Search Results (158)

Background/Objectives: Accurate identification of dental malocclusions from routine clinical photographs can be time-consuming and subject to interobserver variability. A YOLOv11-based deep learning approach is presented and evaluated for automatic malocclusion detection on routine intraoral photographs, testing the hypothesis that training on a structured annotation protocol enables reliable detection of multiple clinically relevant malocclusions. Methods: An anonymized dataset of 5854 intraoral photographs (frontal occlusion; right/left buccal; maxillary/mandibular occlusal) was labeled according to standardized instructions derived from the Index of Orthodontic Treatment Need (IOTN) A total of 17 clinically relevant classes were annotated with bounding boxes. Due to an insufficient number of examples, two malocclusions (transposition and non-occlusion) were excluded from our quantitative analysis. A YOLOv11 model was trained with augmented data and evaluated on a held-out test set using mean average precision at IoU 0.5 (mAP50), macro precision (macro-P), and macro recall (macro-R). Results: Across 15 analyzed classes, the model achieved 87.8% mAP50, 76.9% macro-P, and 86.1% macro-R. The highest per-class AP₅₀ was observed for Deep bite (98.8%), Diastema (97.9%), Angle Class II canine (97.5%), Anterior open bite (92.8%), Midline shift (91.8%), Angle Class II molar (91.1%), Spacing (91%), and Crowding (90.1%). Moderate performance included Anterior crossbite (88.3%), Angle Class III molar (87.4%), Head bite (82.7%), and Posterior open bite (80.2%). Lower values were seen for Angle Class III canine (76%), Posterior crossbite (75.6%), and Big overjet (75.3%). Precision–recall trends indicate earlier precision drop-off for posterior/transverse classes and comparatively more missed detections in Posterior crossbite, whereas Big overjet exhibited more false positives at the chosen threshold. Conclusion: A YOLOv11-based deep learning system can accurately detect several clinically salient malocclusions on routine intraoral photographs, supporting efficient screening and standardized documentation. Performance gaps align with limited examples and visualization constraints in posterior regions. Larger, multi-center datasets, protocol standardization, quantitative metrics, and multimodal inputs may further improve robustness. Full article

Functional appliances constitute a common treatment approach for skeletal Class II malocclusion. However, evidence regarding the effects of appliance design and manufacturing workflows on treatment outcomes remains limited. This study aimed to compare the skeletal, dentoalveolar, and soft tissue effects of conventionally fabricated, prefabricated, and digitally designed functional appliances. A total of 28 growing patients with skeletal Class II malocclusion were retrospectively assessed and evenly assigned to four treatment groups: Twin Block, PowerScope, Invisalign Mandibular Advancement, and digitally designed Herbst. Skeletal, dentoalveolar, and soft tissue parameters were evaluated using lateral cephalometric radiographs obtained before (T0) and after treatment (T1). Statistical analyses included one-way ANOVA, repeated-measures ANOVA, and the Kruskal–Wallis test. All treatment modalities demonstrated significant sagittal improvement, characterized by reductions in ANB and Wits values and increases in SNB angle and mandibular length (Co–Gn). The Twin Block appliance showed a significantly greater increase in mandibular length compared with the other groups (p = 0.037). Dentoalveolar adaptations were more pronounced in the PowerScope and Invisalign Mandibular Advancement groups. In conclusion, within the limitations of this retrospective pilot study, functional appliances with different design and manufacturing characteristics appear to produce distinct skeletal and dentoalveolar response patterns, and digitally designed systems may represent clinically effective alternatives for the treatment of skeletal Class II malocclusion; however, these findings should be considered preliminary and interpreted with caution. Full article

