Three-dimensional comparison of 2 digital models obtained from cone-beam computed tomographic scans of polyvinyl siloxane impressions and plaster models

Purpose: This study was performed to evaluate the dimensional accuracy of digital dental models constructed from cone-beam computed tomographic (CBCT) scans of polyvinyl siloxane (PVS) impressions and cast scan models. Materials and Methods: A pair of PVS impressions was obtained from 20 subjects and scanned using CBCT (resolution, 0.1 mm). A cast scan model was constructed by scanning the gypsum model using a model scanner. After reconstruction of the digital models, the mesio-distal width of each tooth, inter-canine width, and inter-molar width were measured, and the Bolton ratios were calculated and compared. The 2 models were superimposed and the difference between the models was measured using 3-dimensional analysis. Results: The range of mean error between the cast scan model and the CBCT scan model was -0.15 mm to 0.13 mm in the mesio-distal width of the teeth and 0.03 mm to 0.42 mm in the width analysis. The differences in the Bolton ratios between the cast scan models and CBCT scan models were 0.87 (anterior ratio) and 0.72 (overall ratio), with no significant difference (P>0.05). The mean maxillary and mandibular difference when the cast scan model and the CBCT scan model were superimposed was 53 µm. Conclusion: There was no statistically significant difference in most of the measurements. The maximum tooth size difference was 0.15 mm, and the average difference in model overlap was 53 µm. Digital models produced by scanning impressions at a high resolution using CBCT can be used in clinical practice.ope

Comparison of conventional lateral cephalograms with corresponding CBCT radiographs

Purpose: This study was performed to assess the compatibility of cone beam computed tomography (CBCT) synthesized cephalograms with conventional cephalograms, and to find a method for obtaining normative values for three-dimensional (3D) assessments. Materials and methods: The sample group consisted of 10 adults with normal occlusion and well-balanced faces. They were imaged using conventional and CBCT cephalograms. The CBCT cephalograms were synthesized from the CBCT data using OnDemand 3D software. Twenty-one angular and 12 linear measurements from each imaging modality were compared and analyzed using paired-t test. Results: The linear measurements between the two imaging modalities were not statistically different (p>0.05) except for the U1 to facial plane distance. The angular measurements between the two imaging modalities were not statistically different (p>0.05) with the exception of the gonial angle, ANB difference, and facial convexity. Conclusion: Two-dimensional cephalometric norms could be readily used for 3D quantitative assessment, if corrected for lateral cephalogram distortion.ope

Alveolar bone height according to the anatomical relationship between the maxillary molar and sinus

Purpose: The aim of this study was to investigate the available alveolar bone height between the maxillary molars and the sinus floor according to their anatomical relationship using cone-beam computed tomographic (CBCT) images. Methods: A total of 752 maxillary first (M1) and second molars (M2) on CBCT scans of 188 patients were selected. First, each maxillary molar was categorized as type 1, 2, 3, or 4 according to the relationship of the molar root with the maxillary sinus floor. The frequency distribution of each type was analyzed. Second, the shortest vertical distance (VD) of each molar was measured from the furcation midpoints of the roots to the lowest point of the sinus floor by 2 observers. Intraclass correlation coefficients and the t-test were calculated for the VD measurements. Results: For M1, type 3 was the most frequent, followed by type 2. For M2, type 3 was the most common, followed by type 1. The VD measurements of type 1 were 9.51±3.68 mm and 8.07±2.73 mm for M1 and M2, and those of type 3 were 3.70±1.52 mm and 4.03±1.53 mm for M1 and M2, respectively. The VD measurements of M2 were significantly higher in female patients than in male patients. Conclusions: Type 3 was the most frequent anatomical relationship in the maxillary molars, and showed the lowest alveolar bone height. This information will help clinicians to prevent complications related to the maxillary sinus during maxillary molar treatment and to predict the available bone height for immediate implant planningope

Cone beam CT findings of retromolar canals: Report of cases and literature review

