Virtual tumor mapping and margin control with 3-D planning and navigation.

Computer technology-based treatment approaches like intraoperative navigation and intensity-modulated radiation therapy have become important components of state of the art head and neck cancer treatment. Multidirectional exchange of virtual three-dimensional patient data via an interdisciplinary platform allows all medical specialists involved in the patients treatment to take full advantage of these technologies. This review article gives an overview of current technologies and future directions regarding treatment approaches that are based on a virtual, three-dimensional patient specific dataset: storage and exchange of spatial information acquired via intraoperative navigation allow for a highly precise frozen section procedure. In the postoperative setting, virtual reconstruction of the tumor resection surface provides the basis for improved radiation therapy planning and virtual reconstruction of the tumor with integration of molecular findings creates a valuable tool for postoperative treatment and follow-up. These refinements of established treatment components and novel approaches have the potential to make a major contribution to improving the outcome in head and neck cancer patients.

Dimensional accuracy and simulation-based optimization of polyolefins and biocopolyesters for extrusion-based additive manufacturing and steam sterilization.

Polyolefins exhibit robust mechanical and chemical properties and can be applied in the medical field, e.g. for the manufacturing of dentures. Despite their wide range of applications, they are rarely used in extrusion-based printing due to their warpage tendency. The aim of this study was to investigate and reduce the warpage of polyolefins compared to commonly used filaments after additive manufacturing (AM) and sterilization using finite element simulation. Three types of filaments were investigated: a medical-grade polypropylene (PP), a glass-fiber reinforced polypropylene (PP-GF), and a biocopolyester (BE) filament, and they were compared to an acrylic resin (AR) for material jetting. Square specimens, standardized samples prone to warpage, and denture bases (n = 10 of each group), as clinically relevant and anatomically shaped reference, were digitized after AM and steam sterilization (134 °C). To determine warpage, the volume underneath the square specimens was calculated, while the deviations of the denture bases from the printing file were measured using root mean square (RMS) values. To reduce the warpage of the PP denture base, a simulation of the printing file based on thermomechanical calculations was performed. Statistical analysis was conducted using the Kruskal-Wallis test, followed by Dunn's test for multiple comparisons. The results showed that PP exhibited the greatest warpage of the square specimens after AM, while PP-GF, BE, and AR showed minimal warpage before sterilization. However, warpage increased for PP-GF, BE and AR during sterilization, whereas PP remained more stable. After AM, denture bases made of PP showed the highest warpage. Through simulation-based optimization, warpage of the PP denture base was successfully reduced by 25%. In contrast to the reference materials, PP demonstrated greater dimensional stability during sterilization, making it a potential alternative for medical applications. Nevertheless, reducing warpage during the cooling process after AM remains necessary, and simulation-based optimization holds promise in addressing this issue.

AI-Based Detection of Oral Squamous Cell Carcinoma with Raman Histology.

Stimulated Raman Histology (SRH) employs the stimulated Raman scattering (SRS) of photons at biomolecules in tissue samples to generate histological images. Subsequent pathological analysis allows for an intraoperative evaluation without the need for sectioning and staining. The objective of this study was to investigate a deep learning-based classification of oral squamous cell carcinoma (OSCC) and the sub-classification of non-malignant tissue types, as well as to compare the performances of the classifier between SRS and SRH images. Raman shifts were measured at wavenumbers k1 = 2845 cm-1 and k2 = 2930 cm-1. SRS images were transformed into SRH images resembling traditional H&E-stained frozen sections. The annotation of 6 tissue types was performed on images obtained from 80 tissue samples from eight OSCC patients. A VGG19-based convolutional neural network was then trained on 64 SRS images (and corresponding SRH images) and tested on 16. A balanced accuracy of 0.90 (0.87 for SRH images) and F1-scores of 0.91 (0.91 for SRH) for stroma, 0.98 (0.96 for SRH) for adipose tissue, 0.90 (0.87 for SRH) for squamous epithelium, 0.92 (0.76 for SRH) for muscle, 0.87 (0.90 for SRH) for glandular tissue, and 0.88 (0.87 for SRH) for tumor were achieved. The results of this study demonstrate the suitability of deep learning for the intraoperative identification of tissue types directly on SRS and SRH images.

Reconstruction of dental roots for implant planning purposes: a retrospective computational and radiographic assessment of single-implant cases.

