Automated calculation of ontology-based planning proposals: An application in reconstructive oral and maxillofacial surgery.

BACKGROUND: Structured modelling of surgical knowledge and its automated processing is still challenging. The aim of this work is to introduce a novel approach for automated calculation of ontology-based planning proposals in mandibular reconstruction and conduct a feasibility study. METHODS: The presented approach is composed of an RDF(S) ontology, a 3D mandible template and a calculator-optimiser algorithm to automatically calculate reconstruction proposals with fibula grafts. To validate the viability of the approach, a feasibility study was conducted on 164 simulated mandibular reconstructions. RESULTS: The ontology defines 244 different reconstruction variants and 80 analyses for optimization. In 146 simulated cases, a proposal could be automatically calculated (average time 8.79 ± 4.03 s). The assessments of the proposals by three clinical experts indicate the viability of the approach. CONCLUSIONS: Due to the modular separation between computational logic and domain knowledge, the developed concepts can be easily maintained, reused and adapted for other applications.

Concept for the Treatment of Class III Anomalies with a Skeletally Anchored Appliance Fabricated in the CAD/CAM Process-The MIRA Appliance.

OBJECTIVE: Intermaxillary elastics, anchored skeletally, represent a promising concept for treatment in adolescent patients with skeletal Class III anomalies. A challenge in existing concepts is the survival rate of the miniscrews in the mandible or the invasiveness of the bone anchors. A novel concept, the mandibular interradicular anchor (MIRA) appliance, for improving skeletal anchorage in the mandible, will be presented and discussed. CLINICAL CASE: In a ten-year-old female patient with a moderate skeletal Class III, the novel MIRA concept, combined with maxillary protraction, was applied. This involved the use of a CAD/CAM-fabricated indirect skeletal anchorage appliance in the mandible, with interradicularly placed miniscrews distal to each canine (MIRA appliance), and a hybrid hyrax in the maxilla with paramedian placed miniscrews. The modified alt-RAMEC protocol involved an intermittent weekly activation for five weeks. Class III elastics were worn for a period of seven months. This was followed by alignment with a multi-bracket appliance. DISCUSSION: The cephalometric analysis before and after therapy shows an improvement of the Wits value (+3.8 mm), SNA (+5°), and ANB (+3°). Dentally, a transversal postdevelopment in the maxilla (+4 mm) and a labial tip of the maxillary (+3.4°) and mandibular anterior teeth (+4.7°) with gap formation is observed. CONCLUSION: The MIRA appliance represents a less invasive and esthetic alternative to the existing concepts, especially with two miniscrews in the mandible per side. In addition, MIRA can be selected for complex orthodontic tasks, such as molar uprighting and mesialization.

3D-2D Distance Maps Conversion Enhances Classification of Craniosynostosis.

OBJECTIVE: Diagnosis of craniosynostosis using photogrammetric 3D surface scans is a promising radiation-free alternative to traditional computed tomography. We propose a 3D surface scan to 2D distance map conversion enabling the usage of the first convolutional neural networks (CNNs)-based classification of craniosynostosis. Benefits of using 2D images include preserving patient anonymity, enabling data augmentation during training, and a strong under-sampling of the 3D surface with good classification performance. METHODS: The proposed distance maps sample 2D images from 3D surface scans using a coordinate transformation, ray casting, and distance extraction. We introduce a CNN-based classification pipeline and compare our classifier to alternative approaches on a dataset of 496 patients. We investigate into low-resolution sampling, data augmentation, and attribution mapping. RESULTS: Resnet18 outperformed alternative classifiers on our dataset with an F1-score of 0.964 and an accuracy of 98.4%. Data augmentation on 2D distance maps increased performance for all classifiers. Under-sampling allowed 256-fold computation reduction during ray casting while retaining an F1-score of 0.92. Attribution maps showed high amplitudes on the frontal head. CONCLUSION: We demonstrated a versatile mapping approach to extract a 2D distance map from the 3D head geometry increasing classification performance, enabling data augmentation during training on 2D distance maps, and the usage of CNNs. We found that low-resolution images were sufficient for a good classification performance. SIGNIFICANCE: Photogrammetric surface scans are a suitable craniosynostosis diagnosis tool for clinical practice. Domain transfer to computed tomography seems likely and can further contribute to reducing ionizing radiation exposure for infants.

The value of prebent reconstruction plates and in-house 3D printing.

