Journal of the World Federation of Orthodontists最新文献

Background: Although the use of clear aligners (CAs) has gained popularity in orthodontics, it faces challenges in extraction cases, particularly the "roller coaster effect" (mesial molar movement, distal canine tipping, and lingual incisor tipping/extrusion). Previous finite element studies focused on CAs as force-applying agents, neglecting counterforces from teeth to CAs. This study aimed to analyze how canine distal movement patterns affect incisors via tooth-aligner force interactions.

Methods: A three-dimensional finite element model was developed, including teeth, periodontal ligament, attachments, and CAs, based on cone-beam computed tomography and intraoral scanning data. Three groups simulated different canine distal movement modes: Group 1 (bodily movement with vertical rectangular attachments), Group 2 (bodily movement with paired optimized attachments), and Group 3 (distal tipping with vertical rectangular attachments). Multi-step iterative modeling methods were used to simulate long-term treatment, analyzing tooth displacements, contact stresses, and CA deformations.

Results: All groups demonstrated distal tipping of canines with the rotation center at the apical third, despite bodily movements in Groups 1 and 2. Group 2 exhibited significant canine rotation (3.36°). Incisors revealed unintended displacements: Groups 1 and 2 demonstrated higher lingual cervical pressure from CAs, causing greater buccal displacement (0.30-0.39 mm) and rotation (1.30-1.74°) compared to Group 3 (0.14-0.23 mm, 0.59-1.01°). Group 3 revealed better CA adaptation and reduced incisor movement due to minimized counterforces from actively tipped canines.

Conclusions: As current attachments cannot achieve bodily canine distalization, tipping is inevitable. Designed bodily movements induce CA deformation and incisor lingual tipping/extrusion, while active distal tipping reduces adverse effects. Orthodontists should avoid programming unattainable bodily canine movements in premolar extraction cases and prioritize tipping-based strategies with subsequent root control.

Objective: Precise identification of tooth and gingival boundaries in digital models is essential for effective orthodontic diagnosis, treatment planning, and appliance fabrication. Recent advances in artificial intelligence (AI) offer opportunities to automate this critical step with accuracy and generalizability. The objective of this study is to develop and evaluate an AI-based multiview segmentation approach that reduces manual workload, and supports daily orthodontic workflows using 3D intraoral scans.

Methods: A total of 1200 dental models from the public 3D Teeth Challenge dataset and 29 clinical 3D intraoral scans were used. Each 3D model was converted into multiple 2D images using a modified multiview approach. An AI segmentation model, based on the Mask2Former architecture, was trained to segment tooth boundaries automatically. Performance was assessed using mean Intersection over Union (mIoU) and Dice Similarity Coefficient (DICE) scores, comparing results to existing approaches.

Results: The proposed model achieved high accuracy on both public and clinical datasets. On the public testing dataset, it reached an mIoU score of 93.1% ± 0.09 and a DICE score of 95.7% ± 0.09. On the clinical testing set, it maintained strong performance with an mIoU score of 90.7% ± 0.01 and a DICE score of 94.9% ± 0.01, demonstrating its ability to generalize to real-world intraoral scans.

Conclusions: This study demonstrates the clinical potential of our AI-based modified multiview segmentation model for intraoral scans. The approach provides accurate results across varying scan qualities, supporting efficient digital model analysis in orthodontics and promising routine clinical use.

Background: To evaluate the short-term antimicrobial effects of consumer probiotic formulations on bacterial load and biofilm accumulation on clear orthodontic aligners using a randomized four-period crossover design.

Methods: Twenty Invisalign users completed four 7-day intervention periods separated by 14-day washouts. Interventions comprised: (1) probiotic gummy (Bonatona; Bacillus coagulans, 1.5 × 10⁹ CFU/dose), (2) probiotic rinse (Perfora; proprietary multi-strain blend, 1.5 × 10⁹ CFU/10 mL), (3) probiotic capsule (HealthKart; multi-strain, 3.0 × 10¹⁰ CFU/dose), and (4) probiotic drink (Yakult Original; Lacticaseibacillus paracasei Shirota, ∼6.5 × 10⁹ CFU/65 mL). Products were used as labelled; Labelled strains included Bacillus coagulans, Lacticaseibacillus paracasei Shirota, and proprietary multi-strain Lactobacillus/Bifidobacterium blends (10⁹-10¹⁰ CFU/dose). No independent verification of strain identity or viability was undertaken. After each period, 5-mm discs from standardized aligner sites were analysed for total viable counts (CFU/mL) and for biofilm matrix (EPS) and viability using confocal laser scanning microscopy (CLSM) with Concanavalin A staining. Primary analysis used linear mixed-effects models with treatment, period, and sequence as fixed effects and subject as a random intercept. Least-squares means (95 % CI) and Bonferroni-adjusted contrasts are reported. Trial registered at CTRI/2024/08/072820.