PURPOSE: The aim of the study was to assess the deviation between clinical implant axes (CIA) determined by a surgeon during preoperative planning and reconstructed tooth axes (RTA) of missing teeth which were automatically computed by a previously introduced anatomical SSM. METHODS: For this purpose all available planning datasets of single-implant cases of our clinic, which were planned with coDiagnostix Version 9.9 between 2018 and 2021, were collected for retrospective investigation. Informed consent was obtained. First, the intraoral scans of implant patients were annotated and subsequently analyzed using the SSM. The RTA, computed by the SSM, was then projected into the preoperative planning dataset. The amount and direction of spatial deviation between RTA and CIA were then measured. RESULTS: Thirty-five patients were implemented. The mean distance between the occlusal entry point of anterior and posterior implants and the RTA was 0.99 mm ± 0.78 mm and 1.19 mm ± 0.55, respectively. The mean angular deviation between the CIA of anterior and posterior implants and the RTA was 12.4° ± 3.85° and 5.27° ± 2.97° respectively. The deviations in anterior implant cases were systematic and could be corrected by computing a modified RTA (mRTA) with decreased deviations (0.99 mm ± 0.84 and 4.62° ± 1.95°). The safety distances of implants set along the (m)RTA to neighboring teeth were maintained in 30 of 35 cases. CONCLUSION: The RTA estimated by the SSM revealed to be a viable implant axis for most of the posterior implant cases. As there are natural differences between the anatomical tooth axis and a desirable implant axis, modifications were necessary to correct the deviations which occurred in anterior implant cases. However, the presented approach is not applicable for clinical use and always requires manual optimization by the planning surgeon.

Automated detection of cephalometric landmarks using deep neural patchworks.

OBJECTIVES: This study evaluated the accuracy of deep neural patchworks (DNPs), a deep learning-based segmentation framework, for automated identification of 60 cephalometric landmarks (bone-, soft tissue- and tooth-landmarks) on CT scans. The aim was to determine whether DNP could be used for routine three-dimensional cephalometric analysis in diagnostics and treatment planning in orthognathic surgery and orthodontics. METHODS: Full skull CT scans of 30 adult patients (18 female, 12 male, mean age 35.6 years) were randomly divided into a training and test data set (each n = 15). Clinician A annotated 60 landmarks in all 30 CT scans. Clinician B annotated 60 landmarks in the test data set only. The DNP was trained using spherical segmentations of the adjacent tissue for each landmark. Automated landmark predictions in the separate test data set were created by calculating the center of mass of the predictions. The accuracy of the method was evaluated by comparing these annotations to the manual annotations. RESULTS: The DNP was successfully trained to identify all 60 landmarks. The mean error of our method was 1.94 mm (SD 1.45 mm) compared to a mean error of 1.32 mm (SD 1.08 mm) for manual annotations. The minimum error was found for landmarks ANS 1.11 mm, SN 1.2 mm, and CP_R 1.25 mm. CONCLUSION: The DNP-algorithm was able to accurately identify cephalometric landmarks with mean errors <2 mm. This method could improve the workflow of cephalometric analysis in orthodontics and orthognathic surgery. Low training requirements while still accomplishing high precision make this method particularly promising for clinical use.

Stimulated Raman histology for histological evaluation of oral squamous cell carcinoma.

OBJECTIVES: To investigate whether in patients undergoing surgery for oral squamous cell carcinoma, stimulated Raman histology (SRH), in comparison with H&E-stained frozen sections, can provide accurate diagnoses regarding neoplastic tissue and sub-classification of non-neoplastic tissues. MATERIALS AND METHODS: SRH, a technology based on Raman scattering, was applied to generate digital histopathologic images of 80 tissue samples obtained from 8 oral squamous cell carcinoma (OSCC) patients. Conventional H&E-stained frozen sections were then obtained from all 80 samples. All images/sections (SRH and H&E) were analyzed for squamous cell carcinoma, normal mucosa, connective tissue, muscle tissue, adipose tissue, salivary gland tissue, lymphatic tissue, and inflammatory cells. Agreement between SRH and H&E was evaluated by calculating Cohen's kappa. Accuracy of SRH compared to H&E was quantified by calculating sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) as well as area under the receiver operating characteristic curve (AUC). RESULTS: Thirty-six of 80 samples were classified as OSCC by H&E-based diagnosis. Regarding the differentiation between neoplastic and non-neoplastic tissue, high agreement between H&E and SRH (kappa: 0.880) and high accuracy of SRH (sensitivity: 100%; specificity: 90.91%; PPV: 90.00%, NPV: 100%; AUC: 0.954) were demonstrated. For sub-classification of non-neoplastic tissues, SRH performance was dependent on the type of tissue, with high agreement and accuracy for normal mucosa, muscle tissue, and salivary glands. CONCLUSION: SRH provides high accuracy in discriminating neoplastic and non-neoplastic tissues. Regarding sub-classification of non-neoplastic tissues in OSCC patients, accuracy varies depending on the type of tissue examined. CLINICAL RELEVANCE: This study demonstrates the potential of SRH for intraoperative imaging of fresh, unprocessed tissue specimens from OSCC patients without the need for sectioning or staining.

