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The objective of this study was to explore the feasibility of current 3D reconstruction in assessing the position of maxillary impacted canines from 2D panoramic X-rays. A dataset was created using pre-treatment CBCT data from a total of 123 patients, comprising 74 patients with impacted canines and 49 patients without impacted canines. From all 74 subjects, we generated a dataset containing paired 2D panoramic X-rays and pseudo-3D images. This pseudo-3D image contained information about the location of the impacted canine in the buccal/lingual, mesial/distal, and apical/coronal positions. These data were utilized to train a deep-learning reconstruction algorithm, a generative AI. The location of the crown of the maxillary impacted canine was determined based on the output of the algorithm. The reconstruction was evaluated using the structure similarity index measure (SSIM) as a metric to indicate the quality of the reconstruction. The prediction of the impacted canine's location was assessed in both the mesiodistal and buccolingual directions. The reconstruction algorithm predicts the position of the impacted canine in the buccal, middle, or lingual position with 41% accuracy, while the mesial and distal positions are predicted with 55% accuracy. The mean SSIM for the output is 0.71, with a range of 0.63 to 0.84. Our study represents the first application of AI reconstruction output for multidisciplinary care involving orthodontists, periodontists, and maxillofacial surgeons in diagnosing and treating maxillary impacted canines. Further development of deep-learning algorithms is necessary to enhance the robustness of dental reconstruction applications. [ABSTRACT FROM AUTHOR]

Objective: This study aimed to quantify the 3D asymmetry of the maxilla in patients with unilateral cleft lip and palate (UCP) and investigate the defect factors responsible for the variability of the maxilla on the cleft side using a deep-learning-based CBCT image segmentation protocol.Setting and Sample Population: Cone beam computed tomography (CBCT) images of 60 patients with UCP were acquired. The samples in this study consisted of 39 males and 21 females, with a mean age of 11.52 years (SD = 3.27 years; range of 8-18 years).Materials and Methods: The deep-learning-based protocol was used to segment the maxilla and defect initially, followed by manual refinement. Paired t-tests were performed to characterize the maxillary asymmetry. A multiple linear regression was carried out to investigate the relationship between the defect parameters and those of the cleft side of the maxilla.Results: The cleft side of the maxilla demonstrated a significant decrease in maxillary volume and length as well as alveolar length, anterior width, posterior width, anterior height and posterior height. A significant increase in maxillary anterior width was demonstrated on the cleft side of the maxilla. There was a close relationship between the defect parameters and those of the cleft side of the maxilla.Conclusions: Based on the 3D volumetric segmentations, significant hypoplasia of the maxilla on the cleft side existed in the pyriform aperture and alveolar crest area near the defect. The defect structures appeared to contribute to the variability of the maxilla on the cleft side. [ABSTRACT FROM AUTHOR]

To determine the accuracy of three-dimensional (3D) printed models fabricated from cone-beam computed tomography (CBCT) scans of human mandibular dry skulls in comparison with models derived from intraoral scanner (IOS) data. Six human mandibular dry skulls were scanned by IOS and CBCT. Digital models (DMs) constructed from the IOS and CBCT data were fabricated physically using a 3D printer. The width and thickness of individual teeth and intercanine and molar widths were measured using a digital caliper. The accuracy of the DMs was compared between IOS and CBCT. Paired t-tests were used for intergroup comparisons. All intraclass correlation coefficient values for the three measurements (mesial-distal, buccal-lingual, width) exceeded 0.9. For the mandibular teeth, there were significant discrepancies in model accuracy between the IOS (average discrepancies of 0.18 ± 0.08 mm and 0.16 ± 0.12 mm for width and thickness, respectively) and CBCT (0.28 ± 0.07 mm for width, 0.37 ± 0.2 mm for thickness; P <.01). Intercanine (P =.38) and molar widths (P =.41) showed no significant difference between groups. There was a statistically significant difference in the accuracy of DMs obtained from CBCT and IOS; however, this did not seem to result in any important clinical difference. CBCT could be routinely used as an orthodontic diagnostic tool and for appliance construction. [ABSTRACT FROM AUTHOR]

Introduction: The present study investigated the relationship between facial skeletal patterns and morphology of the palate in adult patients with Class III malocclusion using structural equation modelling (SEM).Setting and Sample Population: One hundred cone beam computed tomography images of Class III adults were evaluated for skeletal measurements.Materials and Methods: The skeletal measurements were classified into the vertical, anteroposterior and transverse group based on factor analysis. 3D scanning model of the maxilla was analysed by Generalized procrustes analysis (GPA) and principal component analysis (PCA). Structural equation modelling was used to analyse relationship among the skeletal and morphometric factors.Results: According to the factor analysis, latent variables were extracted by each skeletal variable. First principal component (PC1) and PC2 of palatal morphology were used to analyse relationship with skeletal variables. As results of the structural equation model, the transverse latent variable had the most influence on PC1, followed by vertical and anteroposterior variables. This result means that as the facial width increases, the palate becomes narrower, deeper and longer.Conclusions: The relationship between the skeletal pattern with Class III malocclusion and palatal morphology was analysed through SEM. The transverse facial skeletal pattern showed the highest correlation with PC1 of palatal morphology. [ABSTRACT FROM AUTHOR]