INTRODUCTION: Reconstruction plates, prebent on 3D printed models, are a cheap, quick, and safe solution to improve mandibular reconstruction procedures. The European Medical Device Regulation has changed recently and severely affects 3D printing in hospitals. Therefore, its legitimation must be discussed. This retrospective observational Case-Control Study aimed to evaluate the impact of prebent reconstruction plates on the condylar position in the temporomandibular joint after continuity resection of the mandible in oncological cases. MATERIALS AND METHODS: We included patients who underwent segmental mandibular resection without exarticulation of the condyle or history of prior surgery. The patients were divided into groups with prebent plates on a stereolithographic model and intraoperatively bent reconstruction plates. The segmental defects were categorized using the Jewer Classification. Computed Tomography (CT) scans before and after surgery were analyzed using a standardized method to measure the metric movement of the condyles, as well as their angulation to reference planes to quantify positional changes (primary outcome measures). The influence of the defect location, according to the Jewer classification, was evaluated as a secondary outcome measure. RESULTS: 73 patients, including 33 with preformed reconstruction plates, were included. We could show significantly fewer rotational deviations in cases of prefabricated osteosynthesis in the coronal plane (p<0,001) and in the sagittal plane (p<0,027). DISCUSSION: Using preformed reconstruction plates on 3D printed models improves the correct anatomical position of the condyle after mandibular resection. Especially Jewer-class-L defects seem to benefit from individualized reconstruction plates.

Impact of data synthesis strategies for the classification of craniosynostosis.

Introduction: Photogrammetric surface scans provide a radiation-free option to assess and classify craniosynostosis. Due to the low prevalence of craniosynostosis and high patient restrictions, clinical data are rare. Synthetic data could support or even replace clinical data for the classification of craniosynostosis, but this has never been studied systematically. Methods: We tested the combinations of three different synthetic data sources: a statistical shape model (SSM), a generative adversarial network (GAN), and image-based principal component analysis for a convolutional neural network (CNN)-based classification of craniosynostosis. The CNN is trained only on synthetic data but is validated and tested on clinical data. Results: The combination of an SSM and a GAN achieved an accuracy of 0.960 and an F1 score of 0.928 on the unseen test set. The difference to training on clinical data was smaller than 0.01. Including a second image modality improved classification performance for all data sources. Conclusions: Without a single clinical training sample, a CNN was able to classify head deformities with similar accuracy as if it was trained on clinical data. Using multiple data sources was key for a good classification based on synthetic data alone. Synthetic data might play an important future role in the assessment of craniosynostosis.

CNN-Based Classification of Craniosynostosis Using 2D Distance Maps.

Craniosynostosis is a condition associated with the premature fusion of skull sutures affecting infants. 3D photogrammetric scans are a promising alternative to computed tomography scans in cases of single suture or nonsyndromic synostosis for diagnostic imaging, but oftentimes diagnosis is not automated and relies on additional cephalometric measure-ments and the experience of the surgeon. We propose an alternative representation of the infant's head shape created from 3D photogrammetric surface scans as 2D distance maps. Those 2D distance maps rely on ray casting to extract distances from a center point to the head surface, arranging them into a 2D image grid. We use the distance map for an original convolutional neural network (CNN)-based classification approach, which is evaluated on a publicly available synthetic dataset for benchmarking and also tested on clinical data. Qualitative differences of different head shapes can be ob-served in the distance maps. The CNN-based classifier achieves accuracies of 100 % on the publicly available synthetic dataset and 98.86 % on the clinical test set. Our distance map approach demonstrates the diagnostic value of 3D photogrammetry and the possibility of automatic, CNN-based diagnosis. Future steps include the improvement of the mapping method and testing the CNN on more pathologies.

A Radiation-Free Classification Pipeline for Craniosynostosis Using Statistical Shape Modeling.

BACKGROUND: Craniosynostosis is a condition caused by the premature fusion of skull sutures, leading to irregular growth patterns of the head. Three-dimensional photogrammetry is a radiation-free alternative to the diagnosis using computed tomography. While statistical shape models have been proposed to quantify head shape, no shape-model-based classification approach has been presented yet. METHODS: We present a classification pipeline that enables an automated diagnosis of three types of craniosynostosis. The pipeline is based on a statistical shape model built from photogrammetric surface scans. We made the model and pathology-specific submodels publicly available, making it the first publicly available craniosynostosis-related head model, as well as the first focusing on infants younger than 1.5 years. To the best of our knowledge, we performed the largest classification study for craniosynostosis to date. RESULTS: Our classification approach yields an accuracy of 97.8 %, comparable to other state-of-the-art methods using both computed tomography scans and stereophotogrammetry. Regarding the statistical shape model, we demonstrate that our model performs similar to other statistical shape models of the human head. CONCLUSION: We present a state-of-the-art shape-model-based classification approach for a radiation-free diagnosis of craniosynostosis. Our publicly available shape model enables the assessment of craniosynostosis on realistic and synthetic data.

