Journal of Oral and Maxillofacial Surgery Special Contribution Predicting the Future Focus of Orthognathic Surgery: Outcome-Driven Planning and Treatment With Function, Esthetics, and Occlusion as Key Indicators.

As we reflect on the last 7 decades since the first descriptions of modern orthognathic surgery (OGS) by Trauner and Obwegeser, we ponder what the next "game-changers" will be over the upcoming decades. We certainly recognize the prior contributions of Hullihen in 1849 and others in the 1920s and 1930s, and the pioneering work of Tessier, Obwegeser, and Bell in the 1960s and 1970s. Although there have been some changes in osteotomy design, as well as the landmark game-changing introduction of rigid internal fixation in the 1970s and 1980s, many of the more recent major changes have occurred only in the past decade or 2. The use of personalized and precision medicine with virtual surgical planning, and patient-specific implants has been transformational. Certainly, there will be more advances in the realm of diagnosis, surgical techniques and protocols, biomaterials and tissue engineering, and surgeon and patient education. But, as an international group of orthognathic surgeons, we believe that the most significant "next big thing" will be a clinical and research focus on patient-oriented outcomes and an improved quality of life. This will require outcome-driven planning and treatment with function, esthetics, and occlusion as key outcome indicators. Here we identify some shared visions and objectives for OGS with the aim to delineate future advancements to enhance the care of patients with dentofacial deformities. While we have organized the sections to cover key areas, the fundamental concepts include advances in these areas: diagnosis and treatment planning (eg, imaging, virtual surgical planning, artificial intelligence, and point-of-care workflows); materials development (eg, patient-specific implant, three-dimensional printing, tissue engineering, biodegradable implants, bone cements, titanium and magnesium implants, and developmental and regenerative medicine); and patient management (eg, minimally-invasive surgery, clear aligner therapy, temporary anchorage devices, outpatient OGS, age-centered treatment, and augmented reality/virtual reality).

Advancements in diagnosing oral potentially malignant disorders: leveraging Vision transformers for multi-class detection.

OBJECTIVES: Diagnosing oral potentially malignant disorders (OPMD) is critical to prevent oral cancer. This study aims to automatically detect and classify the most common pre-malignant oral lesions, such as leukoplakia and oral lichen planus (OLP), and distinguish them from oral squamous cell carcinomas (OSCC) and healthy oral mucosa on clinical photographs using vision transformers. METHODS: 4,161 photographs of healthy mucosa, leukoplakia, OLP, and OSCC were included. Findings were annotated pixel-wise and reviewed by three clinicians. The photographs were divided into 3,337 for training and validation and 824 for testing. The training and validation images were further divided into five folds with stratification. A Mask R-CNN with a Swin Transformer was trained five times with cross-validation, and the held-out test split was used to evaluate the model performance. The precision, F1-score, sensitivity, specificity, and accuracy were calculated. The area under the receiver operating characteristics curve (AUC) and the confusion matrix of the most effective model were presented. RESULTS: The detection of OSCC with the employed model yielded an F1 of 0.852 and AUC of 0.974. The detection of OLP had an F1 of 0.825 and AUC of 0.948. For leukoplakia the F1 was 0.796 and the AUC was 0.938. CONCLUSIONS: OSCC were effectively detected with the employed model, whereas the detection of OLP and leukoplakia was moderately effective. CLINICAL RELEVANCE: Oral cancer is often detected in advanced stages. The demonstrated technology may support the detection and observation of OPMD to lower the disease burden and identify malignant oral cavity lesions earlier.

Site and severity of facial asymmetry after bimaxillary surgery for class III deformity: a case-control study.

