Sung-Hoon Han, Jisup Lim, Jun-Sik Kim, Jin-Hyoung Cho, Mihee Hong, Minji Kim, Su-Jung Kim, Yoon-Ji Kim, Young Ho Kim, Sung-Hoon Lim, Sang Jin Sung, Kyung-Hwa Kang, Seung-Hak Baek, Sung-Kwon Choi, Namkug Kim. Korean J Orthod 2024;54:48-58. https://doi.org/10.4041/kjod23.075

Background and Objectives: This study aimed to perform a meta-analysis comparing the effects of corticotomy and flapless piezocision on accelerated tooth movement. Materials and Methods: A comprehensive search using a combination of controlled vocabulary (MeSH) and free-text terms was undertaken by two reviewers to identify published systematic reviews. Three major electronic databases (Medline via PubMed, Cochrane Database, and Embase) were searched up to 2 June 2023. Results: The results of the meta-analysis showed that the pooled standardized mean difference values of accumulative movement distances for flapless piezocision were 1.43 (95% CI, 0.38 to 2.48; p < 0.01), 1.09 (95% CI, −0.08 to 2.26; p = 0.07), and 0.73 (95% CI, −0.58 to 4.02; p = 0.14). The results of the meta-analysis demonstrated that the pooled SMD values of accumulative movement distances for the corticotomy were 2.76 (95% CI, 0.18 to 5.34; p = 0.04), 1.43 (95% CI, −1.10 to 3.96; p = 0.27), and 4.78 (95% CI, −4.54 to 14.10; p = 0.32). Although the test for overall effectiveness was significant for piezocision and corticotomy, there were no significant differences between piezocision and corticotomy. Conclusions: The study determined that both conventional corticotomy and flapless piezosurgery are effective as adjuncts to orthodontic treatment. Moreover, no significant difference was observed in the short-term effectiveness of canine retraction acceleration between conventional corticotomy and flapless piezocision. While piezocision may be a favorable option for orthodontic treatment, corticotomy can be considered in cases requiring additional procedures such as bone grafting.

Platelet-rich fibrin has become increasingly popular in recent years due to its remarkable capacity to accelerate the post-surgery wound healing process, reduce inflammation, and promote tissue repair. This study aimed to perform a meta-analysis to evaluate the effect of platelet-rich fibrin in mixture form with bone substitute, as a membrane, or in combination. A comprehensive search using a combination of controlled vocabulary (MeSH) and free-text terms was undertaken by two reviewers to identify published randomized clinical trials. Three major electronic databases (Medline via PubMed, Cochrane database, and Embase) and the clinical trials registry (clinicaltrials.gov) were searched up to 9 July 2023. The results of the meta-analysis showed that the pooled standardized mean difference of probing depth for platelet-rich fibrin was 0.61 (95% CI, 0.33 to 0.88). The results of the meta-analysis showed that the mean difference in clinical attachment level for platelet-rich fibrin was 0.68 (95% CI, 0.35 to 1.01). The results of the meta-analysis showed that the mean difference in bone fill for platelet-rich fibrin was 0.50 (95% CI, 0.23 to 0.78). In conclusion, the study found that platelet-rich fibrin was effective as adjunct to periodontal regeneration.

The purpose of this retrospective study was to evaluate changes in the temporomandibular joint spaces (TMJSs) in skeletal Class III adult patients with orthognathic surgery using cone-beam computed tomography (CBCT). CBCT images taken from 26 orthognathic surgery adult patients (15 females, 11 males, average 19.6 ± 2.8 years at pretreatment, range 15.8–26.8 years) with skeletal Class III malocclusion (ANB < 1°) were used for this study. TMJSs (AS, anterior space; SS, superior space; PS, posterior space; MS, medial space; CS, central space; LS, lateral space) were measured at each stage of treatment (T0, pretreatment; T1, presurgery; T2, postsurgery; T3, posttreatment, and T4, retention) and were compared according to gender, side, vertical skeletal pattern, number of surgery sites, and amount of mandibular setback. At T0, TMJSs were significantly greater in SS than in AS and PS. The ratio of AS to SS to PS was 1.0 to 1.5 to 1.1. TMJSs were significantly greater in MS and CS than in LS. The ratio of MS to CS to LS was 1.0 to 1.0 to 0.8. All TMJSs in males were significantly greater than in females except in PS. TMJSs on the left side were significantly greater than on the right side only in PS. TMJSs were not significantly different depending on the SN-MP, number of surgery sites, and amount of setback. From T0 to T4, there were no significant changes in TMJSs or their ratios according to gender, side, sella to nasion (SN), mandibular plane (MP), number of surgery sites, and amount of setback. Exceptionally, at T4, SS and CS were significantly greater in the small amount of setback group than in the large amount of setback group. There were no statistical changes in TMJSs throughout all stages when skeletal Class III patients were treated with surgery.

Background: Researchers have noted that the advent of artificial intelligence (AI) heralds a promising era, with potential to significantly enhance diagnostic and predictive abilities in clinical settings. The aim of this meta-analysis is to evaluate the discrepancies in identifying anatomical landmarks between AI and manual approaches. Methods: A comprehensive search strategy was employed, incorporating controlled vocabulary (MeSH) and free-text terms. This search was conducted by two reviewers to identify published systematic reviews. Three major electronic databases, namely, Medline via PubMed, the Cochrane database, and Embase, were searched up to May 2024. Results: Initially, 369 articles were identified. After conducting a comprehensive search and applying strict inclusion criteria, a total of ten studies were deemed eligible for inclusion in the meta-analysis. The results showed that the average difference in detecting anatomical landmarks between artificial intelligence and manual approaches was 0.35, with a 95% confidence interval (CI) ranging from −0.09 to 0.78. Additionally, the overall effect between the two groups was found to be insignificant. Upon further analysis of the subgroup of cephalometric radiographs, it was determined that there were no significant differences between the two groups in terms of detecting anatomical landmarks. Similarly, the subgroup of cone-beam computed tomography (CBCT) revealed no significant differences between the groups. Conclusions: In summary, the study concluded that the use of artificial intelligence is just as effective as the manual approach when it comes to detecting anatomical landmarks, both in general and in specific contexts such as cephalometric radiographs and CBCT evaluations.