Results: All four probiotic delivery forms produced significant reductions in total viable counts and EPS fluorescence compared with pre-intervention controls (P < 0.001). CFU reductions ranged from 0.62-1.06 log₁₀ (mean reduction 3.8-4.3 × 10³ CFU/mL), with the probiotic drink showing the largest decrease (LS-mean difference vs. baseline = 1.055 log₁₀ CFU; 95% CI: 0.93-1.18; P < 0.001). Similar reductions were observed in CLSM fluorescence (mean differences 93-145 AU; all P < 0.001).

Conclusions: Short-term use of consumer probiotics delivered as a drink, rinse, gummy, or capsule, demonstrated statistically significant antimicrobial reductions in aligner biofilm. The probiotic drink yielded the greatest effect. Given the short intervention duration and label-only verification of probiotic content, these findings should be interpreted as preliminary. Larger, species-resolved studies with longer follow-up and comparison against routine mechanical cleaning are needed before clinical recommendations can be established.

The mixed dentition phase represents a fundamental step for guiding occlusal development and addressing dento-skeletal discrepancies in growing patients. Among available modalities, clear aligners (CA) have emerged as a viable option in Phase I therapy, offering benefits in terms of aesthetics, hygiene, and comfort. The present narrative review explores current evidence on CA therapy in growing patients and analyses the biomechanical issues of CA therapy. Two clinical cases are presented to illustrate treatment protocols highlighting the importance of customized digital planning in the application of CA in early orthodontic intervention to obtain aesthetic and functional results.

Background: The aim of this study was to evaluate the effectiveness and side effects of in-office 3D-printed mandibular advancement device (MAD) in the treatment of obstructive sleep apnea (OSA).

Methods: The study included 23 patients. A novel type of 3D-printed MAD was developed specifically for the treatment of OSA. At the beginning of therapy, orthodontic documentation was obtained. During follow-up visits, a cone-beam computed tomography scan was performed with the MAD in situ to verify changes in the airways, and patients were referred to a sleep laboratory to assess the effectiveness of the therapy. After 1 year of treatment, orthodontic documentation was repeated, and the side effects of MAD therapy were noted. Patients also completed questionnaire to evaluate the subjective effectiveness of the treatment.

Results: Side effects were observed during MAD therapy for OSA. These side effects were primarily related to dentoalveolar compensation, most notably changes in the position of the upper (2.22° P < 0.001) and lower (1.91°, P = 0.003) incisors and alterations in occlusion. A statistically significant increase was observed in the maximum cross-sectional area (72.62 mm², P < 0.001). The therapy was objectively successful in 74% of patients. Subjectively, all patients reported an improvement in their condition. The study did not reveal any direct association between the use of the MAD and temporomandibular joint damage in the study cohort.

Conclusions: In-office 3D-printed, titratable MADs represent easily fabricated therapeutic option for OSA treatment, with favorable clinical outcomes. They may offer a solution for a broad spectrum of patients.

Background: Class II Division 2 malocclusion presents biomechanical challenges due to retroclined maxillary incisors, often complicated by soft tissue constraints. Clear aligner therapy (CAT), though patient-friendly, shows limitations in predictably modifying labiolingual inclination. Recent attachment design advancements offer potential solutions but require biomechanical validation. Finite element modelling (FEM) serves as an effective analytical tool to evaluate these mechanics. The present study aims to compare the efficacy of three attachment geometries in expressing labiolingual inclination of maxillary incisors in a FEM model simulating Class II Division 2 malocclusion EIC.

Materials and methods: A FEM of the maxilla was generated from CBCT data of a Class II Division 2 patient. Labiolingual inclinations of 5°, 10°, 15°, 20°, and 25° were simulated on maxillary central and lateral incisors. Three attachment designs were evaluated: labial horizontal attachments (LHA), palatal horizontal attachments with labial power ridges (PHALPR) and labial-palatal reciprocal power ridges (LPRPR). Displacement and von Mises stress were calculated for teeth and supporting structures.

