The aim of the study was to evaluate antagonist enamel wear caused by posterior monolithic zirconia crowns, and the wear of contralateral enamel/enamel tooth pairs over a 36-month observation period. Out of thirty-two patients, each provided with one 5 mol

Orbital exenteration (exenteratio orbitae) is a disfiguring procedure performed with tumor resection. Rapid realization of an implant-retained craniofacial prosthesis with a secure fit for an active life is essential to restore quality of life. Osseointegrated implants are commonly used for maxillofacial rehabilitation. The precise positioning of these implants is more difficult in cases of reduced bone availability, but it enables anaplastologists to achieve an unobtrusive restoration. After computed tomography (CT) scans of 13 cadaver heads, 104 craniomaxillofacial (CMF) implants were digitally planned. Using a split-face study design, one periorbital side was treated with customized surgical guides and one side was operated freehand. The digital evaluation of position, axis, and insertion depth compared to the digital planning was conducted for 78 periorbital implants using digital evaluation of a postoperative CT scan to measure the linear and angular deviation from preoperative planning. The linear deviation in 3D (p = 0.0105), drilling depth (p = 0.0013), and angular deviation (p = 0.0004) were significantly greater in the freehand group than in the guided computer-assisted implant surgery (CAIS) group. Digital planning enables the available bone support to be preoperatively estimated. CAIS with surgical guides offers significantly more accurate results for CMF implant placement than a freehand transfer of digital planning. Guided CAIS requires a larger surgical approach and therefore fails to achieve the goal of a minimally invasive technique.

The free fibular flap (FFF) is a standard procedure for the oral rehabilitation of segmental bone defects in the mandible caused by diseases such as malignant processes, osteonecrosis, or trauma. Digital guides and computer-assisted surgery (CAS) can improve precision and reduce the time and cost of surgery. This study evaluates how different designs of slot cutting guides, guiding heights, and cutting instruments affect surgical accuracy during mandibular reconstruction. Ninety model operations in a three-part fibular transplant for mandibular reconstruction were conducted according to digital planning with three guide designs (standard, flange, and anatomical slots), three guide heights (1 mm, 2 mm, 3 mm), and two osteotomy instruments (piezoelectric instrument and saw). The cut segments were digitized using computed tomography and digitally evaluated to assess surgical accuracy. For vestibular and lingual segment length, the anatomical slot and the flange appear to be the most accurate, with the flange slightly under-contoured vestibularly and the standard slot over-contoured lingually and vestibularly (p < 0.001). There were only minor differences between the use of saw and piezoelectric instrument for lingual (p = 0.005) and vestibular (p < 0.001) length and proximal angle (p = 0.014). The U-distance after global reconstruction for flanges resulted in a median deviation of 0.0468 mm (IQR 8.15), but was not significant (p = 0.067). Anatomical slots and flanges are recommended for osteotomy, with guiding effects relying on both haptic and visual control. Unilateral guided flanges also work accurately at high guidance heights. The results of piezoelectric instrument (PI) and saw showed comparable results in the assessment of individual segments and U-reconstruction in this in vitro study without soft tissue, so that the final decision is left to the expertise of the surgeons.

Mandibular reconstruction following continuity resection due to tumor ablation or osteonecrosis remains a significant challenge in maxillofacial surgery. Virtual surgical planning (VSP) relies on accurate segmentation of the mandible, yet existing AI models typically include teeth, making them unsuitable for planning of autologous transplants dimensions aiming for reconstructing edentulous mandibles optimized for dental implant insertion. This study investigates the feasibility of using deep learning-based segmentation to generate anatomically valid, toothless mandibles from dentate CT scans, ensuring geometric accuracy for reconstructive planning. A two-stage convolutional neural network (CNN) approach was employed to segment mandibles from computed tomography (CT) data. The dataset (n = 246) included dentate, partially dentate, and edentulous mandibles. Ground truth segmentations were manually modified to create Class III (moderate alveolar atrophy) and Class V (severe atrophy) models, representing different degrees of post-extraction bone resorption. The AI models were trained on the original (O), Class III (Cl. III), and Class V (Cl. V) datasets, and performance was evaluated using Dice similarity coefficients (DSC), average surface distance, and automatically detected anatomical curvatures. AI-generated segmentations demonstrated high anatomical accuracy across all models, with mean DSCs exceeding 0.94. Accuracy was highest in edentulous mandibles (DSC 0.96 ± 0.014) and slightly lower in fully dentate cases, particularly for Class V modifications (DSC 0.936 ± 0.030). The caudolateral curve remained consistent, confirming that baseline mandibular geometry was preserved despite alveolar ridge modifications. This study confirms that AI-driven segmentation can generate anatomically valid edentulous mandibles from dentate CT scans with high accuracy. The innovation of the work is the precise adaptation of alveolar ridge geometry, making it a valuable tool for patient-specific virtual surgical planning in mandibular reconstruction.