A retromolar canal is an anatomical variation in the mandible. As it includes the neurovascular bundle, local anesthetic insufficiency can occur, and an injury of the retromolar canal during dental surgery in the mandible may result in excessive bleeding, paresthesia, and traumatic neuroma. Using imaging analysis software, we evaluated the cone-beam computed tomography (CT) images of two Korean patients who presented with retromolar canals. Retromolar canals were detectable on the sagittal and cross-sectional images of cone-beam CT, but not on the panoramic radiographs of the patients. Therefore, the clinician should pay particular attention to the identification of retromolar canals by preoperative radiographic examination, and additional cone beam CT scanning would be recommended.ope

Clinical application of panoramic radiography With multi-layer imaging software : Case reports

Panoramic radiography is widely used as a primary radiological diagnosis in dentistry. However, due to the overlapping of anatomical structures, diagnostic capability of panoramic radiography is limited. Recently, panoramic machine equipped with various image processing software has been introduced to improve the diagnostic capability. This study aims to introduce panoramic equipment with multi-layer imaging software that can provide 41 images from anterior to posterior in region of interest, and to report in various clinical applications.ope

Linear Accuracy of Full-Arch Digital Models Using Four Different Scanning Methods: An In Vitro Study Using a Coordinate Measuring Machine

Improving the accuracy of the digital model is essential for the digitalization of the dental field. This study introduced a novel method of objective accuracy evaluation of digitized full dental arch model using coordinate measuring machine (CMM). To obtain a true linear measurement value using the CMM, 17 reference balls were attached to the typodont, and 12 measurements between balls on the X-(width), Y-(length), and Z-axes (height) were performed automatically. A rubber impression and a plaster cast replica of the typodont with balls were fabricated, and they were digitized with following methods: (a) true model intraoral scans; (b) impression cone-beam computed tomography (CBCT) scans; (c) cast CBCT scans; and (d) cast extraoral scans. Each scanning method was performed 20 times. Twelve linear measurements on the digitized models were automatically made using software. The one-sample t-test and one-way analysis of variance were used for measurement accuracy analysis. The cast extraoral scan was most accurate on X- and Y-axes, while impression CBCT was the most accurate on Z-axis. Over all axes, the intraoral scan resulted in the most deviation from the true model, and the reproducibility of each scan was also low. Extraoral scan shows high precision on width and length, and impression CBCT is advantageous for dental work where height factor is of importance.ope

Trend of Artificial Intelligence technology in oral and maxillofacial radiology

Artificial intelligence (AI) technology is widely used in our life. Likewise, AI in the field of oral and maxillo facial radiology is being studied in various fields such as detection, classification, segmentation, measurement, and image translation. This study aimed to investigate the 1) research papers and 2) developed software based on AI in the oral and maxillofacial radiology to help dentists actively utilize the upcoming AI application. Papers were searched through 5 major data bases until June 2021, and a total of 101 papers corresponding to dental imaging-based AI research in the oral and maxillofacial area were collected. A number of AI papers showed a sharp increase from 2017, and the most research conducted on panoramas. The AI based dental imaging software search for the purpose of commercialization was first collected based on the list announced on October 21, 2020 by the Ministry of Food and Drug Safety of Korea and the web da tabase search was on October 22-23, 2021. Total 23 software were searched, and the function of automatically detecting lesions in panoramic or apical images and the orthodontic diagnosis analysis function by automati cally recognizing important anatomical landmarks in cephalogram were the most popular in the world. If a clear profitability model is presented in the future and evidence for clinical effectiveness and ethical re sponsibility are prepared, the clinical use of AI-based application using dental images will increase. Therefore, it is thought that dentists need to take an interest in AI technology research trends and product development and actively participate.ope

Automated cortical thickness measurement of the mandibular condyle head on CBCT images using a deep learning method

