Efficacy of the methods of age determination using artificial intelligence in panoramic radiographs - a systematic review.

The aim of this systematic review is to analyze the literature to determine whether the methods of artificial intelligence are effective in determining age in panoramic radiographs. Searches without language and year limits were conducted in PubMed/Medline, Embase, Web of Science, and Scopus databases. Hand searches were also performed, and unpublished manuscripts were searched in specialized journals. Thirty-six articles were included in the analysis. Significant differences in terms of root mean square error and mean absolute error were found between manual methods and artificial intelligence techniques, favoring the use of artificial intelligence (p < 0.00001). Few articles compared deep learning methods with machine learning models or manual models. Although there are advantages of machine learning in data processing and deep learning in data collection and analysis, non-comparable data was a limitation of this study. More information is needed on the comparison of these techniques, with particular emphasis on time as a variable.

Mandibular shape prediction model using machine learning techniques.

OBJECTIVE: To create a mandibular shape prediction model using machine learning techniques and geometric morphometrics. MATERIALS AND METHODS: Six hundred twenty-nine radiographs were used to select the most appropriate craniomaxillary variables in different craniofacial pattern classifications using a support vector machine. To obtain the three-dimensional mandibular shape, a Procrustes fit was used on 55 tomograms, in which 17 three-dimensional landmarks were digitized. A partial least square regression was employed to find the best covariation between craniomaxillary angles and the symmetric components of mandibular shape. The model was applied to a new sample of six tomograms and evaluated by the mean absolute error. Each mandible predicted was assessed using the Hausdorff distance (HDu) and a color scale. The model was also exploratively applied to six new radiographs. RESULTS: Covariation was 88.66% with a significance of < 0.0001 explained by twelve craniomaxillary variables. Low differences between the original and predicted models were obtained, with a mean absolute error of 0.0143. The mean distance between meshes ranged from 0.0033 to 0.0059 HDu and each color scale demonstrated general similarity between the surfaces. CONCLUSIONS: This approach offered promising results in obtaining a mandibular prediction model that enhances shape properties in an economical way and is applicable to a Latin American population. Clinical proof of this method will require further studies with larger samples. CLINICAL RELEVANCE: This method offers a reliable, economic alternative to traditional mandibular prediction methods and is applicable to the Latin American population.

Efficiency of maxillomandibular advancement for the treatment of obstructive apnea syndrome: a comprehensive overview of systematic reviews.

OBJECTIVES: To evaluate the efficiency of maxillomandibular advancement using aggregated individual patient data from multiple studies. MATERIALS AND METHODS: This overview was structured according to the PICO strategy. It adhered to the Preferred Reporting Items for Systematic Reviews and Meta-analyses checklist and was recorded on the international prospective register of systematic reviews (PROSPERO-CRD42020206135). Searches were conducted in the PubMed/MEDLINE, Scopus, Embase, Web of Science, LILACS, and Cochrane databases for studies published until January 1, 2021. Data from the included studies were collected by one author, while another reviewed the compilation. RESULTS: Twelve systematic reviews were included. The outcome measures studied were the apnea-hypopnea index, respiratory disturbance index, mean oxygen saturation, lowest oxygen saturation, sleepiness data, posterior air space, sella-nasion point A angle, sella-nasion point B angle, surgical success, and surgical cure in patients who underwent surgery. The AMSTAR scale presented moderate evaluations, with grades varying between 6 and 10 points. The Glenny scale revealed that the study selection did not include all languages. Only three reviews identified quality assessments conducted by at least two reviewers and only five related possible searches for unpublished data. CONCLUSIONS: Bimaxillary advancement surgery improved respiratory indicators, sleepiness data, and increased upper airway size. However, it is necessary to standardize the surgical criteria to establish measurable efficiency of the procedure. CLINICAL RELEVANCE: This overview makes a critical analysis of the results of the selected systematic reviews with the aim of presenting the most clinically relevant data on the maxillomandibular advancement for treating obstructive apnea syndrome, with a focus on improving respiratory, anatomical, and quality of life indices. There are no overviews that approach this theme from a well-structured perspective.

Differences in skeletal growth patterns: an exploratory approach using elliptic Fourier analysis.

