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. [ J Adv

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PURPOSEThe 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 METHODSTwo 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).RESULTSEight 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.CONCLUSIONThe 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.

PurposeImage 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 MethodsA 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)ResultsIn 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.ConclusionThe 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.

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.