Department of Oral and Maxillofacial Radiology, Academic Centre for Dentistry Amsterdam, The Netherlands.
Dentomaxillofac Radiol. 2009 Oct;38(7):431-7. doi: 10.1259/dmfr/55502190.
In this study age and the trabecular pattern present on dental radiographs were used to predict the presence of osteoporosis. The objective was to evaluate the contribution of the trabecular pattern to the prediction.
In this project, 671 women between 45 and 71 years of age were recruited. Medical history was obtained and dental radiographs were made. Bone mineral density (BMD) was measured at three sites to assess the presence of osteoporosis according to the World Health Organization criteria. The radiographs were subjected to image analysis methods yielding measurements of the trabecular pattern. Thereafter, discriminant analysis was used to predict the presence of osteoporosis by means of the trabecular pattern and age. Sensitivity and specificity of age and the trabecular pattern were compared. Also, it was checked whether the inclusion of the trabecular pattern improved the sensitivity and specificity that were obtained when only age was used as the predictor.
The sensitivity and specificity of the trabecular pattern present on dental radiographs were almost equal to those of age. However, combining age with the trabecular pattern increased the sensitivity from 0.71 to 0.75 and the specificity from 0.72 to 0.78; the latter increase was statistically significant.
The trabecular pattern predicts the presence of osteoporosis just as well as age does. When combining the trabecular pattern with age, the sensitivity and specificity increased. Only the latter increase was statistically significant.
本研究通过分析牙片上的骨小梁模式和年龄来预测骨质疏松症的发生。目的是评估骨小梁模式对预测结果的贡献。
本项目共招募了 671 名年龄在 45 至 71 岁之间的女性。采集病史并拍摄牙片。采用三种方法测量骨密度(BMD),以世界卫生组织(WHO)的标准评估骨质疏松症的发生。对牙片进行图像分析,测量骨小梁模式。然后,采用判别分析方法,通过骨小梁模式和年龄预测骨质疏松症的发生。比较年龄和骨小梁模式的敏感性和特异性。还检查了在仅使用年龄作为预测因子的情况下,纳入骨小梁模式是否会提高敏感性和特异性。
牙片上的骨小梁模式的敏感性和特异性与年龄几乎相等。然而,将年龄与骨小梁模式相结合,可使敏感性从 0.71 提高到 0.75,特异性从 0.72 提高到 0.78;后者的提高具有统计学意义。
骨小梁模式与年龄一样可以预测骨质疏松症的发生。当将骨小梁模式与年龄相结合时,敏感性和特异性均提高,仅后者的提高具有统计学意义。