Orthodontics & Craniofacial Research最新文献

Objective

To evaluate the accuracy of artificial intelligence (AI) in predicting the effects of headgear (HG) and/or functional appliance (FA) on the maxillo-mandibular growth in preadolescent patients with skeletal Class II (C-II) malocclusion.

Materials and Methods

The study included 206 Japanese preadolescent C-II patients treated with HG and/or FA, with serial lateral cephalograms taken at ages of 8 (T0) and 10 (T1). A single orthodontist with 7 years of experience identified 28 hard-tissue cephalometric landmarks. A Treatment Prediction Graph Convolutional Neural Network (TP-GCNN), integrating a high-resolution network and a graph neural network, was trained and validated using the landmarks' x- and y-coordinates. Data was split into training, validation and testing sets (ratio of 8:1:1; n = 164, n = 21 and n = 21). Model performance was assessed using the values of prediction error (PE, excellent, ≤ 0.5 mm; very good, 0.5–1.0 mm; good, 1.0–1.5 mm; acceptable, 1.5–2.0 mm; unsatisfactory, > 2.0 mm) and the degree of accurate prediction percentage (APP; very high, ≥ 90%; high, 70%–90%; medium, 50%–70%; low, < 50%).

Results

The mean PE value was 1.45 mm. In terms of PE, all landmarks showed the accuracy above the ‘acceptable’ category. In terms of APP, ‘High’ APP was observed at Hinge axis, Pterygoid point, A-point, PNS, ANS, R1, R3 and Articulare. However, ‘Low’ APP was noted for Pm, Pogonion, B-point and Menton. The remaining landmarks demonstrated ‘Medium’ APP.

Conclusion

This study demonstrates the potential of AI to reliably predict the effects of HG and/or FA treatment in preadolescent patients with Class II malocclusion.

Objective

The study aims to evaluate the effectiveness of deep learning algorithms in skeletal age estimation by comparing the diagnostic reliability of five different hand-wrist maturation (HWM) assessment methods.

Materials and Methods

A total of 6572 hand-wrist radiographs from orthodontic patients aged 8–16 years were retrospectively analysed. Radiographs were categorised into five groups based on HWM classification methods: (I) Björk's nine-stage, (II) Hägg and Taranger's five-stage, (III) Chapman's four-stage, (IV) three-stage hook of hamate ossification based and (V) simplified three-stage Björk's classification based. YOLOv8x-based deep learning models were trained separately for each group. The dataset was split into training, validation and test subsets. Performance was evaluated using accuracy, precision, recall, F1 score and AUC metrics.

Results

The YOLOv8x-cls model demonstrated high classification performance across all five groups. Group IV and Group II achieved the highest accuracy and F1 scores, with average F1 values of 0.99 and 0.96, respectively. Group III and Group V also showed strong performance (F1 = 0.93 and 0.92). In Group I, slightly lower classification performance was observed in the S-H2 and MP3-Cap stages (F1 = 0.72–0.74), which correspond to the pubertal growth peak, while early and late skeletal maturation stages were classified with high accuracy and F1 scores. ROC curve analysis further supported these findings, with AUC values for MP3-Cap and S-H2 recorded as 0.70 and 0.75, respectively, whereas higher AUC values were achieved in most other stages across all groups.

Conclusion

Deep learning models proved effective in evaluating skeletal maturation across five different HWM methods. Particularly high performance was observed in anatomically distinct regions such as the MP3, adductor sesamoid and hamate bone, which can be reliably identified by general dentists, enabling earlier referrals and timely orthodontic interventions.

Objectives

To assess and compare treatment effects and treatment time in adolescents with crowded and displaced teeth during and after non-extraction treatments using a passive self-ligating bracket system (PSLB) and a conventional bracket system (CB).

Materials and Methods

Consecutive adolescents (12–17 years old) with crowded and displaced teeth were randomised through computer generated block randomisation in a two-arm parallel-group design, to non-extraction fixed appliance treatment with either PSLB (Damon Q, n = 62) or CB (Victory, n = 70) at four orthodontic clinics. Study models and cephalograms were collected at baseline, post-alignment and post-treatment. Primary outcome was assessed with weighted Peer Assessment Rating index (wPAR) and secondary outcomes with Little's Irregularity Index (LII), and as transversal width (mm), incisor inclination (°), position (mm) and treatment time (months).

Results

Intergroup differences in wPAR with mean score reductions of −24.07 (CB) and −22.11 (PSLB), LII upper/lower arch reductions of −9.02/−5.96 (CB) and −8.44/−5.29 (PSLB), and mean treatment times of 21.74 (CB) and 24.35 (PSLB) months were non-significant (NS). Lateral expansion was greater in the PSLB group during alignment; mean intergroup maxillary differences (MD) were 1.35 at inter-canines, 1.21 mm at first inter-premolars, and mandibular MD were 0.75 at first, 0.76 mm at second inter-premolars (p ≤ 0.019). Greater incisor proclination was observed in the CB group (L1NB, MD = 2.28°; ILiML, MD = 2.23°) (p ≤ 0.016). Intergroup differences post-treatment were NS.

Conclusion

Great occlusal treatment outcomes were observed in both groups with no significant difference in treatment time. Although the expansion patterns differed during alignment, no significant intergroup difference remained after treatment.