OBJECTIVE: Apply elliptic Fourier analysis to find shape differences among the hypodivergent, normodivergent, and hyperdivergent growth patterns in skeletal classes I, II and, III in mandibular and maxillary curves and evaluate the discriminatory capacity of these differences. MATERIALS AND METHODS: A total of 626 adult patients were included: 354 Brazilian patients (52 with tomographic information and 302 with radiographic information) and 272 Colombian patients with radiographic information. Lateral views were selected. The maxillary and mandibular curves were digitized. Elliptic Fourier analysis was employed considering with 20 harmonics as well as filtering size, rotation, and translation properties. One-way non-parametric MANOVA was employed to determine differences. A confusion matrix tool was employed to analyze the discriminatory capacity of the model. RESULTS: Significant shape differences in the mandibular and maxillary contours were found among the hypodivergent, normodivergent, and hyperdivergent growth patterns in classes I, II, and III (p < 0.05). The accuracies obtained from the confusion matrix were respectively 74.1, 79.5, and 90.1% in classes I, II, and III in the mandibular curves and respectively 71.9, 73.9, and 75% in classes I, II, and III in the maxillary curves. CONCLUSIONS: Elliptic Fourier analysis can be used to find shape differences with an acceptable discriminatory capacity, especially in the mandible contour. Maxillary and mandibular bone curves each significantly defined facial biotypes regardless of the size and position properties. CLINICAL RELEVANCE: This exploration offers a way to quantify mandibular morphology for the construction of an economic mandibular prediction system applicable to the Latin American population.

A prospective non-fatal injuries assessment: A multivariate analysis in medical-legal examinations.

OBJECTIVE: To prospectively determine injury recovery time in the medical-legal examinations of non-fatal injuries and their associated factors, carried out by the National Institute of Legal Medicine and Forensic Sciences of Colombia to create a multivariate analysis. METHODS: A prospective medical-legal assessment of non-fatal injuries was carried out on 281 individuals with complete follow-up, in which the observational unit of analysis was the most serious injury. Variables, such as sex, circumstances of the injury, the mechanism that caused the injury, medical certificate of incapacity to work, among others were related to the injury recovery time, measured in days. The Kruskal Wallis (K-W) ANOVA and a multivariate analysis using the ordinal regression model were applied. RESULTS: In the multivariate analysis, the factors most associated with longer recovery time were the extent of joint damage (CR95%:1.47-5.94,p = 0.0001) and bone damage (CR95%:2.92-7.42,p < 0.001). In terms of circumstances of the injury, traffic accidents (CR95%:1.03-2.96,p < 0.001), medical-legal impairments (CR95%:0.34-2.19,p = 0.007), and complications of the primary injury (CR95%: 1.18-2.57,p < 0.001) had the greatest impact on recovery time. Others factors that significantly impacted injury recovery time are surgical treatments (IC95%: 0.33-3.26,p = 0.0164) and delayed treatment (CR95%:1.41-4.72,p < 0.001). A direct correlation (significant and moderately strong) was found between the recovery time of the injury and the days of incapacity for work (r = 0.802, p < 0.001). CONCLUSION: This prospective analysis determined which variables were most strongly related to the medical-legal assessment of non-fatal injuries and the recovery time of said injuries. Further studies aimed at improving the strategies to help individuals complete the legal process are required.

Biotypic classification of facial profiles using discrete cosine transforms on lateral radiographs.

OBJECTIVE: The aim of the study was to use discrete cosine transforms to graph soft tissue curves in lateral cephalometric radiographs and, with the obtained mathematical values, to group these curves by both traditional biotypes and cluster systems, in order to evaluate discriminatory capacity in terms of accuracy. DESIGN: A sample of 625 lateral radiographs of adult patients (319 women and 306 men) was classified by facial biotype based on the ANB angle and mandibular plane angle. The curves of the facial profile were digitized with 50 equidistant points and discrete cosine transform was applied to analyze these curves mathematically for the determination of the accuracy of the classification of traditional biotypes. Phylogram cluster analysis was then performed for hierarchical grouping and accuracy was determined through cross-validation. RESULTS: Grouping by biotype was performed for men and women separately. Although significant, accuracy did not surpass 71.4%. In the groups by clusters, significant results were achieved when performing four analyses for men and two for women. The best accuracy regarding classification power and qualitative distinction was 89.5% for men and 94% for women. CONCLUSIONS: Discrete cosine transforms using a cluster system had greater discriminatory capacity in terms of accuracy compared to traditional grouping considering the ANB angle and mandibular plane angle. This exploration can be useful for the creation of a soft-tissue facial reconstruction software for the Latin American population.

