Purpose: Vertical root fractures (VRFs) remain a major diagnostic challenge in endodontics due to image noise and artifacts in cone-beam computed tomography (CBCT), particularly those caused by intracanal posts. This study evaluated the effect of an advanced noise reduction (ANR) algorithm on CBCT performance in detecting VRFs inmaxillary second premolars and examined how different post materials influenced diagnostic outcomes. Materials and Methods: Seventy extracted maxillary second premolars with single canals were divided into 5groups according to post material (cast, fiberglass, titanium, stainless steel, and brass). VRFs were induced in half of the specimens using a universal testing machine under standardized conditions. CBCT scans were obtainedusing a Carestream 9600 device with fixed parameters, both with and without ANR. Two experienced radiologists independently evaluated the images using a 5-point scale. Sensitivity, specificity, predictive values, and interobserveragreement were analyzed using SPSS version 21 (IBM Corp., Armonk, NY, USA). Results: The application of ANR increased overall sensitivity and interobserver agreement compared with conventional images. Specificity varied by post material: fiberglass posts demonstrated the highest diagnostic accuracy, while stainless steel and brass produced stronger artifacts and lower sensitivity. Conclusion Incorporating ANR into CBCT imaging improves VRF detection by improving sensitivity and observerconsistency, especially in cases with minimal metallic interference. These findings highlight the clinical benefits of ANR and support further research integrating noise and metal artifact reduction techniques with artificial intelligenceto optimize diagnostic precision.

Purpose: This study investigated the accuracy of laser-scanned models and 3-dimensional (3D) rendered cone-beam computed tomography (CBCT) compared to the gold standard (plaster casts) for linear measurements on dental arches. Materials and Methods: CBCT scans and plaster models from 30 patients were retrieved. Plaster models were scanned by an Emerald laser scanner (Planmeca, Helsinki, Finland). Sixteen different measurements, encompassing the mesiodistal width of teeth and both arches’ length and width, were calculated using various landmarks. Linear measurements were made on laser-scanned models using Autodesk Meshmixer software v. 3.0 (Autodesk, Mill Valley, CA, USA), on 3D-rendered CBCT models using OnDemand 3D v. 1.0 (Cybermed, Seoul, Korea) and on plaster casts by a digital caliper. Descriptive statistics, the paired t-test, and intra- and inter-class correlation coefficients were used to analyze the data. Results: There were statistically significant differences between some measurements on plaster casts and laser-scanned or 3D-rendered CBCT models (P<0.05). Molar mesiodistal width and mandibular anterior arch width deviated significantly different from the gold standard in both methods. The largest mean differences of laser-scanned and 3D-rendered CBCT models compared to the gold standard were 0.12±0.23 mm and 0.42±0.53 mm, respectively. Most of the mean differences were not clinically significant. The intra- and inter-class correlation results were acceptable for all measurements (>0.830) and between observers (>0.801). Conclusion The 3D-rendered CBCT images and laser-scanned models were useful and accurate alternatives to conventional plaster models. They could be used for clinical purposes in orthodontics and prostheses.

Purpose: This study investigated the position of the hyoid bone and its relationship with airway dimensions in different skeletal malocclusion classes using cone-beam computed tomography (CBCT). Materials and Methods: CBCT scans of 180 participants were categorized based on the A point-nasion-B point angle into class I, class Ⅱ, and class Ⅲ malocclusions. Eight linear and 2 angular hyoid parameters (H-C3, H-EB, H-PNS, H-Me, H-X, H-Y, H-[C3-Me], C3-Me, H-S-Ba, and H-N-S) were measured. A 3-dimensional airway model was designed to measure the minimum cross-sectional area, volume, and total and upper airway length. The mean cross-sectional area, morphology, and location of the airway were also evaluated. Data were analyzed using analysis of variance and the Pearson correlation test, with p values <0.05 indicating statistical significance. Results: The mean airway volume differed significantly among the malocclusion classes (p<0.05). The smallest and largest volumes were noted in class Ⅱ (2107.8±844.7 mm3) and class Ⅲ (2826.6±2505.3 mm3), respectively. The means of most hyoid parameters (C3-Me, C3-H, H-Eb, H-Me, H-S-Ba, H-N-S, and H-PNS) differed significantly among the malocclusion classes. In all classes, H-Eb was correlated with the minimum cross-sectional area and airway morphology, and H-PNS was correlated with total airway length. A significant correlation was also noted between H-Y and total airway length in class Ⅱ and Ⅲ malocclusions and between H-Y and upper airway length in class I malocclusions. Conclusion The position of the hyoid bone was associated with airway dimensions and should be considered during orthognathic surgery due to the risk of airway obstruction.