Cephalometric analysis performance discrepancy between orthodontists and an artificial intelligence model using lateral cephalometric radiographs.

PURPOSE: The purpose of the present clinical study was to compare the Ricketts and Steiner cephalometric analysis obtained by two experienced orthodontists and artificial intelligence (AI)-based software program and measure the orthodontist variability. MATERIALS AND METHODS: A total of 50 lateral cephalometric radiographs from 50 patients were obtained. Two groups were created depending on the operator performing the cephalometric analysis: orthodontists (Orthod group) and an AI software program (AI group). In the Orthod group, two independent experienced orthodontists performed the measurements by performing a manual identification of the cephalometric landmarks and a software program (NemoCeph; Nemotec) to calculate the measurements. In the AI group, an AI software program (CephX; ORCA Dental AI) was selected for both the automatic landmark identification and cephalometric measurements. The Ricketts and Steiner cephalometric analyses were assessed in both groups including a total of 24 measurements. The Shapiro-Wilk test showed that the data was normally distributed. The t-test was used to analyze the data (α = 0.05). RESULTS: The t-test analysis showed significant measurement discrepancies between the Orthod and AI group in seven of the 24 cephalometric parameters tested, namely the corpus length (p = 0.003), mandibular arc (p < 0.001), lower face height (p = 0.005), overjet (p = 0.019), and overbite (p = 0.022) in the Ricketts cephalometric analysis and occlusal to SN (p = 0.002) and GoGn-SN (p < 0.001) in the Steiner cephalometric analysis. The intraclass correlation coefficient (ICC) between both orthodontists of the Orthod group for each cephalometric measurement was calculated. CONCLUSIONS: Significant discrepancies were found in seven of the 24 cephalometric measurements tested between the orthodontists and the AI-based program assessed. The intra-operator reliability analysis showed reproducible measurements between both orthodontists, except for the corpus length measurement. CLINICAL SIGNIFICANCE: The artificial intelligence software program tested has the potential to automatically obtain cephalometric analysis using lateral cephalometric radiographs; however, additional studies are needed to further evaluate the accuracy of this AI-based system.

Influence of connected and nonconnected calibrated frameworks on the accuracy of complete arch implant scans obtained by using four intraoral scanners, a desktop scanner, and a photogrammetry system.

STATEMENT OF PROBLEM: Different techniques have been proposed for increasing the accuracy of complete arch implant scans obtained by using intraoral scanners (IOSs), including a calibrated metal framework (IOSFix); however, its accuracy remains uncertain. PURPOSE: The purpose of this in vitro study was to compare the accuracy of complete arch scans obtained with connecting and non-connecting the implant scan bodies (ISBs) recorded using intraoral scanners (IOSs), a laboratory scanner (LBS), and photogrammetry (PG). MATERIAL AND METHODS: A cast with 6 implant abutment analogs was obtained. Six groups were created: TRIOS 4, i700, iTero, CS3800, LBS, and PG groups. The IOSs and LBS groups were divided into 3 subgroups: nonconnected ISBs (ISB), splinted ISBs (SSB), and calibrated framework (CF), (n=15). For the ISB subgroups, an ISB was positioned on each implant abutment analog. For the SSB subgroups, a printed framework was used to connect the ISBs. For the CF subgroups, a calibrated framework (IOSFix) was used to connect the ISBs. For the PG group, scans were captured using a PG (PIC Camera). Implant positions of the reference cast were measured using a coordinate measurement machine, and Euclidean distances were used as a reference to calculate the discrepancies using the same distances obtained on each experimental scan. Wilcoxon squares 2-way ANOVA and pairwise multiple comparisons were used to analyze trueness (α=.05). The Levene test was used to analyze precision (α=.05). RESULTS: Linear and angular discrepancies were found among the groups (P<.001) and subgroups (P<.001). Linear (P=.008) and angular (P<.001) precision differences were found among the subgroups. CONCLUSIONS: The digitizing method and technique impacted the trueness and precision of the implant scans. The photogrammetry and calibrated framework groups obtained the best accuracy. Except for TRIOS 4, the calibrated framework method improved the accuracy of the scans obtained by using the IOSs tested.

Accuracy comparison of the maxillary cast transfer into the virtual semi-adjustable articulator between an analog facebow record and a digital photography technique.

STATEMENT OF PROBLEM: Digital photographs can be used for transferring the maxillary cast into the virtual semi-adjustable articulator; however, its accuracy remains unknown. PURPOSE: The purpose of the present study was to compare the accuracy of the maxillary cast transfer into the virtual semi-adjustable articulator by using an analog and a digital standardized photography technique. MATERIAL AND METHODS: A maxillary cast was digitized (T710) and positioned into a dental mannequin. The dental midline was not coincident with the facial midline and the maxillary occlusal plane was tilted. A reference scan of the assembled mannequin was obtained by using a facial scanner (Instarisa). Two groups were created based on the technique used to transfer the maxillary cast into the articulator (Panadent PCH): conventional facebow record (CNV group) or digital photograph (Photo group) (n=10). In the CNV group, facebow records (Kois Dentofacial analyzer system) were digitized (T710) and used to transfer the maxillary scan into the articulator by aligning it with the reference platform (Kois adjustable platform). In the Photo group, photographs with a reference glasses (Kois Reference Glasses) positioned into the mannequin were acquired. Each photograph was aligned with the maxillary scan. Then, the maxillary scan was transferred into the articulator by using the true horizontal axis information contained in the photograph. On the reference scan and each specimen, 10 linear measurements between the buccal cusps of the maxillary scan and the horizontal plane of the virtual articulator and a linear measurement between the maxillary dental midline and articulator midline were calculated. The measurements of the reference scan were used as a control to compute trueness and precision. Trueness was analyzed by using 1-way ANOVA followed by the pairwise comparison Tukey test (α=.05). Precision was evaluated by using the Levene and Wilcoxon Rank sum tests (α=.05). RESULTS: The overall discrepancy measured in the CNV group was 0.620 ±0.396 mm, while in the Photo group it was 1.282 ±0.118 mm. Significant trueness differences were found in the midline (P=.037), anterior (P=.050), posterior right (P<.001), posterior left (P=.012), and overall discrepancy (P<.001) between the CNV and Photo groups. Significant precision discrepancies were found in the midline (P=.012), posterior right (P<.001), anterior (P<.001), posterior left (P=.002), and overall discrepancy (P<.001) between the CNV and Photo groups. CONCLUSIONS: The facebow record method impacted the accuracy of the maxillary cast transfer. The Photo group obtained better trueness in the midline transfer than the CNV group; however, the CNV group demonstrated better trueness in the anterior, posterior right, posterior left, and overall discrepancy of the maxillary cast transfer compared with the Photo group. Overall, the Photo group obtained better precision than the CNV group.