OBJECTIVES: The study aimed (1) to evaluate the site and severity of facial asymmetry in Class III patients before and after bimaxillary surgery, and (2) to identify the influence of initial severity and positional jaw asymmetry on residual facial asymmetry. MATERIALS AND METHODS: Preoperative and postoperative cone-beam computed tomography of 65 patients with Class III facial asymmetry who underwent bimaxillary surgery were evaluated. Five midline and 14 paramedian facial soft tissue landmarks were identified to assess facial asymmetry. The outcomes were compared to a control group consisting of 30 age- and gender-matched Class I subjects. The postoperative positional jaw asymmetry (i.e., shift, roll, yaw) of each osteotomy segment (maxilla, mandible, chin, ramus) was also measured. RESULTS: Before surgery, the asymmetry was more severe at the chin, middle and lower contour. Bimaxillary surgery effectively corrected facial asymmetry, particularly in achieving normalization of chin deviation. However, significant asymmetry persisted postoperatively in the middle and lower contour (p < 0.001 and p < 0.01, respectively), which was affected by the positional ramus asymmetry in the roll and shift. CONCLUSIONS: Deviation of the chin, middle and lower contour contributed significantly to overall facial asymmetry in Class III asymmetry. Despite normalization of the chin deviation after bimaxillary surgery, asymmetry persisted at the middle and lower contour, primarily as the result of insufficient correction of the positional ramus asymmetry. CLINICAL RELEVANCE: Understanding the residual asymmetry after bimaxillary surgery is important for minimizing deviation and optimizing the surgical planning for its correction.

Determination of Acetylamantadine by γ-Cyclodextrin-Assisted α-HL Nanopore for Potential Cancer Prediagnosis.

The high expression of Spermidine/spermine N1-acetyltransferase (SSAT-1) is an important indicator in early cancer diagnosis. Here, we developed a nanopore-based methodology with γ-cyclodextrin as an adaptor to detect and quantify acetylamantadine, the specific SSAT-1-catalyzed product from amantadine, to accordingly reflect the activity of SSAT-1. We employ γ-cyclodextrin and report that amantadine cannot cause any secondary signals in γ-cyclodextrin-assisted α-HL nanopore, while its acetylation product, acetylamantadine, does. This allows γ-cyclodextrin to practically detect acetylamantadine in the interference of excessive amantadine, superior to the previously reported ß-cyclodextrin. The quantification of acetylamantadine was not interfered with even a 50-fold amantadine and displayed no interference in artificial urine sample analysis, which indicates the good feasibility of this nanopore-based methodology in painless cancer prediagnosis. In addition, the discrimination mechanism is also explored by 2-D nuclear magnetic resonance (NMR) and nanopore experiments with a series of adamantane derivatives with different hydrophilic and hydrophobic groups. We found that both the hydrophobic region matching effect and hydrophilic interactions play a synergistic effect in forming a host-guest complex to further generate the characteristic signals, which may provide insights for the subsequent design and study of drug-cyclodextrin complexes.

Anti-aging effect of glycerophosphocholine in Steinernema kraussei 0657L.

Glycerophosphocholine (GPC) is a water-soluble small molecule found naturally in humans and foods such as milk and soybeans. It can activate the IIS pathway by regulating the expression of daf-2, ins-18 and daf-16 genes, sek-1 and skn-1 genes of MAPK pathway, sod-3, ctl-1, gst-4 and other antioxidant genes. GPC can relieve symptoms related to aging in organisms. The aim of this study was to probe the effects of GPC on the longevity and stress resistance of the entomopathogenic nematode (EPN) Steinernema kraussei 0657L strain. The results showed that the lifespan of S. kraussei 0657L was significantly prolonged by 50 mM GPC treatment, which was 54.55% longer than that of the control (0 mM GPC). GPC significantly inhibited reactive oxygen species (ROS) and lipofuscin accumulation, but the body size and fecundity of S. kraussei 0657L had little changed. At the same time, the longevity of S. kraussei 0657L exposed to heat shock and UV-B radiation was significantly prolonged than that with no external stress. GPC supplementation increased the activity of antioxidant enzymes and corresponding gene expression. Under treatment with 50 mM GPC, the activities of superoxide dismutase and catalase were increased by 1.90- and 4.13-fold, respectively, the expression of the sod-3 and ctl-1 genes was increased by 3.60- and 0.60-fold, respectively, and harmful reactive oxygen species were removed. In addition, the expression levels of the ins-18, skn-1, sek-1 and gst-4 genes related to the insulin/IGF-1 signaling pathway were upregulated 1.04-, 1.84-, 2.21- and 1.24-fold, respectively. These results indicate that GPC is mainly involved in the lifespan regulation of S. kraussei 0657L and plays an important role in resistance to external stress by activating the insulin/IGF-1 signaling pathway and downstream PI3K/MAPK kinase, creating a new idea for improving the commercial efficacy of S. kraussei. It also laid a theoretical foundation for its further efficient development and utilization in the field of biological control.