Presurgical infant orthopedics (PSIO) is the first step in the treatment of cleft lip and palate (CLP) and is designed to approximate the cleft segments as effectively as possible before surgical reconstruction of the lip and palate. The biomechanical efficacy of different PSIO approaches in transferring molding forces to the CLP is unknown. This study aimed to define the biomechanical principles of competing PSIO techniques in a real cleft finite element (FE) model. Active intraoral (Latham), passive alveolar molding (PAM), and extraoral (DynaCleft) molding forces were virtually applied to a real cleft FE model. In the cleft region, PAM (P < 0.001) and Latham (P < 0.05) exerted significantly less stress than DynaCleft. Intraoral molding forces acted primarily at the site of the force initiation without being accompanied by high loads in the midface. PAM showed a tendency toward a better flow behavior of the molding forces than Latham. Extraoral molding transferred high stresses to the cleft, alveolar ridge, and midface. Intraoral passive molding was ultimately characterized by the highest biomechanical efficacy and showed the most favorable load distribution of all of the PSIO approaches considered in this study. Future research is needed to validate the findings against clinical data.

Statement of problem. Internal fit is an important aspect of indirect restorations, but methods for the 3-dimensional (3D) measurement of absolute marginal and intaglio fit are sparse. Purpose. The purpose of this in vitro study was to evaluate an innovative 3D measurement method (AIXFit) based on intraoral scanning data for analyzing the fit of dental restorations. Material and methods. For the evaluation of AIXFit, 12 monolithic zirconia crowns were fabricated on typodont preparations. The fit was measured digitally with the AIXFit system and compared with the results obtained from an established 2-dimensional (2D) sectional procedure. To compare the values of both methods at identical locations, a common reference system was developed, with each die fixed in a gypsum stand with reference points. Using an intraoral scanner (True Definition), each die with its reference points and the intaglio surface of the finished crown were digitalized as standard tessellation language files. The AIXFit software program, with a specially developed best-fit algorithm, was used to match the intaglio surface of the crown with the surface of the preparation. The virtual cement gap was calculated over the entire surface and returned values for x >= 0 mu m. A 2D comparison method involved adhesively fixing the crown to the die and sectioning it into 4 parts with a diamond band saw. The thickness of the cement gap was determined under a light microscope at x100 magnification at 5 defined measuring points per quarter, so that a total of 240 measurements were available for comparison. A software program (Blender Foundation) was used to superimpose the data from the AIXFit system with the data from the 2D method and to compare the cement gaps at the same locations. The agreement between these methods was verified using paired t tests and determine correlation coefficients (alpha=.05). Results. The mean +/- standard deviation difference between the AIXFit and 2D methods was 6.7 +/- 29 mu m). Two 1-sided tests showed statistical equivalence between the methods of measurement when considering an interval between-20 and +20 mu m. The correlation coefficients showed a positive association for both methods (r=.931). Conclusions. The AIXFit software program appeared to be accurate for the digital measurement of internal fit when using the True Definition scanner. It enabled a cast-free workflow and allowed the analysis of the entire intaglio surface. (J Prosthet Dent 2025;134:160-166)

