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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.
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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.
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OBJECTIVES: To describe a new classification for intraoral scans based on the scan extension and to introduce a decision guideline to choose the scan extension for fabricating tooth- and implant-supported fixed dental prostheses (FDPs). OVERVIEW: Multiple operator- and patient-related factors have been identified that can decrease the scanning accuracy of intraoral scanners (IOSs), including scan extension. However, the decision criteria for selecting scan extension for fabricating tooth- and implant-supported restorations is unclear. Based on the extension of the intraoral digital scans, three types of scans can be defined: half-arch (anterior or posterior), extended half-arch, and complete-arch scan. Variables to consider when choosing the scan extension include the number and location of units being restored, as well as the extension and location of edentulous areas. Additionally, the accuracy of the virtual definitive cast and the accuracy of the maxillomandibular relationship captured by using IOSs should be differentiated. CONCLUSIONS: A decision tree for selecting the scan extension is presented. The decision is based on the number and location of units being restored, and the extension and location of edentulous areas. Intraoral scans with reduced scan extension are indicated when fabricating tooth- and implant-supported crowns or short-span fixed prostheses, when the patient does not have more than one missing tooth in the area of the dental arch included in the scan. For the remaining clinical conditions, complete-arch intraoral scans are recommended. CLINICAL SIGNIFICANCE: Scan extension is a clinician's decision that should be based on the number and location of units being restored and the extension and location of edentulous areas. Intraoral scans with a reduced scan extension is recommended, when possible.
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Implantes Dentales , Boca Edéntula , Humanos , Modelos Dentales , Técnica de Impresión Dental , Imagenología Tridimensional , Diseño Asistido por ComputadoraRESUMEN
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.
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The reverse impression method involves the extraoral digitalization of the interim implant-supported prostheses and intraoral digitalization of antagonist arch and maxillomandibular relationship. This technique allows the fabrication of implant-supported prostheses by using a complete-digital workflow. The scan analogs make the reverse impression method feasible. However, this method may not be recommended if the interim polymethyl methacrylate prosthesis does not have passive fit. The present manuscript describes an altered reverse impression technique that involves the extraoral digitalization of a conventional verification jig, which has attached scan analogs. With this technique modification, the implant positions captured using the verification jig are used to obtain the virtual definitive implant cast and fabricate the definitive implant-supported prosthesis.
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Implantes Dentales , Flujo de Trabajo , Técnica de Impresión Dental , Prótesis Dental de Soporte Implantado/métodos , Diseño Asistido por ComputadoraRESUMEN
OBJECTIVE: Immediate implants and immediate alveolar sealing have been a widely utilized treatment with high predictability and biological advantages. The improvement in technology has made it possible to simplify clinical processes. The aim of the present report was to describe the complete digital workflow of the Biologically oriented preparation technique for immediate posterior implant, immediate provisionalization and fabrication of definitive implant crowns. CLINICAL CONSIDERATIONS: The surgical process and prosthetic management to preserve the gingival contours of the extracted natural tooth during immediate implant placement and provisionalization are described. Additionally, during the same clinical intervention, the definitive intraoral digital implant scans for capturing the implant position, peri-implant tissue contours, adjacent and antagonist dentition, and profile emergence of the interim implant crown are captured for the fabrication of the definitive crown. CONCLUSIONS: Based on the technique described, the immediate implant placement and provisionalization in the posterior area provides biological and clinical advantages, reducing the number of abutment-implant disconnections and the number of clinical appointments, as well as increases patient comfort. CLINICAL SIGNIFICANCE: The present article describes a technique for an immediate implant placement and provisionalization in the posterior region for maintaining the gingival architecture of the extracted tooth. During the same appointment, the implant position, peri-implant tissue contours, and adjacent and antagonist dentition, and profile emergence of the interim implant crown are captured by using an intraoral scanner and used for the fabrication of the definitive crown. This technique aims to reduce the number of abutment-implant disconnections and clinical appointments.
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Implantes Dentales de Diente Único , Humanos , Flujo de Trabajo , Coronas , Corona del Diente , Implantación Dental Endoósea/métodosRESUMEN
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.
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OBJECTIVE: Complete arch implant rehabilitation necessitates meticulous treatment planning and high-level collaboration between surgical and prosthetic dental teams. Emerging virtual technologies hold considerable promise in streamlining this process. The aim of this article is to extend recommendations to clinicians venturing into the virtual patient-assisted esthetic implant rehabilitation workflow. OVERVIEW: This article summarizes recommendations for virtual patient-assisted esthetic implant rehabilitation in the following five aspects: three-dimensional data handling and superimposition, occlusion and virtual articulator integration in creating virtual patients, streamlined face- and prosthetic-driven surgical planning, reuse of presurgical data ("Copy & Paste"), and final impression for passive fitting of final restoration. To illustrate these principles, a case with complete-mouth implant rehabilitation completed within six visits using this virtual patient workflow is presented. CONCLUSION: The virtual patient workflow serves as an invaluable tool to perform treatment planning, enhance efficiency, and ensure predictable outcomes in esthetic complete arch implant rehabilitation. CLINICAL SIGNIFICANCE: Virtual workflows are increasingly prevalent in esthetic implant rehabilitation. Nevertheless, these workflows necessitate a distinct set of knowledge and tools divergent from conventional dentistry practices. This article offers guidelines and recommendations for dental clinicians who are new to this field.