Combining public datasets for automated tooth assessment in panoramic radiographs.

OBJECTIVE: Panoramic radiographs (PRs) provide a comprehensive view of the oral and maxillofacial region and are used routinely to assess dental and osseous pathologies. Artificial intelligence (AI) can be used to improve the diagnostic accuracy of PRs compared to bitewings and periapical radiographs. This study aimed to evaluate the advantages and challenges of using publicly available datasets in dental AI research, focusing on solving the novel task of predicting tooth segmentations, FDI numbers, and tooth diagnoses, simultaneously. MATERIALS AND METHODS: Datasets from the OdontoAI platform (tooth instance segmentations) and the DENTEX challenge (tooth bounding boxes with associated diagnoses) were combined to develop a two-stage AI model. The first stage implemented tooth instance segmentation with FDI numbering and extracted regions of interest around each tooth segmentation, whereafter the second stage implemented multi-label classification to detect dental caries, impacted teeth, and periapical lesions in PRs. The performance of the automated tooth segmentation algorithm was evaluated using a free-response receiver-operating-characteristics (FROC) curve and mean average precision (mAP) metrics. The diagnostic accuracy of detection and classification of dental pathology was evaluated with ROC curves and F1 and AUC metrics. RESULTS: The two-stage AI model achieved high accuracy in tooth segmentations with a FROC score of 0.988 and a mAP of 0.848. High accuracy was also achieved in the diagnostic classification of impacted teeth (F1 = 0.901, AUC = 0.996), whereas moderate accuracy was achieved in the diagnostic classification of deep caries (F1 = 0.683, AUC = 0.960), early caries (F1 = 0.662, AUC = 0.881), and periapical lesions (F1 = 0.603, AUC = 0.974). The model's performance correlated positively with the quality of annotations in the used public datasets. Selected samples from the DENTEX dataset revealed cases of missing (false-negative) and incorrect (false-positive) diagnoses, which negatively influenced the performance of the AI model. CONCLUSIONS: The use and pooling of public datasets in dental AI research can significantly accelerate the development of new AI models and enable fast exploration of novel tasks. However, standardized quality assurance is essential before using the datasets to ensure reliable outcomes and limit potential biases.

Detection of caries around restorations on bitewings using deep learning.

OBJECTIVE: Secondary caries lesions adjacent to restorations, a leading cause of restoration failure, require accurate diagnostic methods to ensure an optimal treatment outcome. Traditional diagnostic strategies rely on visual inspection complemented by radiographs. Recent advancements in artificial intelligence (AI), particularly deep learning, provide potential improvements in caries detection. This study aimed to develop a convolutional neural network (CNN)-based algorithm for detecting primary caries and secondary caries around restorations using bitewings. METHODS: Clinical data from 7 general dental practices in the Netherlands, comprising 425 bitewings of 383 patients, were utilized. The study used the Mask-RCNN architecture, for instance, segmentation, supported by the Swin Transformer backbone. After data augmentation, model training was performed through a ten-fold cross-validation. The diagnostic accuracy of the algorithm was evaluated by calculating the area under the Free-Response Receiver Operating Characteristics curve, sensitivity, precision, and F1 scores. RESULTS: The model achieved areas under FROC curves of 0.806 and 0.804, and F1-scores of 0.689 and 0.719 for primary and secondary caries detection, respectively. CONCLUSION: An accurate CNN-based automated system was developed to detect primary and secondary caries lesions on bitewings, highlighting a significant advancement in automated caries diagnostics. CLINICAL SIGNIFICANCE: An accurate algorithm that integrates the detection of both primary and secondary caries will permit the development of automated systems to aid clinicians in their daily clinical practice.

