International Journal of Computerized Dentistry最新文献

Aim: The aim of the present in vitro study was to investigate the influence of scan paths on the accuracy (trueness and precision) of intraoral scanning of an implant impression on an edentulous patient.

Materials and methods: An epoxy resin maxillary cast was made with six bone level implants (NobelParallel Conical Connection RP). The implants were placed at the sites of the central incisors, canines, and first molars. The transgingival component (multi-unit) was screwed onto the implants. The scanbodies (Elos Accurate IO 2C-A) were then screwed onto the multi-units. The cast was run through a coordinate measurement machine to obtain a control model. Then, five different scanning paths were applied by a single operator: the zigzag technique (ZZT); the zigzag technique with palatal (ZZTP); the wrap technique (WT); the wrap technique with palatal (WTP); and the big zigzag technique (BZZT). Finally, each scan was compared with the control model. Results were assessed by one-way ANOVA and linear mixed effects models with a significance level of P 0.05.

Results: The results showed that scan paths ZZT and ZZTP had significantly lower absolute positioning errors and root mean square errors than the other techniques (P 0.0001). For distances between consecutive implant axes and for absolute vertical errors, their superiority was borderline (P 0.10). Overall, techniques ZZT and ZZTP were equally performant and proved to be the most accurate scan paths.

Conclusions: The present in vitro experimental study demonstrates that the scan path can have an influence on the accuracy of the optical impression for full-arch rehabilitations on implants.

Aim: The purpose of the present study was to develop low-cost software that enables the detection of tooth colors by capturing photographs using various devices and to compare the effectiveness with existing expensive methods.

Materials and methods: A total of 60 maxillary central incisors from 30 individuals were included in the study. The CIELAB values (L*, a*, b*) of each tooth were measured using a spectrophotometer, which is considered the gold standard. Subsequently, photographs of the teeth were taken using four different smartphones (iPhone and Xiaomi brands) and one digital camera (Canon EOS 70D DSLR). These images were then subjected to image processing techniques and compared with measurements obtained through computer-based analysis to assess the correlation. The Kruskal-Wallis H test was used (for data in three or more groups), and multiple comparisons were conducted using the Dunn test. The significance level was set at P 0.05.

Results: On examining the results of multiple comparisons, a statistically significant difference was observed (P 0.001) between the Delta E (ΔE) values obtained from the iPhone cameras and those obtained from the Canon and Xiaomi cameras. The iPhone cameras yielded ΔE result values ranging from 2.68 to 2.90.

Conclusions: Color determination methods based on the image processing of photographs taken with iPhone cameras could potentially gain an advantageous position in routine clinical practice as compared with spectrophotometry.

Aim: The objective of the present study was to evaluate the peri-implant marginal bone loss (MBL) and prosthodontic complications of maxillary screw-retained implant prostheses fabricated from digital versus conventional full-arch implant impressions.

Materials and methods: Twenty-eight participants with edentulous maxillary arches were randomly selected and enrolled in two equal groups: Group I (conventional impression group, CIG); Group II (digital impression group, DIG). All patients were rehabilitated with a maxillary screw-retained implant prosthesis retained by six implants. Peri-implant MBL and prosthodontic complications were recorded at 6, 12, and 24 months. Data were collected and statistically analyzed.

Results: Regarding the effect of time, there was a statistically significant increase in MBL at the 6-, 12-, and 24-month follow-ups (P 0.001). Regarding the effect of groups, there was no statistically significant difference in MBL between CIG and DIG at 6, 12, and 24 months, where P = 0.083, 0.087, and 0.133, respectively. Prosthetic complications were recorded 19 times in CIG and 12 times in DIG, with no significant difference between the groups (P = 0.303).

Conclusion: Digital full-arch implant impression is a reliable impression technique and may represent an alternative to conventional implant impression technique in the fabrication of maxillary screw-retained implant prostheses.

Background: This study aimed to evaluate and compare the flexural strength, elastic modulus, and Vicker's microhardness values of glass matrix ceramic and resin matrix ceramic CAD/CAM blocks, and to examine the differences after thermal aging.

Methods: This in vitro study involved seven different CAD/CAM blocks: Amber Mill (Hassbio, Korea), LiSi (GC, Japan), Celtra Duo (Dentsply Sirona, Germany), Tessera (Dentsply Sirona, Germany), IPS e.max CAD (Ivoclar, Liechtenstein), Cerasmart (GC, Japan), and Grandio Blocs (VOCO, Germany). Bar-shaped samples (1.2x4x14mm) for the three-point bending test and rectangular samples (2mm-thickness) for the Vicker's microhardness test were prepared using a precision cutting device under water. Half of the samples underwent 50,000 thermal cycles between 5-55°C, while the other half were kept in distilled water at 37°C for 24 hours. Flexural strength/FS and elastic modulus/EM values were measured using a universal testing machine, and Vicker's microhardness/VHN values were measured using a microhardness tester. Statistical analyses were performed using Kruskal-Wallis and Mann- Whitney U tests, with significance set at p<0.05.

Results: Tessera showed the highest median values for FS (570 MPa), EM (66.2 GPa), and VHN (717.7) after 24 hours, whereas Cerasmart had the lowest values (FS: 260 MPa; EM: 12.8 GPa; VHN: 99.9). Significant differences were found between the materials' FS, EM, and VHN values after 24 hours and after thermal aging (p<0.001). All materials showed a significant decrease in FS values following thermal aging (p<0.05).

Conclusion: In the selection of CAD/CAM materials, it is critical to consider that mechanical properties vary with structure and tend to change over time due to aging.

Aims: The primary aim of this in vitro study was to compare methods for generating 3D-printed replicas through virtual segmentation, utilizing artificial intelligence (AI) or manual processes, by assessing accuracy in terms of volumetric and linear discrepancies. The secondary aims were the assessment of time efficiency with both segmentation methods, and the effect of post-processing on 3D-printed replicas.

Methods: Thirty teeth were scanned through Cone Beam Computed Tomography (CBCT), capturing the region of interest from human subjects. DICOM files underwent virtual segmentation through both AI and manual methods. Replicas were fabricated with a stereolithography 3D printer. After surface scanning of pre-processed replicas and extracted teeth, STL files were superimposed to compare linear and volumetric differences using the extracted teeth as the reference. Post-processed replicas were scanned to assess the effect of post-processing on linear and volumetric changes.

Results: AI-driven segmentation resulted in statistically significant mean linear and volumetric differences of -0.709mm (SD 0.491, P< 0.001) and -4.70%, respectively. Manual segmentation showed no statistically significant differences in mean linear, -0.463mm (SD 0.335, P<0.001) and volumetric (-1.20%) measures. Comparing manual and AI-driven segmentations, AI-driven segmentation displayed mean linear and volumetric differences of -0.329mm (SD 0.566, p=0.003) and -2.23%, respectively. Additionally, AI segmentation reduced the mean time by 21.8 minutes. When comparing post-processed to pre-processed replicas, there was a volumetric reduction of -4.53% and a mean linear difference of -0.151mm (SD 0.564, p=0.042).

Conclusion: Both segmentation methods achieved acceptable accuracy, with manual segmentation slightly more accurate but AI-driven segmentation more time-efficient. Continuous improvement in AI offers the potential for increased accuracy, efficiency, and broader application in the future.

Aim: The aim of this study was to evaluate the accuracy of Dynamic Navigation (DN) in miniscrew insertion in the palatine vault by comparing the deviation between planned and placed miniscrew positions. The secondary outcome was to evaluate the correlation between the number of miniscrews inserted and both the accuracy variables and the duration of interventions.

Materials and methods: Twenty-three subjects were included in the study and each had 2 miniscrews inserted using a DN system (46 miniscrews inserted overall). Pre-operative STL and DICOM files were matched to planned miniscrews insertion and a post-operative CBCT was performed immediately afterwards to measure the deviations between the planned and placed miniscrews, evaluating four variables: Entry-3D, Apex-3D, Apex-vertical and angular deviation. The duration of intervention was also calculated. Descriptive statistics and Pearson correlation coefficient were performed; P-value was set at ≤ 0.05.

Results: The mean Entry-3D deviation was 2.55 mm; the mean Apex-3D deviation was 3.11 mm; the mean Apex-point deviation was 0.87 mm; the mean angular deviation was 8.50°. The mean duration of the intervention was 2:75 min:sec. A statistically significant correlation was found only between the number of surgeries and the duration of the interventions, which decreased over time.

Conclusion: It is possible to conclude that DN is a viable alternative to miniscrew insertion in the palatal vault even if there is a wide deviation range. There is no significant correlation between the accuracy variables and the number of surgeries. In contrast, the duration of the interventions shortens over time.

Aim: To evaluate the accuracy of the intraoral scanner (IOS) for obtaining digital scans of maxillary defects and adjacent tissues to fabricate obturator prosthesis.

Material and methods: Ten randomly selected patients who required an obturator prosthesis after maxillary resection underwent both conventional (CI) and digital (DI) impressions. CI was obtained using traditional methods, and cast models were prepared. The cast models were digitized using a reference scanner in standard tessellation language (STL) format. For Group DI, an intraoral scanner (Trios 5; 3Shape TRIOS®Copenhagen, Denmark) was used for digital scans and the virtual models were created. The data of both groups were analysed by superimposing predetermined points using unreversed engineering software (Geomagic GmbH, 3D Systems, Rock Hill, USA).

Results: No significant deviations from normality (P > 0.05) were found in the predetermined points of the residual hard tissue in the STLs. No interaction was observed between the hard tissue components and the impression techniques used. However, accuracy significantly varied between overlapped points in defect parts across the two impression methods (P= 0 .028).

