An evaluation of quantitative percussion diagnostics for determining the probability of a microgap defect in restored and unrestored teeth: A prospective clinical study

• Published in: The Journal of prosthetic dentistry
• Main Authors: Sheets, Cherilyn G., Quan, Dennis A., Wu, Jean C., Earthman, James C.
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 25-05-2023
• ISSN: 0022-3913; 1097-6841
• DOI: 10.1016/j.prosdent.2023.04.016

Current dental diagnostics are image based and cannot detect a structural microgap defect such as a crack in a tooth. Whether percussion diagnostics can effectively diagnose a microgap defect is unclear.
The purpose of the present study was to determine from a large multicenter prospective clinical study whether quantitative percussion diagnostics (QPD) could detect structural damage in teeth and whether a probability of its presence could be provided.
A nonrandomized prospective and multicenter clinical validation study with 224 participants was performed in 5 centers with 6 independent investigators. The study used QPD and the normal fit error to determine whether a microgap defect was present in a natural tooth. Teams 1 and 2 were blinded. Team 1 tested teeth scheduled for restoration with QPD, and Team 2 disassembled the teeth aided by a clinical microscope, transillumination, and a penetrant dye. Microgap defects were documented in written and video formats. Controls were participants without damaged teeth. The percussion response from each tooth was stored on a computer and analyzed. A total of 243 teeth were tested to provide approximately 95% power to test the performance goal of 70%, based on an assumed population overall agreement of 80%.
Regardless of the collection method, tooth geometry, restoration material used, or restoration type, the data on detecting a microgap defect in a tooth were accurate. The data also reflected good sensitivity and specificity consistent with previously published clinical studies. The combined study data showed an overall agreement of 87.5% with a 95% confidence interval (84.2 to 90.3), beyond the 70% predetermined performance goal. The combined study data determined whether it was possible to predict the probability of a microgap defect.
The results showed that the data on detecting microgap defects in a tooth site were consistently accurate and confirmed that QPD provided information to aid the clinician in treatment planning and early preventative treatment. QPD can also alert the clinician of probable diagnosed and undiagnosed structural problems via the use of a probability curve.