Digital panoramic radiography and CBCT as auxiliary tools for detection of low bone mineral density in post-menopausal women: a cross-sectional study

Abstract

BackgroundOsteoporosis is a chronic, multifactorial skeletal disease that occurs especially in women following a decrease in estrogen levels and decrease in bone mineral density. The aim of this study was to evaluate the relationship between qualitative and quantitative indexes in panoramic radiographs and quantitative indexes in CBCT images with femoral and vertebral BMD in postmenopausal women.MethodsThis comparative cross-sectional study was performed on postmenopausal women aging 40 to 80 years attending for obtaining either panoramic radiograph or mandibular CBCT scan. Dual energy X-ray absorptiometry (DEXA) was performed from the femur and lumbar vertebra. Quantitative parameters of mental index (MI), panoramic mandibular index (PMI), antegonial index (AI) as well as qualitative parameters of mandibular cortical index (MCI) and trabecular bone pattern (TP) were evaluated in panoramic radiographs. Quantitative parameters computed tomography mandibular index (CTMI), computed tomography index (inferior) [CTI(I)] and computed tomography index (superior) [CTI(S)] were analyzed in CBCT images. Kolmogorov-Smirnov tests and Pearson correlation coefficient were used (α = 0.05).ResultsIn individuals with panoramic radiography, statistically significant correlations were observed between MI with vertebral and femoral T-score, AI with vertebral and femoral T-score (except for the right AI with femoral T-score), and TP with vertebral and femoral T-score (p < 0.05). In the group with CBCT scans, the correlations between CTMI with vertebral and femoral T-score, CTI(I) with vertebral and femoral T-score, and CTI(S) with vertebral and femoral T-score were statistically significant (p < 0.05).Conclusionsin CBCT images, quantitative indexes of CTMI, CTI(I), and CTI(S), and in panoramic images, quantitative indexes of MI and AI and qualitative index of TP can be used to predict the possibility of osteoporosis in postmenopausal women.