This study aimed to evaluate the new orthodontic TiNb wires in direct comparison to the gold standard in orthodontics, NiTi wires, when treating. There is limited literature on patients with severe malocclusions being treated from start to end with TiNb, and TiNb wires were mostly used in the final stages of treatment. Our protocol consisted of three orthodontic wires: 0.016, 0.016 × 0.025, and 0.019 × 0.025 for levelling and aligning the stage and 0.019 × 0.025 stainless steel for the finishing stage, in order to treat the same case reproduced on a modified scientific simulator. The bracket system used was made by GC slot 0.22, TiNb wires made by Morita, and NiTi wires produced by GC. We ligated all brackets using SS wire ligatures 0.008, and for anchorage, we used a transpalatal arch. The temperature of the scientific simulator was set between 20 and 25 degrees Celsius. We have used upper arches and studied the repositioning of upper ectopic canines and space closure in order to obtain an equilibrated maxillary arch. After each change of orthodontic wires, we scanned the upper arch using Medit i600 (Medit, Seoul, Republic of Korea). After concluding all stages on all upper arches, we assessed the results using LITTLE’s Irregularity index and stereo microscopy to explain metal stress on NiTi and TiNb. We propose an optimized process for using TiNb and NiTi wires when treating class II severe malocclusions with premolar extractions. Thus, we observed permanent deformation for all 0.016 TiNb wires used in the first stage, so TiNb underperformed in comparison with NiTi. Also, the Little’s Irregularity Index was superior in the NiTi wires group on 0.016 wires, verifying the change of state in the TiNb wires group. Full article

Background/Objectives: The aim of this study is to evaluate pretreatment osseous changes in the temporomandibular joint (TMJ) in orthognathic surgery patients using cone-beam computed tomography (CBCT) and to determine the distribution of the findings according to sagittal skeletal malocclusion groups. Methods: CBCT images of 103 patients (206 condyles) were retrospectively analyzed. Patients were classified as Class I, II, and III based on ANB angles. Condylar morphology was assessed for flattening, sclerosis, erosion, osteophyte formation, and subchondral bone cysts. All evaluations were performed by a single investigator (κ = 0.87). Group differences were analyzed using the chi-square test with Bonferroni correction (p < 0.05). Results: The most frequent alteration was flattening (29.6%), followed by sclerosis (11.2%), erosion (10.7%), osteophyte formation (8.3%), and subchondral bone cysts (4.4%). No significant sex-related differences were found (p > 0.05). A significant difference was observed only in sclerosis (p = 0.049), which was more prevalent in Class I than Class III. Flattening predominated in all groups, while erosion and osteophytes were more common in Class II, and sclerosis was more frequent in Class I. Conclusions: This study demonstrated that condylar flattening was the most common morphological alteration in orthognathic patients across all skeletal malocclusion groups. The higher prevalence of sclerosis in Class I compared with Class III suggests that mandibular positioning may influence adaptive and degenerative remodeling processes of the TMJ. This study emphasizes the importance of CBCT evaluation for detecting osseous changes in TMJ before orthognathic surgery and demonstrates that pre-existing alterations may impact surgical stability and postoperative functional outcomes. Full article

Background: This narrative review synthesizes evidence on AI for orthodontic malocclusion diagnosis across five imaging modalities and maps diagnostic metrics to validation tiers and regulatory readiness, with focused appraisal of Class III detection (2019–2025). Key algorithms, datasets, clinical validation, and ethical/regulatory considerations are synthesized. Methods: PubMed, Scopus, and Web of Science were searched for studies published January 2019–October 2025 using (“artificial intelligence”) AND (“malocclusion” OR “skeletal class”) AND “cephalometric.” Records were screened independently by two reviewers, with disagreements resolved by consensus. Eligible studies reported diagnostic performance (accuracy, area under the receiver operating characteristic curve (AUC), sensitivity/specificity) or landmark-localization error for AI-based malocclusion diagnosis. Data on dataset size and validation design were extracted; no formal quality appraisal or risk-of-bias assessments were undertaken, consistent with a narrative review. Results: Deep learning models show high diagnostic accuracy: cephalogram classifiers reach 90–96% for skeletal Class I/II/III; intraoral photograph models achieve 89–93% for Angle molar relationships; automated landmarkers localize ~75% of points within 2 mm. On 9870 multicenter cephalograms, landmarking achieved 0.94 ± 0.74 mm with ≈89% skeletal-class accuracy when landmarks fed a classifier. Conclusion: AI can reduce cephalometric tracing time by ~70–80% and provide consistent skeletal classification. Regulator-aligned benchmarks (multicenter external tests, subgroup reporting, explainability) and pragmatic open-data priorities are outlined, positioning AI as a dependable co-pilot once these gaps are closed. Full article