Accuracy of the maxillary cast transfer into the virtual semi-adjustable articulator by using analog and digital facebow record methods.

STATEMENT OF PROBLEM: Different digital methods have been described for transferring the maxillary cast into a virtual articulator; however, its accuracy remains uncertain. PURPOSE: The purpose of this in vitro study was to compare the accuracy of the maxillary cast transfer into the virtual semi-adjustable articulator by using analog and digital methods. MATERIAL AND METHODS: A maxillary typodont with 5 markers was positioned into a mannequin, which was digitized by using an industrial scanner (ATOS Q) and an extraoral scan of the typodont obtained (T710). Three groups were created based on the technique used to transfer the maxillary cast into the virtual articulator (Panadent PCH Articulator): conventional facebow record (CNV group), digital photograph (P group), and facial scanning (FS group) (n=10). In the CNV group, conventional facebow records (Kois Dentofacial analyzer system) were digitized (T710) and used to mount the maxillary scan into the articulator by aligning it with the reference platform (Kois adjustable platform) (DentalCAD). In the P group, photographs with the reference glasses (Kois Reference Glasses 3.0) were positioned in the mannequin. Each photograph was superimposed with the maxillary scan. Then, the maxillary scan was transferred into the virtual articulator by using the true horizontal plane information of the photograph. In the FS group, facial scans with an extraoral scan body (Kois Scan Body) were positioned in the mannequin by using a facial scanner (Instarisa). The extraoral scan body was digitized by using the same extraoral scanner. The digitized extraoral scan body provided the true horizontal plane information that was used to mount the maxillary scan into the articulator, along with the Kois disposable tray of the scan body. On the reference scan and each specimen, 15 linear measurements between the markers of the maxillary scans and the horizontal plane of the virtual articulator and 3 linear measurements between the maxillary dental midline and articulator midline were calculated. The measurements of the reference scan were used as a control to assess trueness and precision. Trueness was analyzed by using 1-way ANOVA followed by the pairwise comparison Tukey tests (α=.05). Precision was evaluated by using the Levene and pairwise comparisons Wilcoxon Rank sum tests. RESULTS: No significant trueness (P=.996) or precision (P=.430) midline discrepancies were found. Significant posterior right (P<.001), anterior (P=.005), posterior left (P<.001), and overall (P<.001) trueness discrepancies were revealed among the groups. The P group obtained the best posterior right, posterior left, and overall trueness and precision. The P and FS groups demonstrated the best anterior trueness, but no anterior precision discrepancies were found. CONCLUSIONS: The techniques tested affected the accuracy of the maxillary cast transfer into the virtual semi-adjustable articulator. In the majority of the parameters assessed, the photography method tested showed the best trueness and precision values. However, the maxillary cast transfer accuracy ranged from 137 ±44 µm to 453 ±176 µm among the techniques tested.

Accuracy of maximum intercuspal position located by using four intraoral scanners and an artificial intelligence-based program.

STATEMENT OF PROBLEM: Maxillary and mandibular scans can be articulated in maximum intercuspal position (MIP) by using an artificial intelligence (AI) based program; however, the accuracy of the AI-based program locating the MIP relationship is unknown. PURPOSE: The purpose of the present clinical study was to assess the accuracy of the MIP relationship located by using 4 intraoral scanners (IOSs) and an AI-based program. MATERIAL AND METHODS: Conventional casts of a participant mounted on an articulator in MIP were digitized (T710). Four groups were created based on the IOS used to record a maxillary and mandibular scan of the participant: TRIOS4, iTero, i700, and PrimeScan. Each pair of nonarticulated scans were duplicated 20 times. Three subgroups were created: IOS, AI-articulated, and AI-IOS-corrected subgroups (n=10). In the IOS-subgroup, 10 duplicated scans were articulated in MIP by using a bilateral occlusal record. In the AI-articulated subgroup, the remaining 10 duplicated scans were articulated in MIP by using an AI-based program (BiteFinder). In the AI-IOS-corrected subgroup, the same AI-based program was used to correct the occlusal collisions of the articulated specimens obtained in the IOS-subgroup. A reverse engineering program (Geomagic Wrap) was used to calculate 36 interlandmark measurements on the digitized articulated casts (control) and each articulated specimen. Two-way ANOVA and pairwise multiple comparison Tukey tests were used to analyze trueness (α=.05). The Levene and pairwise multiple comparison Wilcoxon rank tests were used to analyze precision (α=.05). RESULTS: Significant trueness discrepancies among the groups (P<.001) and subgroups (P<.001) were found, with a significant interaction group×subgroup (P<.001). The Levene test showed significant precision discrepancies among the groups (P<.001) and subgroups (P=.005). The TRIOS4 and iTero groups obtained better trueness and lower precision than the i700 and PrimeScan systems. Additionally, the AI-articulated subgroup showed worse trueness and precision than the IOS and AI-IOS-corrected subgroups. The AI-based program improved the MIP trueness of the scans articulated by using the iTero and PrimeScan systems but reduced the MIP trueness of the articulated scans obtained by using the TRIOS4 and i700. CONCLUSIONS: The trueness and precision of the maxillomandibular relationship was impacted by the IOS system and program used to locate the MIP.