This study proposes a deep learning model for cortical bone segmentation in the mandibular condyle head using cone-beam computed tomography (CBCT) and an automated method for measuring cortical thickness with a color display based on the segmentation results. In total, 12,800 CBCT images from 25 normal subjects, manually labeled by an oral radiologist, served as the gold-standard. The segmentation model combined a modified U-Net and a convolutional neural network for target region classification. Model performance was evaluated using intersection over union (IoU) and the Hausdorff distance in comparison with the gold standard. The second automated model measured the cortical thickness based on a three-dimensional (3D) model rendered from the segmentation results and presented a color visualization of the measurements. The IoU and Hausdorff distance showed high accuracy (0.870 and 0.928 for marrow bone and 0.734 and 1.247 for cortical bone, respectively). A visual comparison of the 3D color maps showed a similar trend to the gold standard. This algorithm for automatic segmentation of the mandibular condyle head and visualization of the measured cortical thickness as a 3D-rendered model with a color map may contribute to the automated quantification of bone thickness changes of the temporomandibular joint complex on CBCT.ope

Dose Assessment in Dental Cone-Beam Computed Tomography: Comparison of Optically Stimulated Luminescence Dosimetry With Monte Carlo Method

The variety of cone-beam computed tomography (CBCT) machines and their applications has rapidly increased in recent years, making the dose evaluation of individual devices an important issue. Patient doses from CBCT were assessed with two different methods: optically stimulated luminescence dosimeter (OSLD) measurements and Monte Carlo (MC) simulations, in four different examination modes. Based on an analysis of the measurement process and the obtained values, a recommendation is made regarding which method is more practical and efficient for acquiring the effective dose of CBCT. Twenty-two OSLDs were calibrated and equipped in human phantoms of head and neck organs. They were exposed to radiation from two CBCT units-CS9300 (Carestream Dental LLC, Atlanta, Georgia) and RAYSCAN α+ (Ray Co. Ltd, Hwaseong-si, Korea)-using two different examination modes. The dose recorded using the OSLDs was used to calculate the organ dose and the effective dose for each unit in each examination mode. These values were also calculated using MC software, PCXMC (STUK, Helsinki, Finland). The organ doses and effective doses obtained using both methods were compared for each examination mode of the individual units. The OSLD-measured effective dose value was higher than that obtained using the MC method for each examination mode, except the dual jaw mode of CS9300. The percent difference of the effective dose between the two methods ranged from 4.0% to 14.3%. The dose difference between the methods decreased as the field of view became smaller. The organ dose values varied according to the method, although the overall trend was similar for both methods. The organs showing high doses were mostly consistent for both methods. In this study, the effective dose obtained by OSLD measurements and MC simulations were compared, and both methods were described in detail. As a relatively efficient and easy-to-perform method, we cautiously suggest using MC simulations for dose evaluations in the future.ope

Radiomics approach to the condylar head for legal age classification using cone-beam computed tomography: A pilot study

Legal age estimation of living individuals is a critically important issue, and radiomics is an emerging research field that extracts quantitative data from medical images. However, no reports have proposed age-related radiomics features of the condylar head or an age classification model using those features. This study aimed to introduce a radiomics approach for various classifications of legal age (18, 19, 20, and 21 years old) based on cone-beam computed tomography (CBCT) images of the mandibular condylar head, and to evaluate the usefulness of the radiomics features selected by machine learning models as imaging biomarkers. CBCT images from 85 subjects were divided into eight age groups for four legal age classifications: ≤17 and ≥18 years old groups (18-year age classification), ≤18 and ≥19 years old groups (19-year age classification), ≤19 and ≥20 years old groups (20-year age classification) and ≤20 and ≥21 years old groups (21-year age classification). The condylar heads were manually segmented by an expert. In total, 127 radiomics features were extracted from the segmented area of each condylar head. The random forest (RF) method was utilized to select features and develop the age classification model for four legal ages. After sorting features in descending order of importance, the top 10 extracted features were used. The 21-year age classification model showed the best performance, with an accuracy of 91.18%, sensitivity of 80%, and specificity of 95.83%. Radiomics features of the condylar head using CBCT showed the possibility of age estimation, and the selected features were useful as imaging biomarkers.ope