GEnZ explorer: a tool for visualizing agroclimate to inform research and regulatory risk assessment.

Confined field trials (CFT) of genetically engineered (GE) crops are used to generate data to inform environmental risk assessments (ERA). ERAs are required by regulatory authorities before novel GE crops can be released for cultivation. The transportability of CFT data to inform risk assessment in countries other than those where the CFT was conducted has been discussed previously in an analysis showing that the primary difference between CFT locations potentially impacting trial outcomes is the physical environment, particularly the agroclimate. This means that data from trials carried out in similar agroclimates could be considered relevant and sufficient to satisfy regulatory requirements for CFT data, irrespective of the country where the CFTs are conducted. This paper describes the development of an open-source tool to assist in determining the transportability of CFT data. This tool provides agroclimate together with overall crop production information to assist regulators and applicants in making informed choices on whether data from previous CFTs can inform an environmental risk assessment in a new country, as well as help developers determine optimal locations for planning future CFTs. The GEnZ Explorer is a freely available, thoroughly documented, and open-source tool that allows users to identify the agroclimate zones that are relevant for the production of 21 major crops and crop categories or to determine the agroclimatic zone at a specific location. This tool will help provide additional scientific justification for CFT data transportability, along with spatial visualization, to help ensure regulatory transparency.

Donor site morbidity after computer assisted surgical reconstruction of the mandible using deep circumflex iliac artery grafts: a cross sectional study.

BACKGROUND: Computer Assisted Design and Computer Assisted Manufacturing (CAD/CAM) have revolutionized oncologic surgery of the head and neck. A multitude of benefits of this technique has been described, but there are only few reports of donor site comorbidity following CAD/CAM surgery. METHODS: This study investigated comorbidity of the hip following deep circumflex iliac artery (DCIA) graft raising using CAD/CAM techniques. A cross-sectional examination was performed to determine range of motion, muscle strength and nerve disturbances. Furthermore, correlations between graft volume and skin incision length with postoperative donor site morbidity were assessed using Spearman's rank correlation, linear regression and analysis of variance (ANOVA). RESULTS: Fifteen patients with a mean graft volume of 21.2 ± 5.7 cm3 and a mean incision length of 228.0 ± 30.0 mm were included. Patients reported of noticeable physical limitations in daily life activities (12.3 ± 11.9 weeks) and athletic activities (38.4 ± 40.0 weeks in mean) following surgery. Graft volume significantly correlated with the duration of the use of walking aids (R = 0.57; p = 0.033) and impairment in daily life activities (R = 0.65; p = 0.012). The length of the scar of the donor-site showed a statistically significant association with postoperative iliohypogastric nerve deficits (F = 4.4, p = 0.037). Patients with anaesthaesia of a peripheral cutaneous nerve had a larger mean scar length (280 ± 30.0 mm) than subjects with hypaesthesia (245 ± 10.1 mm) or no complaints (216 ± 27.7 mm). CONCLUSIONS: Despite sophisticated planning options in modern CAD/CAM surgery, comorbidity of the donor site following  iliac graft harvesting is still a problem. This study is the first to investigate comorbidity after DCIA graft raising in a patient group treated exclusively with CAD/CAM techniques. The results indicate that a minimal invasive approach in terms of small graft volumes and small skin incisions could help to reduce postoperative symptomatology. Trial registration Retrospectively registered at the German Clinical Trials Register (DRKS-ID: DRKS00029066); registration date: 23/05/2022.

