In vitro evaluation of accuracy and precision of automated robotic tooth preparation system for porcelain laminate veneers.

Statement of problemControlling tooth reduction for porcelain laminate veneers (PLVs) in fractions of millimeters is challenging.PurposeThe purpose of this study was to assess an automated robotic tooth preparation system for PLVs for accuracy and precision compared with conventional freehand tooth preparation.Material and methodsTwenty maxillary central incisor tooth models were divided into 2 groups. Ten were assigned to a veneer preparation with a robotic arm according to preoperative preparation design-specific guidelines (experimental group). Ten were assigned to conventional tooth preparation by a clinician (control group). Initially, all tooth models were scanned with a 3- dimensional (3D) laser scanner, and a tooth preparation for PLVs was designed on a 3D image. Each tooth model was attached to a typodont. For the experimental group, an electric high-speed handpiece with a 0.9-mm-diameter round diamond rotary cutting instrument was mounted on the robotic arm. The teeth were prepared automatically according to the designed image. For the control group, several diamond rotary cutting instruments were used to prepare the tooth models according to preoperative preparation design guidelines. All prepared tooth models were scanned. The preoperative preparation design image and scanned postoperative preparation images were superimposed. The dimensional difference between those 2 images was measured on the facial aspect, finish line, and incisal edge. Differences between the experimental and the control groups from the 3D design image were computed. Accuracy and precision were compared for all sites and separately for each tooth surface (facial, finish line, incisal). Statistical analyses were conducted with a permutation test for accuracy and with a modified robust Brown-Forsythe Levene-type test for precision (α=.05).ResultsFor accuracy for all sites, the mean absolute deviation was 0.112 mm in the control group and 0.133 mm in the experimental group. No significant difference was found between the 2 (P=.15). For precision of all sites, the standard deviation was 0.141 mm in the control group and 0.185 mm in the experimental group. The standard deviation in the control group was significantly lower (P=.030). In terms of accuracy for the finish line, the control group was significantly less accurate (P=.038). For precision, the standard deviation in the control group was significantly higher at the finish line (P=.034).ConclusionsFor the data from all sites, the experimental procedure was able to prepare the tooth model as accurately as the control, and the control procedure was able to prepare the tooth model with better precision. The experimental group showed better accuracy and precision at the finish line

In vitro evaluation of accuracy and precision of automated robotic tooth preparation system for porcelain laminate veneers.

Statement of problemControlling tooth reduction for porcelain laminate veneers (PLVs) in fractions of millimeters is challenging.PurposeThe purpose of this study was to assess an automated robotic tooth preparation system for PLVs for accuracy and precision compared with conventional freehand tooth preparation.Material and methodsTwenty maxillary central incisor tooth models were divided into 2 groups. Ten were assigned to a veneer preparation with a robotic arm according to preoperative preparation design-specific guidelines (experimental group). Ten were assigned to conventional tooth preparation by a clinician (control group). Initially, all tooth models were scanned with a 3- dimensional (3D) laser scanner, and a tooth preparation for PLVs was designed on a 3D image. Each tooth model was attached to a typodont. For the experimental group, an electric high-speed handpiece with a 0.9-mm-diameter round diamond rotary cutting instrument was mounted on the robotic arm. The teeth were prepared automatically according to the designed image. For the control group, several diamond rotary cutting instruments were used to prepare the tooth models according to preoperative preparation design guidelines. All prepared tooth models were scanned. The preoperative preparation design image and scanned postoperative preparation images were superimposed. The dimensional difference between those 2 images was measured on the facial aspect, finish line, and incisal edge. Differences between the experimental and the control groups from the 3D design image were computed. Accuracy and precision were compared for all sites and separately for each tooth surface (facial, finish line, incisal). Statistical analyses were conducted with a permutation test for accuracy and with a modified robust Brown-Forsythe Levene-type test for precision (α=.05).ResultsFor accuracy for all sites, the mean absolute deviation was 0.112 mm in the control group and 0.133 mm in the experimental group. No significant difference was found between the 2 (P=.15). For precision of all sites, the standard deviation was 0.141 mm in the control group and 0.185 mm in the experimental group. The standard deviation in the control group was significantly lower (P=.030). In terms of accuracy for the finish line, the control group was significantly less accurate (P=.038). For precision, the standard deviation in the control group was significantly higher at the finish line (P=.034).ConclusionsFor the data from all sites, the experimental procedure was able to prepare the tooth model as accurately as the control, and the control procedure was able to prepare the tooth model with better precision. The experimental group showed better accuracy and precision at the finish line

Chemical Composition and Flexural Strength Discrepancies Between Milled and Lithography-Based Additively Manufactured Zirconia