Objective. The purpose of this study was to develop a robust deep learning approach trained with a small in-vivo MRI dataset for multi-label segmentation of all eight carpal bones for therapy planning and wrist dynamic analysis. Approach. A small dataset of 15 3.0-T MRI scans from five health subjects was employed within this study. The MRI data was variable with respect to the field of view (FOV), wide range of image intensity, and joint pose. A two-stage segmentation pipeline using modified 3D U-Net was proposed. In the first stage, a novel architecture, introduced as expansion transfer learning (ETL), cascades the use of a focused region of interest (ROI) cropped around ground truth for pretraining and a subsequent transfer by an expansion to the original FOV for a primary prediction. The bounding box around the ROI generated was utilized in the second stage for high-accuracy, labeled segmentations of eight carpal bones. Different metrics including dice similarity coefficient (DSC), average surface distance (ASD) and hausdorff distance (HD) were used to evaluate performance between proposed and four state-of-the-art approaches. Main results. With an average DSC of 87.8 %, an ASD of 0.46 mm, an average HD of 2.42 mm in all datasets (96.1 %, 0.16 mm, 1.38 mm in 12 datasets after exclusion criteria, respectively), the proposed approach showed an overall strongest performance than comparisons. Significance. To our best knowledge, this is the first CNN-based multi-label segmentation approach for MRI human carpal bones. The ETL introduced in this work improved the ability to localize a small ROI in a large FOV. Overall, the interplay of a two-stage approach and ETL culminated in convincingly accurate segmentation scores despite a very small amount of image data.

OBJECTIVES:In advanced stages of osteoradionecrosis, medication-related osteonecrosis of the jaw, and osteomyelitis, a resection of sections of the mandible may be unavoidable. The determination of adequate bony resection margins is a fundamental problem because bony resection margins cannot be secured intraoperatively. Single-photon emission computed tomography (SPECT-CT) is more accurate than conventional imaging techniques in detecting inflammatory jaw pathologies. The clinical benefit for virtual planning of mandibular resection and primary reconstruction with vascularized bone flaps has not yet been investigated. This study aimed to evaluate the determination of adequate bony resection margins using SPECT computed tomography (SPECT-CT) for primary microvascular reconstruction of the mandible in inflammatory jaw pathologies. MATERIALS AND METHODS:The cases of 20 patients with inflammatory jaw pathologies who underwent primary microvascular mandibular reconstruction after the bony resection margins were determined with SPECT-CT were retrospectively analyzed. The bony resection margins determined by SPECT-CT were histologically validated. The sensitivity was calculated as the detection rate and the positive predictive value as the diagnostic precision. Radiological ossification of the vascularized bone flaps with the mandibular stumps was assessed at least 6 months after reconstruction. The clinical course was followed for 12 months. RESULTS:The determination of adequate bony resection margins with SPECT-CT yielded a sensitivity of 100% and a positive predictive value of 94.7%. Of all the bony resection margins, 97.4% were radiologically sufficiently ossified with the vascularized bone flap and showed no complications in the clinical course. CONCLUSIONS:SPECT-CT could increase the probability of determining adequate bony resection margins. CLINICAL RELEVANCE:SPECT-CT could have a beneficial clinical impact in the context of primary microvascular bony reconstruction in inflammatory jaw pathologies.

This study proposes a fully automatic segmentation of the fibula bone from CT images for application in pre-operative planning of reconstructive surgery. The objective is to make use of new developments in the image segmentation field to optimize and reduce the costs of patient-specific surgery planning. Two different approaches are proposed to perform the fibula bone segmentation, both based on a two-step segmentation method using a 3D-UNet architecture. To account for the symmetry of the left and right fibula bones, input images of the right fibula are mirrored to the left side. The accuracy of the trained models is measured using common evaluation metrics, together with specific metrics focused on facial reconstructive surgery. Both of the described approaches achieve high-accuracy results. For the best-trained model, an average Dice score of 0.95 and Average Surface Distances below 0.31 mm is measured on the test set in the region of interest for the surgery. Both approaches are robust segmentation techniques and permit data pre-processing for further application in the context of preoperative surgical planning of procedures for facial reconstruction with bony transplants.

BACKGROUND AND OBJECTIVE:Identification of anatomical landmarks in 3D imaging data is an essential step in patient-specific cranio-maxillofacial surgery. Today, precise landmark localization remains largely manual, prone to inter-operator variability, and a bottleneck in streamlined workflows of digitalized preoperative planning, that have in recent years, become a key aspect of cranio-maxillofacial surgery. In clinical practice, bone segmentation and landmark detection in CT imaging is often avoided and automated solutions fall back to the analysis of 2D cephalograms. METHODS:This work investigates different pipelines to automate the process of landmark localization in the mandible from volumetric CT imaging using convolutional neural networks. As a central element, a 3D U-Net architecture is employed to treat landmark localization and classification like a multi-label segmentation problem. We leverage a two-stage coarse-to-fine approach to tackle heterogeneous input data and preserve high resolution for the final prediction. Our primary innovation is a novel dual-input architecture for the second stage, which uses both the cropped CT data and a mandible segmentation to provide the model with explicit geometric priors for improved accuracy. The method was developed and tested on a clinical dataset comprising 287 CT datasets to localize nine different landmarks on the human mandible, including the Condyles, Coronoids, Gonions, Pogonion, Gnathion and Menton. RESULTS:On a test dataset of 29 CTs, landmarks were predicted with a mean absolute error of 1.40±1.04 while successfully predicting 99.6% of all landmarks. CONCLUSION:The proposed method demonstrates high accuracy, robustness, and speed suggesting strong potential for integration into clinical workflows for automated, patient-specific surgical planning in cranio-maxillofacial surgery.