Feasibility of Implant Strain Measurement for Assessing Mandible Bone Regeneration.

Nonunion is one of the most dreaded complications after operative treatment of mandible fractures or after mandible reconstruction using vascularized and non-vascularized bone grafts. Often diagnosis is made at advanced stage of disease when pain or complications occur. Devices that monitor fracture healing and bone regeneration continuously are therefore urgently needed in the craniomaxillofacial area. One promising approach is the strain measurement of plates. An advanced prototype of an implantable strain measurement device was tested after fixation to a locking mandible reconstruction plate in multiple compression experiments to investigate the potential functionality of strain measurement in the mandibular region. Compression experiments show that strain measurement devices work well under experimental conditions in the mandibular angle and detect plate deformation in a reliable way. For monitoring in the mandibular body, the device used in its current configuration was not suitable. Implant strain measurement of reconstruction plates is a promising methodical approach for permanent monitoring of bone regeneration and fracture healing in the mandible. The method helps to avoid or detect complications at an early point in time after operative treatment.

Cranial reconstruction evaluation - comparison of European statistical shape model performance on Chinese dataset.

Purpose: Morphological variability of the skull is an important consideration for cranioplasty and implant design. Differences in morphology of the skull based on the ethnicity are known. In a previous study we could show the accuracy and benefits of virtual reconstructions based on a statistical shape model (SSM) for neurocranial defects. As the SSM is trained on European data, the question arises how well this model fares when dealing with patients with a different ethnic background. In this study we aim to evaluate the accuracy and applicability of our proposed method when deploying a cranial SSM generated from European data to estimate missing parts of the neurocranium in a Chinese population. Methods: We used the same data and methods as in our previous study and compared the outcomes when applied to Chinese individuals. A large unilateral defect on the right side and a bilateral defect were created. The outer surface of the cranial table was reconstructed from CT scans, meshed with triangular elements, and registered to a template. Principal component analysis together with Thin Plate Spines (TPS) deformation was applied to quantify modes of variation. The mesh to mesh distances between the original defects´ surfaces and the reconstructed surface were computed. Results: Comparing the Chinese test group with the European control group, regarding the entire defect the analysis shows no significant difference for unilateral defects (test vs. control group/0.46 mm ± vs. 0.44 mm). Reconstruction of bilateral defects exhibited only in slightly higher prediction errors than those of unilateral defects (0.49 mm ± vs. 0.45 mm). Conclusion: The proposed method shows a high accuracy that seems to be ethnical independent - with low error margins for virtual skull reconstruction and implant design.Clinical relevance: Metallic objects may severely impact image quality in several CBCT devices.

Analysis of the accuracy of computer-assisted DCIA flap mandibular reconstruction applying a novel approach based on geometric morphometrics.

BACKGROUND: This study evaluated the accuracy of computer-assisted surgery (CAS)-driven DCIA (deep circumflex iliac artery) flap mandibular reconstruction by traditional morphometric methods and geometric morphometric methods (GMM). METHODS: Reconstruction accuracy was evaluated by measuring distances and angles between bilateral anatomical landmarks. Additionally, the average length of displacements vectors between landmarks was computed to evaluate factors assumed to influence reconstruction accuracy. Principal component analysis (PCA) was applied to unveil main modes of dislocation. RESULTS: High reconstruction accuracy could be demonstrated for a sample consisting of 26 patients. The effect of the number of segments and length of defect on reconstruction accuracy were close to the commonly used significance threshold (p = 0.062/0.060). PCA demonstrated displacement to result mainly from sagittal and transversal shifts. CONCLUSIONS: CAS is a viable approach to achieve high accuracy in mandibular reconstruction and GMM can facilitate the evaluation of factors influencing reconstruction accuracy and unveil main modes of dislocation in this context.

Reconstruction of dental roots for implant planning purposes: a feasibility study.

