CAD-CAM resin composites: Effective components for further development.

OBJECTIVE: This paper summarizes the effective components of computer-aided design and computer-aided manufacturing (CAD-CAM) resin composites that contribute to achieving greater mechanical properties and further development. METHODS: In silico multi-scale analysis, in silico nonlinear dynamic finite element analysis (FEA), and artificial intelligence (AI) were used to explore the effective components of CAD-CAM resin composites. The effects of the filler diameter and silane coupling ratio on the mechanical properties of CAD-CAM resin composites have been clarified through multi-scale analysis. The effects of the filler contents, and filler and monomer compositions have been investigated by AI algorithms. The fracture behavior of CAD-CAM composite crown was analyzed using in silico non-linear dynamic FEA. The longevity of CAD-CAM composite crown was assessed through step-stress accelerating life testing (SSALT). RESULTS: As the filler diameter decreases, there is an increase in elastic moduli and compressive strengths at the macroscale. At the nanoscale, a decrease in the filler diameter results in a decrease in the maximum value of the maximum principal strain. When the silane coupling ratio decreases, there is a decrease in the elastic modulus and compressive strength. According to the exhaustive search and feature importance analysis based on the AI algorithm, the combination of certain components was narrowed down to achieve a flexural strength of 269.5 MPa. The in silico non-linear FEA successfully detected the sign of the initial crack of the CAD-CAM composite molar crown. The SSALT revealed that CAD-CAM resin composite molar crowns containing nanofillers with a high fraction of resin matrix demonstrated great longevity. SIGNIFICANCE: This paper summarized the effective components of CAD-CAM resin composites for their further development. The integration of in vitro and in silico approaches will expedite the advancement of CAD-CAM resin composites, offering benefits such as time efficiency and reduction of material waste for researchers and manufacturers.

In vitro analysis of durability of S-PRG filler-containing composite crowns for primary molar restoration.

OBJECTIVE: To evaluate the reliability, maximum principal stress, shear stress, and crack initiation of a computer-aided design/computer-aided manufacturing (CAD/CAM) resin composite (RC) incorporating surface pre-reacted glass (S-PRG) filler for primary molar teeth. METHODS: Mandibular primary molar crowns fabricated by experimental (EB) or commercially available CAD/CAM RCs (HC) were prepared and cemented to a resinous abutment tooth using an adhesive resin cement (Cem) or a conventional glass-ionomer cement (CX). These specimens were subjected to a single compressive test (n = 5/each) and the step-stress accelerated life testing (SSALT) (n = 12/each). Data was evaluated using Weibull analyses and reliability was calculated. Afterwards, the maximum principal stress and crack initiation point of each crown was analyzed by finite element analysis. To evaluate bonding of EB and HC to dentin, microtensile bond strength (µTBS) testing was conducted using primary molar teeth (n = 10/each). RESULTS: There was no significant difference between the fracture loads of EB and HC for either cement (p > 0.05). The fracture loads of EB-CX and HC-CX were significantly lower than EB-Cem and HC-Cem (p < 0.05). The reliability at 600 N for EB-Cem was greater than that for EB-CX, HC-Cem, and HC-CX. The maximum principal stress concentrated on EB was lower than that on HC. The shear stress concentrated in the cement layer for EB-CX was higher than that for HC-CX. There was no significant difference among the µTBSs of EB-Cem, EB-CX, HC-Cem, and HC-CX (p > 0.05). SIGNIFICANCE: The crowns fabricated with the experimental CAD/CAM RC incorporating S-PRG filler yielded greater fracture loads and reliability than the crowns manufactured with commercially available CAD/CAM RC regardless of the luting materials. These findings suggest that the experimental CAD/CAM RC crown may be clinically useful for the restoration of primary molars.

Development of artificial intelligence model for supporting implant drilling protocol decision making.

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.

Color matching ability of resin composites incorporating supra-nano spherical filler producing structural color.