Three Rounds of Stability-Guided Optimization and Systematical Evaluation of Oncolytic Peptide LTX-315.

Oncolytic peptides represent promising novel candidates for anticancer treatments. In our efforts to develop oncolytic peptides possessing both high protease stability and durable anticancer efficiency, three rounds of optimization were conducted on the first-in-class oncolytic peptide LTX-315. The robust synthetic method, in vitro and in vivo anticancer activity, and anticancer mechanism were investigated. The D-type peptides represented by FXY-12 possessed significantly improved proteolytic stability and sustained anticancer efficiency. Strikingly, the novel hybrid peptide FXY-30, containing one FXY-12 and two camptothecin moieties, exhibited the most potent in vitro and in vivo anticancer activities. The mechanism explorations indicated that FXY-30 exhibited rapid membranolytic effects and induced severe DNA double-strand breaks to trigger cell apoptosis. Collectively, this study not only established robust strategies to improve the stability and anticancer potential of oncolytic peptides but also provided valuable references for the future development of D-type peptides-based hybrid anticancer chemotherapeutics.

Deep-HPI-pred: An R-Shiny applet for network-based classification and prediction of Host-Pathogen protein-protein interactions.

Host-pathogen interactions (HPIs) are vital in numerous biological activities and are intrinsically linked to the onset and progression of infectious diseases. HPIs are pivotal in the entire lifecycle of diseases: from the onset of pathogen introduction, navigating through the mechanisms that bypass host cellular defenses, to its subsequent proliferation inside the host. At the heart of these stages lies the synergy of proteins from both the host and the pathogen. By understanding these interlinking protein dynamics, we can gain crucial insights into how diseases progress and pave the way for stronger plant defenses and the swift formulation of countermeasures. In the framework of current study, we developed a web-based R/Shiny app, Deep-HPI-pred, that uses network-driven feature learning method to predict the yet unmapped interactions between pathogen and host proteins. Leveraging citrus and CLas bacteria training datasets as case study, we spotlight the effectiveness of Deep-HPI-pred in discerning Protein-protein interaction (PPIs) between them. Deep-HPI-pred use Multilayer Perceptron (MLP) models for HPI prediction, which is based on a comprehensive evaluation of topological features and neural network architectures. When subjected to independent validation datasets, the predicted models consistently surpassed a Matthews correlation coefficient (MCC) of 0.80 in host-pathogen interactions. Remarkably, the use of Eigenvector Centrality as the leading topological feature further enhanced this performance. Further, Deep-HPI-pred also offers relevant gene ontology (GO) term information for each pathogen and host protein within the system. This protein annotation data contributes an additional layer to our understanding of the intricate dynamics within host-pathogen interactions. In the additional benchmarking studies, the Deep-HPI-pred model has proven its robustness by consistently delivering reliable results across different host-pathogen systems, including plant-pathogens (accuracy of 98.4% and 97.9%), human-virus (accuracy of 94.3%), and animal-bacteria (accuracy of 96.6%) interactomes. These results not only demonstrate the model's versatility but also pave the way for gaining comprehensive insights into the molecular underpinnings of complex host-pathogen interactions. Taken together, the Deep-HPI-pred applet offers a unified web service for both identifying and illustrating interaction networks. Deep-HPI-pred applet is freely accessible at its homepage: https://cbi.gxu.edu.cn/shiny-apps/Deep-HPI-pred/ and at github: https://github.com/tahirulqamar/Deep-HPI-pred.

Is there a difference in surgical accuracy following bimaxillary surgery between cleft and non-cleft patients?

