Determination of prognostic factors for orthognathic surgery in children with cleft lip and/or palate

Cephalometric Parameters as Predictive Factors for Orthognathic Surgery in Unilateral Cleft Lip and Palate Patients: A Systematic Review and Meta-Analysis

To identify cephalometric parameters that could predict future need for orthognathic surgery (OGS) in patients with unilateral cleft lip and palate (UCLP).

Final search was conducted on July 7, 2024, across PubMed, Scopus, Embase, Web of Science, Cochrane, Ovid Medline, EBSCO, and LILACS, without any language and publication time restriction. Studies comparing surgical versus nonsurgical UCLP patients were included. Two independent reviewers screened studies, and those included were evaluated using Quality in Prognostic Studies (QUIPS) tool. Random-effects meta-analysis of various sagittal and vertical cephalometric parameters (SNA, SNB, ANB, mandibular plane angle [MPA], and lower anterior face height [%LFH]) was performed.

Ten studies were included in systematic review and 5 in meta-analysis. Quality in Prognostic Studies tool assessment indicated moderate risk in 6 studies, with 2 demonstrating high and low risks of bias. Meta-analysis revealed that in the 5- to 8-year age group, significant differences were observed in SNA and ANB angles between surgical and nonsurgical groups, with mean differences of 2.25° (95% confidence interval [CI] = 1.12, 3.39) and 3° (95% CI = 1.86, 4.15), respectively. In 9- to 14-year age group, significant differences were found in all 3 sagittal parameters: SNA angle difference of 2.65° (95% CI = 1.44, 3.86), SNB angle difference of 3.23° (95% CI = -4.69, -1.77), and ANB angle difference of 5.54° (95% CI = 3.66, 7.42). Vertical parameters (MPA and %LFH) were not statistically significant between groups in any age group.

Cephalometric parameters could be a valuable predictive factor for determining the future need for OGS in patients with UCLP. ANB angle has been shown to be a significant predictor for distinguishing between surgical and nonsurgical patients.

Complications of orthognathic surgery in patients with cleft lip and palate: A systematic review

OBJECTIVE

Determine the main complications of orthognathic surgery in patients with cleft lip and palate.

METHODS

PubMed, LILACS, Cochrane, Embase, Scopus, and Google Scholar were systematically reviewed. Studies addressing the complications of orthognathic surgery in patients with cleft lip and palate were included. For the search, the strategy was used with the descriptors extracted from MeSH "Cleft Palate", "Orthognathic Surgery" and "Complications". The Newcastle-Ottawa Scale (NOS) was used to assess the risk of bias in the included studies. Patients of any sex, age, and ethnicity with cleft lip and palate submitted to orthognathic surgery were included in this systematic review. The study followed the PRISMA 2020 standards and was registered in PROSPERO with protocol CRD42020195927.

RESULTS

In the initial search, 1090 articles were found and after applying the inclusion and exclusion criteria, eleven studies were selected. The sample consisted of 629 patients who underwent Orthognathic Surgery, with an average age of 21.52 years. The majority of patients (390) presented unilateral transforamen proposals. In total, 150 complications were identified in the included studies, the most frequent being relapse of movement with 77 cases (51.3 %). Other reported, but less frequent, complications were gingival recession with root exposure, premaxillary mobility, intraoperative hemorrhage, fistulas and infection and velopharyngeal impairment. Most included studies did not have a control group, making meta-analysis unfeasible. Seven of the included studies presented a low risk of bias according to the NOS.

CONCLUSIONS

Orthognathic surgery in cleft patients is a safe procedure, however it presents particularities and more complications when compared to a non-cleft patient. In this study, the most common complication found was the relapse, and the surgeon must be aware of this complication and others, and try to minimize its negative effects on the patient. We strongly recommend further investigations with detailed methodologies, control groups, well-described criteria for reported complications, and comprehensive sample characteristics to provide higher-quality evidence.

Orthognathic Surgery Rates in Furlow Double-Opposing Z-Plasty Versus Straight-Line Repair: A Review of Three Decades of Experience

OBJECTIVE

The influence of different surgical techniques on maxillary growth remains unclear. This study investigates the long-term impact of Furlow double-opposing Z-plasty versus straight-line repair (SLR) techniques on midface growth and subsequent orthognathic surgery.

DESIGN

Retrospective cohort study.

SETTING

Tertiary children's hospital.

PATIENTS/PARTICIPANTS

This study evaluated patients who underwent primary palatoplasty with Furlow or SLR techniques from 1994-2023. Patients were >14 years old at their most recent follow-up.

INTERVENTIONS

No interventions were performed.

MAIN OUTCOME MEASURE(S)

Primary outcomes were orthognathic surgery and orthognathic surgery recommendation rates to correct midface hypoplasia (MFH). Cephalometrics at the time of orthognathic surgery recommendation were traced to validate MFH.

