DentalSegmentator: Robust open source deep learning-based CT and CBCT image segmentation.

OBJECTIVES: Segmentation of anatomical structures on dento-maxillo-facial (DMF) computed tomography (CT) or cone beam computed tomography (CBCT) scans is increasingly needed in digital dentistry. The main aim of this research was to propose and evaluate a novel open source tool called DentalSegmentator for fully automatic segmentation of five anatomical structures on DMF CT and CBCT scans: maxilla/upper skull, mandible, upper teeth, lower teeth, and the mandibular canal. METHODS: A retrospective sample of 470 CT and CBCT scans was used as a training/validation set. The performance and generalizability of the tool was evaluated by comparing segmentations provided by experts and automatic segmentations in two hold-out test datasets: an internal dataset of 133 CT and CBCT scans acquired before orthognathic surgery and an external dataset of 123 CBCT scans randomly sampled from routine examinations in 5 institutions. RESULTS: The mean overall results in the internal test dataset (n = 133) were a Dice similarity coefficient (DSC) of 92.2 ± 6.3 % and a normalised surface distance (NSD) of 98.2 ± 2.2 %. The mean overall results on the external test dataset (n = 123) were a DSC of 94.2 ± 7.4 % and a NSD of 98.4 ± 3.6 %. CONCLUSIONS: The results obtained from this highly diverse dataset demonstrate that this tool can provide fully automatic and robust multiclass segmentation for DMF CT and CBCT scans. To encourage the clinical deployment of DentalSegmentator, the pre-trained nnU-Net model has been made publicly available along with an extension for the 3D Slicer software. CLINICAL SIGNIFICANCE: DentalSegmentator open source 3D Slicer extension provides a free, robust, and easy-to-use approach to obtaining patient-specific three-dimensional models from CT and CBCT scans. These models serve various purposes in a digital dentistry workflow, such as visualization, treatment planning, intervention, and follow-up.

[The challenges of artificial intelligence in odontology]. / Les enjeux de l'intelligence artificielle en odontologie.

Artificial intelligence has numerous potential applications in dentistry, as these algorithms aim to improve the efficiency and safety of several clinical situations. While the first commercial solutions are being proposed, most of these algorithms have not been sufficiently validated for clinical use. This article describes the challenges surrounding the development of these new tools, to help clinicians to keep a critical eye on this technology.

Title: Les enjeux de l'intelligence artificielle en odontologie. Abstract: Les applications potentielles de l'intelligence artificielle, ces algorithmes visant à améliorer l'efficacité et la sécurité de diverses décisions cliniques, sont nombreuses en odontologie. Alors que les premiers logiciels commerciaux commencent à être proposés, la plupart des algorithmes n'ont pas été solidement validés pour une utilisation clinique. Cet article décrit les enjeux entourant le développement de ces nouveaux outils, afin d'aider les praticiens à garder un regard éclairé et critique sur cette nouvelle approche.

Fully automatic segmentation of craniomaxillofacial CT scans for computer-assisted orthognathic surgery planning using the nnU-Net framework.

OBJECTIVES: To evaluate the performance of the nnU-Net open-source deep learning framework for automatic multi-task segmentation of craniomaxillofacial (CMF) structures in CT scans obtained for computer-assisted orthognathic surgery. METHODS: Four hundred and fifty-three consecutive patients having undergone high-resolution CT scans before orthognathic surgery were randomly distributed among a training/validation cohort (n = 300) and a testing cohort (n = 153). The ground truth segmentations were generated by 2 operators following an industry-certified procedure for use in computer-assisted surgical planning and personalized implant manufacturing. Model performance was assessed by comparing model predictions with ground truth segmentations. Examination of 45 CT scans by an industry expert provided additional evaluation. The model's generalizability was tested on a publicly available dataset of 10 CT scans with ground truth segmentation of the mandible. RESULTS: In the test cohort, mean volumetric Dice similarity coefficient (vDSC) and surface Dice similarity coefficient at 1 mm (sDSC) were 0.96 and 0.97 for the upper skull, 0.94 and 0.98 for the mandible, 0.95 and 0.99 for the upper teeth, 0.94 and 0.99 for the lower teeth, and 0.82 and 0.98 for the mandibular canal. Industry expert segmentation approval rates were 93% for the mandible, 89% for the mandibular canal, 82% for the upper skull, 69% for the upper teeth, and 58% for the lower teeth. CONCLUSION: While additional efforts are required for the segmentation of dental apices, our results demonstrated the model's reliability in terms of fully automatic segmentation of preoperative orthognathic CT scans. KEY POINTS: • The nnU-Net deep learning framework can be trained out-of-the-box to provide robust fully automatic multi-task segmentation of CT scans performed for computer-assisted orthognathic surgery planning. • The clinical viability of the trained nnU-Net model is shown on a challenging test dataset of 153 CT scans randomly selected from clinical practice, showing metallic artifacts and diverse anatomical deformities. • Commonly used biomedical segmentation evaluation metrics (volumetric and surface Dice similarity coefficient) do not always match industry expert evaluation in the case of more demanding clinical applications.

