Effect of socioeconomic and malocclusion-related factors on duration of orthodontic treatment by fixed appliance: A retrospective study

OBJECTIVES

The aims of this study were to evaluate the effect of related factors that influence orthodontic treatment time and to identify the predictors of orthodontic treatment duration in a Chinese population.

MATERIALS AND METHODS

Information for 29 sociodemographic, malocclusion and orthodontic treatment characteristics was collected. Patients were divided into two groups: the duration ≤24 months group and duration >24 months group. The treatment dates of the initial visit and end of orthodontic treatment were obtained to calculate duration. The data were subjected to univariate and multivariate logistic regression modelling to quantify the association between characteristics and the treatment duration; odds ratios (ORs) and 95% confidence intervals (95% CIs) are reported.

RESULTS

Of 2120 patients, 704 patients (mean age, 15.9 ± 6.0 years) were included. Age, extraction, Bolton ratio (overall), rotated teeth, overjet and crowding (lower arch) were predictors for duration. The nomogram based on predictive factors exhibited strong discrimination ability, with concordance indices of 0.755 (95% CI = 0.712-0.798) in the training cohort model and 0.717 (95% CI = 0.647-0.787) in the validation cohort model. The calibration curves for the training and validation cohorts showed that the probabilities of the nomogram agreed well with actual probabilities.

CONCLUSIONS

Young age, non-extraction and severe crowding (lower arch) can increase the chance of durations of ≤24 months. Rotated teeth, excessive overjet and Bolton ratio (overall) can increase the chance of durations of >24 months.

Evaluating the accuracy of automated cephalometric analysis based on artificial intelligence

BACKGROUND

The purpose of this study was to evaluate the accuracy of automatic cephalometric landmark localization and measurements using cephalometric analysis via artificial intelligence (AI) compared with computer-assisted manual analysis.

METHODS

Reconstructed lateral cephalograms (RLCs) from cone-beam computed tomography (CBCT) in 85 patients were selected. Computer-assisted manual analysis (Dolphin Imaging 11.9) and AI automatic analysis (Planmeca Romexis 6.2) were used to locate 19 landmarks and obtain 23 measurements. Mean radial error (MRE) and successful detection rate (SDR) values were calculated to assess the accuracy of automatic landmark digitization. Paired t tests and Bland‒Altman plots were used to compare the differences and consistencies in cephalometric measurements between manual and automatic analysis programs.

RESULTS

The MRE for 19 cephalometric landmarks was 2.07 ± 1.35 mm with the automatic program. The average SDR within 1 mm, 2 mm, 2.5 mm, 3 and 4 mm were 18.82%, 58.58%, 71.70%, 82.04% and 91.39%, respectively. Soft tissue landmarks (1.54 ± 0.85 mm) had the most consistency, while dental landmarks (2.37 ± 1.55 mm) had the most variation. In total, 15 out of 23 measurements were within the clinically acceptable level of accuracy, 2 mm or 2°. The rates of consistency within the 95% limits of agreement were all above 90% for all measurement parameters.

CONCLUSION

Automatic analysis software collects cephalometric measurements almost effectively enough to be acceptable in clinical work. Nevertheless, automatic cephalometry is not capable of completely replacing manual tracing. Additional manual supervision and adjustment for automatic programs can increase accuracy and efficiency.

Mechanical force induces macrophage-derived exosomal UCHL3 promoting bone marrow mesenchymal stem cell osteogenesis by targeting SMAD1

BACKGROUND

Orthodontic tooth movement (OTM), a process of alveolar bone remodelling, is induced by mechanical force and regulated by local inflammation. Bone marrow-derived mesenchymal stem cells (BMSCs) play a fundamental role in osteogenesis during OTM. Macrophages are mechanosensitive cells that can regulate local inflammatory microenvironment and promote BMSCs osteogenesis by secreting diverse mediators. However, whether and how mechanical force regulates osteogenesis during OTM via macrophage-derived exosomes remains elusive.

RESULTS

Mechanical stimulation (MS) promoted bone marrow-derived macrophage (BMDM)-mediated BMSCs osteogenesis. Importantly, when exosomes from mechanically stimulated BMDMs (MS-BMDM-EXOs) were blocked, the pro-osteogenic effect was suppressed. Additionally, compared with exosomes derived from BMDMs (BMDM-EXOs), MS-BMDM-EXOs exhibited a stronger ability to enhance BMSCs osteogenesis. At in vivo, mechanical force-induced alveolar bone formation was impaired during OTM when exosomes were blocked, and MS-BMDM-EXOs were more effective in promoting alveolar bone formation than BMDM-EXOs. Further proteomic analysis revealed that ubiquitin carboxyl-terminal hydrolase isozyme L3 (UCHL3) was enriched in MS-BMDM-EXOs compared with BMDM-EXOs. We went on to show that BMSCs osteogenesis and mechanical force-induced bone formation were impaired when UCHL3 was inhibited. Furthermore, mothers against decapentaplegic homologue 1 (SMAD1) was identified as the target protein of UCHL3. At the mechanistic level, we showed that SMAD1 interacted with UCHL3 in BMSCs and was downregulated when UCHL3 was suppressed. Consistently, overexpression of SMAD1 rescued the adverse effect of inhibiting UCHL3 on BMSCs osteogenesis.

CONCLUSIONS

This study suggests that mechanical force-induced macrophage-derived exosomal UCHL3 promotes BMSCs osteogenesis by targeting SMAD1, thereby promoting alveolar bone formation during OTM.