To (1) introduce a novel machine learning method and (2) assess maxillary structure variation in unilateral canine impaction for advancing clinically viable information. A machine learning algorithm utilizing Learning-based multi-source IntegratioN frameworK for Segmentation (LINKS) was used with cone-beam computed tomography (CBCT) images to quantify volumetric skeletal maxilla discrepancies of 30 study group (SG) patients with unilaterally impacted maxillary canines and 30 healthy control group (CG) subjects. Fully automatic segmentation was implemented for maxilla isolation, and maxillary volumetric and linear measurements were performed. Analysis of variance was used for statistical evaluation. Maxillary structure was successfully auto-segmented, with an average dice ratio of 0.80 for three-dimensional image segmentations and a minimal mean difference of two voxels on the midsagittal plane for digitized landmarks between the manually identified and the machine learning–based (LINKS) methods. No significant difference in bone volume was found between impaction ([2.37 ± 0.34] 104 mm3) and nonimpaction ([2.36 ± 0.35] 104 mm3) sides of SG. The SG maxillae had significantly smaller volumes, widths, heights, and depths (P <.05) than CG. The data suggest that palatal expansion could be beneficial for those with unilateral canine impaction, as underdevelopment of the maxilla often accompanies that condition in the early teen years. Fast and efficient CBCT image segmentation will allow large clinical data sets to be analyzed effectively. [ABSTRACT FROM AUTHOR]

Objective: The correlations between morphology of the temporomandibular joint structure, the anterior guidance angle, and occlusal plane were investigated.Materials and Methods: A cone beam computed tomography analysis was performed in 158 patients (86 women and 72 men). 3D software was employed to obtain the coordinates of the shape of the incisal guidance angle, occlusal guidance angle, articular fossa, and mandibular condyle. Generalized Procrustes analysis including principal components analysis (PCA) were performed and produced principal components (PCs) scores of each shape and their centroid size (CS).Results: A significant Pearson correlation coefficient of 0.3451 (p < .001) was observed between the incisal guidance angle and occlusal plane. The CS also showed a correlation with the incisal guidance angle, but not with the occlusal plane angle. The PCA results revealed that there were no significant correlations between the temporomandibular joint structure (TMJ) shape (fossa and condyle) and the incisal guidance angle.Conclusions: Incisor guidance angle and occlusal plane angle were correlated. In addition, there was a correlation between CS and incisal guidance angle. In the PCA, It can be concluded that the size is more related to the incisor guidance angle than the morphological factors of the constituent components of the TMJ. [ABSTRACT FROM AUTHOR]

Objectives: The purpose of this study was to establish multivariable regression models for the estimation of skeletal maturation status in Japanese boys and girls using the cone-beam computed tomography (CBCT)-based cervical vertebral maturation (CVM) assessment method and hand-wrist radiography. Materials and methods: The analyzed sample consisted of hand-wrist radiographs and CBCT images from 47 boys and 57 girls. To quantitatively evaluate the correlation between the skeletal maturation status and measurement ratios, a CBCT-based CVM assessment method was applied to the second, third, and fourth cervical vertebrae. Pearson's correlation coefficient analysis and multivariable regression analysis were used to determine the ratios for each of the cervical vertebrae ( p < 0.05). Results: Four characteristic parameters ((OH + PH)/W, (OH + AH)/W, D, AH/W), as independent variables, were used to build the multivariable regression models: for the Japanese boys, the skeletal maturation status according to the CBCT-based quantitative cervical vertebral maturation (QCVM) assessment was 5.90 + 99.11 × AH/W − 14.88 × (OH + AH)/W + 13.24 × D; for the Japanese girls, it was 41.39 + 59.52 × AH/W − 15.88 × (OH + PH)/W + 10.93 × D. Conclusions: The CBCT-generated CVM images proved very useful to the definition of the cervical vertebral body and the odontoid process. The newly developed CBCT-based QCVM assessment method showed a high correlation between the derived ratios from the second cervical vertebral body and odontoid process. Clinical relevance: There are high correlations between the skeletal maturation status and the ratios of the second cervical vertebra based on the remnant of dentocentral synchondrosis. [ABSTRACT FROM AUTHOR]