Accuracy of an artificial intelligence-based program for locating the maxillomandibular relationship of scans acquired by using intraoral scanners.

STATEMENT OF PROBLEM: An artificial-intelligence (AI) based program can be used to articulate scans in maximum intercuspal position (MIP) or correct occlusal collisions of articulated scans at MIP; however, the accuracy of the AI program determining the MIP relationship is unknown. PURPOSE: The purpose of the present clinical study was to assess the influence of intraoral scanner (IOS) (TRIOS 5 or i700) and program (IOS or AI-based program) on the accuracy of the MIP relationship. MATERIAL AND METHODS: Casts of a participant mounted on an articulator were digitized (T710). A maxillary and a mandibular scan of the participant were recorded by using 2 IOSs: TRIOS 5 and i700. The scans were duplicated 15 times. Then, each duplicated pair of scans was articulated in MIP using a bilateral occlusal record. Articulated scans were duplicated and allocated into 2 groups based on the automatic occlusal collisions' correction completed by using the corresponding IOS program: IOS-corrected and IOS-noncorrected group. Three subgroups were created based on the AI-based program (Bite Finder) method: AI-articulated, AI-IOS-corrected, and AI-IOS-noncorrected (n=15). In the AI-articulated subgroup, the nonarticulated scans were imported and articulated. In the AI-IOS-corrected subgroup, the articulated scans obtained in the IOS-corrected group were imported, and the occlusal collisions were corrected. In the AI-IOS-corrected subgroup, the articulated scans obtained in the IOS-noncorrected subgroup were imported, and the occlusal collisions were corrected. A total of 36 interlandmark measurements were calculated on each articulated scan (Geomagic Wrap). The distances computed on the reference scan were used as a reference to calculate the discrepancies with each experimental scan. Nonparametric 2-way ANOVA and pairwise multiple comparison Dwass-Steel-Critchlow-Fligner tests were used to analyze trueness. The general linear model procedure was used to analyze precision (α=.05). RESULTS: Significant maxillomandibular trueness (P=.003) and precision (P<.001) differences were found among the subgroups. The IOS-corrected and IOS-noncorrected (P<.001) and AI-articulated and IOS-noncorrected subgroups (P=.011) were significantly different from each other. The IOS-corrected and AI-articulated subgroups obtained significantly better maxillomandibular trueness and precision than the IOS-noncorrected subgroups. CONCLUSIONS: The IOSs tested obtained similar MIP accuracy; however, the program used to articulate or correct occlusal collusions impacted the accuracy of the MIP relationship.

Discrepancies of centric occlusion located by using a conventional method and four intraoral scanners combined with a computer-aided design program: A pilot investigation.

STATEMENT OF PROBLEM: Intraoral scanners (IOSs) can be used to record the maxillomandibular relationship at centric relation (CR). The articulated digital scans can be imported into a dental computer-aided design (CAD) program and used to locate centric occlusion (CO); however, the accuracy of the CO recorded by using IOSs and a dental CAD program remains unknown. PURPOSE: The purpose of this clinical study was to compare the position of the CO located by using a conventional method and 4 IOSs combined with a dental CAD program. MATERIAL AND METHODS: A patient volunteered to participate in this study. Conventional diagnostic stone casts were obtained. A facebow record (Kois Dentofacial Analyzer) was used to transfer the maxillary cast into a semi-adjustable articulator (Panadent PCH Articulator). A Kois deprogrammer (KD) was used to record the maxillomandibular relationship at CR and to transfer the mandibular cast into the articulator. Afterwards, CO was located in the articulated casts by removing the incisal pin and using an 8-µm articulating foil. CO was marked in the casts by using a blue articulating paper (control). Three groups were created based on the IOS used: TRIOS 4, iTero Element 5D Plus, i700, and Primescan. In each IOS group, a maxillary and mandibular scan were obtained. The scans were duplicated 10 times. Afterwards, a bilateral occlusal record captured with the KD was used to articulate each pair of duplicated scans. Each articulated specimen was imported into a CAD program (DentalCAD) and CO was virtually located. The teeth contacting at the CO of each specimen were compared with the control group. Categorical data were analyzed by using the chi-squared test (α=.05). RESULTS: The chi-squared test revealed a significant association between the IOS system and the location of the CO (P=.004). The highest association was found between the TRIOS 4 and CO position, in which 100% of the specimens obtained the same CO position as in the conventional group. The lowest association was found between the i700 and CO position. In the i700 group, 20% of the specimens showed the same CO position as in the control group. A similar outcome was obtained in the iTero and Primescan groups. In both groups, 60% of the specimens demonstrated the same CO position as the control group. CONCLUSIONS: The IOS system used to acquire articulated scans at CR impacted the CO position located by using the evaluated digital methods. The TRIOS 4 system was the only IOS that consistently reproduced the same CO position as the conventional method.

Influence of scan extension and starting quadrant on the accuracy of four intraoral scanners for fabricating tooth-supported crowns.