Background and objectives: For the planning of surgical procedures involving the bony reconstruction of the mandible, the autologous iliac crest graft, along with the fibula graft, has become established as a preferred donor region. While computer-assisted planning methods are increasingly gaining importance, the necessary preparation of geometric data based on CT imaging remains largely a manual process. The aim of this work was to develop and test a method for the automated segmentation of the iliac crest for subsequent reconstruction planning. Methods: A total of 1,398 datasets with manual segmentations were obtained as ground truth, with a subset of 400 datasets used for training and validation of the Neural Networks and another subset of 177 datasets used solely for testing. A deep Convolutional Neural Network implemented in a 3D U-Net architecture using Tensorflow was employed to provide a pipeline for automatic segmentation. Transfer learning was applied for model training optimization. Evaluation metrics included the Dice Similarity Coefficient, Symmetrical Average Surface Distance, and a modified 95% Hausdorff Distance focusing on regions relevant for transplantation. Results: The automated segmentation achieved high accuracy, with qualitative and quantitative assessments demonstrating predictions closely aligned with ground truths. Quantitative evaluation of the correspondence yielded values for geometric agreement in the transplant-relevant area of 92% +/- 7% (Dice coefficient) and average surface deviations of 0.605 +/- 0.41 mm. In all cases, the bones were identified as contiguous objects in the correct spatial orientation. The geometries of the iliac crests were consistently and completely recognized on both sides without any gaps. Conclusions: The method was successfully used to extract the individual geometries of the iliac crest from CT data. Thus, it has the potential to serve as an essential starting point in a digitized planning process and to provide data for subsequent surgical planning. The complete automation of this step allows for efficient and reliable preparation of anatomical data for reconstructive surgeries.

Background Surgical correction of unicoronal craniosynostosis (UCS) is highly complex due to its asymmetric appearance. Although fronto-orbital advancement (FOA) is a versatile technique for craniosynostosis correction, harmonization of the orbital bandeau in UCS is difficult to predict. This study evaluates the biomechanics of the orbital bandeau using different patterns and varying characteristics of inner cortical bone layer osteotomies in a finite element (FE) analysis. Method An FE model was created using the computed tomography (CT) scan of a 6.5-month-old male infant with a right-sided UCS. The unaffected side of the orbital bandeau was virtually mirrored, and anatomical correction of the orbital bandeau was simulated. Different combinations of osteotomy patterns, numbers, depths, and widths were examined (n = 48) and compared to an uncut model. Results Reaction forces and maximum stress values differed significantly (p < 0.01) among osteotomy patterns and between each osteotomy characteristic. Regardless of the osteotomy pattern, higher numbers of osteotomies significantly (p < 0.05) correlated with reductions in reaction force and maximum stress. An X-shaped configuration with three osteotomies deep and wide to the bone was biomechanically the most favorable model. Conclusion Inner cortical bone layer osteotomy might be an effective modification to the conventional FOA approach in terms of predictable shaping of the orbital bandeau.

The repair of hemimandibulectomy defects involving the temporomandibular joint (TMJ) is challenging. This study compared the functional outcomes and reconstruction accuracy using a deep circumflex iliac artery (DCIA) flap with and without a virtually planned stock TMJ prosthesis (TMJP) after hemimandibulectomy. Ten patients were assessed: five with a TMJP (TMJP group) and five without (control group). A three-dimensional comparison revealed a mean deviation of 0.11 ± 0.04 mm between the planned and actual DCIA flap with TMJP. The planned and actual TMJP positions differed by 0.56 ± 0.57 mm in height, 0.33 ± 0.24 mm ventrally/dorsally, and 1.18 ± 0.42 mm medially/laterally. Mouth opening, laterotrusion, and midline deviation were significantly greater in the control group than in the TMJP group (P = 0.024, P = 0.008, P = 0.024). The deviation in ventral to dorsal translation for the DCIA flap was slightly higher than reported values in the literature, while height deviation was comparable. Lower deviations in the literature were due to the DCIA flap being used where both TMJs were intact. The in-house virtually planned DCIA flap with stock TMJP yielded results comparable to more expensive patient-specific prostheses.