OBJECTIVES: To assess the surgical accuracy of 3D virtually planned orthognathic surgery among patients with and without cleft. MATERIALS AND METHODS: This retrospective cohort study included cleft and non-cleft patients with class III malocclusion who underwent bimaxillary surgery. CBCT scans were acquired before and immediately after surgery. 3D virtual surgical planning (VSP) was performed using CBCT and digitalized dentition data. All orthognathic surgeries were performed by the same surgeons using interocclusal splints. The primary outcome variable was surgical accuracy, defined as the difference between the planned and surgically achieved maxillary movements, quantified in six degrees of freedom. Analysis of covariance was used to test for intergroup differences in surgical accuracy after correcting for differences in the magnitude of planned surgical maxillary movements. RESULTS: Twenty-eight cleft and 33 non-cleft patients were enrolled, with mean ages of 18.5 and 25.4 years, respectively (P=0.01). No significant gender difference was present between the groups (P=0.10). After adjustment for small differences in surgical movements, no significant differences in surgical accuracy were observed between cleft and non-cleft patients. CONCLUSION: The present study demonstrates that high surgical accuracy in maxillary movements can be achieved in both cleft and non-cleft patients using VSP and interocclusal splints. CLINICAL RELEVANCE: Orthognathic cases with cleft can be performed with 3D VSP to obtain a satisfactory surgical accuracy.

High-quality genome assemblies for two Australimusa bananas (Musa spp.) and insights into regulatory mechanisms of superior fiber properties.

Bananas (Musa spp.) are monocotyledonous plants with high genetic diversity in the Musaceae family that are cultivated mainly in tropical and subtropical countries. The fruits are a popular food, and the plants themselves have diverse uses. Four genetic groups (genomes) are thought to have contributed to current banana cultivars: Musa acuminata (A genome), Musa balbisiana (B genome), Musa schizocarpa (S genome), and species of the Australimusa section (T genome). However, the T genome has not been effectively explored. Here, we present the high-quality TT genomes of two representative accessions, Abaca (Musa textilis), with high-quality natural fiber, and Utafun (Musa troglodytarum, Fe'i group), with abundant ß-carotene. Both the Abaca and Utafun assemblies comprise 10 pseudochromosomes, and their total genome sizes are 613 Mb and 619 Mb, respectively. Comparative genome analysis revealed that the larger size of the T genome is likely attributable to rapid expansion and slow removal of transposons. Compared with those of Musa AA or BB accessions or sisal (Agava sisalana), Abaca fibers exhibit superior mechanical properties, mainly because of their thicker cell walls with a higher content of cellulose, lignin, and hemicellulose. Expression of MusaCesA cellulose synthesis genes peaks earlier in Abaca than in AA or BB accessions during plant development, potentially leading to earlier cellulose accumulation during secondary cell wall formation. The Abaca-specific expressed gene MusaMYB26, which is directly regulated by MusaMYB61, may be an important regulator that promotes precocious expression of secondary cell wall MusaCesAs. Furthermore, MusaWRKY2 and MusaNAC68, which appear to be involved in regulating expression of MusaLAC and MusaCAD, may at least partially explain the high accumulation of lignin in Abaca. This work contributes to a better understanding of banana domestication and the diverse genetic resources in the Musaceae family, thus providing resources for Musa genetic improvement.

Two haplotype-resolved genome assemblies for AAB allotriploid bananas provide insights into banana subgenome asymmetric evolution and Fusarium wilt control.

Bananas (Musa spp.) are one of the world's most important fruit crops and play a vital role in food security for many developing countries. Most banana cultivars are triploids derived from inter- and intraspecific hybridizations between the wild diploid ancestor species Musa acuminate (AA) and M. balbisiana (BB). We report two haplotype-resolved genome assemblies of the representative AAB-cultivated types, Plantain and Silk, and precisely characterize ancestral contributions by examining ancestry mosaics across the genome. Widespread asymmetric evolution is observed in their subgenomes, which can be linked to frequent homologous exchange events. We reveal the genetic makeup of triploid banana cultivars and verify that subgenome B is a rich source of disease resistance genes. Only 58.5% and 59.4% of Plantain and Silk genes, respectively, are present in all three haplotypes, with >50% of genes being differentially expressed alleles in different subgenomes. We observed that the number of upregulated genes in Plantain is significantly higher than that in Silk at one-week post-inoculation with Fusarium wilt tropical race 4 (Foc TR4), which confirms that Plantain can initiate defense responses faster than Silk. Additionally, we compared genomic and transcriptomic differences among the genes related to carotenoid synthesis and starch metabolism between Plantain and Silk. Our study provides resources for better understanding the genomic architecture of cultivated bananas and has important implications for Musa genetics and breeding.