PURPOSE: Modern virtual implant planning is a time-consuming procedure, requiring a careful assessment of prosthetic and anatomical factors within a three-dimensional dataset. In order to facilitate the planning process and provide additional information, this study examines a statistical shape model (SSM) to compute the course of dental roots based on a surface scan. MATERIAL AND METHODS: Plaster models of orthognathic patients were scanned and superimposed with three-dimensional data of a cone-beam computer tomography (CBCT). Based on the open-source software "R", including the packages Morpho, mesheR, Rvcg and RvtkStatismo, an SSM was generated to estimate the tooth axes. The accuracy of the calculated tooth axes was determined using a leave-one-out cross-validation. The deviation of tooth axis prediction in terms of angle or horizontal shift is described with mean and standard deviation. The planning dataset of an implant surgery patient was additionally analyzed using the SSM. RESULTS: 71 datasets were included in this study. The mean angle between the estimated tooth-axis and the actual tooth-axis was 7.5 ± 4.3° in the upper jaw and 6.7 ± 3.8° in the lower jaw. The horizontal deviation between the tooth axis and estimated axis was 1.3 ± 0.8 mm close to the cementoenamel junction, and 0.7 ± 0.5 mm in the apical third of the root. Results for models with one missing tooth did not differ significantly. In the clinical dataset, the SSM could give a reasonable aid for implant positioning. CONCLUSIONS: With the presented SSM, the approximate course of dental roots can be predicted based on a surface scan. There was no difference in predicting the tooth axis of existent or missing teeth. In clinical context, the estimation of tooth axes of missing teeth could serve as a reference for implant positioning. However, a higher number of training data must be achieved to obtain increasing accuracy.

Risk Factors for Prolonged Mechanical Ventilation and Delayed Extubation Following Bimaxillary Orthognathic Surgery: A Single-Center Retrospective Cohort Study.

BACKGROUND: Bimaxillary orthognathic surgery bears the risk of severe postoperative airway complications. There are no clear recommendations for immediate postoperative follow-up and monitoring. OBJECTIVE: to identify potential risk factors for prolonged mechanical ventilation and delayed extubation in patients undergoing bimaxillary orthognathic surgery. METHODS: The data of all consecutive patients undergoing bimaxillary surgery between May 2012 and October 2019 were analyzed in a single-center retrospective cohort study. The clinical data were evaluated regarding baseline characteristics and potential factors linked with delayed extubation. RESULTS: A total of 195 patients were included; 54.9% were female, and the median age was 23 years (IQR 5). The median body mass index was 23.1 (IQR 8). Nine patients (4.6%) were of American Society of Anesthesiologists Physical Status Classification System III or higher. The median duration of mechanical ventilation in the intensive care unit was 280 min (IQR, 526 min). Multivariable analysis revealed that premedication with benzodiazepines (odds ratio (OR) 2.60, 95% confidence interval (0.99; 6.81)), the male sex (OR 2.43, 95% confidence interval (1.10; 5.36)), and the duration of surgery (OR 1.54, 95% confidence interval (1.07; 2.23)) were associated with prolonged mechanical ventilation. By contrast, total intravenous anesthesia was associated with shorter ventilation time (OR 0.19, 95% confidence interval (0.09; 0.43)). CONCLUSION: premedication with benzodiazepines, the male sex, and the duration of surgery might be considered to be independent risk factors for delayed extubation in patients undergoing bimaxillary surgery.

Automated segmentation of head CT scans for computer-assisted craniomaxillofacial surgery applying a hierarchical patch-based stack of convolutional neural networks.

PURPOSE: Computer-assisted techniques play an important role in craniomaxillofacial surgery. As segmentation of three-dimensional medical imaging represents a cornerstone for these procedures, the present study was aiming at investigating a deep learning approach for automated segmentation of head CT scans. METHODS: The deep learning approach of this study was based on the patchwork toolbox, using a multiscale stack of 3D convolutional neural networks. The images were split into nested patches using a fixed 3D matrix size with decreasing physical size in a pyramid format of four scale depths. Manual segmentation of 18 craniomaxillofacial structures was performed in 20 CT scans, of which 15 were used for the training of the deep learning network and five were used for validation of the results of automated segmentation. Segmentation accuracy was evaluated by Dice similarity coefficient (DSC), surface DSC, 95% Hausdorff distance (95HD) and average symmetric surface distance (ASSD). RESULTS: Mean for DSC was 0.81 ± 0.13 (range: 0.61 [mental foramen] - 0.98 [mandible]). Mean Surface DSC was 0.94 ± 0.06 (range: 0.87 [mental foramen] - 0.99 [mandible]), with values > 0.9 for all structures but the mental foramen. Mean 95HD was 1.93 ± 2.05 mm (range: 1.00 [mandible] - 4.12 mm [maxillary sinus]) and for ASSD, a mean of 0.42 ± 0.44 mm (range: 0.09 [mandible] - 1.19 mm [mental foramen]) was found, with values < 1 mm for all structures but the mental foramen. CONCLUSION: In this study, high accuracy of automated segmentation of a variety of craniomaxillofacial structures could be demonstrated, suggesting this approach to be suitable for the incorporation into a computer-assisted craniomaxillofacial surgery workflow. The small amount of training data required and the flexibility of an open source-based network architecture enable a broad variety of clinical and research applications.