3D-Guided Face Manipulation of 2D Images for the Prediction of Post-Operative Outcome After Cranio-Maxillofacial Surgery.

Cranio-maxillofacial surgery often alters the aesthetics of the face which can be a heavy burden for patients to decide whether or not to undergo surgery. Today, physicians can predict the post-operative face using surgery planning tools to support the patient's decision-making. While these planning tools allow a simulation of the post-operative face, the facial texture must usually be captured by another 3D texture scan and subsequently mapped on the simulated face. This approach often results in face predictions that do not appear realistic or lively looking and are therefore ill-suited to guide the patient's decision-making. Instead, we propose a method using a generative adversarial network to modify a facial image according to a 3D soft-tissue estimation of the post-operative face. To circumvent the lack of available data pairs between pre- and post-operative measurements we propose a semi-supervised training strategy using cycle losses that only requires paired open-source data of images and 3D surfaces of the face's shape. After training on "in-the-wild" images we show that our model can realistically manipulate local regions of a face in a 2D image based on a modified 3D shape. We then test our model on four clinical examples where we predict the post-operative face according to a 3D soft-tissue prediction of surgery outcome, which was simulated by a surgery planning tool. As a result, we aim to demonstrate the potential of our approach to predict realistic post-operative images of faces without the need of paired clinical data, physical models, or 3D texture scans.

Mandibular Brown Tumor as a Result of Secondary Hyperparathyroidism: A Case Report with 5 Years Follow-Up and Review of the Literature.

BACKGROUND: Brown tumor is a rare skeletal manifestation of secondary hyperparathyroidism. Although diagnosis of the disease is increasingly seen in early stages due to improved screening techniques, some patients still present in a progressed disease stage. The treatment depends on tumor mass and varies from a conservative approach with supportive parathyroidectomy to extensive surgical resection with subsequent reconstruction. CASE PRESENTATION: We report a case of extensive mandibular brown tumor in a patient with a history of systemic lupus erythematosus, chronic kidney disease, and secondary hyperparathyroidism. Following radical resection of the affected bone, reconstruction could be successfully performed using a free flap. CONCLUSIONS: There were no signs of recurrence during five years of close follow-up. Increased awareness and multidisciplinary follow-ups could allow early diagnosis and prevent the need for radical therapeutical approaches.

Knowledge Acquisition and Construction of a RDF-Ontology for Computer-Assisted Surgery.

The integration of surgical knowledge into virtual planning systems plays a key role in computer-assisted surgery. The knowledge is often implicitly contained in the implemented algorithms. However, a strict separation would be desirable for reasons of maintainability, reusability and readability. Along with the Department of Oral and Maxillofacial Surgery at Heidelberg University Hospital, we are working on the development of a virtual planning system for mandibular reconstruction. In this work we describe a process for the structured acquisition and representation of surgical knowledge for mandibular reconstruction. Based on the acquired knowledge, an RDF(S) ontology was created. The ontology is connected to the virtual planning system via a SPARQL interface. The described process of knowledge acquisition can be transferred to other surgical use cases. Furthermore, the developed ontology is characterised by a reusable and easily expandable data model.

Accuracy of laser-melted patient-specific implants in genioplasty - A three-dimensional retrospective study.

PURPOSE: To assess the accuracy of laser-melted patient-specific implants (PSI) with regard to a preoperative virtual treatment plan for genioplasty based on a new analysis method without the use of landmarks. MATERIALS AND METHODS: A retrospective evaluation of a cohort of Class II and Class III patients who had undergone virtually planned orthognathic surgery (including genioplasty) was carried out. The preoperative virtual treatment plan and the postoperative outcome were fused to calculate the translational and rotational discrepancies between the 3D planning and the actual surgical outcome. RESULTS: The accuracy of left/right positioning was 0.25 ± 0.28 mm (p < 0.001), that of anterior/posterior positioning was 0.70 ± 0.64 mm (p < 0.001), and that of up/down-positioning was 0.45 ± 0.38 mm (p < 0.001). The rotational discrepancies were less than 2 deg. The virtually planned and postoperative positions of the chin differed significantly from each other (p < 0.001 for all rotational and translational discrepanices). CONCLUSION: The findings demonstrate that PSIs can transfer the planned virtual genioplasty into the operation theatre with small but significant deviations. However, since no conclusions can be drawn from the results regarding surgical success in terms of shaping the soft tissue profile as well as the esthetic result, no superiority of PSI over traditional plate osteosynthesis can be demonstrated.