Recognition of Oligonucleotide C by Polydopamine-Coated Solid-State Nanopores.

Selective recognition of short oligonucleotides at the single-molecule level is particularly important for early disease detection and treatment. In this work, polydopamine (PDA)-coated nanopores were prepared via self-polymerization as a solid-state nanopore sensing platform for the recognition of oligonucleotide C (PolyC). The PDA coating possesses abundant active sites, such as indole, amino, carboxyl, catechol, and quinone structures, which had interactions with short oligonucleotides to slow down the translocation rate. PDA-coated nanopores selectively interact with PolyC20 by virtue of differences in hydrogen bonding forces, generating a larger blocking current, while polyA and polyT demonstrated very small blockings. At the same time, PDA-coated nanopores can sensitively distinguish PolyC with different lengths, such as 20, 14, and 10 nt. The functionalization of PDA on the solid-state nanopore provides an opportunity for the rational design of the recognition surface for biomolecules.

Comparative genomics profiling revealed multi-stress responsive roles of the CC-NBS-LRR genes in three mango cultivars.

The nucleotide-binding site-leucine-rich repeat (NBS-LRR) gene family is the largest group of disease resistance (R) genes in plants and is active in response to viruses, bacteria, and fungi usually involved in effector-triggered immunity (ETI). Pangenome-wide studies allow researchers to analyze the genetic diversity of multiple species or their members simultaneously, providing a comprehensive understanding of the evolutionary relationships and diversity present among them. The draft pan-genome of three Mangifera indica cultivars (Alphonso, Hong Xiang Ya, and Tommy atkins) was constructed and Presence/absence variants (PAVs) were filtered through the ppsPCP pipeline. As a result, 2823 genes and 5907 PAVs from H. Xiang Ya, and 1266 genes and 2098 PAVs from T. atkins were added to the reference genome. For the identification of CC-NBS-LRR (CNL) genes in these mango cultivars, this draft pan-genome study has successfully identified 47, 27, and 36 members in Alphonso, H. Xiang Ya, and T. atkins respectively. The phylogenetic analysis divided MiCNL proteins into four distinct subgroups. All MiCNL genes are unevenly distributed on chromosomes. Both tandem and segmental duplication events played a significant role in the expansion of the CNL gene family. These genes contain cis-elements related to light, stress, hormone, and development. The analysis of protein-protein interactions (PPI) revealed that MiCNL proteins interacted with other defense-responsive proteins. Gene Ontology (GO) analysis indicated that MiCNL genes play a role in defense mechanisms within the organism. The expression level of the identified genes in fruit peel was observed under disease and cold stress which showed that Mi_A_CNL13 and 14 were up-regulated while Mi_A_CNL15, 25, 30, 31, and 40 were down-regulated in disease stress. On the other hand, Mi_A_CNL2, 14, 41, and 45 were up-regulated and Mi_A_CNL47 is down-regulated in cold stress. Subsequently, the Random Forest (RF) classifier was used to assess the multi-stress response of MiCNLs. It was found that Mi_A_CNL14 is a gene that responds to multiple stress conditions. The CNLs have similar protein structures which show that they are involved in the same function. The above findings provide a foundation for a deeper understanding of the functional characteristics of the mango CNL gene family.

Solid-State Nanopore Distinguishes Ferritin and Apo-Ferritin with Identical Exteriors through Amplified Flexibility at Single-Molecule Level.

Protein identification and discrimination at the single-molecule level are big challenges. Solid-state nanopores as a sensitive biosensor have been used for protein analysis, although it is difficult to discriminate proteins with similar structures in the traditional discrimination method based on the current blockage fraction. Here, we select ferritin and apo-ferritin as the model proteins that exhibit identical exterior and different interior structures and verify the practicability of their discrimination with flexibility features by the strategy of gradually decreasing the nanopore size. We show that the larger nanopore (relative to the protein size) has no obvious effect on discriminating two proteins. Then, the comparable-sized nanopore plays a key role in discriminating two proteins based on the dwell time and fraction distribution, and the conformational changes of both proteins are also studied with this nanopore. Finally, in the smaller nanopore, the protein molecules are trapped rather than translocated, where two proteins are obviously discriminated through the current fluctuation caused by the vibration of proteins. This strategy has potential in the discrimination of other important similar proteins.

