Effectiveness of digital subtraction radiography in detecting artificially created osteophytes and erosions in the temporomandibular joint

数字减影放射成像技术在检测颞下颌关节人工骨赘和骨侵蚀方面的有效性

阅读:1

Abstract

PURPOSE: Erosions and osteophytes are radiographic characteristics that are found in different stages of temporomandibular joint (TMJ) osteoarthritis. This study assessed the effectiveness of digital subtraction radiography (DSR) in diagnosing simulated osteophytes and erosions in the TMJ. MATERIALS AND METHODS: Five intact, dry human skulls were used to assess the effectiveness of DSR in detecting osteophytes. Four cortical bone chips of varying thicknesses (0.5 mm, 1.0 mm, 1.5 mm, and 2.0 mm) were placed at the medial, central, and lateral aspects of the condyle anterior surface. Two defects of varying depth (1.0 mm and 1.5 mm) were created on the lateral, central, and medial poles of the condyles of 2 skulls to simulate erosions. Panoramic images of the condyles were acquired before and after artificially creating the changes. Digital subtraction was performed with Emago dental image archiving software. Five observers familiar with the interpretation of TMJ radiographs evaluated the images. Receiver operating characteristic (ROC) analysis was used to evaluate the diagnostic accuracy of the imaging methods. RESULTS: The area under the ROC curve (Az) value for the overall diagnostic accuracy of DSR in detecting osteophytic changes was 0.931. The Az value for the overall diagnostic accuracy of panoramic imaging was 0.695. The accuracy of DSR in detecting erosive changes was 0.854 and 0.696 for panoramic imaging. DSR was remarkably more accurate than panoramic imaging in detecting simulated osteophytic and erosive changes. CONCLUSION: The accuracy of panoramic imaging in detecting degenerative changes was significantly lower than the accuracy of DSR (P<.05). DSR improved the accuracy of detection using panoramic images.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。