STATEMENT OF PROBLEM: Multiple factors can influence the accuracy of intraoral scanners (IOSs). However, the impact of scan extension and starting quadrant on the accuracy of IOSs for fabricating tooth-supported crowns remains uncertain. PURPOSE: The purpose of the present in vitro study was to measure the influence of scan extension (half or complete arch scan) and the starting quadrant (same quadrant or contralateral quadrant of the location of the crown preparation) on the accuracy of four IOSs. MATERIAL AND METHODS: A typodont with a crown preparation on the left first molar was digitized (T710) to obtain a reference scan. Four scanner groups were created: TRIOS 5, PrimeScan, i700, and iTero. Then, 3 subgroups were defined based on the scan extension and starting quadrant: half arch (HA subgroup), complete arch scan starting on the left quadrant (CA-same subgroup), and complete arch scan starting on the right quadrant (CA-contralateral subgroup), (n=15). The reference scan was used as a control to measure the root mean square (RMS) error discrepancies with each experimental scan on the tooth preparation, margin of the tooth preparation, and adjacent tooth areas. Two-way ANOVA and pairwise multiple comparisons were used to analyze trueness (α=.05). The Levene and pairwise comparisons using the Wilcoxon Rank sum tests were used to analyze precision (α=.05). RESULTS: For the tooth preparation analysis, significant trueness and precision differences were found among the groups (P<.001) and subgroups (P<.001), with a significant interaction group×subgroup (P=.002). The iTero and TRIOS5 groups obtained better trueness than the PrimeScan and i700 groups (P<.001). Moreover, half arch scans obtained the best trueness, while the CA-contralateral scans obtained the worst trueness (P<.001). The iTero group showed the worst precision among the IOSs tested. For the margin of the tooth preparation evaluation, significant trueness and precision differences were found among the groups (P<.001) and subgroups (P<.001), with a significant interaction group×subgroup (P=.005). The iTero group obtained best trueness (P<.001), but the worst precision (P<.001) among the IOSs tested. Half arch scans obtained the best trueness and precision values. For the adjacent tooth analysis, trueness and precision differences were found among the groups (P<.001) and subgroups tested (P<.001), with a significant interaction group×subgroup (P=.005). The TRIOS 5 obtained the best trueness and precision. Half arch scans obtained the best accuracy. CONCLUSIONS: Scan extension and the starting quadrant impacted the scanning trueness and precision of the IOSs tested. Additionally, the IOSs showed varying scanning discrepancies depending on the scanning area assessed. Half arch scans presented the highest trueness and precision, and the complete arch scans in which the scan started in the contralateral quadrant of where the crown preparation was obtained the worst trueness and precision.

Influence of implant reference on the scanning accuracy of complete arch implant scans captured by using a photogrammetry system.

STATEMENT OF PROBLEM: Photogrammetry has been reported to be a reliable digital alternative for recording implant positions; however, the factors that may impact the accuracy of photogrammetry techniques remain unknown. PURPOSE: The purpose of this in vitro study was to assess the influence of the implant reference on the accuracy of complete arch implant scans acquired by using a photogrammetry system. MATERIAL AND METHODS: An edentulous cast with 6 implant abutment analogs (MultiUnit Abutment Plus Replica) was obtained and digitized by using a laboratory scanner (T710; Medit). A photogrammetry system (PIC System) was selected to obtain complete arch implant scans. An optical marker (PIC Transfer, HC MUA Metal; PIC Dental) was positioned on each implant abutment of the reference cast. Each optical marker code and position was determined in the photogrammetry software program. Three groups were created based on the implant reference selected before acquiring the photogrammetry scans: right first molar (IPR-3 group), left canine (IPR-11 group), and left first molar (IPR-14 group) (n=30). Euclidean linear and angular measurements were obtained on the digitized reference cast and used to compare the discrepancies with the same measurements obtained on each experimental scan. One-way ANOVA and the Tukey tests were used to analyze the trueness data. The Levene test was used to analyze the precision values (α=.05 for all tests). RESULTS: One-way ANOVA revealed significant linear (P=.003) and angular (P=.009) trueness differences among the groups tested. Additionally, the Tukey test showed that the IPR-11 and IPR-14 groups had significantly different linear (P<.001) and angular trueness (P<.001). The Levene test showed no significant precision linear (P=.197) and angular (P=.235) discrepancies among the groups tested. The IPR-3 group obtained the highest trueness (P<.001) and precision (P<.001) values among the groups tested. CONCLUSIONS: Implant reference impacted the accuracy of complete arch implant scans obtained by using the photogrammetry system tested. However, a trueness ±precision linear discrepancy of 6 ±3 µm and an angular discrepancy of 0.01 ±0.01 degrees were measured among the groups tested; therefore, the impact of the discrepancy measured should not be clinically significant.

Influence of apical finish line location of tooth preparations on the scanning accuracy of intraoral scanners with various focal lengths and scanning technologies.

STATEMENT OF PROBLEM: Limited studies have reported the influence of finish line location on the accuracy of intraoral scanners (IOSs). Focal length is a hardware characteristic of IOSs. Whether there is a relationship between scanning accuracy of tooth preparations with the finish located at different apical positions and focal length and IOS technology or system remains uncertain. PURPOSE: The purpose of the present in vitro study was to assess the influence of the apical finish line location of tooth preparations on the accuracy of 4 IOSs with various focal lengths and scanning technologies. MATERIAL AND METHODS: A maxillary typodont with a crown preparation on the left first molar was digitized (T710). Afterwards, a removable die was created on the prepared first molar of the virtual cast and duplicated to create 4 dies with different apical finish line locations: 2- or 1-mm supragingival, 0-mm or equigingival, and -0.5-mm or intracrevicular. The cast and die designs were additively fabricated (Asiga Pro 4K with Keystone Model Ultra). Each die was independently scanned by using the same laboratory scanner (reference scans). Four groups were created: TRIOS 5, i700, iTero, and Primescan. Four subgroups were developed depending on the apical position of the finish line (n=15). In each subgroup, the cast was assembled by positioning the corresponding die into the cast. The cast was then scanned by using the corresponding IOS. The reference scans were used as a control to compute the root mean square (RMS) error discrepancies with each experimental scan on the preparation and margin of the preparation areas. Two-way ANOVA and pairwise comparisons were used to analyze trueness (α=.05). The Levene and pairwise comparisons using the Wilcoxon Rank sum test were used to analyze precision (α=.05). RESULTS: Trueness discrepancies in the preparation area were found among the groups (P=.010) and subgroups (P<.001), with a significant interaction between group×subgroup (P<.001). The -0.5 mm location obtained significantly worse trueness in the preparation area. The TRIOS 5 and i700 obtained the best trueness in the preparation area. Trueness discrepancies in the margin area were found among the groups (P=.002) and subgroups (P<.001), with a significant interaction between group×subgroup (P=.004). The -0.5 mm location obtained the worst trueness in the margin area. The i700 and Primescan obtained the best trueness in the margin area. Precision discrepancies were found in the preparation area (P<.001). The TRIOS 5 obtained the best precision in the preparation area (P=.001). Precision discrepancies in the margin area were obtained (P<.001). The 1-mm subgroup obtained the best precision (P=.001). CONCLUSIONS: The apical position of the finish line of the tooth preparation tested affected the trueness and precision of the IOSs tested.