Clockwise versus counterclockwise rotation in bimaxillary surgery: 3D analysis of facial soft tissue outcomes.

PURPOSE: This study aimed to compare facial 3D soft tissue changes in subjects with Class III deformities who underwent bimaxillary clockwise (CW) and counterclockwise (CCW) rotational orthognathic surgery. METHODS: Asian Class III subjects who completed bimaxillary surgical orthodontic treatments were enrolled and categorized into CW and CCW groups based on maxillary occlusal plane alterations. Preoperative and 9-month follow-up cone-beam computed tomography (CBCT) and 3D stereophotogrammetry were obtained, superimposed, and quantified for skeletal movements and soft tissue changes in six facial regions. Inverse probability of treatment weighting (IPTW) adjusted for potential confounding factors. RESULTS: Thirty-seven subjects were included (CW group, n = 20; CCW group, n = 17). Postsurgical chin volume significantly reduced in the CW group compared to the CCW group (mean difference 6362 mm3; p = 0.037), and intergonial width significantly decreased in the CW group (mean difference 6.2 mm; p = 0.005). The postoperative alar width increased by 1.04 mm and 1.22 mm in the CW and CCW groups, respectively (p = 0.70). However, these changes were not significantly correlated to the direction of MMC pitch. CONCLUSION: Clockwise rotation of the bimaxillary complex demonstrated a significant advantage in reducing chin volume and intergonial width compared to counterclockwise rotation, leading to a reduced frontal lower face width among Asian Class III subjects.

Intra-oral scan segmentation using deep learning.

OBJECTIVE: Intra-oral scans and gypsum cast scans (OS) are widely used in orthodontics, prosthetics, implantology, and orthognathic surgery to plan patient-specific treatments, which require teeth segmentations with high accuracy and resolution. Manual teeth segmentation, the gold standard up until now, is time-consuming, tedious, and observer-dependent. This study aims to develop an automated teeth segmentation and labeling system using deep learning. MATERIAL AND METHODS: As a reference, 1750 OS were manually segmented and labeled. A deep-learning approach based on PointCNN and 3D U-net in combination with a rule-based heuristic algorithm and a combinatorial search algorithm was trained and validated on 1400 OS. Subsequently, the trained algorithm was applied to a test set consisting of 350 OS. The intersection over union (IoU), as a measure of accuracy, was calculated to quantify the degree of similarity between the annotated ground truth and the model predictions. RESULTS: The model achieved accurate teeth segmentations with a mean IoU score of 0.915. The FDI labels of the teeth were predicted with a mean accuracy of 0.894. The optical inspection showed excellent position agreements between the automatically and manually segmented teeth components. Minor flaws were mostly seen at the edges. CONCLUSION: The proposed method forms a promising foundation for time-effective and observer-independent teeth segmentation and labeling on intra-oral scans. CLINICAL SIGNIFICANCE: Deep learning may assist clinicians in virtual treatment planning in orthodontics, prosthetics, implantology, and orthognathic surgery. The impact of using such models in clinical practice should be explored.

Influence of miniscrew-assisted rapid palatal expansion (MARPE) on the interdental papilla height of maxillary central incisors.