OBJECTIVE: The aim of this study was to evaluate the optical properties of supra-nano spherical fillers with different diameters and the color matching ability of resin composites (RC) incorporating these fillers. METHODS: Two types of SiO2-ZrO2 nano fillers with different diameters (150nm and 260nm) were used. The size distribution of each filler was measured and filler morphology was observed. The colors and spectral reflection spectra were measured by a spectral reflectometer. Experimental RCs incorporating ϕ150-nm/ϕ260-nm filler (D150RC/D260RC) were prepared. For the base dentin part, disc specimens (Estelite Astelia: A1B, A2B, A3B, A3.5B, or A4B) were prepared with a cylindrical cavity. Estelite Astelia with NE shade was layered on top as the enamel layer. Disk specimens with different cavity depths were prepared using A3B shade. Experimental RC was used to fill the cavity, and spectral reflection spectrums were obtained and analyzed. Filtek Supreme Ultra (FSU) with A3B shade was used (n=10) as a control. RESULTS: Both ϕ150-nm and ϕ260-nm nano fillers showed uniform spherical shape and exhibited no aggregation. The maximum peaks of the spectral reflection spectra of the ϕ150-nm and ϕ260-nm nano fillers were 380nm and 580nm, producing structural colors close to blue and yellow, respectively. The spectral reflection spectrum of FSU had a broad peak at 540nm, and D150RC had a significant peak at 420nm. The D260RC specimen had a broad peak at 680nm. The peaks of D150RC and D260RC significantly decreased in accordance with the shift in base RC shade from A1B to A4B. There was no significant difference in the peak of the reflection spectral spectra among different cavity depths of D260RC. These results suggest that the experimental RC could reflect base RC colors via the matrix resin, and the amount of transmitted light from the base RC was not much different with cavity depth. SIGNIFICANCE: D260RC producing structural color demonstrated a broad spectrum and reduction in brightness and chromatic value by adapting to surrounding restorative materials, suggesting its ability to enhance the chameleon (blending) effects to improve color matching. D260RC showed better color matching ability than resin composite containing uniformly sized ϕ150-nm SiO2-ZrO2 supra-nano spherical filler.

Multi-scale analysis of the influence of filler shapes on the mechanical performance of resin composites using high resolution nano-CT images.

OBJECTIVE: The aim of this study was to investigate the criteria for predicting the fracture initiation of resin composites (RCs) at the micro-scale and assess the influence of filler shapes on the flexural properties of RCs by combining nano-CT imaging and in silico multi-scale analysis. METHODS: Experimental RCs composed of irregular-shaped (IS) silica filler (31.2 vol%/50.0 wt%) and Bis-GMA/TEGDMA were prepared. The RC specimens were scanned by a nano-CT with 500-nm resolution, and 10 micro-scale models (100 × 100 × 100 µm) were randomly extracted from a scanned region. In silico micro-scale models containing sphere-shaped (SS) fillers with the same volume content as the experimental RC were designed. Each RC model's elastic modulus and Poisson's ratio at the macro-scale were calculated using homogenization analysis. The flexural strength of the RC models were predicted by finite element analysis using the elastic moduli and Poisson's ratio values. RESULTS: Significantly greater elastic modulus values were obtained in the X, Y, and Z directions for RC models containing IS fillers than SS fillers. Similarly, smaller Poisson's ratio values were observed in the Y and Z directions for RC model containing IS fillers than SS fillers (p < 0.05). The flexural strength of RC model containing IS fillers was significantly greater than the RC model containing SS fillers (p < 0.05). SIGNIFICANCE: The in silico multi-scale analysis established in this study demonstrated that RC model containing irregular-shaped fillers had greater flexural strength than RC model loaded with SS fillers, suggesting that the mechanical strength of the RC can be improved by optimizing the shape of the silica fillers.

In vitro/in silico investigation of failure criteria to predict flexural strength of composite resins.

The aim of this study was to investigate a failure criterion to predict flexural strengths of composite resins (CR) by three-dimensional finite element analysis (3D-FEA). Models of flexural strength for test specimens of CR and rods comprising a three-point loading were designed. Calculation of Young's moduli and Poisson's ratios of CR were conducted using a modified McGee-McCullough model. Using the experimental CR, flexural strengths were measured by three-point bending tests with crosshead speed 1.0 mm/min and compared with the values determined by in silico analysis. The flexural strengths of experimental CR calculated using the maximum principal strain significantly correlated with those obtained in silico amongst the four types of failure criteria applied. The in silico analytical model established in this study was found to be effective to predict the flexural strengths of CR incorporating various silica filler contents by maximum principal strain.

Multi-scale analysis of the effect of nano-filler particle diameter on the physical properties of CAD/CAM composite resin blocks.

The objective of this study was to assess the effect of silica nano-filler particle diameters in a computer-aided design/manufacturing (CAD/CAM) composite resin (CR) block on physical properties at the multi-scale in silico. CAD/CAM CR blocks were modeled, consisting of silica nano-filler particles (20, 40, 60, 80, and 100 nm) and matrix (Bis-GMA/TEGDMA), with filler volume contents of 55.161%. Calculation of Young's moduli and Poisson's ratios for the block at macro-scale were analyzed by homogenization. Macro-scale CAD/CAM CR blocks (3 × 3 × 3 mm) were modeled and compressive strengths were defined when the fracture loads exceeded 6075 N. MPS values of the nano-scale models were compared by localization analysis. As the filler size decreased, Young's moduli and compressive strength increased, while Poisson's ratios and MPS decreased. All parameters were significantly correlated with the diameters of the filler particles (Pearson's correlation test, r = -0.949, 0.943, -0.951, 0.976, p < 0.05). The in silico multi-scale model established in this study demonstrates that the Young's moduli, Poisson's ratios, and compressive strengths of CAD/CAM CR blocks can be enhanced by loading silica nanofiller particles of smaller diameter. CAD/CAM CR blocks by using smaller silica nano-filler particles have a potential to increase fracture resistance.