RESULTS

In total, 1857 patients underwent palatoplasty, of which 335 met inclusion criteria (49 SLR, 286 Furlow). Average age at last follow-up was 18.5±2.6 years. Patients who underwent Furlow versus SLR showed no significant difference in orthognathic surgery rates (p=0.428) or recommendation for orthognathic surgery rates (p=0.900). Patients recommended to undergo orthognathic surgery had more negative ANB angles (p<0.001) and smaller SNA angles (p<0.001) than patients not recommended for orthognathic surgery, demonstrating maxillary hypoplasia. Upon multivariate regression, patients with Veau III and IV clefts had an increased need for orthognathic surgery, p=0.047 and p=0.008, respectively.

CONCLUSIONS

Our findings suggest that higher cleft severity contributes to future orthognathic surgery. However, palatoplasty technique did not influence orthognathic surgery rates. Our results provide valuable data when surgeons are considering the impact of palatoplasty technique on sagittal growth restriction.

Artificial Intelligence Used for Diagnosis in Facial Deformities: A Systematic Review

AI is included in a lot of different systems. In facial surgery, there are some AI-based software programs oriented to diagnosis in facial surgery. This study aims to evaluate the capacity and training of models for diagnosis of dentofacial deformities in class II and class III patients using artificial intelligence and the potential use for indicating orthognathic surgery. The search strategy is from 1943 to April 2024 in PubMed, Embase, Scopus, Lilacs, and Web of Science. Studies that used imaging to assess anatomical structures, airway volume, and craniofacial positions using the AI algorithm in the human population were included. The methodological quality of the studies was assessed using the Effective Public Health Practice Project instrument. The systematic search identified 697 articles. Eight studies were obtained for descriptive analysis after exclusion according to our inclusion and exclusion criteria. All studies were retrospective in design. A total of 5552 subjects with an age range between 14.7 and 56 years were obtained; 2474 (44.56%) subjects were male, and 3078 (55.43%) were female. Six studies were analyzed using 2D imaging and obtained highly accurate results in diagnosing skeletal features and determining the need for orthognathic surgery, and two studies used 3D imaging for measurement and diagnosis. Limitations of the studies such as age, diagnosis in facial deformity, and the included variables were observed. Concerning the overall analysis bias, six studies were at moderate risk due to weak study designs, while two were at high risk of bias. We can conclude that, with the few articles included, using AI-based software allows for some craniometric recognition and measurements to determine the diagnosis of facial deformities using mainly 2D analysis. However, it is necessary to perform studies based on three-dimensional images, increase the sample size, and train models in different populations to ensure accuracy of AI applications in this field. After that, the models can be trained for dentofacial diagnosis.

Prognostic Factors for Orthognathic Surgery in Children With Cleft Lip and/or Palate: Dentition and Palatal Morphology

To determine dental and palatal morphology in children with cleft lip and/or palate (CL/P) and identify morphological prognostic factors for orthognathic surgery (OGS).

Retrospective cohort study.

Orthodontic department of a university dental hospital.

This study included 80 patients with bilateral and unilateral CL/P who had lateral cephalograms at the ages of 7 (T1), 15 (T2) years, and a dental plaster model at T1.

Plaster models at T1 were scanned with a three-dimensional (3D) scanner. Morphological features were extracted from 3D models with geometric morphometrics software as principal components (PCs). The combinations of the PCs and other predictive factors (ie, the No. of clefts in the lip and alveolus, the palatal repair method, sex, cephalometric variables at T1, and the No. of missing teeth) were examined by logistic regression to determine the predictability for OGS. The need for OGS and skeletal and dental discrepancies at T2 were examined as outcomes.

Shrinkage of the palate, including vertical shallowing and transverse narrowing of the posterior maxilla and cleft-side asymmetry of the anterior maxilla at T1, as well as the No. of clefts in the lip and alveolus, the palatal repair method, male sex, several cephalometric variables for the sagittal and vertical dimensions, and the No. of missing teeth, were found to be predictive factors for OGS.

Morphological prognostic factors for OGS in children with CL/P were determined.

A Narrative Review of Artificial Intelligence (AI) for Objective Assessment of Aesthetic Endpoints in Plastic Surgery

Notoriously characterized by subjectivity and lack of solid scientific validation, reporting aesthetic outcome in plastic surgery is usually based on ill-defined end points and subjective measures very often from the patients' and/or providers' perspective. With the tremendous increase in demand for all types of aesthetic procedures, there is an urgent need for better understanding of aesthetics and beauty in addition to reliable and objective outcome measures to quantitate what is perceived as beautiful and attractive. In an era of evidence-based medicine, recognition of the importance of science with evidence-based approach to aesthetic surgery is long overdue. View the many limitations of conventional outcome evaluation tools of aesthetic interventions, objective outcome analysis provided by tools described to be reliable is being investigated such as advanced artificial intelligence (AI). The current review is intended to analyze available evidence regarding advantages as well as limitations of this technology in objectively documenting outcome of aesthetic interventions. It has shown that some AI applications such as facial emotions recognition systems are capable of objectively measuring and quantitating patients' reported outcomes and defining aesthetic interventions success from the patients' perspective. Though not reported yet, observers' satisfaction with the results and their appreciation of aesthetic attributes may also be measured in the same manner.Level of Evidence III This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