OBJECTIVES: To evaluate the influence of miniscrew-assisted rapid palatal expansion (MARPE) on the interdental papilla height of maxillary central incisors. MATERIALS AND METHODS: Patients who completed MARPE treatment at the Radboud University Medical Center between 2018 and 2021 were included in this retrospective study. The papilla height between the maxillary central incisors was evaluated on frontal intraoral photographs taken before expansion (T0) and 1.5 years after MARPE treatment (T1) using the Jemt classification. The difference in Jemt score at T0 and T1 was the primary outcome variable. In addition, gender, age, Angle classification, MARPE duration, midpalatal suture maturation stage, maximal central diastema (MCD) immediately after expansion, crown width to length ratio (W/L), pretreatment overlap of maxillary central incisors, and the distance between the approximal contact point of the central incisors and the bone crest (CP-B) were also record. RESULTS: Twenty-two patients were included (2 men, 20 women, mean age 27.3 ± 8.8 years) and 4 patients (18%) showed a significant reduction in the Jemt score following MARPE (p = 0.04), indicating papilla recession. Interdental papilla recession was significantly associated with the increase of CP-B (p = 0.02), smaller W/L (p < 0.01), overlapping of maxillary central incisors (p < 0.01), and smaller MCD immediately after expansion (p = 0.02). CONCLUSIONS: One and a half years after MARPE, 18% of patients exhibited mild recession of papilla height of the maxillary central incisors. Overlapping and smaller W/L of maxillary central incisors were prognostic factors for interdental papilla recession. CLINICAL RELEVANCE: Clinicians have to be aware of and inform the patients about the occurrence of papilla recession following MARPE.

Skeletal structure of asymmetric mandibular prognathism and retrognathism.

BACKGROUND: This study aimed to compare the skeletal structures between mandibular prognathism and retrognathism among patients with facial asymmetry. RESULTS: Patients who had mandibular asymmetry with retrognathism (Group A) in The Netherlands were compared with those with deviated mandibular prognathism (Group B) in Korea. All the data were obtained from 3D-reformatted cone-beam computed tomography images from each institute. The right and left condylar heads were located more posteriorly, inferiorly, and medially in Group B than in Group A. The deviated side of Group A and the contralateral side of Group B showed similar condylar width and height, ramus-proper height, and ramus height. Interestingly, there were no inter-group differences in the ramus-proper heights. Asymmetric mandibular body length was the most significantly correlated with chin asymmetry in retrognathic asymmetry patients whereas asymmetric elongation of condylar process was the most important factor for chin asymmetry in deviated mandibular prognathism. CONCLUSION: Considering the 3D positional difference of gonion and large individual variations of frontal ramal inclination, significant structural deformation in deviated mandibular prognathism need to be considered in asymmetric prognathism patients. Therefore, Individually planned surgical procedures that also correct the malpositioning of the mandibular ramus are recommended especially in patients with asymmetric prognathism.

What is the impact of miniscrew-assisted rapid palatal expansion on the midfacial soft tissues? A prospective three-dimensional stereophotogrammetry study.

OBJECTIVES: To evaluate the midfacial soft tissue changes of the face in patients treated with miniscrew-assisted rapid palatal expansion (MARPE). MATERIALS AND METHODS: 3D facial images and intra-oral scans (IOS) were obtained before expansion (T0), immediately after completion of expansion (T1), and 1 year after expansion (T2). The 3D images were superimposed and two 3D distance maps were generated to measure the midfacial soft tissue changes: immediate effects between timepoints T0 and T1 and overall effects between T0 and T2. Changes of the alar width were also measured and dental expansion was measured as the interpremolar width (IPW) on IOS. RESULTS: Twenty-nine patients (22 women, 7 men, mean age 25.9 years) were enrolled. The soft tissue in the regions of the nose, left of philtrum, right of philtrum, and upper lip tubercle demonstrated a statistically significant anterior movement of 0.30 mm, 0.93 mm, 0.74 mm, and 0.81 mm, respectively (p < 0.01) immediately after expansion (T0-T1). These changes persisted as an overall effect (T0-T2). The alar width initially increased by 1.59 mm, and then decreased by 0.08 mm after 1 year, but this effect was not significant. The IPW increased by 4.58 mm and remained stable 1 year later. There was no significant correlation between the increase in IPW and alar width (r = 0.35, p = 0.06). CONCLUSIONS: Our findings indicate that MARPE results in significant but small changes of the soft tissue in the peri-oral and nasal regions. However, the clinical importance of these findings is limited. CLINICAL RELEVANCE: MARPE is an effective treatment modality to expand the maxilla, incurring only minimal and clinically insignificant changes to the midfacial soft tissues.