Background: The relationship between sagittal malocclusion, temporomandibular disorders (TMD), and musculoskeletal pain remains uncertain. Methods: Cross-sectional study (April 2020–August 2021) in Małopolska, Poland. Ninety participants (ages 19–35) were classified into Angle Classes I–III (n = 30 each) and examined using RDC/TMD (Axis I/II). A proprietary, nonvalidated, piloted whole-body pain-map questionnaire, presented in anterior and posterior views and subdividing the body into predefined craniofacial, spinal, and limb regions, was used to capture pain presence, Numerical Rating Scale (NRS, 0–10) scores by region, and the total number of painful sites. Group differences were analyzed using χ² and Kruskal–Wallis tests with corresponding effect sizes (measures of association strength). For NRS outcomes, a minimal clinically important difference (MCID)—defined as the smallest difference in NRS considered clinically relevant—was prespecified as approximately 1 point. Results: Occlusal class was not associated with TMD Axis I prevalence. However, sagittal malocclusion—particularly Class III—was linked to a less favorable pain profile. Left temporal pain was more frequent in Class III than in Classes I–II (p = 0.024, Cramér’s V = 0.31, medium effect), and cervical spine pain occurred more often in malocclusion groups than in Class I (p = 0.043, Cramér’s V = 0.26, small effect), indicating statistically significant associations. Cervical pain intensity was higher in Classes II–III than in Class I, with a pooled mean difference—defined as the difference in mean NRS between the combined Classes II–III and Class I—of 1.23 NRS points (95% CI 0.38–2.08), exceeding the ≈1-point MCID and suggesting a clinically important burden. The total number of painful sites was also greater in Class III than in Class I (p = 0.023, η² = 0.09; Δ = 1.40 sites, 95% CI 0.39–2.41), which indicates a statistically significant association with a medium effect size and a higher overall pain burden. Conclusions: Sagittal occlusal class was not associated with TMD diagnosis, but malocclusion—especially Class III—was associated with a more unfavorable craniofacial pain pattern and higher cervical pain burden (p ≤ 0.05), with effects of potential clinical relevance. Full article

Background: The aim of this study was to evaluate the correlation between skeletal class and morphological patterns of the mandibular symphysis. Methods: The sample consisted of 90 patients with an average age of 18 years (44 > x > 12). In order to investigate any correlation between skeletal class and morphological patterns of the mandibular symphysis, the following tests were used: Pearson’s correlation test, Spearman’s test, and the analysis of variance test (ANOVA) followed by Tukey’s post hoc HDS test. The significance level was set at 0.050. Results: Pearson’s correlation test and ANOVA showed a weak negative correlation between malocclusion and symphyseal height. Therefore, as ANB increases, symphyseal height decreases (r = −0.25, p < 0.01). In addition, a strong positive correlation was found between ANB and IMPA (r = 0.47, p < 0.01). So, as ANB increases, IMPA increases. No statistically significant association was found between symphyseal morphology and IMPA (Spearman’s test). Conclusions: The analysis revealed a weak but statistically significant negative correlation between ANB angle and symphysis height, indicating that as sagittal discrepancy increases (higher ANB), the symphysis tends to be shorter (r = −0.25, p < 0.01). A moderate positive correlation was also found between ANB and IMPA (r = 0.47, p < 0.01), suggesting that a more pronounced Class II skeletal pattern is associated with greater incisor proclination. However, no significant relationship was observed between symphysis type (A/B/C) and IMPA. When comparing skeletal classes, Class III subjects displayed significantly greater symphyseal height than Class II subjects (p < 0.001), while Class II subjects showed the highest IMPA values (p < 0.001). Full article

