Observer differentiation of proximal enamel mechanical defects versus natural proximal dental caries with computed dental radiography.
OBJECTIVE
Various models have been used to study the accuracy of imaging systems for detection of dental caries. This study compares the ability of dentists to detect mechanically created defects versus natural dental caries cavitations on the proximal surfaces of extracted teeth with Computed Dental Radiography (Schick Industries, Long Island City, N.Y.). Detection rates are investigated according to lesion depth to permit comparisons to be made between studies in the literature with other mechanical defects or natural caries models. Discrimination of natural caries versus artificial defects with Computed Dental Radiography is also compared with a previous report that used standard dental film.


METHODS
Fifty-two extracted molar and premolar teeth were mounted into representative sets of maxillary and mandibular posterior arches for bite-wing radiography. There were 16 proximal surfaces with natural caries and 28 proximal surfaces with mechanical defects. An optical bench was used to ensure constant beam geometry. A 1.8 cm acrylic soft tissue equivalent attenuator was placed in front of the receptor. Thirty dentists acted independently as observers to differentiate between sound proximal tooth surfaces, natural dental caries, and mechanical defects. Evaluation of intra- and interobserver variability was made with use of the kappa statistic. The Zelen test of odds ratios was used to test for homogeneity, and the Mantel-Haenszel analysis plus stratified logistic regression were used for inference about the common odds ratio. Significance was set at p < 0.05.


CONCLUSIONS
Ignoring stipulation of cavity type, detection was 74% for mechanical defects and 67% for natural caries. The odds of detecting a mechanical defect were 1.40 times the odds of finding natural dental caries cavitation of the same depth. Lesion depth did influence the probability of correctly identifying the presence of a lesion; the odds of identifying cavitation increased 1.41 times with every 0.1 mm increase in lesion depth. Correct designation of lesion type was 1.42 times more likely with mechanical defects than with natural caries (p = 0.003). Intraobserver (kappa = 0.65) and interobserver (kappa = 0.43) agreements were fair to good. Discrimination between natural and artificial lesions was less with the Computed Dental Radiography than that found in our previous study with standard direct emulsion x-ray film.
Kang
B C
BC
Divison of Radiology and Imaging Sciences, School of Dentistry, University of Louisville, Ky, USA.
Farman
A G
AG
Scarfe
W C
WC
Goldsmith
L J
LJ
D001641:Bicuspid / Q000000981:diagnostic imaging; D003731:Dental Caries / Q000000981:diagnostic imaging*; D003743:Dental Enamel / Q000473:pathology; D006801:Humans; D016015:Logistic Models; D008963:Molar / Q000000981:diagnostic imaging; D015588:Observer Variation; D016017:Odds Ratio; D019047:Phantoms, Imaging; D011856:Radiographic Image Enhancement; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000592:standards*; D011862:Radiography, Panoramic / Q000592:standards*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity