Impacts of Thresholds of Gray Value for Cone-Beam Computed Tomography 3D Reconstruction on the Accuracy of Image Matching with Optical Scan.

In cone-beam computed tomography (CBCT), the minimum threshold of the gray value of segmentation is set to convert the CBCT images to the 3D mesh reconstruction model. This study aimed to assess the accuracy of image registration of optical scans to 3D CBCT reconstructions created by different thresholds of grey values of segmentation in partial edentulous jaw conditions. CBCT of a dentate jaw was reconstructed to 3D mesh models using three different thresholds of gray value (-500, 500, and 1500), and three partially edentulous models with different numbers of remaining teeth (4, 8, and 12) were made from each 3D reconstruction model. To merge CBCT and optical scan data, optical scan images were registered to respective 3D reconstruction CBCT images using a point-based best-fit algorithm. The accuracy of image registration was assessed by measuring the positional deviation between the matched 3D images. The Kruskal-Wallis test and a post hoc Mann-Whitney U test with Bonferroni correction were used to compare the results between groups (α = 0.05). The correlations between the experimental factors were calculated using the two-way analysis of variance test. The positional deviations were lowest with the threshold of 500, followed by the threshold of 1500, and then -500. A significant interaction was found between the threshold of gray values and the number of remaining teeth on the registration accuracy. The most significant deviation was observed in the arch model with four teeth reconstructed with a gray-value threshold of -500. The threshold for the gray value of CBCT segmentation affects the accuracy of image registration of optical scans to the 3D reconstruction model of CBCT. The appropriate gray value that can visualize the anatomical structure should be set, especially when few teeth remain in the dental arch.

Effects of scan body exposure and operator on the accuracy of image matching of implant impressions with scan bodies.

STATEMENT OF PROBLEM: Accurate image matching of the scan with the design of the scan body is essential to replicate the actual implant position in the software program. In situations where the scan part of the scan body is partially embedded in the gingival tissue, the influence of the scan image deficiency on the accuracy of image matching has not been clarified. PURPOSE: The purpose of this in vitro study was to examine the effects of scan body exposure and different operators on the accuracy of image matching of the scan body. MATERIAL AND METHODS: Six groups with different scan body exposures (fully exposed, 0.5 mm, 1.0 mm, 1.5 mm, 2.0 mm, and 2.5 mm less exposed) were digitized, and the scan images were transferred to a CAD software program, where the design of the scan body was matched to the scan image of each group. Based on the position of the scan body design, a virtual implant was created. The image matching process was performed 7 times for each group by 2 operators (N=84). The linear and angular deviations of the virtual implants were analyzed 3-dimensionally. Two-way ANOVA, equivalence, and concordance correlation coefficient statistics were used to verify the effects of scan body exposure and operator on the image matching. RESULTS: As the exposure of the scan body was reduced, the deviations in implant positioning were significantly increased (P<.001). The concordance correlation coefficient indicated strong agreement between the 2 operators. CONCLUSIONS: Reduced exposure of the scan body significantly influenced the accuracy of implant positioning in the software program. Operator differences may not affect the accuracy of scan body image matching.

The effect of the improperly scanned scan body images on the accuracy of virtual implant positioning in computer-aided design software.

PURPOSE: The aim of this study was to examine the importance of the defect-free scanning of a scan body by assessing the accuracy of virtual implant positioning in computer-aided design (CAD) software when the scan body image is improperly scanned. MATERIALS AND METHODS: A scan body was digitized in a dentiform model using an intraoral scanner, and scanned images with differing levels of image deficiency were generated: 5%, 10%, and 15% deficiency in the flat or rounded area. Using a best-fit image matching algorithm on each of the deficient scan body images, corresponding virtual implants were created. The accuracy of the implant position was evaluated by comparing the linear and angular discrepancies between the actual and virtual positions of the implant. Kruskal-Wallis tests and Mann-Whitney U tests with Bonferroni correction were used to determine the statistical differences among the seven scanned image deficiency groups (α=.05). RESULTS: In general, the linear and angular discrepancies of the implant position in the software increased as the deficiency of the scan body images increased. A 15% scan body image deficiency generated larger discrepancies than deficiency of 5% and 10%. The difference of scan defect position, flat or rounded area, did not affect the accuracy of virtual implant orientation at 5% and 10% deficiency level, but did affect the accuracy at 15% deficiency level. CONCLUSION: Deficiencies in the scanned images of a scan body can decrease the accuracy of the implant positioning in CAD software when the defect is large, thus leading to the incorrect fabrication of implant prostheses.

The Effects of Distribution of Image Matched Fiducial Markers on Accuracy of Computer-Guided Implant Surgery.

PURPOSE: Image registration of the optical intraoral scan to computed tomography image is essential for computer-guided implant surgery. The remaining teeth, which are considered to be congruent structures observed in the scan and radiographic images, are used to perform the image registration. The purpose of this study was to evaluate the effects of the distribution of matching fiducial points on the accuracy of the image registration. MATERIALS AND METHODS: A partially edentulous model with three anterior remaining teeth was prepared. Two mini dental implants were inserted in the posterior edentulous areas on both sides, and computed tomography and surface scan data were obtained. Three groups were set according to the distribution of the image matching points used: localized distribution, unilateral distribution, and bilateral distribution. Fifteen graduate students performed the registration process in each group using the same image matching method. The accuracy of image registration was evaluated by measuring the geometric discrepancies between the radiographic and registered scan images in the anterior, middle, and posterior regions. One-way and two-way analysis of variance with the Tukey HSD post hoc test were used for statistical analysis (α = 0.05) RESULTS: In general, the registration discrepancy was lowest in the bilateral distribution group, followed by the unilateral distribution and localized distribution groups (p< 0.001). In the regional analysis, the registration error tended to increase as the measurement region moved farther from the matching points. The distribution of the matching points and measurement regions had a statistical interaction in the accuracy of image registration. CONCLUSION: The accuracy of image registration of the surface scan to the computed tomography is affected by the matching point distribution that can be improved by placing artificial markers in the edentulous areas.

Comparative clinical study of the marginal discrepancy of fixed dental prosthesis fabricated by the milling-sintering method using a presintered alloy.

PURPOSE: The present study was designed to examine the clinical fit of fixed dental prosthesis fabricated by the milling-sintering method using a presintered cobalt-chromium alloy. MATERIALS AND METHODS: Two single metal-ceramic crowns were fabricated via milling-sintering method and casting method in each of the twelve consecutive patients who required an implant-supported fixed prosthesis. In the milling-sintering method, the prosthetic coping was designed in computer software, and the design was converted to a non-precious alloy coping using milling and post-sintering process. In the casting method, the conventional manual fabrication process was applied. The absolute marginal discrepancy of the prostheses was evaluated intraorally using the triple-scan technique. Statistical analysis was conducted using Mann-Whitney U test (α=.05). RESULTS: Eight patients (66.7%) showed a lower marginal discrepancy of the prostheses made using the milling-sintering method than that of the prosthesis made by the casting method. Statistically, the misfit of the prosthesis fabricated using the milling-sintering method was not significantly different from that fabricated using the casting method (P=.782). There was no tendency between the amount of marginal discrepancy and the measurement point. CONCLUSION: The overall marginal fit of prosthesis fabricated by milling-sintering using a presintered alloy was comparable to that of the prosthesis fabricated by the conventional casting method in clinical use.