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Diseño Asistido por Computadora , Implantes Dentales , Humanos , Prótesis Dental de Soporte Implantado/métodos , Estética Dental , Flujo de TrabajoRESUMEN
OBJECTIVE: The present manuscript describes a technique to virtually switch an implant scan body eliminating the need of obtaining a new intraoral implant digital scan. CLINICAL CONSIDERATIONS: Implant scan bodies assist on transferring the 3-dimensional position of the implants into the virtual definitive implant cast. However, if a different implant part is desired during the designing procedures of the implant restoration such as selecting a different implant abutment of varying height, angulation, or manufacturer, a new intraoral implant digital scan with the specific implant scan body is required. CONCLUSIONS: This novel protocol aims to reduce possible complications that require capturing a new intraoral implant digital scan, facilitate prostheses design modifications after the obtention of the definitive intraoral implant digital scan, and to ease the manufacturing procedures. CLINICAL SIGNIFICANCE: The novel technique may provide a solution for virtually switch implant scan bodies for fabricating implant-supported single crowns or short-span prostheses. Additional studies are needed before its clinical implementation.
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Diseño Asistido por Computadora , Implantes Dentales , Coronas , Técnica de Impresión Dental , Imagenología TridimensionalRESUMEN
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.
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Inteligencia Artificial , Ortodoncistas , Humanos , Reproducibilidad de los Resultados , CefalometríaRESUMEN
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.
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Different reference planes can be used to transfer the maxillary cast into the analog articulator, including the true horizontal or gravity reference plane. Different techniques have been described to record the gravity reference plane for transferring the maxillary scan into the virtual articulator by using facial scanning techniques. However, these digital facebow procedures require the use of an extraoral scan body system, printed reference device, or orientation reference board. This manuscript describes a technique for recording the gravity reference plane by using a facial scanner without the use of an additional device. This technique aims to reduce the clinical time needed to capture a patient's digital data and minimize the laboratory time needed to integrate the virtual patient and transfer the maxillary scan into the virtual articulator.
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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.
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Intraoral scanners (IOSs) are digital data acquisition technologies that ease the recording of virtual diagnostic casts. Some IOSs have a specific software tool to assess volumetric changes between 2 scans acquired on the patient at different times. The scans are superimposed and volumetric differences between both meshes are reported. However, these software tools may be limited to scans captured only by the IOS of the same manufacturer. The present manuscript describes a protocol for comparing volumetric changes between 2 scans recorded using any IOS. Additionally, 1 of the scans is divided into 3 sections to minimize the alignment distortion and maximize the evaluation of the volumetric changes.
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Optical jaw tracking systems are designed to record the static maxillomandibular relationship and the mandibular motion of a patient, including excursive movements and mastication pattern. This digital data acquisition technology can be integrated into diagnostic and treatment planning procedures, as well as into designing dental prostheses. A step-by-step protocol to record a patient's digital data, including the repeatable reference position of the jaw or centric relation, by using an intraoral scanner, Kois deprogrammer, and optical jaw tracking system is described. The data are then processed in the software program of the jaw tracking system to locate centric occlusion.
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Patients with aberrant occlusal patterns, including constricted mastication patterns or occlusal dysfunction, may require occlusal equilibration. Conventional diagnostic procedures involve diagnostic stone casts mounted in the articulator. During diagnostic procedures, occlusal equilibration methods are simulated on mounted stone casts to analyze the amount of dental structure that may need to be removed. A technique to virtually simulate an occlusal equilibration procedure is described. Digital data acquisition procedures include diagnostic casts acquired using an intraoral scanner and the repeatable reference position of the mandible or centric relation, excursive movements, and the mastication pattern captured using an optical jaw tracking system. The jaw tracker and dental design programs are used to simulate the occlusal equilibration.
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Jaw tracking systems can record mandibular movement such as the repeatable reference position and excursive movements of the mandible. A technique for integrating the recorded repeatable reference position of the mandible and excursive movements captured using an optical jaw tracking system into the design procedures of an occlusal device is described. The mandibular motion of the patient is directly used to design the occlusal device, replacing the virtual articulator. The described technique aims to reduce the delivery time by incorporating the recorded motion of the patient into the virtual design of the occlusal device.
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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.
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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.
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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.