Effect of 3D printer, implant analog system, and implant angulation on the accuracy of analog position in implant casts.

OBJECTIVES: To evaluate the accumulative effect of 3D printer, implant analog systems, and implant angulation on the accuracy of analog position in implant casts. METHODS: A reference cast, presenting a case of a three-unit implant-supported prosthesis, was scanned with a coordinate measurement machine, producing the first reference data set (CMM, n = 1). The second reference data set (n = 10) was prepared using an intraoral scanner (IOS) (Trios4). Test quadrant casts were produced using three DLP type 3D printers, Max (MAX UV385), Pro (PRO 4K65 UV), and Nex (NextDent 5100), and three implant analog systems, El (Elos), Nt (Nt-trading), and St (Straumann) (n = 90). Stone casts were also produced via analog impressions (Stone, n = 10). After digitization, the accuracy of 3D distance, local angulation (angle between implants) and global angulation (angle between the implant center axis and an axis perpendicular to the global plane) was evaluated by comparing the reference (CMM, IOS), test (3D print), and control (Stone) groups using metrology software. Data were statistically analyzed using three-way ANOVA and Tukey`s tests (α=0.05). RESULTS: IOS was truer in 3D implant distance and more precise in capturing local angulation than Stone (p ≤ 0.05). Other measurements were similar between both groups (p > 0.05). The amount of error introduced in the workflow by IOS and 3D printing was mostly similar (p > 0.05). 3D printed casts had similar or even higher accuracy than Stone group (p > 0.05). In most cases, higher trueness was achieved when using PRO 4K65 UV 3D printer and Elos implant analog system (p ≤ 0.05). CONCLUSION: 3D printer, implant analog system, and implant angulation have a significant effect on the accuracy of analog position in implant casts. Limited-span implant-supported cases could be reproduced digitally with similar accuracy as conventional methods. CLINICAL SIGNIFICANCE: A fully digital workflow with a carefully selected 3D printer and implant analog system can increase the accuracy of digitally produced implant casts with comparable accuracy to conventional workflow.

Locating centric occlusion by using intraoral scanners and open access or dental computer-aided design programs: A dental technique.

When using conventional methods, centric occlusion (CO) can be determined on conventional gypsum casts that are mounted in an analog articulator at centric relation (CR). In the digital environment, intraoral scanners (IOSs) can be used to record maxillary and mandibular scans articulated in CR. However, a digital protocol to locate the CO on articulated intraoral digital scans at CR by using computer-aided design (CAD) programs is needed. The present manuscript describes a straightforward technique to record CR by combining an IOS and a Kois deprogrammer. Afterwards, the acquired digital data are imported into a CAD program to locate CO. The technique includes a complete digital protocol to locate CO by using 3 different CAD programs: open-access non-dental, open-access dental, and dental CAD program.

Accuracy of artificial intelligence-based segmentation of the mandibular canal in CBCT.

OBJECTIVES: To investigate the accuracy of artificial intelligence (AI)-based segmentation of the mandibular canal, compared to the conventional manual tracing, implementing implant planning software. MATERIALS AND METHODS: Localization of the mandibular canals was performed for 104 randomly selected patients. A localization was performed by three experienced clinicians in order to serve as control. Five tracings were performed: One from a clinician with a moderate experience with a manual tracing (I1), followed by the implementation of an automatic refinement (I2), one manual from a dental student (S1), and one from the experienced clinician, followed by an automatic refinement (E). Subsequently, two fully automatic AI-driven segmentations were performed (A1,A2). The accuracy between each method was measured using root mean square error calculation. RESULTS: The discrepancy among the models of the mandibular canals, between the experienced clinicians and each investigated method ranged from 0.21 to 7.65 mm with a mean of 3.5 mm RMS error. The analysis of each separate mandibular canal's section revealed that mean RMS error was higher in the posterior and anterior loop compared to the middle section. Regarding time efficiency, tracing by experienced users required more time compared to AI-driven segmentation. CONCLUSIONS: The experience of the clinician had a significant influence on the accuracy of mandibular canal's localization. An AI-driven segmentation of the mandibular canal constitutes a time-efficient and reliable procedure for pre-operative implant planning. Nevertheless, AI-based segmentation results should always be verified, as a subsequent manual refinement of the initial segmentation may be required to avoid clinical significant errors.