Applications of artificial intelligence and machine learning in orthognathic surgery: A scoping review

Over the recent years, Artificial Intelligence (AI) has been progressing rapidly with its ability to mimic human cognitive functions. The potential applications of AI technology in diagnosis, treatment planning, and prognosis prediction have been demonstrated in various studies. The present scoping review aimed to provide an overview of AI and Machine Learning (ML) algorithms and their applications in orthognathic surgery. A comprehensive search was conducted in databases including PubMed, Embase, Scopus, Web of Science and OVID Medline until November 2021. This scoping review was conducted following the PRISMA-ScR guidelines. After applying the inclusion and exclusion criteria, a total of 19 studies were included for final review. AI has profoundly impacted the diagnosis and prediction of orthognathic surgeries with a clinically acceptable accuracy range. Furthermore, AI reduces the work burden of the clinician by eliminating the tedious registration procedures, thereby helping in efficient and automated planning. However, focussing on the research gaps, there is a need to foster the AI models/algorithms to contemporize their efficiency in clinical decision making, diagnosis and surgical planning in future studies.

Clinical Applications of Artificial Intelligence and Machine Learning in Children with Cleft Lip and Palate-A Systematic Review

OBJECTIVE

The objective of this systematic review was (a) to explore the current clinical applications of AI/ML (Artificial intelligence and Machine learning) techniques in diagnosis and treatment prediction in children with CLP (Cleft lip and palate), (b) to create a qualitative summary of results of the studies retrieved.

MATERIALS AND METHODS

An electronic search was carried out using databases such as PubMed, Scopus, and the Web of Science Core Collection. Two reviewers searched the databases separately and concurrently. The initial search was conducted on 6 July 2021. The publishing period was unrestricted; however, the search was limited to articles involving human participants and published in English. Combinations of Medical Subject Headings (MeSH) phrases and free text terms were used as search keywords in each database. The following data was taken from the methods and results sections of the selected papers: The amount of AI training datasets utilized to train the intelligent system, as well as their conditional properties; Unilateral CLP, Bilateral CLP, Unilateral Cleft lip and alveolus, Unilateral cleft lip, Hypernasality, Dental characteristics, and sagittal jaw relationship in children with CLP are among the problems studied.

RESULTS

Based on the predefined search strings with accompanying database keywords, a total of 44 articles were found in Scopus, PubMed, and Web of Science search results. After reading the full articles, 12 papers were included for systematic analysis.

CONCLUSIONS

Artificial intelligence provides an advanced technology that can be employed in AI-enabled computerized programming software for accurate landmark detection, rapid digital cephalometric analysis, clinical decision-making, and treatment prediction. In children with corrected unilateral cleft lip and palate, ML can help detect cephalometric predictors of future need for orthognathic surgery.

Where Is the Artificial Intelligence Applied in Dentistry? Systematic Review and Literature Analysis

This literature research had two main objectives. The first objective was to quantify how frequently artificial intelligence (AI) was utilized in dental literature from 2011 until 2021. The second objective was to distinguish the focus of such publications; in particular, dental field and topic. The main inclusion criterium was an original article or review in English focused on dental utilization of AI. All other types of publications or non-dental or non-AI-focused were excluded. The information sources were Web of Science, PubMed, Scopus, and Google Scholar, queried on 19 April 2022. The search string was “artificial intelligence” AND (dental OR dentistry OR tooth OR teeth OR dentofacial OR maxillofacial OR orofacial OR orthodontics OR endodontics OR periodontics OR prosthodontics). Following the removal of duplicates, all remaining publications were returned by searches and were screened by three independent operators to minimize the risk of bias. The analysis of 2011–2021 publications identified 4413 records, from which 1497 were finally selected and calculated according to the year of publication. The results confirmed a historically unprecedented boom in AI dental publications, with an average increase of 21.6% per year over the last decade and a 34.9% increase per year over the last 5 years. In the achievement of the second objective, qualitative assessment of dental AI publications since 2021 identified 1717 records, with 497 papers finally selected. The results of this assessment indicated the relative proportions of focal topics, as follows: radiology 26.36%, orthodontics 18.31%, general scope 17.10%, restorative 12.09%, surgery 11.87% and education 5.63%. The review confirms that the current use of artificial intelligence in dentistry is concentrated mainly around the evaluation of digital diagnostic methods, especially radiology; however, its implementation is expected to gradually penetrate all parts of the profession.