The deep circumflex iliac crest flap (DCIA) is used for the reconstruction of the jaw. For fitting of the transplant by computer-aided planning (CAD), a computerized tomography (CT) of the jaw and the pelvis is necessary. Ready-made cutting guides save a pelvic CT and healthcare resources while maintaining the advantages of the CAD planning. A total of 2000 CTs of the pelvis were divided into groups of 500 by sex and age (≤ 45 and > 45 years). Three-dimensional (3D) pelvis models were aligned and averaged. Cutting guides were designed on the averaged pelvis for each group and an overall averaged pelvis. The cutting guides and 50 randomly selected iliac crests (10 from each group and 10 from the whole collective) were 3D printed. The appropriate cutting guide was mounted to the iliac crest and a cone beam CT was performed. The thickness of the space between the iliac crest and the cutting guide was evaluated. Overall the mean thickness of the space was 2.137 mm and the mean volume of the space was 4513 mm3. The measured values were significantly different between the different groups. The overall averaged group had not the greatest volume, maximum thickness and mean thickness of the space. Ready-made cutting guides for the DCIA flap fit to the iliac crest and make quick and accurate flap raising possible while radiation dose and resources can be saved. The cutting guides fit sufficient to the iliac crest and should keep the advantages of a standard CAD planning.

Tumorous diseases of the jaw demand effective treatments, often involving continuity resection of the jaw. Reconstruction via microvascular bone flaps, like deep circumflex iliac artery flaps (DCIA), is standard. Computer aided planning (CAD) enhances accuracy in reconstruction using patient-specific CT images to create three-dimensional (3D) models. Data on the accuracy of CAD-planned DCIA flaps is scarce. Moreover, the data on accuracy should be combined with data on the exact positioning of the implants for well-fitting dental prosthetics. This study focuses on CAD-planned DCIA flaps accuracy and proper positioning for prosthetic rehabilitation. Patients post-mandible resection with CAD-planned DCIA flap reconstruction were evaluated. Postoperative radiograph-derived 3D models were aligned with 3D models from the CAD plans for osteotomy position, angle, and flap volume comparison. To evaluate the DCIA flap’s suitability for prosthetic dental rehabilitation, a plane was created in the support zone and crestal in the middle of the DCIA flap. The lower jaw was rotated to close the mouth and the distance between the two planes was measured. 20 patients (12 males, 8 females) were included. Mean defect size was 73.28 ± 4.87 mm; 11 L defects, 9 LC defects. Planned vs. actual DCIA transplant volume difference was 3.814 ± 3.856 cm³ (p = 0.2223). The deviation from the planned angle was significantly larger at the dorsal osteotomy than at the ventral (p = 0.035). Linear differences between the planned DCIA transplant and the actual DCIA transplant were 1.294 ± 1.197 mm for the ventral osteotomy and 2.680 ± 3.449 mm for the dorsal (p = 0.1078). The difference between the dental axis and the middle of the DCIA transplant ranged from 0.2 mm to 14.8 mm. The mean lateral difference was 2.695 ± 3.667 mm in the region of the first premolar. The CAD-planned DCIA flap is a solution for reconstructing the mandible. CAD planning results in an accurate reconstruction enabling dental implant placement and dental prosthetics.