A Novel Method for Digital Reconstruction of the Mucogingival Borderline in Optical Scans of Dental Plaster Casts.

Adequate soft-tissue dimensions have been shown to be crucial for the long-term success of dental implants. To date, there is evidence that placement of dental implants should only be conducted in an area covered with attached gingiva. Modern implant planning software does not visualize soft-tissue dimensions. This study aims to calculate the course of the mucogingival borderline (MG-BL) using statistical shape models (SSM). Visualization of the MG-BL allows the practitioner to consider the soft tissue supply during implant planning. To deploy an SSM of the MG-BL, healthy individuals were examined and the intra-oral anatomy was captured using an intra-oral scanner (IOS). The empirical anatomical data was superimposed and analyzed by principal component analysis. Using a Leave-One-Out Cross Validation (LOOCV), the prediction of the SSM was compared with the original anatomy extracted from IOS. The median error for MG-BL reconstruction was 1.06 mm (0.49-2.15 mm) and 0.81 mm (0.38-1.54 mm) for the maxilla and mandible, respectively. While this method forgoes any technical work or additional patient examination, it represents an effective and digital method for the depiction of soft-tissue dimensions. To achieve clinical applicability, a higher number of datasets has to be implemented in the SSM.

Aspirin, heparin and ischemia time in microvascular free flap surgery - their influence and an optimal anticoagulation protocol.

BACKGROUND: Microvascular surgery has become a standardized technique for reconstruction of large tissue defects in Head and Neck Reconstructive Surgery. However, the main dreaded complications are thrombosis of blood vessels or major bleeding after surgery. Several different anticoagulation protocols have been established in the last decades to overcome these problems with varying degrees of success. METHODS: Over a period of six years, a standardized anticoagulation protocol including acetylsalicylic acid (ASA) and unfractionated heparin (UFH) for direct intraoperative and postoperative administration was established, optimized and compared to a previously used non-standardized protocol. A total of 178 flap surgeries were included in the development and optimization process of the protocol. RESULTS: ASA significantly increased the risk of complications when used for longer than 72 h (OR = 2.52; p = 0.002; 95% CI 1.39-4.59). Administration of UFH reduced flap loss (bolus: OR 0.68; p = 0.47; 95% CI 0.24-1.93; continuous UFH administration: OR = 0.61; p = 0.33; 95% CI 0.22-1.66), however doses greater than 500 IU/ h of UFH as continuous infusion increased the risk of complications. Reduction in ischemia time had no effect on the occurrence of complications. CONCLUSION: Anticoagulation regimes in microvascular surgery can influence the postoperative complication rate. The optimal protocol should consist of a combination of ASA and UFH for the intraoperative and direct postoperative phase. Prolonged administration of ASA as well as doses >500 IU/ h of UFH are to be avoided due to the increased complication rate.

Creating an anatomical wax-up in partially edentulous patients by means of a statistical shape model.