Accuracy of manual and artificial intelligence-based superimposition of cone-beam computed tomography with digital scan data, utilizing an implant planning software: A randomized clinical study.

OBJECTIVES: To investigate the accuracy of conventional and automatic artificial intelligence (AI)-based registration of cone-beam computed tomography (CBCT) with intraoral scans and to evaluate the impact of user's experience, restoration artifact, number of missing teeth, and free-ended edentulous area. MATERIALS AND METHODS: Three initial registrations were performed for each of the 150 randomly selected patients, in an implant planning software: one from an experienced user, one from an inexperienced operator, and one from a randomly selected post-graduate student of implant dentistry. Six more registrations were performed for each dataset by the experienced clinician: implementing a manual or an automatic refinement, selecting 3 small or 3 large in-diameter surface areas and using multiple small or multiple large in-diameter surface areas. Finally, an automatic AI-driven registration was performed, using the AI tools that were integrated into the utilized implant planning software. The accuracy between each type of registration was measured using linear measurements between anatomical landmarks in metrology software. RESULTS: Fully automatic-based AI registration was not significantly different from the conventional methods tested for patients without restorations. In the presence of multiple restoration artifacts, user's experience was important for an accurate registration. Registrations' accuracy was affected by the number of free-ended edentulous areas, but not by the absolute number of missing teeth (p < .0083). CONCLUSIONS: In the absence of imaging artifacts, automated AI-based registration of CBCT data and model scan data can be as accurate as conventional superimposition methods. The number and size of selected superimposition areas should be individually chosen depending on each clinical situation.

Influence of the Manufacturing Trinomial (Technology, Printer, and Material) on the Marginal and Internal Discrepancies of Printed Metal Frameworks for the Fabrication of Tooth-Supported Prostheses: A Systematic Review and Meta-analysis.

PURPOSE: The purpose of this systematic review and meta-analysis was to compare the influence of fabrication method (conventional, subtractive, and additive procedures) and manufacturing trinomial (technology, printer, and material combination) on the marginal and internal fit of cobaltchromium (Co-Cr) tooth-supported frameworks. MATERIALS AND METHODS: An electronic systematic review was performed in five data bases: MEDLINE/PubMed, Embase, World of Science, Cochrane, and Scopus. Studies that reported the marginal and internal discrepancies of tooth-supported Co-Cr additive manufacturing (AM) frameworks were included. Two authors independently completed the quality assessment of the studies by applying the Joanna Briggs Institute Critical Appraisal Checklist for Quasi-Experimental Studies. A third examiner was consulted to resolve lack of consensus. RESULTS: A total of 31 articles were included and classified based on the evaluation method: manufacturing accuracy, the dual- or triple-scan method, stereomicroscope, optical coordinate measurement machine, microCT, profilometer, and silicone replica. Six subgroups were created: 3D Systems, Bego, Concept Laser, EOS, Kulzer, and Sisma. Due to the heterogeneity and limited data available, only the silicone replica group was considered for meta-analysis. The metaanalysis showed a mean marginal discrepancy of 91.09 µm (I2 = 95%, P < .001) in the conventional group, 77.48 µm (I2 = 99%, P < .001) in the milling group, and 82.92 µm (I2 = 98%, P < .001) in the printing group. Additionally, a mean internal discrepancy of 111.29 µm (I2 = 94%, P < .001) was obtained in the conventional casting group, 121.96 µm (I2 = 100%, P < .001) in the milling group, and 121.25 µm (I2 = 99%, P < .001) in the printing group. CONCLUSIONS: Manufacturing method and selective laser melting (SLM) metal manufacturing trinomial did not impact the marginal and internal discrepancies of Co-Cr frameworks for the fabrication of tooth-supported restorations.

