An interpretable machine learning approach to study the relationship beetwen retrognathia and skull anatomy.

Mandibular retrognathia (C2Rm) is one of the most common oral pathologies. Acquiring a better understanding of the points of impact of C2Rm on the entire skull is of major interest in the diagnosis, treatment, and management of this dysmorphism, but also permits us to contribute to the debate on the changes undergone by the shape of the skull during human evolution. However, conventional methods have some limits in meeting these challenges, insofar as they require defining in advance the structures to be studied, and identifying them using landmarks. In this context, our work aims to answer these questions using AI tools and, in particular, machine learning, with the objective of relaying these treatments automatically. We propose an innovative methodology coupling convolutional neural networks (CNNs) and interpretability algorithms. Applied to a set of radiographs classified into physiological versus pathological categories, our methodology made it possible to: discuss the structures impacted by retrognathia and already identified in literature; identify new structures of potential interest in medical terms; highlight the dynamic evolution of impacted structures according to the level of gravity of C2Rm; provide for insights into the evolution of human anatomy. Results were discussed in terms of the major interest of this approach in the field of orthodontics and, more generally, in the field of automated processing of medical images.

The orthodontist: such a common and complex expert / L'orthodontiste : un expert si commun, si complexe

Introduction: Considered from the perspective of the finesse and skill they require of those who practice them, each of the existing trades has its own specificity. However, by referring to literature on expertise and talent7, we realize to what extent the patterns of the acquisition of expertise and its implementation can have invariants among the different trades. Methods: Human expertise has been studied in depth, among others, by cognitive sciences, psychology and neurosciences. After exposing the notions of domain of expertise, perceptual-cognitive and sensory-motor competence, the neurobiological and cognitive mechanisms of expertise demonstrating the importance of long-term memory in the acquisition of expertise, for example, by reference to the concept of chunking. Results: We will seek to determine the characteristics of the orthodontist as an expert, the implications of this quality for the expert's training process, the importance of clinical experience, the extent to which the expert can trust his/her intuition (clinical sense) in his/her daily practice and the paradigm shift constituted by the digital transition, which requires new expertise in the field of developing spatial mental models of 3D structures.

Introduction: Considérés sous l'angle de la finesse et de l'habileté qu'ils exigent de ceux qui les pratiquent, les différents métiers ont chacun leur spécificité. Cependant, en se référant à la bibliographie existant sur le talent et sur l'expertise, on se rend compte à quel point les schémas de l'acquisition de l'expertise et de sa mise en œuvre peuvent avoir des invariants dans les différents corps de métiers. Méthodes: L'expertise humaine est un sujet étudié en profondeur, entre autres, par les sciences cognitives, la psychologie et les neurosciences. Après avoir exposé les domaines d'expertise (expertise perceptuelle, expertise cognitive et expertise sensori-motrice), les mécanismes neurobiologiques et cognitifs de l'expertise démontrant l'importance de la mémoire à long terme (MLT) dans l'acquisition de l'expertise, par exemple, à travers le concept de chunking seront abordés. Résultats: Nous avons déterminé les caractéristiques de l'expert qu'est l'orthodontiste, ce que sa qualité d'expert implique dans sa formation, la portée de son expérience clinique, la mesure dans laquelle il peut faire confiance à son intuition (le fameux « sens clinique ¼) dans sa pratique quotidienne et le changement de paradigme que représente la transition numérique, laquelle entraîne de nouveaux types d'expertise dans le développement des modèles mentaux spatiaux de la structure en 3D. Ce changement de paradigme affecte également la matrice de prise de décision clinique du praticien.

Estimation of Distances within Real and Virtual Dental Models as a Function of Task Complexity.