Trial Registration

The protocol is registered on ClinicalTrials.gov (NCT05664282)

Objective

To classify and characterise facial asymmetry (FA) phenotypes in adult patients with bilateral cleft lip and palate (BCLP) and skeletal Class III (C-III) malocclusion.

Materials and Methods

The samples consisted of 72 adult BCLP patients (56 males, 16 females; mean age, 21.0 years), who were candidates for orthognathic surgery (OGS) or had undergone OGS for the correction of C-III malocclusion. Because BCLP patients have two cleft sides, the vertically longer defect (VLD) side was used for the reference side. Twenty-three cephalometric parameters were measured in posteroanterior cephalograms taken at least 1month before OGS. Principal component analysis was performed to obtain seven representative parameters [ANS-deviation (mm), U1-deviation (mm), L1-deviation (mm), Me-deviation (mm), MaxAntOP-cant (°), MaxPostOP-cant (°), ManBorder-cant (°)]. K-means cluster analysis was conducted using these representative parameters. Differences in cephalometric parameters among the clusters were statistically analysed.

Results

FA phenotypes were classified based on the deviation direction towards the VLD or less VLD side and the upward or downward cant in the VLD side. The classifications were: (1) Symmetry type (20.8%); (2) MxMn-VLD-dev & MxMn-no-cant type (22.2%); (3) MxMn-less-VLD-dev & Mnbase-VLD-down-cant type (9.7%); (4) Mn-less-VLD-dev & MxMn-VLD-down-cant type (20.8%); (5) MxMn-no-dev & MxMn-VLD-up-cant type (19.4%), and (6) MxMn-VLD-dev & MxMn-VLD-up-cant type (6.9%). The possible etiologies of FA phenotypes included ANS deviation, movement of the maxillary incisor by pre-operative orthodontic treatment, and adaptive growth or compensatory growth of the maxilla and/or mandible.

Conclusion

This FA phenotype classification could serve as a guideline for diagnosis and OGS planning for BCLP patients.

Objectives

Oral myofunctional therapy (OMFT) has been proposed as a potential treatment for improving low tongue posture (LTP) and alleviating obstructive sleep apnea. However, its effectiveness remains uncertain. This study aimed to quantify the effects of OMFT on LTP.

Materials and Methods

This study analysed pre- and post-treatment cone-beam computed tomography images from 43 children with LTP treated with rapid maxillary expansion (RME) only (mean age: 9.09 years, no-OMFT group), 46 children with LTP treated with RME plus OMFT (mean age: 9.40 years, OMFT group), and 20 children (mean age: 9.87 years, control group). The primary outcomes measured were intraoral airway volume (an indicator of LTP), nasal airway pressure differences (assessed using computational fluid dynamics), and maxillary dental arch width. Comparisons were made among groups, with the frequency and relationship between these measures investigated.

Results

There were no significant differences between OMFT and no-OMFT groups before treatment. Post-treatment, the OMFT group showed significantly smaller intraoral airway volume (0.66 cm³) compared to the no-OMFT group (1.34 cm³). Nasal airway pressure drop was also significantly lower in the OMFT group (44.2 Pa) than in the no-OMFT group (143.3 Pa).

The LTP improvement rate was significantly higher in the OMFT group (76.1%) than in the no-OMFT group (51.2%). Similarly, the improvement rate of nasal airway obstruction was significantly higher in the OMFT group than in the no-OMFT group.

Conclusion

OMFT improves LTP and nasal airway obstruction. Improvements in nasal airway obstruction by OMFT are likely correlated with the observed improvements in LTP.

Objectives

Orthodontically induced inflammatory root resorption (OIIRR) is an inflammation induced by excessive orthodontic force in the periodontium. The aim of this study was to identify the role of ferroptosis in periodontal ligament cells in OIIRR and its underlying mechanism.

Materials and Methods

Human periodontal ligament cells (hPDLCs) were subjected to 2 g/cm² of compressive stress along with 20 ng/mL of interleukin-1β (IL-1β) stimulation for 24 h. The occurrence of ferroptosis in hPDLCs is detected by Western blot analysis and ferroptosis-related kits. For in vivo analyses, a mouse OIIRR model was established, and the ACSL4 inhibitor (Rosiglitazone, Rosi) was administered intraperitoneally. Micro-CT was employed to evaluate the occurrence of OIIRR, and immunohistochemical staining (IHC) was performed to detect changes in ferroptosis-related markers.

Results

Upon applying compressive stress and IL-1β stimulation to hPDLCs, Western blot analysis showed an upregulation of the ferroptosis marker ACSL4 and a downregulation of GPX4, along with significant increases in ROS, MDA and Fe²⁺ levels, indicating enhanced ferroptosis. However, when hPDLCs were treated with Rosi (1 μM), ferroptosis was alleviated. Micro-CT analysis showed that root resorption volume decreased after Rosi application. Additionally, Ferroptosis-related markers changed significantly in the PDLCs in mice via IHC staining.

Conclusions

ACSL4-mediated ferroptosis, triggered by compressive stress and inflammation in hPDLCs, contributed to the development of OIIRR. Rosi has been shown to inhibit OIIRR and serve as a novel therapeutic target for OIIRR treatment.