Conclusion: The evaluation of IOS for digitally scanning maxillary defects shows that they are less effective than CI methods, performing adequately with shallow defects but facing challenges with deeper cavities. It is essential to advance these techniques and conduct clinical studies with larger patient groups to gain broader acceptance of DI methods for routine clinical use, particularly for deep defects.

Aim: The aim of this study was to evaluate the reliability of a digital jaw registration system for measuring mandibular movement and condylar position.

Materials and methods: Data on mandibular movement and condylar position were collected from a consecutively recruited sample of 20 functionally healthy adults (age range: 19-77 years; 45% female) using an optoelectronic registration system (Tizian JMA optic, zebris Medical GmbH, Isny, Germany). Participants were randomly assigned to one of two calibrated examiners, who exclusively performed the measurements for the entire study period. Condylar position was measured five times on two separate days, approximately one week apart, while mandibular movements were recorded once per appointment. The measurement results were analyzed within (intra-appointment) and compared across both measurement appointments (inter-appointment). Analysis of condylar position involved comparing the condylar positions in the resting position to the maximum intercuspation. Reliability was assessed using the intraclass correlation coefficients (ICCs).

Result: For mandibular movement, ICCs indicated high reliability for mouth opening (0.95) and protrusion (0.94), with slightly lower values for laterotrusion (0.89 to 0.87), without significant differences between appointments. The condylar position showed an overall intra-appointment ICC value of 0.98. No significant differences were found within or between the examiners, intraappointment as well as inter-appointment.

Conclusion: The evaluation of mandibular movements and condylar position relative to habitual occlusion using the tested digital registration system proved to be a reliable procedure. The measurements were not significantly influenced by different examiners. The results confirm the applicability of the device in clinical settings, particularly in functional diagnostics and the digital prosthetic workflow. Although the actual benefits of the application for patients have yet to be established, this study provides a scientific foundation for future research considering more vulnerable cohorts, particularly patients with a higher average age, reduced dentition, or the presence of temporomandibular disorders.

Aim: The aim of the present study was to measure the surface roughness of monolithic chairside CAD/CAM zirconia materials to evaluate the influence of milling speed on the ability to create a clinically smooth surface. The null hypothesis was that there would be no significant difference in the surface roughness of different zirconia materials based on the speed of milling.

Materials and methods: All test samples were milled from four different monolithic CAD/CAM zirconia blocks: Cerec Zirconia, Cerec Zirconia+, Cerec MTL Zirconia (all three Dentsply Sirona), and Katana Zirconia (Kuraray Noritake). Four different dry milling speeds - Super Fast/Good, Super Fast/Very Good, Fast, and Fine - were used to dry mill the specimens in a Cerec Primemill (Dentsply Sirona) milling unit. A 3D measuring laser microscope (OLS4100 LEXT; Olympus) was used to measure surface roughness.

Results: Analysis of variance (ANOVA) was used to analyze the surface roughness data for each material and milling speed. There was a significant difference for milling speed (P 0.05) but not between the zirconia materials (P > 0.05).

Conclusions: Based on the limitations of the present study, the milling speed was found to influence the surface roughness of dry milled and sintered zirconia, with slower speeds resulting in smoother surfaces. The largest improvement in surface roughness occurred between the Super Fast and Fast milling speeds, with a smaller incremental improvement in surface roughness with Fine milling in the Primemill. All recorded surface roughness values were within the expected range of values to be able to efficiently hand polish a clinically acceptable surface finish.

Aim: To develop a periodontal disease prediction (PDP) software program and a patient-based gingival recession simulator for clinical practice with the aim of improving the oral hygiene motivation of patients with periodontal problems.

Materials and methods: The developed PDP software has three components: a) A data loading window (DLW), b) A three-dimensional mouth model (3DM), and c) a periodontal attachment loss indicator (PLI). The demographic and clinical examination details of 1057 volunteers were recorded to the DLW. An unsupervised machine learning K means clustering analysis was used to categorize the data obtained from the study population and to identify the periodontal risk groups. An intraoral scanner was utilized to capture the direct optical intraoral data of the patients, which was transferred to the 3DM. The intraoral model underwent two algorithm steps to obtain a recessed model: First, the gingival curves separating the gingiva and tooth were extracted using a Dijkstra's algorithm. Then, the limit curves determining the boundaries of the recessed regions in the intraoral model were obtained using the gingival curves.

Results: Study participants were divided into three different periodontal risk categories: low- (n = 462), medium- (n = 336), and high-risk (n = 259) groups. The gingival curves separating the gingiva and tooth were extracted, and recessed models were obtained and given inputs for the expected amount of recession via the here-proposed method/algorithm. Furthermore, the user can also demonstrate the gingival recession gradually via the slider method incorporated into the developed program.

Conclusions: A user-friendly computer-based periodontal risk estimation tool that is also a patient-specific gingival recession simulator was developed and presented for clinical use by dentists.