Orthodontists have seen their practices evolve from estimating distances on plaster models to estimating distances on non-immersive virtual models. However, if the estimation of distance using real models can generate errors (compared to the real distance measured using tools), which remains acceptable from a clinical point of view, is this also the case for distance estimation performed on digital models? To answer this question, 50 orthodontists (31 women and 19 men) with an average age of 36 years (σ = 12.84; min = 23; max = 63) participated in an experiment consisting of estimating 3 types of distances (mandibular crowding, inter-canine distance, and inter-molar distance) on 6 dental models, including 3 real and 3 virtual models. Moreover, these models were of three different levels of complexity (easy, medium, and difficult). The results showed that, overall, the distances were overestimated (compared to the distance measured using an instrument) regardless of the situation (estimates on real or virtual models), but this overestimation was greater for the virtual models than for the real models. In addition, the mental load associated with the estimation tasks was considered by practitioners to be greater for the estimation tasks performed virtually compared to the same tasks performed on plaster models. Finally, when the estimation task was more complex, the number of estimation errors decreased in both the real and virtual situations, which could be related to the greater number of therapeutic issues associated with more complex models.

Open-Full-Jaw: An open-access dataset and pipeline for finite element models of human jaw.

BACKGROUND: State-of-the-art finite element studies on human jaws are mostly limited to the geometry of a single patient. In general, developing accurate patient-specific computational models of the human jaw acquired from cone-beam computed tomography (CBCT) scans is labor-intensive and non-trivial, which involves time-consuming human-in-the-loop procedures, such as segmentation, geometry reconstruction, and re-meshing tasks. Therefore, with the current practice, researchers need to spend considerable time and effort to produce finite element models (FEMs) to get to the point where they can use the models to answer clinically-interesting questions. Besides, any manual task involved in the process makes it difficult for the researchers to reproduce identical models generated in the literature. Hence, a quantitative comparison is not attainable due to the lack of surface/volumetric meshes and FEMs. METHODS: We share an open-access repository composed of 17 patient-specific computational models of human jaws and the utilized pipeline for generating them for reproducibility of our work. The used pipeline minimizes the required time for processing and any potential biases in the model generation process caused by human intervention. It gets the segmented geometries with irregular and dense surface meshes and provides reduced, adaptive, watertight, and conformal surface/volumetric meshes, which can directly be used in finite element (FE) analysis. RESULTS: We have quantified the variability of our 17 models and assessed the accuracy of the developed models from three different aspects; (1) the maximum deviations from the input meshes using the Hausdorff distance as an error measurement, (2) the quality of the developed volumetric meshes, and (3) the stability of the FE models under two different scenarios of tipping and biting. CONCLUSIONS: The obtained results indicate that the developed computational models are precise, and they consist of quality meshes suitable for various FE scenarios. We believe the provided dataset of models including a high geometrical variation obtained from 17 different models will pave the way for population studies focusing on the biomechanical behavior of human jaws.

In-house 3D printing: Why, when, and how? Overview of the national French good practice guidelines for in-house 3D-printing in maxillo-facial surgery, stomatology, and oral surgery.

3D-printing is part of the daily practice of maxillo-facial surgeons, stomatologists and oral surgeons. To date, no French health center is producing in-house medical devices according to the new European standards. Based on all the evidence-based data available, a group of experts from the French Society of Stomatology, Maxillo-Facial Surgery and Oral Surgery (Société Française de Chirurgie Maxillofaciale, Stomatologie et Chirurgie Orale, SFSCMFCO), provide good practice guidelines for in-house 3D-printing in maxillo-facial surgery, stomatology, and oral surgery. Briefly, technical considerations related to printers and CAD software, which were the main challenges in the last ten years, are now nearly trivial questions. The central current issues when planning the implementation of an in-house 3D-printing platform are economic and regulatory. Successful in-house 3D platforms rely on close collaborations between health professionals and engineers, backed by regulatory and logistic specialists. Several large-scale academic projects across France will soon provide definitive answers to governance and economical questions related to the use of in-house 3D printing.

[The digital workflow at the service of the practitioner's clinical learning] / Le workflow numérique au service de l'apprentissage clinique du praticien.

Our relationship to digital technologies will be a determining factor in building our identity as 21st century orthodontists. The digital workflow used in orthodontics can be summarized in four successive phases: diagnosis, treatment planning, computer Aid Manufacturing, therapeutic follow-up. According to Professor Stanislas Dehaene, cognitive neuroscience has identified four criteria on which learning success depends. Attention, active engagement, feedback and consolidation. Our article demonstrates that a good organization of the digital workflow, thought upstream and coherent, allows the practitioner to strengthen his learning from each treated clinical case by potentiating the four criteria of learning. This design which is a real challenge is part of an increase strategy.