Wear at the implant-framework interface between titanium implant platform and the additively manufactured titanium and cobalt-chromium frameworks.

PURPOSE: To measure the wear at the implant interface between the Grade 4 titanium (Ti) of the implant and frameworks fabricated using two additively manufactured alloys (Ti alloy and cobalt-chromium [Co-Cr]) pre- and post-artificial aging. MATERIAL AND METHODS: Three-unit frameworks supported by two implants were additively manufactured (Atlantis; Dentsply Sirona) using Ti and Co-Cr dental alloys. Two implants (OsseoSpeed EV, Astra Tech; Dentsply Sirona) were torqued on each non-engaging framework. The assembled implant-frameworks were secured into polyurethane foam blocks. Groups were created based on the material and surface assessed: framework (Ti-framework and Co-Cr-framework groups) and implant (Ti-implant group). Two subgroups were created depending on the location: premolar (PM) and molar (M). Computed tomography images were obtained pre- (as manufactured) and post-simulated mastication procedures. The pre- and post-simulated mastication files of each specimen were aligned using the best-fit algorithm using a metrology program. Wear was measured by calculating the volumetric discrepancies at the implant interface on 64 measurement points per area analyzed. Three-way ANOVA and Tukey tests were used to analyze the data (α = 0.05). RESULTS: The mean volumetric discrepancy values ranged from 0.8 to 3.1 µm among all the subgroups tested. The group (framework vs. implant) (p < 0.001) and tooth location (p < 0.001) were significant factors of the mean volumetric discrepancy values obtained. The framework group presented with significantly lower volumetric discrepancy mean values (1 µm) compared with the implant group (3 µm), whereas the premolar area obtained significantly lower mean volumetric discrepancy values (1.9 µm) compared with the molar location (2.3 µm). CONCLUSIONS: Volumetric discrepancies were found at the implant-framework interface tested between the pre- and post-artificial aging measurements ranging from 1 to 3 µm after 1,200,000 cyclic loading that simulated approximately 12 months of function.

Comparison of surface roughness of additively manufactured implant-supported interim crowns fabricated with different print orientations.

PURPOSE: To assess the influence of print orientation on the surface roughness of implant-supported interim crowns manufactured by using digital light processing (DLP) 3D printing procedures. MATERIALS AND METHODS: An implant-supported maxillary right premolar full-contour crown was obtained. The interim restoration design was used to fabricate 30 specimens with 3 print orientations (0, 45, and 90 degrees) using an interim resin material (GC Temp PRINT) and a DLP printer (Asiga MAX UV) (n = 10). The specimens were manufactured, and each was cemented to an implant abutment with autopolymerizing composite resin cement (Multilink Hybrid Abutment). Surface roughness was assessed on the buccal surface of the premolar specimen by using an optical measurement system (InfiniteFocusG5 plus). The data were analyzed with a Shapiro-Wilk test, resulting in a normal distribution. One-way ANOVA and the Tukey HSD tests were selected (α = 0.05). RESULTS: Statistically significant discrepancies were found in the surface roughness mean values among the groups tested (p < 0.001). The lowest mean ± standard deviation surface roughness was found with the 90-degree group (1.2 ± 0.36 µm), followed by the 0-degree orientation (2.23 ± 0.18 µm) and the 45-degree group (3.18 ± 0.31 µm). CONCLUSIONS: Print orientation parameter significantly impacted the surface roughness of the implant-supported interim crowns manufactured by using the additive procedures tested.

Influence of arch location and scanning pattern on the scanning accuracy, scanning time, and number of photograms of complete-arch intraoral digital implant scans.

OBJECTIVES: To measure the influence of arch location and scanning pattern on the accuracy, scanning time, and number of photograms of complete-arch implant scans acquired using an intraoral scanner (IOS). MATERIALS AND METHODS: A maxillary (maxillary group) and mandibular (mandibular group) model with 6 implant abutments on each cast was digitized using a desktop scanner (control scans). Six subgroups were created based on the scanning pattern used to acquire the scans using an IOS (Trios 4): occluso-buccal-lingual (OBL subgroup), occluso-linguo-buccal (OLB subgroup), bucco-linguo-occlusal (BLO subgroup), linguo-buccal-occlusal (LBO subgroup), zigzag (ZZ subgroup), and circumferential (C subgroup). The control scans were used as a reference to measure the discrepancy with the experimental scans calculating the root mean square error. Two-way ANOVA and the pairwise comparison Tukey tests were used to analyze the data (α = .05). RESULTS: Significant discrepancies in trueness (p < .001), precision (p < .001), scanning time (p < .001), and number of photograms (p < .001) were found. The maxillary group obtained poorer trueness and precision values, higher scanning times, and a larger number of photograms than the mandibular group. The C subgroup obtained the best trueness and precision values, but was not significantly different from the OLB, BLO, and LBO subgroups. The ZZ subgroup obtained the worst trueness and precision values (p < .05). The C subgroup obtained the lowest scanning time and number of photograms (p < .05). CONCLUSIONS: Arch location and scanning pattern influenced scanning accuracy, scanning time, and number of photograms of complete-arch implant scans.