Biplanar Low-Dose Radiograph Is Suitable for Cephalometric Analysis in Patients Requiring 3D Evaluation of the Whole Skeleton.

BACKGROUND: The biplanar 2D/3D X-ray technology (BPXR) is a 2D/3D imaging system allowing simultaneous stereo-corresponding posteroanterior (PA) and lateral 2D views of the whole body. The aim of our study was to assess the feasibility of cephalometric analysis based on the BPXR lateral skull view to accurately characterize facial morphology. METHOD: A total of 17 landmarks and 11 angles were placed and/or calculated on lateral BPXR and lateral cephalograms of 13 patients by three investigators. Five methods of angle identification were performed: the direct construction of straight lines on lateral cephalograms (LC-A) and on BPXR (BPXR-A), as well as the calculation of angles based on landmark identification on lateral cephalograms (LA-L) and on BPXR with the PA image (BPXR-LPA) or without (BPXR-L). Intra- and interoperator reliability of landmark identification and angle measurement of each method were calculated. To determine the most reliable method among the BPXR-based methods, their concordance with the reference method, LC-A, was evaluated. RESULTS: Both imaging techniques had excellent intra- and interoperator reliability for landmark identification. On lateral BPXR, BPXR-A presented the best concordance with the reference method and a good intra- and interoperator reliability. CONCLUSION: BPXR provides a lateral view of the skull suitable for cephalometric analysis with good reliability.

Three-Dimensional Cephalometric Landmarking and Frankfort Horizontal Plane Construction: Reproducibility of Conventional and Novel Landmarks.

In some dentofacial deformity patients, especially patients undergoing surgical orthodontic treatments, Computed Tomography (CT) scans are useful to assess complex asymmetry or to plan orthognathic surgery. This assessment would be made easier for orthodontists and surgeons with a three-dimensional (3D) cephalometric analysis, which would require the localization of landmarks and the construction of reference planes. The objectives of this study were to assess manual landmarking repeatability and reproducibility (R&R) of a set of 3D landmarks and to evaluate R&R of vertical cephalometric measurements using two Frankfort Horizontal (FH) planes as references for horizontal 3D imaging reorientation. Thirty-three landmarks, divided into "conventional", "foraminal" and "dental", were manually located twice by three experienced operators on 20 randomly-selected CT scans of orthognathic surgery patients. R&R confidence intervals (CI) of each landmark in the -x, -y and -z directions were computed according to the ISO 5725 standard. These landmarks were then used to construct 2 FH planes: a conventional FH plane (orbitale left, porion right and left) and a newly proposed FH plane (midinternal acoustic foramen, orbitale right and left). R&R of vertical cephalometric measurements were computed using these 2 FH planes as horizontal references for CT reorientation. Landmarks showing a 95% CI of repeatability and/or reproducibility > 2 mm were found exclusively in the "conventional" landmarks group. Vertical measurements showed excellent R&R (95% CI < 1 mm) with either FH plane as horizontal reference. However, the 2 FH planes were not found to be parallel (absolute angular difference of 2.41°, SD 1.27°). Overall, "dental" and "foraminal" landmarks were more reliable than the "conventional" landmarks. Despite the poor reliability of the landmarks orbitale and porion, the construction of the conventional FH plane provided a reliable horizontal reference for 3D craniofacial CT scan reorientation.

A new protocol to accurately track long-term orthodontic tooth movement and support patient-specific numerical modeling.

Numerical simulation of long-term orthodontic tooth movement based on Finite Element Analysis (FEA) could help clinicians to plan more efficient and mechanically sound treatments. However, most of FEA studies assume idealized loading conditions and lack experimental calibration or validation. The goal of this paper is to propose a novel clinical protocol to accurately track orthodontic tooth displacement in three-dimensions (3D) and provide 3D models that may support FEA. Our protocol uses an initial cone beam computed tomography (CBCT) scan and several intra-oral scans (IOS) to generate 3D models of the maxillary bone and teeth ready for use in FEA. The protocol was applied to monitor the canine retraction of a patient during seven months. A second CBCT scan was performed at the end of the study for validation purposes. In order to ease FEA, a frictionless and statically determinate lingual device for maxillary canine retraction was designed. Numerical simulations were set up using the 3D models provided by our protocol to show the relevance of our proposal. Comparison of numerical and clinical results highlights the suitability of this protocol to support patient-specific FEA.