BackgroundOrbital floor fractures result in critical changes in the shape and inferior rectus muscle (IRM) position. Radiological imaging of IRM changes can be used for surgical decision making or prediction of ocular symptoms. Studies with a systematic consideration of the orbital floor defect ratio in this context are missing in the literature. Accordingly, this study on human cadavers aimed to systematically investigate the impact of the orbital floor defect ratio on changes in the IRM and the prediction of posttraumatic enophthalmos.MethodsSeventy-two orbital floor defects were placed in cadaver specimens using piezosurgical removal. The orbital defect area (ODA), orbital floor area (OFA), position and IRM shape, and enophthalmos were measured using computed tomography (CT) scans.ResultsThe ODA/OFA ratio correlated significantly (p < 0.001) with the shape (Spearman’s rho: 0.558) and position (Spearman’s rho: 0.511) of the IRM, and with enophthalmos (Spearman’s rho: 0.673). Increases in the ODA/OFA ratio significantly rounded the shape of the IRM (ß: 0.667; p < 0.001) and made a lower position of the IRM more likely (OR: 1.093; p = 0.003). In addition, increases in the ODA/OFA ratio were significantly associated with the development of relevant enophthalmos (OR: 1.159; p = 0.008), adjusted for the defect localization and shape of the IRM. According to receiver operating characteristics analysis (AUC: 0.876; p < 0.001), a threshold of ODA/OFA ratio ≥ 32.691 for prediction of the risk of development of enophthalmos yielded a sensitivity of 0.809 and a specificity of 0.842.ConclusionThe ODA/OFA ratio is a relevant parameter in the radiological evaluation of orbital floor fractures, as it increases the risk of relevant enophthalmos, regardless of fracture localization and shape of the IRM. Therefore, changes in the shape and position of the IRM should be considered in surgical treatment planning. A better understanding of the correlates of isolated orbital floor fractures may help to develop diagnostic scores and standardize therapeutic algorithms in the future.

Objectives Due to advancing digitalisation, it is of interest to develop standardised and reproducible fully automated analysis methods of cranial structures in order to reduce the workload in diagnosis and treatment planning and to generate objectifiable data. The aim of this study was to train and evaluate an algorithm based on deep learning methods for fully automated detection of craniofacial landmarks in cone-beam computed tomography (CBCT) in terms of accuracy, speed, and reproducibility. Materials and methods A total of 931 CBCTs were used to train the algorithm. To test the algorithm, 35 landmarks were located manually by three experts and automatically by the algorithm in 114 CBCTs. The time and distance between the measured values and the ground truth previously determined by an orthodontist were analyzed. Intraindividual variations in manual localization of landmarks were determined using 50 CBCTs analyzed twice. Results The results showed no statistically significant difference between the two measurement methods. Overall, with a mean error of 2.73 mm, the AI was 2.12% better and 95% faster than the experts. In the area of bilateral cranial structures, the AI was able to achieve better results than the experts on average. Conclusion The achieved accuracy of automatic landmark detection was in a clinically acceptable range, is comparable in precision to manual landmark determination, and requires less time. Clinical relevance Further enlargement of the database and continued development and optimization of the algorithm may lead to ubiquitous fully automated localization and analysis of CBCT datasets in future routine clinical practice.

Die ästhetische und funktionelle Rehabilitation von Patienten mit knöchernen Defekten des Gesichtsschädels ist eine der Königsdisziplinen der Mund‑, Kiefer- und Gesichtschirurgie. Die computergestützte Planung ermöglicht die patientenindividuelle Rekonstruktion fehlender Knochenabschnitte mit mikrovaskulären Beckenkamm‑, Fibula- oder Scapulatransplantaten. Für den Transfer dieser Planung in den Operationssaal sind „computer-aided design/computer-aided manufacturing“(CAD/CAM)-Fertigungsmethoden heute erfolgreicher Standard. Aktuelle Forschungsanstrengungen streben nach Verbesserungen in der Prozesskette der digitalen Planung, um diese durch eine weitgehende Automatisierung zu standardisieren und zu objektivieren. Neueste Methoden der künstlichen Intelligenz präzisieren die Aufbereitung der digitalen Bildgebung und tragen dazu bei, die präoperative Planung noch individueller an die klinischen und operativen Anforderungen anpassen zu können. Die Umsetzung der virtuellen Planung kann mithilfe individuell gefertigter Schablonen zur Überführung der virtuellen Schnittführungen und mithilfe patientenspezifischer Implantate zur Überbrückung von knöchernen Kontinuitätsdefekten optimiert werden. Insgesamt kann die schrittweise Optimierung der digitalen Prozesskette die knöcherne Rekonstruktionsgenauigkeit und die dentale Rehabilitationsrate gegenüber nicht virtuell geplanten Knochenrekonstruktionen steigern. Die Entwicklung maßgeschneiderter Prozessketten mit Automatisierung aller Teilschritte kann die Planung trotz aller patientenspezifischen Besonderheiten vereinfachen. Limitationen im Hinblick auf die onkologische Sicherheit und die intraoperative Inflexibilität der virtuellen Planung können durch Synergismen chirurgischer und technischer Innovationen adressiert werden.

