Search

Sakai T., Li H., Shimada T., et al. Development of artificial intelligence model for supporting implant drilling protocol decision making. Journal of Prosthodontic Research 67, 360 (2023); https://doi.org/10.2186/jpr.JPR_D_22_00053., Purpose: This study aimed to develop an artificial intelligence (AI) model to support the determination of an appropriate implant drilling protocol using cone-beam computed tomography (CBCT) images. Methods: Anonymized CBCT images were obtained from 60 patients. For each case, after implant placement, images of the bone regions at the implant site were extracted from 20 slices of CBCT images. Based on the actual drilling protocol, the images were classified into three categories: protocols A, B, and C. A total of 1,200 images were divided into training and validation datasets (n = 960, 80%) and a test dataset (n = 240, 20%). Another 240 images (80 images for each type) were extracted from the 60 cases as test data. An AI model based on LeNet-5 was developed using these data sets. The accuracy, sensitivity, precision, F-value, area under the curve (AUC) value, and receiver operating curve were calculated. Results: The accuracy of the trained model is 93.8%. The sensitivity results for drilling protocols A, B, and C were 97.5%, 95.0%, and 85.0%, respectively, while those for protocols A, B, and C were 86.7%, 92.7%, and 100%, respectively, and the F values for protocols A, B, and C were 91.8%, 93.8%, and 91.9%, respectively. The AUC values for protocols A, B, and C are 98.6%, 98.6%, and 99.4%, respectively. Conclusions: The AI model established in this study was effective in predicting drilling protocols from CBCT images before surgery, suggesting the possibility of developing a decision-making support system to promote primary stability.

Lee C., Yamaguchi S., Imazato S.. Quantitative evaluation of the degradation amount of the silane coupling layer of CAD/CAM resin composites by water absorption. Journal of Prosthodontic Research 67, 55 (2023); https://doi.org/10.2186/jpr.JPR_D_21_00236., Purpose: Degradation of silane coupling layers by water ingress in computer-aided design/computer-aided manufacturing (CAD/CAM) of resin composites has been reported qualitatively. In this study, we quantitatively evaluated how water absorption of CAD/CAM resin composites affects the silane coupling layer by in vitro and in silico methods. Methods: A Katana Avencia block (KAB) and an experimental matrix block composed of only a matrix resin were used to evaluate the effect of water immersion for seven days on the elastic modulus. X-ray photoelectron spectroscopy (XPS) with fluorine-labeling of the KAB was performed to evaluate the atomic percentage of F1s, which represents the hydrolysis amount by water immersion. In silico analysis of the three-dimensional model of the KAB was performed to determine the coupling ratios before and after water immersion. Results: The elastic modulus of the KAB was 8.2 GPa before and 6.9 GPa after immersion in water. The atomic percentages of F1s in the after-and before-immersion groups were 14.31% and 11.52%, respectively, suggesting that hydrolysis of the silane coupling layer occurred during water immersion. From in silico analysis of the three-dimensional model of the KAB, the coupling ratio was predicted to be 78.2% before water immersion. After water immersion, the coupling ratio was predicted to be 68.4%. Conclusions: The in vitro and in silico approaches established in this study were able to predict the silane coupling ratios of CAD/CAM resin composites, and they showed that the silane coupling ratio decreased by water absorption.