Shape differences among symmetrically shaped skeletal growth patterns in a panoramic view: a Fourier analysis.

The objective of this study was to apply elliptic Fourier analysis (EFA) to find shape differences among skeletal growth patterns in both radiographic and tomographic panoramic views, controlling for asymmetry. Lateral and panoramic images were obtained from 350 patients. After screening patients with asymmetric linear and angular values and natural asymmetric hemimandibular shape, 240 patients were included in the study: 48 with tomographic information and 192 with radiographic information. The images were classified according to the mandibular plane angle and the ANB angle. Mandibular contours were digitized on the panoramic images and EFA was performed with 20 harmonics, filtering rotation, translation and size properties. As there were no differences between radiographic and tomographic panoramic mandibular contours and normal distribution was found in all groups, MANOVA was conducted to determine differences using a Hotelling's p-values with Bonferroni correction and an XY graph tool was applied to visualize these differences graphically. A 95% confidence level was used. Significative differences were found among hypodivergent, normodivergent, and hyperdivergent patterns in Class I, II, and III (p < 0.05), located mainly in the symphyseal region. The results of this study suggest that EFA is a useful tool to mathematically analyze mandibular contours and their morphological differences given by facial biotypes. This method could improve the precision of the mandibular prediction models.

Incidence of condylar resorption after bimaxillary, Lefort I, and mandibular surgery: an overview.

The aim of the present overview was to evaluate the outcomes of systematic reviews to determine the incidence of condylar resorption in patients submitted to orthognathic surgery and analyze whether the risk of developing this condition is related to a specific type of surgery. Searches were conducted in the PubMed/MEDLINE, Embase, and Cochrane electronic databases for systematic reviews with quantitative data on condylar resorption due to any type of orthognathic surgery for dentoskeletal deformities published up to May 25, 2019. The AMSTAR 2 and Glenny tools were applied for the quality appraisal. Five systematic reviews were included for analysis. Only one article was considered to have high quality. Among a total of 5128 patients, 12.32% developed condylar resorption. From those patients, 70.1% had double jaw surgery, 23.4% had mandibular surgery alone, and in 6.5% a Lefort I technique was used. Based on these findings, bimaxillary surgery could be considered a risk factor for condylar resorption. However, these results should be interpreted with caution, since other factors, such as pre-operative skeletal deformities, type of movement, and type of fixation, can contribute to the development of this condition. Further studies should consider reporting main cephalometric data, temporomandibular diagnosis, hormonal levels, and tomographic measures before and after the surgery at least every 6 months during the firsts two years to identify accurately risk factors for condylar resorption.

Efficacy of proportional versus high condylectomy in active condylar hyperplasia - A systematic review.

OBJECTIVE: To perform a systematic literature review to test the efficacy of proportional condylectomy versus high condylectomy in patients with active condylar hyperplasia, in terms of avoiding secondary surgeries. METHOD: Following a search of Medline (Pubmed), Embase, Scopus, Web of Science and Cochrane databases, ten studies were included for qualitative analysis, and two studies were included for meta-analysis. Quality assessment was performed using the Newcastle-Ottawa scale for cohort studies and the 18-item modified Delphi technique for case series. RESULTS: 259 patients were included in the qualitative analysis, with a weighted arithmetic mean age of 20.4 years, and a female:male ratio of 2:1. Meta-analysis was carried out for 52 patients, and it was found that proportional condylectomy reduced the need for secondary surgery (p = 0.0003). Although this evidence had limitations, excised bone on proportional condylectomy was superior when compared with excised bone on high condylectomy, re-establishing the occlusal plane, resulting in fewer asymmetries, and therefore reducing the need for further surgery. CONCLUSIONS: This systematic review showed a tendency for proportional condylectomies to avoid additional surgeries; however, more comparative studies are necessary.

Use of automated learning techniques for predicting mandibular morphology in skeletal class I, II and III.