Relationship between European postgraduate programme accreditation and national research output: The case of the Network of Erasmus-Based European Orthodontic Postgraduate Programmes (NEBEOP) in orthodontics. A bibliometric study.

AIMS: To assess in each European country the correlation between the number of Network of Erasmus-Based European Orthodontic Postgraduate Programmes (NEBEOP) members and orthodontic research activity. Secondary objectives were to describe and quantify Europe's orthodontic research. MATERIALS AND METHODS: Articles published between 2014 and 2018 in 4 major orthodontic journals (American Journal of Orthodontics and Dentofacial Orthopedics, European Journal of Orthodontics, The Angle Orthodontist, Orthodontics and Craniofacial Research) and oral presentation abstracts of five European Orthodontic Society (EOS) congresses were analysed. For each European country, the total number of orthodontic programmes and NEBEOP memberships were collected. Descriptive statistics were performed, and Spearman correlation coefficients and risk ratios were calculated. RESULTS: 2039 articles and 261 oral presentation abstracts were included. Correlation coefficients between national number of publications, oral presentations, sum of these, all adjusted for population, and number of NEBEOP members in each country were 0.64, 0.65 and 0.62, respectively. Risk ratios were all above 1 and statistically significant for number of NEBEOP memberships per country, indicating positive associations with national orthodontic research productivity. Europe accounted for 30.5% of publications and 68.6% of oral presentations at EOS congresses during this period. European orthodontic research was not evenly distributed, since 9 countries were responsible for around 80% of the output. CONCLUSIONS: A positive association was found between number of NEBEOP programmes and national research activity. These results could be an additional argument to support similar pan-European initiatives and guidelines for postgraduate education, not only in orthodontics but in all other dental specialties.

[Automatic superimpositions of 3-dimensional craniofacial imaging: illustration with a mandibular distraction osteogenesis case]. / Superpositions automatisées d'imageries tridimensionnelles cranio-faciales : illustration par un cas clinique de distraction mandibulaire chirurgicale.

When performed several times over the course of an orthodontic or surgical orthodontic treatment, three-dimensional (3D) imaging like CBCT or CT-Scans can be superimposed. The purpose of this article is to illustrate the implementation of voxel-based 3D superimpositions with a clinical case of mandibular distraction osteogenesis A 13-year old patient underwent a surgical orthodontic treatment with a « 3D ¼ mandibular distractor. He presented a bilateral atrophy of his mandibular condyles due to a staphylococcus aureus bacteremia at birth. 3D general and mandibular regional superimpositions were performed using CT-Scan and CBCT images acquired respectively before and after completion of the distraction osteogenesis. Two superimposition methods were used, one relying on commercially-available software and the other one relying on a series of « open-source ¼ softwares. Using commercially-available software, 3D superimpositions were automatically performed in a few minutes by a sparsely-trained operator. The method relying on « open-source ¼ software asked for more training and time. Results of the superimpositions were presented under various formats. Evaluation of 3D superimposition results is still challenging, as only a qualitative evaluation can be easily performed. In years to come, this interpretation should however become more straightforward for clinicians.

Voxel-based superimposition of Cone Beam CT scans for orthodontic and craniofacial follow-up: Overview and clinical implementation.

INTRODUCTION: The increasing use of three-dimensional (3D) imaging in orthodontics has led to the development of 3D superimposition techniques. These techniques use stable anatomic structures as references in order to compare Cone Beam CT (CBCT) scans of the same subject at different time-points. Three methods have been described in the literature: landmark-based, surface-based and voxel-based 3D superimpositions. OBJECTIVE: This article focuses on the voxel-based approach, which is the most described and the only one that can be fully automatized. The aim of this paper is to offer clinicians a practical tutorial on craniofacial voxel-based 3D superimposition. MATERIAL AND METHODS: We provide an updated overview of the available implementation methods, describing their methodology, validations, main steps, advantages and drawbacks. The historical open-source method is the most widespread for research purposes, but takes around three hours to achieve for an experienced operator. Several commercially-available software perform superimpositions in a few minutes. RESULTS: We used two of the available methods to conduct the superimposition process with three representative clinical cases in order to illustrate the different types of results that can be obtained. CONCLUSIONS: Commercially-available software provide user-friendly and fully automatized superimposition methods, allowing clinicians to perform it easily and helping to reduce human error in image analysis. Still, quantitative evaluation of the results remains the main challenge of this technique.