An overview of artificial intelligence based applications for assisting digital data acquisition and implant planning procedures.

OBJECTIVES: To provide an overview of the current artificial intelligence (AI) based applications for assisting digital data acquisition and implant planning procedures. OVERVIEW: A review of the main AI-based applications integrated into digital data acquisitions technologies (facial scanners (FS), intraoral scanners (IOSs), cone beam computed tomography (CBCT) devices, and jaw trackers) and computer-aided static implant planning programs are provided. CONCLUSIONS: The main AI-based application integrated in some FS's programs involves the automatic alignment of facial and intraoral scans for virtual patient integration. The AI-based applications integrated into IOSs programs include scan cleaning, assist scanning, and automatic alignment between the implant scan body with its corresponding CAD object while scanning. The more frequently AI-based applications integrated into the programs of CBCT units involve positioning assistant, noise and artifacts reduction, structures identification and segmentation, airway analysis, and alignment of facial, intraoral, and CBCT scans. Some computer-aided static implant planning programs include patient's digital files, identification, labeling, and segmentation of anatomical structures, mandibular nerve tracing, automatic implant placement, and surgical implant guide design.

Trueness of maxillomandibular relationship in 3D-printed and conventional casts.

OBJECTIVES: To compare the trueness of maxillomandibular relationship between articulated 3D-printed and conventional diagnostic casts in maximum intercuspation (MIP). METHODS: Reference casts were articulated in MIP, and scanned using a Coordinate Measurement Machine (CMM, n = 1). Digital scans were made from the reference casts by using an intraoral scanner (IOS, n = 10) (Trios 4; 3Shape A/S). IOS scans were processed to create 3D-printed casts by using MAX UV385 (Asiga) and NextDent 5100 (3DSystems) 3D-printers. The conventional workflow implemented vinylpolysiloxane (VPS) impressions and Type IV stone. Stone and 3D-printed casts were articulated and digitized with a laboratory scanner (E4; 3Shape A/S). The 3D-printed casts were scanned on two occasions: with and without positioning pins. Inter-arch distances and 3D-contact area were measured and compared. Statistical tests used were Shapiro-Wilk, Levene's, Welch's t-test, and 2-way ANOVA (α=0.05). RESULTS: IOS group showed similar or better maxillomandibular relationship trueness than stone casts and 3D-printed casts (p < 0.05). 3D-contact area analysis showed similar deviations between 3D-printed and stone casts (p > 0.05). The choice of 3D-printer and presence of positioning pins on the casts significantly influenced maxillomandibular relationship trueness (p < 0.05). CONCLUSIONS: Articulated 3D-printed and stone casts exhibited similar maxillomandibular relationship trueness. CLINICAL SIGNIFICANCE: Although 3D-printing methods can introduce a considerable amount of deviations, the maxillomandibular relationship trueness of articulated 3D-printed and stone casts in MIP can be considered similar.

True horizontal or gravity plane for transferring the maxillary cast into the virtual articulator by using an optical jaw tracking system.

Different techniques of transferring the maxillary cast into the analog semi-adjustable articulator by using the true horizontal or gravity reference plane have been reported. However, procedures are required for recording this reference plane and transferring the maxillary cast into the virtual semi-adjustable articulator. In the present manuscript, a technique is described for registering the true horizontal or gravity plane in relationship to the natural head position of the patient by using an optical jaw tracking system. Additionally, the recorded true horizontal plane is used to transfer the maxillary cast into the virtual semi-adjustable articulator by using a dental computer-aided design program. This technique facilitates the maxillary cast transfer into the virtual articulator by using the true horizontal plane recorded with an optical jaw tracking system, maximizing the functionality of the optical jaw tracking device.

Use of an optical jaw tracking system to capture the envelope of function when designing interim and definitive prostheses: A dental technique.

Jaw tracking systems can record mandibular motion for incorporation into programs used for designing dental prostheses. However, the protocol for data acquisition and design using the recorded mandibular motion is unclear. The envelope of function recorded in a patient with acceptable occlusal function provides important functional information that can be integrated into the design of dental prostheses. A protocol for recording a patient's digital data, including the envelope of function using a jaw tracker, for incorporation into the design procedures and a delivery protocol are described. This technique may simplify the delivery of prostheses by reducing the adjustments needed to the definitive prostheses.