This study focuses on the tight reservoirs of the Jingzigou Formation in the Satan 1 block of the Jinan Sag, Junggar Basin. By integrating analyses of sedimentary microfacies, reservoir characteristics, and fracture distribution, it innovatively applies machine learning algorithms for the quantitative identification and prediction of “sweet spots”. The results indicate that subaqueous distributary channels within the braided river delta front are the dominant sedimentary microfacies. The reservoir exhibits typical tight oil characteristics, with porosity primarily below 10% and permeability generally less than 0.01 mD. Sedimentary microfacies significantly control reservoir quality, with the subaqueous distributary channels exhibiting the best physical properties. Mid- to high-angle structural fractures effectively enhance reservoir permeability and show a strong positive correlation with oil saturation. This research employs machine learning techniques—including Decision Trees, Random Forest, and Support Vector Machines—to establish a comprehensive sweet spot classification model by integrating pore-throat structure, petrophysical parameters, reservoir thickness, and fracture development intensity. Among these, the Random Forest algorithm demonstrated optimal performance across all evaluation metrics. Prediction results reveal that Class I and Class II sweet spots are predominantly distributed in the northern slope area, while Class III sweet spots are located in the central trough and southern nose-like structural zone. These classification results show a high consistency with actual production data, confirming the effectiveness and applicability of machine learning for sweet spot prediction in this study area. The research outcomes provide reliable geological guidance for well placement optimization and reserve development in the Satan 1 block, offering significant reference value for the prediction and development of sweet spots in similar heterogeneous tight oil reservoirs. Full article

Background: Class II malocclusion is one of the most prevalent dentoskeletal disorders, usually caused by mandibular retrusion. The Invisalign^® Mandibular Advancement System is an aesthetic, comfortable alternative to conventional braces for growing patients allowing mandibular projection and dental alignment. This retrospective study assessed the effectiveness of the Invisalign^® Mandibular Advancement (MA) System in growing patients with mandibular retrognathia. Methods: At treatment onset, seventeen patients were divided into the following two groups according to the aligner system used and cervical vertebral maturation stage: the Invisalign^® First group (CVM2), and the Invisalign^® Teen group (CVM3, some transitioning to CVM4), all treated with the Comprehensive Package. Treatment efficacy was evaluated through cephalometric analysis, occlusal classification, and three-dimensional tooth movement assessment. Cephalometric evaluations were performed pre-(T0) and post-treatment (TF). In addition, a clinical follow-up during the retention period was conducted to assess post-treatment stability. Results: Significant dentoalveolar and skeletal changes were observed in both groups. The Teen group showed greater mesial movement of the lower molars (3.57 ± 1.26 mm) compared to the First group (1.34 ± 0.48 mm; p < 0.001). Conversely, the First group showed greater distal movement of the upper molars (2.24 ± 0.64 mm) compared to the Teen group (1.35 ± 0.69 mm; p = 0.002). The PAR index showed significant reductions in both groups (p < 0.001), and although the Teen group achieved greater improvements, the First group demonstrated a clinically relevant reduction (23.60 vs. 19.43 points), despite two severe cases that did not achieve full Class II correction. Conclusions: Both the Invisalign^® First and Comprehensive Package for teens systems improved occlusion and skeletal patterns. These findings support the MA System as an effective option for correcting Class II malocclusion during growth. Full article

Background: The posterosuperior maxillary region poses a challenge in orthognathic surgery due to its complex three-dimensional anatomy. The pterygomaxillary suture (PMS) is a key landmark for various procedures. Understanding its anatomical relationships is essential to improving surgical precision. Methods: A retrospective analysis of CBCT images from 120 patients aged 18–70 years at Ankara Medipol University was conducted. Patients were categorized into skeletal Classes I, II, and III according to the ANB angle. Linear and angular measurements of the PMS and adjacent structures were performed. The statistical analysis included the Shapiro–Wilk, Independent t-test, Mann–Whitney U test, and regression analysis (p < 0.05). Results: There were clear differences between the skeletal groups. Class II and III patients had a lesser lateral PMS–baseline intersection distance (IV–VI) and Class II had a lesser medial PMS–baseline perpendicular distance (VV′) compared to Class I (p < 0.05). Additionally, the angle V–IV–VI was significantly narrower in Class II and III groups, indicating altered PMS orientation in these skeletal patterns. Conclusions: PMS morphology, including thickness, width, and angulation, is influenced by skeletal pattern. A preoperative CBCT assessment and individualized surgical planning are essential to ensure the safety and accuracy of Le Fort I osteotomies, especially in Class II and III patients. Full article