Manufacturing accuracy of the intaglio surface of definitive resin-ceramic crowns fabricated at different print orientations by using a stereolithography printer.

STATEMENT OF PROBLEM: Stereolithography (SLA) procedures can be chosen for manufacturing definitive crowns; however, how the print orientation impacts the trueness and precision of the intaglio surface of the printed definitive restorations is unclear. PURPOSE: The purpose of this in vitro investigation was to calculate the manufacturing accuracy of the intaglio surface of SLA definitive resin-ceramic crowns fabricated at varying print orientations (0, 45, 75, or 90 degrees). MATERIAL AND METHODS: The standard tessellation language (STL) file of an anatomic contour molar crown was obtained and used to fabricate all the crowns by using a definitive resin-ceramic material (Permanent Crown) and an SLA printer (Form 3B+). Four groups were developed depending on the print orientation selected to manufacture the crowns: 0-, 45-, 70-, and 90-degree print orientation (n=30). Each crown specimen was digitized without the use of scanning powder by using a desktop scanner (T710). The crown design file was determined as the reference (control) group and used to calculate the fabricating trueness and precision of the intaglio surface of the specimens using the root mean square (RMS) error computation. Trueness data were examined by using 1-way ANOVA and post hoc pairwise multiple comparison Tukey tests, while precision data were analyzed using the Levene test (α=.05). RESULTS: The mean ±standard deviation RMS error discrepancies ranged from 37 ±3 µm to 113 ±11 µm. One-way ANOVA exposed significant trueness (P<.001) differences among the groups considered in this study. Furthermore, all the print orientation groups tested were different from each other (P<.001). The 0-degree group presented the best trueness value (37 µm), while the 90-degree group obtained the worst trueness value (113 µm). The Levene test exposed significant precision differences among the groups assessed (P<.001). The 0-degree group had a significantly lower standard deviation (higher precision) (3 µm) than the other groups, with no difference among the other groups tested (P>.05). CONCLUSIONS: The fabricating trueness and precision of the intaglio surface of the SLA resin-ceramic crowns was impacted by the varying print orientations assessed.

Influence of print orientation on the intaglio surface accuracy (trueness and precision) of tilting stereolithography definitive resin-ceramic crowns.

STATEMENT OF PROBLEM: Vat-polymerization tilting stereolithography (TSLA) technology can be selected for fabricating definitive crowns; however, how the printing variables, including print orientation, influence its manufacturing accuracy remains unclear. PURPOSE: The purpose of this in vitro study was to assess the influence of different print orientations (0, 45, 75, or 90 degrees) on the intaglio surface accuracy (trueness and precision) of TSLA definitive resin-ceramic crowns. MATERIAL AND METHODS: The virtual design of an anatomic contour molar crown was obtained in standard tessellation language (STL) file format and used to manufacture all the specimens by using a TSLA printer (DFAB Chairside) and a resin-ceramic material (Irix Max Photoshade single-use cartridges). Four groups were created depending on the print orientation used to manufacture the specimens: 0- (Group 0), 45- (Group 45), 70- (Group 75), and 90-degree (Group 90) print orientation (n=30). Each specimen was digitized by using a laboratory scanner (T710) according to the manufacturer's scanning protocol. The reference STL file was used as a control to measure the volumetric discrepancies of the intaglio surface with the digitized specimens by using the root mean square (RMS) error calculation. The trueness data were analyzed by using 1-way ANOVA followed by post hoc pairwise multiple comparison Tukey tests, and precision data were analyzed using the Levene test (α=.05). RESULTS: Significant mean trueness (P<.001) and precision (P<.001) value discrepancies were found among the groups tested. Additionally, all the groups were significantly different from each other (P<.001), except for the 45- and 90-degree groups (P=.868). Group 0 showed the best mean trueness and precision values, while the Group 90 demonstrated the lowest mean trueness and precision values. CONCLUSIONS: The print orientations tested influenced the intaglio surface trueness and precision values of the TSLA definitive resin-ceramic crowns.

Scanning accuracy and scanning area discrepancies of intraoral digital scans acquired at varying scanning distances and angulations among 4 different intraoral scanners.