An overview of the different digital facebow methods for transferring the maxillary cast into the virtual articulator.

OBJECTIVES: The purposes of this study were to classify the described digital facebow techniques for transferring the maxillary cast into the semi-adjustable virtual articulator based on the digital data acquisition technology used and to review the reported accuracy values of the different digital facebow methods described. OVERVIEW: Digital data acquisition technologies, including digital photographs, facial scanners, cone beam computed tomography (CBCT) imaging, and jaw tracking systems, can be used to transfer the maxillary cast into the virtual articulator. The reported techniques are reviewed, as well as the reported accuracy values of the different digital facebow methods. CONCLUSIONS: Digital photographs can be used to transfer the maxillary cast into the virtual articulator using the true horizontal reference plane, but limited studies have assessed the accuracy of this method. Facial scanning and CBCT techniques can be used to transfer the maxillary cast into the virtual articulator, in which the most frequently selected references planes are the Frankfort horizontal, axis orbital, and true horizontal planes. Studies analyzing the accuracy of the maxillary cast transfer by using facial scanning and CBCT techniques are restricted. Lastly, optical jaw trackers can be selected for transferring the maxillary cast into the virtual articulator by using the axis orbital or true horizontal planes, yet the accuracy of these systems is unknown. CLINICAL IMPLICATIONS: Digital data acquisition technologies, including digital photographs, facial scanning methods, CBCTs, and optical jaw tracking systems, can be used to transfer the maxillary cast into the virtual articulator. Studies are needed to assess the accuracy of these digital data acquisition technologies for transferring the maxillary cast into the virtual articulator.

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.

Influence of the ambient color lighting on the accuracy of complete arch implant scans recorded by using two intraoral scanners.

STATEMENT OF PROBLEM: The influence of different ambient factors including lighting has been previously studied. However, the influence of ambient color lighting settings on intraoral scanning accuracy remains uncertain. PURPOSE: The purpose of this in vitro study was to assess the influence of ambient color lighting on the accuracy of complete arch implant scans recorded by using 2 intraoral scanners (IOSs). MATERIAL AND METHODS: An edentulous maxillary cast with 6 implant scan bodies was digitized by using a laboratory scanner (DW-7-140) to obtain a reference file. Two groups were created based on the IOS tested: TRIOS 4 (IOS-1) and i700 (IOS-2). Seven subgroups were developed depending on the ambient color lighting (red, green, blue, yellow, cyan, magenta, and white) (n=15). Scanning accuracy was analyzed by using a metrology software program (Geomagic Control X). The Kruskal-Wallis, 1-way ANOVA, and pairwise comparisons were used to analyze the data (α=.05). RESULTS: Significant trueness and precision values were found across the groups (P<.05) and subgroups (P<.05). For IOS-1, blue ambient lighting obtained the best trueness (19.8 ±1.8 µm) (P<.05); in precision, white light (20.8 ±7.3 µm) and blue light (22.1 ±13.5) showed the best results (P<.05). For IOS-2, white light showed the best trueness (51.9 ±16.7 µm); the best precision was obtained under magenta (38.6 ±10.4 µm) and yellow light (52.6 ±24.0 µm) (P<.05). CONCLUSIONS: The optimal ambient color lighting varied between the IOSs assessed. As the best condition for maximizing accuracy was not found, ambient color lighting must be individualized for the IOS system used.

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.

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.

Virtual Implant Planning and Surgical Guide for Single Implant Placement Fabricated from a Digital Diagnostic Cast, 2-dimensional Radiographic Imaging, and an Open-source Program: A Dental Technique.

