Accuracy of cone-beam computed tomography in detecting alveolar bone dehiscences and fenestrations.
BACKGROUND
The purposes of this study were to evaluate the accuracy of cone-beam computed tomography (CBCT) for detecting naturally occurring alveolar bone dehiscences and fenestrations and to find a better method to diagnose them.


METHODS
The sample consisted of 122 anterior teeth in 14 patients with Class III malocclusion who accepted accelerated osteogenic orthodontic surgery in the anterior tooth region. Dehiscences and fenestrations were measured both directly, with a gauge during surgery, and indirectly, by CBCT scans collected before treatment. A Bland-Altman plot for calculating agreement between the 2 methods was used. Direct data were regarded as the gold standard, and indirect data were analyzed to evaluate the accuracy of CBCT for detecting dehiscences and fenestrations by sensitivity, specificity, positive predictive value, negative predictive value, Youden index, positive likelihood ratio, and negative likelihood ratio. Receiver operator characteristic curves were also used to determine the area under curve and the best critical points of CBCT for detecting dehiscences and fenestrations.


RESULTS
Both the sensitivity and specificity of CBCT for dehiscences and fenestrations were over 0.7. The negative predictive values were high (dehiscence, 0.82; fenestration, 0.98), whereas the positive predictive values were relatively low (dehiscence, 0.75; fenestration, 0.16). Areas under the curve were 0.873 for dehiscences and 0.766 for fenestrations. The best critical points for detecting both dehiscences and fenestrations were 2.2 mm.


CONCLUSIONS
Our study showed that the CBCT method has some diagnostic value for detecting naturally occurring alveolar bone dehiscences and fenestrations. However, this method might overestimate the actual measurements.
Resident, Department of Oral & Cranio-Maxillofacial Science, Ninth People's Hospital, College of Stomatology, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Liangyan
L
Sun
Lecturer, Department of Biostatistics, College of Stomatology, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Lina
L
Zhang
Professor, Department of Oral & Cranio-Maxillofacial Science, Ninth People's Hospital, College of Stomatology, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Guofang
G
Shen
Orthodontist, Department of Oral & Cranio-Maxillofacial Science, Ninth People's Hospital, College of Stomatology, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Bo
B
Wang
Professor, Department of Oral & Cranio-Maxillofacial Science, Ninth People's Hospital, College of Stomatology, School of Medicine, Shanghai Jiao Tong University, Shanghai, China. Electronic address: fangbing@sjtu.edu.cn.
Bing
B
Fang
D016301:Alveolar Bone Loss / Q000000981:diagnostic imaging*; D000539:Alveolar Process / Q000000981:diagnostic imaging; D019540:Area Under Curve; D002508:Cephalometry / Q000706:statistics & numerical data; D054893:Cone-Beam Computed Tomography / Q000706:statistics & numerical data*; D003481:Cuspid / Q000000981:diagnostic imaging; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000706:statistics & numerical data; D021621:Imaging, Three-Dimensional / Q000706:statistics & numerical data; D007180:Incisor / Q000000981:diagnostic imaging; D016013:Likelihood Functions; D008313:Malocclusion, Angle Class III / Q000000981:diagnostic imaging / Q000601:surgery; D008334:Mandible / Q000000981:diagnostic imaging; D008437:Maxilla / Q000000981:diagnostic imaging; D009295:Nasal Bone / Q000000981:diagnostic imaging; D056948:Orthognathic Surgical Procedures; D011237:Predictive Value of Tests; D012372:ROC Curve; D012680:Sensitivity and Specificity; D014092:Tooth Root / Q000000981:diagnostic imaging