This in-vitro study was designed to investigate whether conventionally produced casts and printed casts for orthodontic purposes show comparable full-arch accuracy. To produce casts, either a conventional impression or a digital data set is needed. A fully dentate all ceramic master cast was digitized with an industrial scanner to obtain a digital reference cast [REF]. Intraoral scans [IOS] and alginate impressions were taken from the master cast so that ten printed and ten gypsum casts were obtained. The printed casts [DLP] were digitized by an industrial scanner and as well as the gypsum casts [GYPSUM]. The following absolute mean trueness evaluations by superimposition were accomplished: [REF vs. GYPSUM]; [REF vs. DLP]; [REF vs. IOS]; [IOS vs. DLP]. For precision analysis the data sets of [GYPSUM], [IOS] and [DLP] were available. The absolute mean trueness values were 68 μm ± 15 μm for [REF vs. GYPSUM], 46 μm ± 4 μm for [REF vs. DLP], 20 μm ± 2 μm for [REF vs. IOS] and 41 μm ± 4 μm for [IOS vs. DLP]. [REF vs. GYPSUM] and [REF vs. DLP], [REF vs. IOS], [REF vs. DLP] and [IOS vs. DLP] showed statistically significant differences. The precision values were 56 μm ± 17 μm for [GYPSUM], 25 μm ± 9 μm for [DLP] and 12 μm ± 2 μm for [IOS] and differed significantly among each other. In the present study the print workflow revealed superior results in comparison to the conventional workflow. Due to contrary deviations in the [REF vs. IOS] and the [IOS vs. DLP] data sets the overall trueness deviations was enhanced.

Objectives: To investigate the complete arch accuracy of intraoral scanners (IOS) on two different ceramic surfaces.Methods: Two maxillary master cast samples were prepared. The bases of both the master casts were made from zirconium oxide. The difference between the two casts was that the teeth of the [ZR] cast were produced from zirconium oxide and that of the [LD] cast were made of lithium disilicate glass-ceramic. Unlike the zirconia teeth of the [ZR] cast, the lithium disilicate teeth of the [LD] cast were glazed. The two master casts were digitized using a high-resolution scanner (Atos Compact Scan 5 M, GOM GmbH, Braunschweig, Germany) to obtain digital reference casts. Subsequently, each master cast was scanned 15 times using four IOSs. The IOSs were the Cerec Omnicam [OM], Primescan [PR], Trios 4 [TR4], and VivaScan [VS]. On surface comparison, the absolute mean deviation values were obtained for trueness and precision. For multiple comparisons, statistically significant differences were analyzed using one-way ANOVA and the Kruskal-Wallis H test. The p-value was adjusted to control for the increased risk of type I error (p < 0.0083). To compare the two means, the t -test and Mann -Whitney U test were used (p < 0.05).Results: Trueness values for [ZR] ranged from 24.6 (+/- 6.3) mu m for [PR] and 77.1 (+/- 8.3) mu m for [OM]. Trueness values for [LD] were between 28.3 (+/- 6.3) mu m for [PR] and 72.8 (+/- 15.6) mu m for [OM]. Precision values for [ZR] ranged from 17.6 (+/- 3.7) mu m for [PR] to 37.3 (+/- 9.9) mu m for [OM]. Precision values for [LD] ranged from 17.5 (+/- 3.6) mu m for [PR] to 41.8 (+/- 8.7) mu m for [OM]. Statistically significant differences were found among all the IOSs (p < 0.0083). The trueness values of the four IOSs did not differ significantly (p < 0.05) with respect to either the [ZR] or [LD] cast. The precision values of [OM] and [VS] differed significantly with respect to the scanned surface.Conclusions: Complete arch scans achieved with the four IOSs showed significantly different trueness and pre-cision results. [VS] and [OM] were more sensitive in terms of the scanned material. Clinical significance: The latest IOSs showed the required accuracy for complete arch digital impressions in-vitro investigations. These findings should be implemented under conditions relevant to complete arch deviations, such as the construction of occlusal splints, analysis of occlusal relationships, and long-span restorations. Cli-nicians should be aware that the clinically acceptable threshold varies depending on the purpose of the IOS.