Results: LPRPR showed the highest displacement (0.1418 mm) and stress (384.89 MPa), followed by PHALPR (0.1211 mm; 327.35 MPa) and LHA (0.1048 mm; 204.65 MPa) respectively. Lateral incisors demonstrated greater displacement and stress than central incisors. Supporting structures showed peak stress under LPRPR conditions.

Conclusions: Attachment geometry significantly affects labiolingual inclination expression in CAT. Among the tested designs, the LPRPR configuration demonstrated superior biomechanical efficiency for managing labiolingual inclination in Class II Division 2 malocclusion.

Background: This systematic review aims to assess whether extending Alt-RAMEC (Alternating Rapid Maxillary Expansions and Constrictions) protocols from four to nine weeks yields superior skeletal, dental, and soft-tissue outcomes in growing noncleft Class III patients when compared to conventional rapid maxillary expansion (RME).

Methods: A systematic literature search was conducted across the Cochrane Central Register of Controlled Trials (CENTRAL), PubMed, Scopus, Embase, Web of Science, Google Scholar, Ovid MEDLINE, EBSCOhost, and LILACS databases over the past 20 years up to 7 January 2025. Clinical trials comparing cephalometrically conventional RME with Alt-RAMEC-assisted maxillary protraction in growing noncleft Class III subjects were included. Risk of bias was assessed using the Methodological Index for Nonrandomized Studies (MINORS) and the Cochrane Risk of Bias (RoB 2) tool. A random-effects meta-analysis using RevMan was conducted for quantitative synthesis.

Results: Out of 1847 articles screened, 24 studies were included for qualitative synthesis and 11 studies for meta-analysis. The five-week Alt-RAMEC protocol showed a statistically significant improvement in the ANB angle compared to RME (mean difference 1.37°; 95% confidence intervals 0.85-1.89; P < 0.01; c² = 2.14; I² = 0%). However, both 7-week and 9-week protocols demonstrated no significant advantage over conventional RME/facemask.

Conclusions: Only the five-week Alt-RAMEC protocol offers a statistically significant but clinically negligible improvement in maxillofacial, dental, and soft-tissue outcomes over conventional RME-assisted protraction in managing growing noncleft Class III malocclusion using a Hyrax-type expander. However, this is supported by only moderate to weak evidence.

Background: The present study assessed the performance of four prominent chatbots (ChatGPT-4o, Grok 3, Gemini Advanced, and Claude 3.7 Sonnet) in answering orthodontics- and dentofacial orthopedics-related multiple-choice questions (MCQs).

Methods: One hundred MCQs were prepared by three orthodontic consultants. These questions, each with four potential answers, covered basic and advanced orthodontic knowledge and clinical case scenarios. The chatbots' answers were assessed twice at a one-week interval. Three orthodontists' answers were reported once on a Google Form. Performance was measured as the percentage of correct answers, while consistency was measured as the McNemar test and Cohen's Kappa. A P ≤ 0.05 was considered significant.

Results: The chatbots' performance ranged from 72% to 84% and from 79% to 85% in the first and second rounds, respectively. Orthodontists' performances ranged from 71% to 84%. The highest intrachatbot consistency was observed for Grok 3 (McNemar P = 1, and Kappa = 0.793), while the lowest was for Gemini Advanced and ChatGPT-4o (McNemar P = 0.001 and 0.167, respectively, and Kappa = 0.490 each). The interchatbot consistencies showed variability over time and were significantly different between Grok 3 and Claude 3.7 Sonnet (McNemar P = 0.109, and Kappa = 0.677) in the first round and between Gemini Advanced and Claude 3.7 Sonnet (McNemar P = 0.344, and Kappa = 0.647) in the second round. The consistencies among the orthodontists and between the orthodontists and chatbots were highly variable.

Conclusions: The performance of the evaluated chatbots in answering MCQs in orthodontics and dentofacial orthopedics is still below expectations, although it was slightly better than that of orthodontists. Substantial inconsistencies existed among the chatbots, thus making them unsuitable for completely replacing existing educational methods and strongly suggesting that further improvement, continuous updating, and assessments are needed.