A technique for virtually planning single implant by combining an intraoral digital scan, an opensource computer-aided design software program, bone sounding, and 2-dimensional radiographic imaging is described. The surgical implant guide is fabricated by using additive manufacturing technologies. Furthermore, the surgical implant guide positioned in the patient's mouth is used to radiographically verify the estimated mesio-distal implant angulation before proceeding with the surgical intervention and modified, if necessary. When a cone bean computed tomography scan is not available, this technique eases implant planning procedures and minimize possible surgical complications.

Effect of Polymerization Unit, Polishing, and Coffee Thermocycling on the Color and Translucency of Additively Manufactured Resins Used for Definitive Prostheses.

PURPOSE: To evaluate the effect of polymerization unit, polishing, and coffee thermocycling on the color and translucency of additively manufactured polyurethane-based resins with different viscosities. In addition, their color behavior was compared with the color of the shade tab throughout the fabrication steps and aging. MATERIALS AND METHODS: Disk-shaped specimens (Ø10 × 2 mm) were fabricated from polyurethane-based resins with different viscosities (Tera Harz TC-80DP and C&B permanent; n = 30 per material). Baseline color coordinates were measured after cleaning. The specimens in each resin group were divided into three subgroups (n = 10 per subgroup) to be polymerized with different polymerization units (Otoflash G171 [FLN], Wash and Cure 2.0 [CLED1], and P Cure [CLED2]), polished, and subjected to coffee thermocycling. Color coordinates were remeasured after each process. Color differences (ΔE00) and relative translucency parameter (RTP) values were calculated. Data were statistically analyzed (α = .05). RESULTS: Time points and polymerization units affected the ΔE00 for each material (P ≤ .049). ΔE00 of each polymerization unit pair had significant differences within and among different time points within each material (P ≤ .024). ΔE00 (when compared with the shade tab) and RTP were mostly affected by polymerization units and time points within both materials (P ≤ .042). CONCLUSIONS: Tested polymerization units, polishing, and coffee thermocycling affected the color difference and translucency of tested resins. Color differences ranged from moderately unacceptable to extremely unacceptable, and the differences in translucency values mostly ranged from perceptible to unacceptable, according to previous thresholds. In addition, tested resin-polymerization unit pairs had unacceptable color differences when compared to the shade tab. CLED1 may enable higher color stability for tested resins.

Effect of Hydrothermal Aging on the Flexural Strength and Microhardness of Materials Used for Additive or Subtractive Manufacturing of Definitive Restorations.

PURPOSE: To evaluate the flexural strength (FS) and microhardness of various CAD/CAM restorative materials intended for definitive use. The effect of hydrothermal aging on the mechanical properties of these materials was also investigated. MATERIALS AND METHODS: A total of 210 bar-shaped specimens (17 × 4 × 1.5 mm ± 0.02 mm) were fabricated via either subtractive manufacturing (SM) methods-reinforced composite resin (SM-CR), polymer-infiltrated ceramic network (SM-PICN), fine-structured feldspathic ceramic (SMFC), nanographene-reinforced polymethyl methacrylate (PMMA; SM-GPMMA), PMMAbased resin (SM-PMMA)-or additive manufacturing (AM) methods with urethane acrylate-based resins (AM-UA1 and AM-UA2). Specimens were then divided into two subgroups (nonaged or hydrothermal aging; n = 15). A three-point flexural strength test was performed, and five specimens from the nonaged group were submitted to microhardness testing. Specimens were subjected to 10,000 thermal cycles, and the measurements were repeated. RESULTS: Regardless of aging, SM-CR had the highest FS (P < .001), followed by SM-GPMMA (P ≤ .042). In nonaged groups, AM-UA2 had a lower FS than all other materials except SM-FC (P = 1.000). In hydrothermal aging groups, AM specimens had lower FS values than other materials, except SM-PMMA. With regard to microhardness, there was no significant difference found between any of the tested materials (P ≥ .945) in the nonaged and hydrothermal aging groups. CONCLUSIONS: The effect of hydrothermal aging on FS varied depending on the type of restorative material. Regardless of aging condition, SM-CR showed the highest FS values, whereas SM-FC had the highest microhardness. Hydrothermal aging had no significant influence on the microhardness of the tested materials.

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.

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.