STATEMENT OF PROBLEM: The accuracy of intraoral scanners (IOSs) can be affected by operator handling; however, the scanning area and accuracy discrepancies acquired at different scanning distances and angulations among IOSs remain uncertain. PURPOSE: The objective of this in vitro study was to compare the scanning area and scanning accuracy of the intraoral digital scans obtained at 3 scanning distances with 4 different scanning angulations among 4 different IOSs. MATERIAL AND METHODS: A reference device (reference file) was designed with 4 inclinations (0, 15, 30, and 45 degrees) and printed. Four groups were created based on the IOS: i700, TRIOS4, CS 3800, and iTero scanners. Four subgroups were generated depending on the scanning angulation (0, 15, 30, and 45 degrees). Each subgroup was divided into 3 subgroups based on the scanning distance: 0, 2, and 4 mm (N=720, n=15). The reference devices were positioned in a z-axis calibrated platform for standardizing the scanning distance. In the i700-0-0 subgroup, the 0-degree reference device was positioned in the calibrated platform. The wand of the IOS was positioned in a supporting framework with a 0-mm scanning distance, and the scans were acquired. In the i700-0-2 subgroup, the platform was lowered for a 2-mm scanning distance followed by the specimen acquisition. In the i700-0-4 subgroup, the platform was further lowered for a 4-mm scanning distance, and the scans were obtained. For the i700-15, i700-30, and i700-45 subgroups, the same procedures were carried out as in the i700-0 subgroups respectively, but with the 10-, 15-, 30-, or 45-degree reference device. Similarly, the same procedures were completed for all the groups with the corresponding IOS. The area of each scan was measured. The reference file was used to measure the discrepancy with the experimental scans by using the root mean square (RMS) error. Three-way ANOVA and post hoc Tukey pairwise comparison tests were used to analyze the scanning area data. Kruskal-Wallis and multiple pairwise comparison tests were used to analyze the RMS data (α=.05). RESULTS: IOS (P<.001), scanning distance (P<.001), and scanning angle (P<.001) were significant factors of the scanning area measured among the subgroups tested. A significant group×subgroup interaction was found (P<.001). The iTero and the TRIOS4 groups obtained higher scanning area mean values than the i700 and CS 3800 groups. The CS 3800 obtained the lowest scanning area among the IOS groups tested. The 0-mm subgroups obtained a significantly lower scanning area than the 2- and 4-mm subgroups (P<.001). The 0- and 30-degree subgroups obtained a significantly lower scanning area than the 15- and 45-degree subgroups (P<.001). The Kruskal-Wallis test revealed significant median RMS discrepancies (P<.001). All the IOS groups were significantly different from each other (P<.001), except for the CS 3800 and TRIOS4 groups (P>.999). All the scanning distance groups were different from each other (P<.001). CONCLUSIONS: Scanning area and scanning accuracy were influenced by the IOS, scanning distance, and scanning angle selected to acquire the digital scans.

Discrepancies in the occlusal devices designed by an experienced dental laboratory technician and by 2 artificial intelligence-based automatic programs.

STATEMENT OF PROBLEM: Artificial intelligence (AI) models have been developed for different applications, including the automatic design of occlusal devices; however, the design discrepancies of an experienced dental laboratory technician and these AI automatic programs remain unknown. PURPOSE: The purpose of this in vitro study was to compare the overall, intaglio, and occlusal surface discrepancies of the occlusal device designs completed by an experienced dental laboratory technician and two AI automatic design programs. MATERIAL AND METHODS: Virtually articulated maxillary and mandibular diagnostic casts were obtained in a standard tessellation language (STL) file format. Three groups were created depending on the operator or program used to design the occlusal devices: an experienced dental laboratory technician (control group) and two AI programs, namely Medit Splints from Medit (Medit group) and Automate from 3Shape A/S (3Shape group) (n=10). To minimize the discrepancies in the parameter designs among the groups tested, the same printing material and design parameters were selected. In the control group, the dental laboratory technician imported the articulated scans into a dental design program (DentalCAD) and designed a maxillary occlusal device. The occlusal device designs were exported in STL format. In the Medit and 3Shape groups, the diagnostic casts were imported into the respective AI programs. The AI programs automatically designed the occlusal device without any further operator intervention. The occlusal device designs were exported in STL format. Among the 10 occlusal designs of the control group, a random design (shuffle deck of cards) was used as a reference file to calculate the overall, intaglio, and occlusal discrepancies in the specimens of the AI groups by using a program (Medit Design). The root mean square (RMS) error was calculated. Kruskal-Wallis, and post hoc Dwass-Steel-Critchlow-Fligner pairwise comparison tests were used to analyze the trueness of the data. The Levene test was used to assess the precision data (α=.05). RESULTS: Significant overall (P<.001), intaglio (P<.001), and occlusal RMS median value (P<.001) discrepancies were found among the groups. Significant overall RMS median discrepancies were observed between the control and the Medit groups (P<.001) and the control and 3Shape groups (P<.001). Additionally, significant intaglio RMS median discrepancies were found between the control and the Medit groups (P<.001), the Medit and 3Shape groups (P<.001), and the control and 3Shape groups (P=.008). Lastly, significant occlusal RMS median discrepancies were found between the control and the 3Shape groups (P<.001) and the Medit and 3Shape groups (P<.001). The AI-based software programs tested were able to automatically design occlusal devices with less than a 100-µm trueness discrepancy compared with the dental laboratory technician. The Levene test revealed significant overall (P<.001), intaglio (P<.001), and occlusal (P<.001) precision among the groups tested. CONCLUSIONS: The use of a dental laboratory technique influenced the overall, intaglio, and occlusal trueness of the occlusal device designs obtained. No differences were observed in the precision of occlusal device designs acquired among the groups tested.

Differences in maxillomandibular relationship recorded at centric relation when using a conventional method, four intraoral scanners, and a jaw tracking system: A clinical study.