PURPOSE To evaluate the chemical composition, flexural strength, and Weibull characteristics of milled and lithography-based additively manufactured (AM) zirconia. MATERIALS AND METHODS A virtual design of a bar (25×4×2 mm) was completed using a software program. The standard tessellation language file was used to manufacture all the specimens: 3Y-TZP zirconia (Priti multidisc ZrO$_{2}$ monochrome) milled (M group) and 3Y-TZP zirconia (LithaCon 3Y 210) lithography-based AM (CeraFab System S65 Medical) (AM group) bar specimens (n = 20). The chemical composition of the specimens was determined by using energy dispersive X-ray (EDAX) elemental analysis in a scanning electron microscope. Flexural strength was measured in all specimens using 3-point bend test according to ISO/CD 6872.2 with a universal testing machine (Instron Model 8501). Two-parameter Weibull distribution values were calculated. The Shapiro-Wilk test revealed that the data were normally distributed (p < 0.05). Flexural strength values were analyzed using independent Student's t-test (α = 0.05). RESULTS There were no major chemical composition differences observed between M and AM groups. The AM specimens (1518.9 ± 253.9 MPa) exhibited a significantly higher flexural strength mean value compared to the milled (980.5 ± 130.3 MPa) specimens (DF = 13, T-value = -5.97, p < 0.001). The Weibull distribution presented the highest shape for M specimens (11.49) compared to those of AM specimens (6.95). CONCLUSIONS There was no significant difference in the chemical composition of milled and AM zirconia material tested. AM zirconia tested exhibited significantly higher flexural strength compared with the milled zirconia evaluated

Chemical Composition and Flexural Strength Discrepancies Between Milled and Lithography-Based Additively Manufactured Zirconia.

PURPOSE To evaluate the chemical composition, flexural strength, and Weibull characteristics of milled and lithography-based additively manufactured (AM) zirconia. MATERIALS AND METHODS A virtual design of a bar (25×4×2 mm) was completed using a software program. The standard tessellation language file was used to manufacture all the specimens: 3Y-TZP zirconia (Priti multidisc ZrO2 monochrome) milled (M group) and 3Y-TZP zirconia (LithaCon 3Y 210) lithography-based AM (CeraFab System S65 Medical) (AM group) bar specimens (n = 20). The chemical composition of the specimens was determined by using energy dispersive X-ray (EDAX) elemental analysis in a scanning electron microscope. Flexural strength was measured in all specimens using 3-point bend test according to ISO/CD 6872.2 with a universal testing machine (Instron Model 8501). Two-parameter Weibull distribution values were calculated. The Shapiro-Wilk test revealed that the data were normally distributed (p < 0.05). Flexural strength values were analyzed using independent Student's t-test (α = 0.05). RESULTS There were no major chemical composition differences observed between M and AM groups. The AM specimens (1518.9 ± 253.9 MPa) exhibited a significantly higher flexural strength mean value compared to the milled (980.5 ± 130.3 MPa) specimens (DF = 13, T-value = -5.97, p < 0.001). The Weibull distribution presented the highest shape for M specimens (11.49) compared to those of AM specimens (6.95). CONCLUSIONS There was no significant difference in the chemical composition of milled and AM zirconia material tested. AM zirconia tested exhibited significantly higher flexural strength compared with the milled zirconia evaluated

In vitro evaluation of accuracy and precision of automated robotic tooth preparation system for porcelain laminate veneers

Statement of problemControlling tooth reduction for porcelain laminate veneers (PLVs) in fractions of millimeters is challenging.PurposeThe purpose of this study was to assess an automated robotic tooth preparation system for PLVs for accuracy and precision compared with conventional freehand tooth preparation.Material and methodsTwenty maxillary central incisor tooth models were divided into 2 groups. Ten were assigned to a veneer preparation with a robotic arm according to preoperative preparation design-specific guidelines (experimental group). Ten were assigned to conventional tooth preparation by a clinician (control group). Initially, all tooth models were scanned with a 3- dimensional (3D) laser scanner, and a tooth preparation for PLVs was designed on a 3D image. Each tooth model was attached to a typodont. For the experimental group, an electric high-speed handpiece with a 0.9-mm-diameter round diamond rotary cutting instrument was mounted on the robotic arm. The teeth were prepared automatically according to the designed image. For the control group, several diamond rotary cutting instruments were used to prepare the tooth models according to preoperative preparation design guidelines. All prepared tooth models were scanned. The preoperative preparation design image and scanned postoperative preparation images were superimposed. The dimensional difference between those 2 images was measured on the facial aspect, finish line, and incisal edge. Differences between the experimental and the control groups from the 3D design image were computed. Accuracy and precision were compared for all sites and separately for each tooth surface (facial, finish line, incisal). Statistical analyses were conducted with a permutation test for accuracy and with a modified robust Brown-Forsythe Levene-type test for precision (α=.05).ResultsFor accuracy for all sites, the mean absolute deviation was 0.112 mm in the control group and 0.133 mm in the experimental group. No significant difference was found between the 2 (P=.15). For precision of all sites, the standard deviation was 0.141 mm in the control group and 0.185 mm in the experimental group. The standard deviation in the control group was significantly lower (P=.030). In terms of accuracy for the finish line, the control group was significantly less accurate (P=.038). For precision, the standard deviation in the control group was significantly higher at the finish line (P=.034).ConclusionsFor the data from all sites, the experimental procedure was able to prepare the tooth model as accurately as the control, and the control procedure was able to prepare the tooth model with better precision. The experimental group showed better accuracy and precision at the finish line