Accuracy of Cone-beam Computed Tomography in Measuring Dentin Thickness and Its Potential of Predicting the Remaining Dentin Thickness after Removing Fractured Instruments

Abstract

Introduction: The purpose of this study was to evaluate the accuracy of cone-beam computed tomographic (CBCT) to measure dentin thickness and its potential of predicting the remaining dentin thickness after the removal of fractured instrument fragments.

Methods: Twenty-three human mandibular molars were selected, and 4-mm portions of #25/.06 taper K3 files (SybronEndo, Orange, CA) were fractured in mesial canals. The teeth were then scanned using a micro-computed tomographic (micro-CT) system and a CBCT unit. Dentin thickness was measured and compared between both micro-CT and CBCT images to study the accuracy of CBCT readings. Then, the process of removing the fragments was simulated in CBCT images using the MeVisLab package (MeVis Research, Bremen, Germany); the predicted minimal remaining dentin thickness after removal was measured in different layers using VGStudio MAX software (Volume Graphics, Heidelberg, Germany). Data were compared with the actual minimal remaining dentin thickness acquired from micro-CT images, which were scanned after removing fractured instruments using the microtrepan technique. The results were analyzed statistically using intraclass correlation coefficients (ICCs) and a forecasting regression model analysis.

Results: The ICC for the dentin thickness was 0.988. The forecasting regression model of CBCT imaging estimating dentin thickness was micro-CT imaging = 15.835 + 1.080*CBCT, R² = 0.963. The ICC for the remaining dentin thickness was 0.975 (P < .001). The forecasting regression model of CBCT imaging forecasting remaining dentin thickness was micro-CT imaging = 147.999 + 0.879*adjusted CBCT, R² = 0.906.

Conclusions: The study showed that CBCT imaging could measure dentin thickness accurately. Furthermore, using CBCT images, it is reliable and feasible to forecast the remaining dentin thickness after simulated instrument removal.

Keywords: Cone-beam computed tomographic imaging; dentin thickness; instrument fragment removal; micro–computed tomographic imaging; treatment simulation.