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Background: Orthodontic treatment planning involves the precise assessment of dental and skeletal anomalies, which can be facilitated by AI-enhanced diagnostic tools. Materials and Methods: A total of 100 orthodontic cases were included in this RCT. Patients were randomly assigned to two groups: an AI-enhanced diagnostic group and a traditional diagnostic group. The AI-enhanced diagnostic group underwent orthodontic assessment with the aid of AI-powered software, which provided automated cephalometric analysis, 3D model evaluations, and treatment suggestions. The traditional diagnostic group received conventional diagnostic assessments by orthodontists. The primary outcome measures included treatment planning accuracy, treatment time, and patient satisfaction. Secondary outcomes included the number of appointments required and treatment cost. Results: The AI-enhanced diagnostic group demonstrated a significantly higher accuracy in treatment planning compared to the traditional diagnostic group (P < 0.05). The AI group also required fewer appointments (mean ± SD: 10.2 ± 2.1 vs. 12.8 ± 3.4) and had a shorter treatment time (mean ± SD: 14.6 ± 3.2 months vs. 18.9 ± 4.5 months) (P < 0.001 for both comparisons). Additionally, patient satisfaction scores were higher in the AI group (mean ± SD: 9.2 ± 0.6 vs. 8.1 ± 0.8) (P < 0.001). However, the AI-enhanced diagnostic group had a slightly higher treatment cost. Conclusion: AI-enhanced diagnostic tools significantly enhance the accuracy of treatment planning in orthodontic cases, leading to reduced treatment time, fewer appointments, and increased patient satisfaction.
RESUMO
BACKGROUND: When it comes to orthodontic diagnosis and treatment planning, the structures of the upper and lower airway space are crucial because of the role they play in craniofacial development. AIM: The major objective of this study was to evaluate the accuracy of lateral cephalogram in the evaluation of upper and lower pharyngeal space by comparing it to clinical usage of cone-beam computed tomography (CBCT) in quantifying the 3D morphology of the pharyngeal airway. METHODS AND MATERIALS: In total, 70 patients were included in the study. They had both a CBCT scan and a lateral cephalogram performed within a week of each other. Different cephalometric landmarks have been utilized to estimate linear and area dimensions for use in lateral cephalogram airway investigations. By superimposing the lateral cephalogram measurement of the vertical height of the pharyngeal airway over axial CBCT slices of 0.8 to 1 mm in thickness, airway volumes were calculated. For this study, we measured the pharyngeal airway space in each patient in two dimensions (2D) using the airway area from the lateral cephalogram and in three dimensions (3D) using the airway volume from the CBCT scan over the same region of interest, using a uniform scale and magnification throughout all split 3D volumes. RESULTS: The mean value of the area of pharyngeal space calculated by lateral cephalograph analysis (LCA) was 336.35 ± 86.49 mm2. The maximum value was 551.234 mm2. The minimum value was 206.32 mm2. The mean value of the volume of the same area calculated using CBCT was 3409.11 ± 1237.96 mm3. The maximum value was 5887.23 mm3. When the area calculated using LCA was compared with the volume calculated using CBCT, the correlation between them was significant statistically (r=0.831, p-value =0.000). The mean values of volume evaluated in 3D CBCT in males were 4198±1008 mm3 while for females it was 2980±1134.5 mm3. During the statistical analysis, these observations were found to have a positive correlation with increased volume of pharyngeal space in males as compared to that of females (p=0.006). The values of the area of pharyngeal space calculated using LCA in males was 370.1±60.9 mm2. while it was 301.9±88 mm2 in females. CONCLUSION: The area estimated for the pharyngeal airway on LCA correlates strongly with the volume determined by a CBCT scan. Since we have considered pharyngeal space analysis using CBCT to be a reliable and standard methodology, therefore a positive correlation of area calculated using LCA with volume calculated using CBCT shows that the analysis made by LCA can be reliable.
RESUMO
BACKGROUND: Success of an implant depends on its placement in the bone and how well the stress and strain are distributed to the surrounding structures when occlusal force is applied to it. The size and shape of the implant plays an important role is the formation and distribution of stress and strains in the periodontium. Von Mises stresses and micromovements need to be evaluated while placing implants in D4 bone quality regions for a higher success rate. AIM: To evaluate the peri-implant Von Mises stresses, strains, and micromovements distribution in D4 bone quality around ultra-short implants of 5 mm length with varying diameters of 4 mm, 5 mm, and 6 mm. MATERIALS AND METHODS: The finite element method was employed to make models replacing maxillary molars in D4 type bone that was missing. Implants that could be classified as ultrashort (5 mm) were used. These implants were of varying diameters of 4, 5, and 6 mm. In each model, the implant was subjected to a force of 100 N and analyzed. The force was applied in an oblique (45 degrees) and vertical direction (90°) to the long axis of the tooth. The models were made such that they simulated cortical and cancellous anisotropic properties of the bone. The models were then analyzed using the program ANSYS workbench version 12.1. RESULTS: When all the three diameters were compared wide diameter, i.e., 6 mm threads had the least values of peri-implant von Mises stresses, strains, and micro-movements around them. When thread shapes were taken into consideration square micro thread created the most favorable stress parameters around them with minimum values of stress, strains, and micromovements. CONCLUSION: Ultrashort implants combined with a wide diameter and platform switched can be used in atrophic ridges or when there is a need for extensive surgery to prepare the implant site.