STATEMENT OF PROBLEM: Digital systems including intraoral scanners (IOSs) and optical jaw tracking systems can be used to acquire the maxillomandibular relationship at the centric relation (CR). However, the discrepancy of the maxillomandibular relationship recorded at the CR position when using digital methods remains uncertain. PURPOSE: The purpose of this clinical study was to compare the accuracy of the maxillomandibular relationship recorded at the CR position using a conventional procedure, 4 different IOSs, and an optical jaw tracking system. MATERIAL AND METHODS: A completely dentate volunteer was selected. A Kois deprogrammer (KD) was fabricated. Six groups were created based on the technique used to obtain diagnostic casts and record the maxillomandibular relationship at the CR position: conventional procedures (CNV group), 4 IOS groups: TRIOS4 (TRIOS4 group), iTero Element 5D (iTero group), i700 wireless (i700 group), Primescan (Primescan group), and a jaw tracking system (Modjaw) (Modjaw group) (n=10). In the CNV group, conventional diagnostic stone casts were obtained. A facebow record was used to mount the maxillary cast on an articulator (Panadent). The KD was used to obtain a CR record for mounting the mandibular cast, and the mounted casts were digitized by using a scanner (T710) to acquire the reference scans. In the TRIOS group, intraoral scans were obtained and duplicated 10 times. The KD was used to obtain a bilateral virtual occlusal record at the CR position. To acquire the specimens of the iTero, i700, and Primescan groups, the procedures in the TRIOS4 group were followed, but with the corresponding IOS. In the Modjaw group, the KD was used to record and export the maxillomandibular relationship at the CR position. Articulated virtual casts of each group were exported. Thirty-six interlandmark linear measurements were computed on both the reference and experimental scans. The distances obtained on the reference scan were used to calculate the discrepancies with the distances obtained on each experimental scan. The data were analyzed by using 1-way ANOVA followed by the pairwise comparison Tukey tests (α=.05). RESULTS: The trueness and precision of the maxillomandibular relationship record were significantly affected by the technique used (P<.001). The maxillomandibular relationship trueness values from high to low were iTero (0.14 ±0.09 mm), followed by the Modjaw (0.20 ±0.04 mm) and the TRIOS4 (0.22 ±0.09 mm) groups. However, the iTero, Modjaw, and TRIOS4 groups were not significantly different from each other (P>.05). The i700 group obtained the lowest trueness and precision values (0.40 ±0.22 mm) of all groups tested, followed by the Primescan grop (0.26±0.13 mm); however, the i700 and Primescan groups had significantly lower trueness and precision than only the iTero group (P<.05). CONCLUSIONS: The trueness and precision of the maxillomandibular relationship recorded at the CR position were influenced by the different digital techniques tested.

Influence of ambient temperature changes on intraoral scanning accuracy.

STATEMENT OF PROBLEM: Different variables that decrease the accuracy of intraoral scanners (IOSs) have been identified. Ambient temperature changes can occur in the dental environment, but the impact of ambient temperature changes on intraoral scanning accuracy is unknown. PURPOSE: The purpose of this in vitro study was to assess the impact of ambient temperature changes on the accuracy (trueness and precision) of an IOS. MATERIAL AND METHODS: A complete arch maxillary dentate Type IV stone cast was obtained. Four 6-mm-diameter gauge balls were added to the maxillary cast to aid future evaluation measurements. The maxillary cast was digitized by using an industrial scanner (GOM Atos Q 3D 12M). The manufacturer's recommendations were followed in obtaining a reference scan. Then, the maxillary cast was digitized by using an IOS (TRIOS 4) according to the scanning protocol recommended by the manufacturer. Four groups were created depending on the ambient temperature change assessed: 24 °C or room temperature (24-D or control group), 19 °C or a 5-degree temperature drop (19-D group), 15 °C or a 9-degree temperature drop (15-D group), and 29 °C or a 5-degree temperature rise (29-D group). The Shapiro-Wilk and Kolmogorov-Smirnov tests revealed that the data were not normally distributed (P<.05). For trueness, the nonparametric Kruskal-Wallis followed by the Dwass-Steel-Critchlow-Fligner pairwise comparison tests were used. Precision analysis was obtained by using the Levene test based on the comparison of the standard deviations of the 4 groups with 95% Bonferroni confidence intervals for standard deviations (α=.05). RESULTS: The Kruskal-Wallis test revealed significant differences in the trueness values among all 4 groups (P<.001). Furthermore, significant differences between the linear discrepancy medians between the control and 19-D groups (P<.001), control and 15-D groups (P=.002), control and 29-D groups (P<.001), 19-D and 29-D groups (P=.003), and 15-D and 29-D groups (P<.001) were found. The Levene test for the comparison of the variances among the 4 groups did not detect a significant difference (P>.999), indicating that precision wise the 4 groups were not significantly different from each other. CONCLUSIONS: Ambient temperature changes had a detrimental effect on the accuracy (trueness and precision) of the IOS tested. Ambient temperature changes significantly decreased the scanning accuracy of the IOS system tested. Increasing the ambient temperature has a greater influence on the intraoral scanning accuracy of the IOS selected when compared with decreasing the ambient temperature.

Artificial intelligence models for diagnosing gingivitis and periodontal disease: A systematic review.

STATEMENT OF PROBLEM: Artificial intelligence (AI) models have been developed for periodontal applications, including diagnosing gingivitis and periodontal disease, but their accuracy and maturity of the technology remain unclear. PURPOSE: The purpose of this systematic review was to evaluate the performance of the AI models for detecting dental plaque and diagnosing gingivitis and periodontal disease. MATERIAL AND METHODS: A review was performed in 4 databases: MEDLINE/PubMed, World of Science, Cochrane, and Scopus. A manual search was also conducted. Studies were classified into 4 groups: detecting dental plaque, diagnosis of gingivitis, diagnosis of periodontal disease from intraoral images, and diagnosis of alveolar bone loss from periapical, bitewing, and panoramic radiographs. Two investigators evaluated the studies independently by applying the Joanna Briggs Institute critical appraisal. A third examiner was consulted to resolve any lack of consensus. RESULTS: Twenty-four articles were included: 2 studies developed AI models for detecting plaque, resulting in accuracy ranging from 73.6% to 99%; 7 studies assessed the ability to diagnose gingivitis from intraoral photographs reporting an accuracy between 74% and 78.20%; 1 study used fluorescent intraoral images to diagnose gingivitis reporting 67.7% to 73.72% accuracy; 3 studies assessed the ability to diagnose periodontal disease from intraoral photographs with an accuracy between 47% and 81%, and 11 studies evaluated the performance of AI models for detecting alveolar bone loss from radiographic images reporting an accuracy between 73.4% and 99%. CONCLUSIONS: AI models for periodontology applications are still in development but might provide a powerful diagnostic tool.