoporosis revealed an altered trabecular pattern compared to controls. Using Fourier and strut variables allows classification of subjects with 92% sensitivity, 96% specificity, and a 22% cross-validation error rate. Wavelet analysis was also useful but did not perform better than Fourier analysis for subject classification. CONCLUSIONS: Spatial frequency analysis of digitized dental radiographs, especially Fourier analysis, and strut analysis provide value for identifying individuals with osteoporosis.
OBJECTIVES:Osteoporosis results in loss of bone mass and microarchitectural deterioration. Dental radiographs potentially offer a means of screening for osteoporosis as they are commonly made on adults. Spatial frequency analyses are well suited to detect subtle changes in image patterns. We hypothesize that individuals with osteoporosis exhibit an altered radiographic trabecular pattern that can be detected by spatial frequency and strut analysis. STUDY DESIGN: Maxillary and mandibular periapical radiographs of 26 women with osteoporosis and 23 controls were examined using one-dimensional discrete Fourier and wavelet analyses in both jaws to measure the spatial frequency distributions of trabecular structures. A strut analysis was also performed. RESULTS: Individuals with osteoporosis revealed an altered trabecular pattern compared to controls. Using Fourier and strut variables allows classification of subjects with 92% sensitivity, 96% specificity, and a 22% cross-validation error rate. Wavelet analysis was also useful but did not perform better than Fourier analysis for subject classification. CONCLUSIONS: Spatial frequency analysis of digitized dental radiographs, especially Fourier analysis, and strut analysis provide value for identifying individuals with osteoporosis.
Authors: Chantal Nguyen; Kimberly J Schlesinger; Timothy W James; Kristin M James; Robert L Sah; Koichi Masuda; Jean M Carlson Journal: R Soc Open Sci Date: 2018-08-29 Impact factor: 2.963