BACKGROUND: The prediction of the mandibular bone morphology in facial reconstruction for forensic purposes is usually performed considering a straight profile corresponding to skeletal class I, with application of linear and parametric analysis which limit the search for relationships between mandibular and craniomaxillary variables. OBJECTIVE: To predict the mandibular morphology through craniomaxillary variables on lateral radiographs in patients with skeletal class I, II and III, using automated learning techniques, such as Artificial Neural Networks and Support Vector Regression. MATERIALS AND METHODS: 229 standardized lateral radiographs from Colombian patients of both sexes aged 18-25 years were collected. Coordinates of craniofacial landmarks were used to create mandibular and craniomaxillary variables. Mandibular measurements were selected to be predicted from 5 sets of craniomaxillary variables or input characteristics by using automated learning techniques, and they were evaluated through a correlation coefficient by a ridge regression between the real value and the predicted value. RESULTS: Coefficients from 0.84 until 0.99 were obtained with Artificial Neural Networks in the 17 mandibular measures, and two coefficients above 0.7 were obtained with the Support Vector Regression. CONCLUSION: The craniomaxillary variables used, showed a high predictability ability of the selected mandibular variables, this may be the key to facial reconstruction from specific craniomaxillary measures in the three skeletal classifications.

Shape differences among symmetrically shaped skeletal growth patterns in a panoramic view: a Fourier analysis

Abstract The objective of this study was to apply elliptic Fourier analysis (EFA) to find shape differences among skeletal growth patterns in both radiographic and tomographic panoramic views, controlling for asymmetry. Lateral and panoramic images were obtained from 350 patients. After screening patients with asymmetric linear and angular values and natural asymmetric hemimandibular shape, 240 patients were included in the study: 48 with tomographic information and 192 with radiographic information. The images were classified according to the mandibular plane angle and the ANB angle. Mandibular contours were digitized on the panoramic images and EFA was performed with 20 harmonics, filtering rotation, translation and size properties. As there were no differences between radiographic and tomographic panoramic mandibular contours and normal distribution was found in all groups, MANOVA was conducted to determine differences using a Hotelling's p-values with Bonferroni correction and an XY graph tool was applied to visualize these differences graphically. A 95% confidence level was used. Significative differences were found among hypodivergent, normodivergent, and hyperdivergent patterns in Class I, II, and III (p < 0.05), located mainly in the symphyseal region. The results of this study suggest that EFA is a useful tool to mathematically analyze mandibular contours and their morphological differences given by facial biotypes. This method could improve the precision of the mandibular prediction models.

An automatic method for skeletal patterns classification using craniomaxillary variables on a Colombian population.

BACKGROUND: The mandibular bone is an important part of the forensic facial reconstruction and it has the possibility of getting lost in skeletonized remains; for this reason, it is necessary to facilitate the identification process simulating the mandibular position only through craniomaxillary measures, for this task, different modeling techniques have been performed, but they only contemplate a straight facial profile that belong to skeletal pattern Class I, but the 24.5% corresponding to the Colombian skeletal patterns Class II and III are not taking into account, besides, craniofacial measures do not follow a parametric trend or a normal distribution. OBJECTIVE: The aim of this study was to employ an automatic non-parametric method as the Support Vector Machines to classify skeletal patterns through craniomaxillary variables, in order to simulate the natural mandibular position on a contemporary Colombian sample. MATERIALS AND METHODS: Lateral cephalograms (229) of Colombian young adults of both sexes were collected. Landmark coordinates protocols were used to create craniomaxillary variables. A Support Vector Machine with a linear kernel classifier model was trained on a subset of the available data and evaluated over the remaining samples. The weights of the model were used to select the 10 best variables for classification accuracy. RESULTS: An accuracy of 74.51% was obtained, defined by Pr-A-N, N-Pr-A, A-N-Pr, A-Te-Pr, A-Pr-Rhi, Rhi-A-Pr, Pr-A-Te, Te-Pr-A, Zm-A-Pr and PNS-A-Pr angles. The Class Precision and the Class Recall showed a correct distinction of the Class II from the Class III and vice versa. CONCLUSIONS: Support Vector Machines created an important model of classification of skeletal patterns using craniomaxillary variables that are not commonly used in the literature and could be applicable to the 24.5% of the contemporary Colombian sample.