Background/Objectives: The hyoid bone plays a central role in functions such as swallowing, speech, and airway maintenance, and its morphology may vary with anatomical and functional parameters. This study aimed to evaluate the influence of skeletal class, respiratory mode, age, and sex on the morphometric features of the hyoid bone using cone-beam computed tomography (CBCT). Methods: A total of 560 CBCT scans (295 females, 265 males; aged 8–73 years) were retrospectively analyzed. Hyoid angle, horizontal length, and vertical height were measured using Dolphin 3D software. Participants were categorized by skeletal class (I, II, III), breathing pattern (nasal vs. oral), and age group. Data were analyzed using robust three-way ANOVA and Bonferroni post hoc tests. Results: In females, nasal breathers exhibited significantly larger hyoid angles and vertical heights than oral breathers (p < 0.001), independent of age and skeletal class. In males, both age and breathing mode significantly influenced hyoid angle and vertical length (p < 0.001). Vertical height was also significantly greater in skeletal Class I compared to Class III (p = 0.008). Notably, significant respiration–skeletal class interaction was found in females (p = 0.029) but not in males. Conclusions: Hyoid bone morphology is affected by age, breathing pattern, and skeletal class, with sex-specific differences. Nasal breathing and younger age were associated with more inferior and angularly favorable hyoid positions, which may have implications for airway stability and craniofacial development. Full article

Background: Class II malocclusion is one of the most common and challenging orthodontic problems, often requiring complex, lengthy treatment and sometimes involving extractions or surgery. While conventional fixed appliances have been the gold standard, the increasing demand for aesthetic and comfortable treatment alternatives has made clear aligners a prevalent choice. Understanding the specific biomechanics, limitations, and successful clinical strategies for using aligners—especially in managing vertical dimension and achieving skeletal correction (mandibular advancement)—is crucial for expanding non-invasive treatment options and improving outcomes for a broad range of Class II patients. Objective: The objective of this review is to examine the effectiveness and clinical approaches of clear aligners in Class II correction across different age groups, with particular attention to vertical control, mandibular advancement methods, and the predictability of tooth movements in both growing and fully mature patients. Materials and Methods: This review narratively discusses the most relevant clinical findings and practical strategies for managing Class II malocclusions with clear aligners. Particular attention is given to the integration of auxiliary devices, such as elastics, attachments, and temporary anchorage devices (TADs), which can enhance biomechanical control. Results: The combination of aligners with mini-implants and attachments resulted in a consequent decrease in excessive overjet, improvement in facial profile, and long-term stability supported by fixed retention. In growing patients, correction benefited from mandibular advancement protocols and control of molar extrusion, allowing for preservation of the mandibular plane angle. Movement predictability showed higher reliability in anterior torque movements, whereas maxillary incisor intrusion remained less predictable. Conclusions: Clear aligners, especially when supported by auxiliary device, such as mini-implants and attachments, offer a reliable and aesthetic alternative to conventional orthodontic treatment for Class II malocclusions. However, certain tooth movements may still be less predictable, highlighting the need for careful planning, individualized biomechanics, and ongoing technological improvements. Full article

Background: To investigate if the sagittal inclinations of anterior occlusal plane (AOP) and posterior occlusal plane (POP) differ between skeletal classes II and III in the mixed dentition period. Methods: Retrospective analysis of cross-sectional lateral cephalometric radiograph data of 61 children with skeletal class II and 60 children with skeletal class III (average age 8.4 ± 1.5 years). We measured the inclinations of AOP and POP to the Frankfort horizontal (FH) and the sella-nasion line (SN). Angles FH–AOP, FH–POP, SN–AOP, and SN–POP were compared between both groups using model-based ANOVA F tests and quantile regressions. Results: The differences in means between the groups came to 1.3° ± 5.1 (FH–AOP), 1.8° ± 4.6 (FH–POP), 2.6° ± 5.3 (SN–AOP), and 5.5° ± 4.4 (SN–POP). In the ANOVA, angles SN–AOP, FH–POP, and SN–POP differed significantly between the groups (p = 0.041, p = 0.006, p < 0.001, respectively). Quantile regressions showed significant between-group differences for FH–AOP (lower quartile, p = 0.012), FH–POP (upper quartile, p = 0.006), SN–AOP (median, p = 0.004; upper quartile, p = 0.011), and SN–POP (all 3 quartiles, p < 0.001). Conclusions: Distinct occlusal plane inclinations of mixed dentitions represent diagnostic traits. Longitudinal and interventional data are needed if therapeutic flattening of mixed dentition AOP or POP is beneficial in treating skeletal class II, same as their steepening in skeletal class III. Our clinical hypothesis suggests alterations by approximately 3° (AOP) and 6° (POP) but requires further study and confirmation. Full article