[Autotransplantation of a maxillary incisor and orthodontic care: a case study]. / Autotransplantation d'une incisive maxillaire et prise en charge orthodontique : à propos d'un cas.

INTRODUCTION: Severely impacted teeth with atypical root anatomy do not respond well to orthodontic traction after surgical exposure. Consequently, they are often removed, but replacing them with dental prostheses can prove difficult in patients who are still growing. Thus, autotransplantation seems to be the only way to preserve a natural tooth and the alveolar bone. MATERIALS AND METHODS: An upper central incisor impacted in the region of the nasal cavities with an open apex was diagnosed in an 8.5-year-old female patient. The tooth displayed a curved root pressed against the maxillary cortical bone preventing orthodontic traction treatment. Through this clinical case involving autotransplantation of a maxillary incisor report and a review of the literature, this article explores the indications and exposes the different stages of this orthodontic-surgical protocol. RESULTS: In this case, autotransplantation enabled restoration of maxillary arch continuity. After two years of orthodontic treatment, the bone reconstruction of the extraction site was very satisfactory. DISCUSSION: The benefits of this technique and the precautions to be taken are discussed as well as the various protocols. The increasing success rate of this surgical procedure makes it possible to consider it as a protocol for the future.

Dental ontogeny in pliocene and early pleistocene hominins.

Until recently, our understanding of the evolution of human growth and development derived from studies of fossil juveniles that employed extant populations for both age determination and comparison. This circular approach has led to considerable debate about the human-like and ape-like affinities of fossil hominins. Teeth are invaluable for understanding maturation as age at death can be directly assessed from dental microstructure, and dental development has been shown to correlate with life history across primates broadly. We employ non-destructive synchrotron imaging to characterize incremental development, molar emergence, and age at death in more than 20 Australopithecus anamensis, Australopithecus africanus, Paranthropus robustus and South African early Homo juveniles. Long-period line periodicities range from at least 6-12 days (possibly 5-13 days), and do not support the hypothesis that australopiths have lower mean values than extant or fossil Homo. Crown formation times of australopith and early Homo postcanine teeth fall below or at the low end of extant human values; Paranthropus robustus dentitions have the shortest formation times. Pliocene and early Pleistocene hominins show remarkable variation, and previous reports of age at death that employ a narrow range of estimated long-period line periodicities, cuspal enamel thicknesses, or initiation ages are likely to be in error. New chronological ages for SK 62 and StW 151 are several months younger than previous histological estimates, while Sts 24 is more than one year older. Extant human standards overestimate age at death in hominins predating Homo sapiens, and should not be applied to other fossil taxa. We urge caution when inferring life history as aspects of dental development in Pliocene and early Pleistocene fossils are distinct from modern humans and African apes, and recent work has challenged the predictive power of primate-wide associations between hominoid first molar emergence and certain life history variables.

Dental evidence for ontogenetic differences between modern humans and Neanderthals.

Humans have an unusual life history, with an early weaning age, long childhood, late first reproduction, short interbirth intervals, and long lifespan. In contrast, great apes wean later, reproduce earlier, and have longer intervals between births. Despite 80 y of speculation, the origins of these developmental patterns in Homo sapiens remain unknown. Because they record daily growth during formation, teeth provide important insights, revealing that australopithecines and early Homo had more rapid ontogenies than recent humans. Dental development in later Homo species has been intensely debated, most notably the issue of whether Neanderthals and H. sapiens differ. Here we apply synchrotron virtual histology to a geographically and temporally diverse sample of Middle Paleolithic juveniles, including Neanderthals, to assess tooth formation and calculate age at death from dental microstructure. We find that most Neanderthal tooth crowns grew more rapidly than modern human teeth, resulting in significantly faster dental maturation. In contrast, Middle Paleolithic H. sapiens juveniles show greater similarity to recent humans. These findings are consistent with recent cranial and molecular evidence for subtle developmental differences between Neanderthals and H. sapiens. When compared with earlier hominin taxa, both Neanderthals and H. sapiens have extended the duration of dental development. This period of dental immaturity is particularly prolonged in modern humans.