PURPOSE: Creating wax-ups of missing teeth for backward planning in implant surgery is a complex and time-consuming process. To facilitate implant-planning procedures, the automatic generation of a virtual wax-up would be useful. In the present study, the reconstruction of missing teeth in partially edentulous patients was performed automatically using newly developed software. The accuracy was investigated in order to test its clinical applicability. MATERIALS AND METHODS: This study presents a new method for creating an automatic virtual wax-up, which could serve as a basic tool in modern implant-planning procedures. First, a statistical shape model (SSM) based on 76 maxillary and mandibular arch scans from dentally healthy individuals was generated. Then, artificially generated tooth gaps were reconstructed. The accuracy of the workflow was evaluated on a separate testing sample of 10 individuals with artificially created tooth gaps given as a median deviation, in millimeters. Scans of three clinical cases with partial edentulism were equally reconstructed using the SSM and compared with the final prosthodontic work. RESULTS: The reconstruction of the artificial tooth gaps could be performed with the following median reconstruction accuracy: gap 21 with 0.15 mm; gap 27 with 0.20 mm; gap 34 with 0.22 mm: gap 36 with 0.22 mm; gaps 12 to 22 with 0.22 mm; gaps 34 to 36 with 0.22 mm. A scenario for an almost edentulous mandible with all teeth missing except teeth 33 and 43 could be reconstructed with a median reconstruction accuracy of 0.37 mm. The median tooth gap deviation of the SSM-based reconstruction in clinical cases differed from the final inserted prosthodontic teeth by 0.49 to 0.86 mm in median. CONCLUSION: A first feasibility of creating virtual wax-ups using an SSM could be shown. Artificially generated tooth gaps could be reconstructed close to the original with the proposed workflow. In the clinical cases, the SSM proposes an anatomical reconstruction, which does not yet consider prosthodontic aspects. To obtain clinical use, contact with antagonist teeth must be considered and more training data must be implemented. However, the presented method offers a fast and viable way for the approximate placement of missing crowns. This could be used in a digital planning workflow when implant position must be determined. (Int J Comput Dent 2022;25(4):349-0; doi: 10.3290/j.ijcd.b2599407).

Virtual reconstruction of orbital floor defects using a statistical shape model.

PURPOSE: The current standard in reconstructing defects of the orbital floor, by using the concept of mirroring, is time-consuming and ignores the natural asymmetry of the skull. By using a statistical shape model (SSM), the reconstruction can be automatized and improved in accuracy. The present study aims to show the possibilities of the virtual reconstruction of artificial defects of the orbital floor using an SSM and its potentials for clinical implementation. METHODS: Based on 131 unaffected CT scans of the midface, an SSM was created which contained the shape variability of the orbital floor. Nineteen midface CT scans, that were not included in the SSM, were manually segmented to establish ground truth (control group). Then artificial defects of larger and smaller sizes were created and reconstructed using SSM (Group I) and the gold standard of mirroring (Group II). Eventually, a comparison to the surface of the manual segmentation (control group) was performed. RESULTS: The proposed method of reconstruction using an SSM leads to more precise reconstruction results, compared with the conventional method of mirroring. Whereas mirroring led to the reconstruction errors of 0.7 mm for small defects and 0.73 mm for large defects, reconstruction using SSM led to deviations of 0.26 mm (small defect) and, respectively, 0.34 mm (large defect). CONCLUSIONS: The presented approach is an effective and accurate method for reconstructing the orbital floor. In connection with modern computer-aided design and manufacturing, individual patient-specific implants could be produced according to SSM-based reconstructions and could replace current methods using manual bending techniques. By acknowledging the natural asymmetry of the human skull, the SSM-based approach achieves higher accuracy in reconstructing injured orbits.

Analyzing the Fitting of Novel Preformed Osteosynthesis Plates for the Reduction and Fixation of Mandibular Fractures.

PURPOSE: The known preformed osteosynthesis plates for the midface are helpful tools for a precise and fast fixation of repositioned fractures. The purpose of the current study is to analyze the precision of newly developed prototypes of preformed osteosynthesis plates for the mandible. METHODS: Four newly designed preformed osteosynthesis plates, generated by a statistical shape model based on 115 CT scans, were virtually analyzed. The used plates were designed for symphyseal, parasymphyseal, angle, and condyle fractures. Each type of plate has three different sizes. For analysis, the shortest distance between the plate and the bone surface was measured, and the sum of the plate-to-bone distances over the whole surface was calculated. RESULTS: A distance between plate and bone of less than 1.5 mm was defined as sufficient fitting. The plate for symphyseal fractures showed good fitting in 90% of the cases for size M, and in 84% for size L. For parasymphyseal fractures, size S fits in 80%, size M in 68%, and size L in 65% of the cases. Angle fractures with their specific plate show good fitting for size S in 53%, size M in 60%, and size L in 47%. The preformed plate for the condyle part fits for size S in 75%, for size M in 85%, and for size L in 74% of the cases. CONCLUSION: The newly developed mandible plates show sufficient clinical fitting to ensure adequate fracture reduction and fixation.