Background: This study aimed to evaluate the volumetric characteristics of the inferior and middle nasal conchae and maxillary sinuses in individuals with different skeletal malocclusion classes and cranio-maxillary relationships using cone beam computed tomography (CBCT). Methods: A total of 150 adult patients were retrospectively analyzed. CBCT scans were used to obtain volumetric measurements of the right and left inferior nasal conchae (INC), middle nasal conchae (MNC), and maxillary sinuses (MS). Patients were categorized into skeletal Classes I, II, or III based on ANB angles, and into retrognathic, normal, or prognathic groups according to SNA angles. Gender- and age-related differences were also analyzed. Statistical comparisons were performed using appropriate parametric and non-parametric tests. Results: Class II individuals exhibited significantly lower conchal volumes compared to Class I and III groups, while MS volumes were highest in Class II, although statistical significance was reached only on the left side. Gender differences were evident, with males presenting greater volumes than females in both the right and left INC and MS; however, significant differences were observed only for the left INC and left MS. A significant age-related decrease in left INC volume was found between the 21–30 and 61+ age groups. No statistically significant correlation was detected between conchal and sinus volumes. Conclusions: Skeletal malocclusion patterns, gender, and age significantly influence concha and sinus volumes. These findings emphasize the utility of CBCT-based three-dimensional assessments in enhancing diagnostic accuracy and informing interdisciplinary treatment planning in orthodontics and craniofacial care. Full article

Objectives: This study aimed to compare the skeletal and dentoalveolar effects of a fully customized elastodontic appliance with those of the traditional Twin Block appliance in growing patients with Class II malocclusion during the mixed dentition phase. Methods: A total of 35 patients were included: 18 treated with a customized elastodontic appliance (C-Ela group) and 17 with a Twin Block appliance (TB group). Digital dental models and lateral cephalometric radiographs were obtained at baseline (T1) and after 12 months of treatment (T2). All patients were treated by experienced clinicians according to standardized appliance protocols. Data analysis was performed by a blinded operator using Ortho Analyzer and Dolphin Imaging software. The Shapiro–Wilk test was applied to verify the normal distribution of the data. Paired-sample t-tests were used to assess within-group changes between T1 and T2. For intergroup comparisons two-tail independent-sample t-tests were used, and chi-square tests were used for categorical variables. Statistical significance was set at p < 0.05. Results: Both groups showed significant intragroup improvements in overjet (C-Ela: −2.77 ± 2.07; TB: −2.30 ± 2.72 mm), overbite (C-Ela: −1.79 ± 1.95; TB: −1.40 ± 2.65 mm), and sagittal molar relationship (p < 0.05) after treatment. The C-Ela group exhibited a significantly greater reduction in anterior dental crowding (p < 0.05) and better control of upper (C-Ela: −4.93 ± 7.65°; TB: −1.80 ± 5.72°) and lower incisor inclination (C-Ela: +1.70 ± 4.80°; TB: +4.35 ± 6.22°). In intergroup comparisons, the TB group showed a significantly greater proclination of the lower incisors at T2 (L1/Go-Gn: +4.35°; L1/A-Pog: +1.44 mm), whereas the C-Ela more effectively limited these changes (L1/Go-Gn: +1.70°; L1/A-Pog: +1.18 mm). Skeletal analysis revealed an increase in ANB angle in both groups (C-Ela: −1.49 ± 2.62°; TB: −1.78 ± 2.78°), with no statistically significant intergroup differences, and no other skeletal parameters showed significant between-group changes. Conclusions: Both appliances effectively corrected Class II malocclusions. However, the customized elastodontic device provided better dentoalveolar control, particularly in managing anterior crowding and incisor inclination. Its individualized fit may enhance biomechanical precision and improve overall treatment outcomes in growing patients. Full article