Advanced Statistical Analyses to Reduce Inconsistency of Bond Strength Data

Abstract

This study was designed to clarify the interrelationship of factors that affect the value of microtensile bond strength (µTBS), focusing on nondestructive testing by which information of the specimens can be stored and quantified. µTBS test specimens were prepared from 10 noncarious human molars. Six factors of µTBS test specimens were evaluated: presence of voids at the interface, X-ray absorption coefficient of resin, X-ray absorption coefficient of dentin, length of dentin part, size of adhesion area, and individual differences of teeth. All specimens were observed nondestructively by optical coherence tomography and micro–computed tomography before µTBS testing. After µTBS testing, the effect of these factors on µTBS data was analyzed by the general linear model, linear mixed effects regression model, and nonlinear regression model with 95% confidence intervals. By the general linear model, a significant difference in individual differences of teeth was observed (P < 0.001). A significantly positive correlation was shown between µTBS and length of dentin part (P < 0.001); however, there was no significant nonlinearity (P = 0.157). Moreover, a significantly negative correlation was observed between µTBS and size of adhesion area (P = 0.001), with significant nonlinearity (P = 0.014). No correlation was observed between µTBS and X-ray absorption coefficient of resin (P = 0.147), and there was no significant nonlinearity (P = 0.089). Additionally, a significantly positive correlation was observed between µTBS and X-ray absorption coefficient of dentin (P = 0.022), with significant nonlinearity (P = 0.036). A significant difference was also observed between the presence and absence of voids by linear mixed effects regression analysis. Our results showed correlations between various parameters of tooth specimens and µTBS data. To evaluate the performance of the adhesive more precisely, the effect of tooth variability and a method to reduce variation in bond strength values should also be considered.