Korean J Oral Maxillofac Radiol.  2002 Dec;32(4):187-194.

Computer-aided proximal caries diagnosis: correlation with clinical examination and histologys

Affiliations
  • 1University of Louisville, School of Dentistry, Louisville, Kentucky 40292, USA.
  • 2Chonnam University, School of Dentistry, Gwangju, Korea. bckang@ chonnam.ac.kr

Abstract

PURPOSE: To evaluate the performance of the LOGICON Caries Detector using RVG-4 and RVG-ui sensors, by comparing results of each detector to the results of clinical and histological examinations.
MATERIALS AND METHODS
Pairs of extracted teeth were radiographed, and a total of 57 proximal surfaces, which included both carious and non-carious situations, were analyzed. The RVG-4 produced 8-bit images, while the RVG-ui unit produced 12-bit images, which were taken in the high sensitivity mode. The images produced by the LOGICON were evaluated by a trained observer using both automated and manual caries detection software modes. Ground sections of the teeth established the actual absence or existence of caries.
RESULTS
LOGICON-aided caries detection and depth discrimination of the RVG-4 and RVG-ui sensors were equally inconsistent irrespective of whether the LOGICON software was set to the automated or manual mode. Sensitivity ranged from 50% to 57% for caries penetration of the enamel-dentin junction.
CONCLUSION
Care needs to be taken when using LOGICON in conjunction with RVG images as an adjunct for treatment planning dental caries. Even when applied by a trained observer, substantial discrepancies exist between the results of the LOGICON software-guided evalutations using RVG images and histologic examination.

Keyword

dental caries; diagnosis; computer-assisted

MeSH Terms

Dental Caries
Diagnosis*
Discrimination (Psychology)
Tooth
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