Purpose: This study examined (1) if cone-beam computed tomography (CBCT) can determine relative differences in bone mineral density distribution using clinical images of patients' mandibular bone and (2) if the relative differences can be used to detect the effects of sex and age on bone mineral density distribution.
Materials And Methods: Sixty-six clinical CBCT images from patients (36 females and 30 males) of 3 age groups (40, 50, and 60 years) were identified. Alveolar (AB) and basal cortical bone (CB) regions were digitally isolated. A histogram of gray levels, which are proportional to degrees of bone mineralization, was obtained from each region. Mean, variability (SD and coefficient of variation), and percentage differences of gray level parameters between AB and basal CBs were computed.
Results: Significant sex differences in gray level variability were observed within the postmenopausal age group (P < 0.042).
Conclusion: These findings suggest that clinical CBCT images can be a valuable tool in providing information on bone quality, which is an important criterion for optimum planning for dental implant placement.
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http://dx.doi.org/10.1097/ID.0000000000000542 | DOI Listing |
J Prosthet Dent
December 2024
Associate Chief Physician, Department of Prosthodontic, Stomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Clinical Research Center for Oral Diseases of Zhejiang Province, Key Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Center of Zhejiang University, Engineering Research Center of Oral Biomaterials and Devices of Zhejiang Province, Hangzhou, PR China. Electronic address:
Statement Of Problem: Endodontically treated teeth often require post-and-core restorations for structural support because of extensive hard tissue loss. Assessment of the effect of the residual dentin thickness on the biomechanical performance of these restorations is lacking.
Purpose: The purpose of this study was to evaluate the residual dentin thickness in mandibular premolars after post-and-core restorations using cone beam computed tomography (CBCT) and to analyze the stress distribution with finite element analysis (FEA).
Oral Radiol
December 2024
Department of Oral, Dental and Maxillofacial Radiology, Faculty of Dentistry, Ataturk University, Erzurum, 25240, Turkey.
Objective: The aim of this study is to determine the contact relationship and position of impacted mandibular third molar teeth (IMM) with the mandibular canal (MC) in panoramic radiography (PR) images using deep learning (DL) models trained with the help of cone beam computed tomography (CBCT) and DL to compare the performances of the architectures.
Methods: In this study, a total of 546 IMMs from 290 patients with CBCT and PR images were included. The performances of SqueezeNet, GoogLeNet, and Inception-v3 architectures in solving four problems on two different regions of interest (RoI) were evaluated.
Clin Oral Investig
December 2024
Hospital of Stomatology, Sun Yat-sen University, Guangzhou, Guangdong, 510055, China.
Objectives: To compare the variations in the upper airway of children with skeletal Class II mandibular retrognathism treated with van Beek Headgear-Activator (vBHGA) and Twin-Block (TB) appliances.
Materials And Methods: 40 children were involved in this retrospective study and divided into two intervention groups: the vBHGA group and the TB group, each comprising 20 individuals with an average age of 11.13 years.
Am J Orthod Dentofacial Orthop
December 2024
Department of Orthodontics, Teerthanker Mahavir Dental College and Research Centre, Teerthanker Mahaveer University, Moradabad, Uttar Pradesh, India.
Introduction: The primary objective of this study was to assess the 3-dimensional position of the mandibular canal (MC) in different craniofacial patterns to know about the safe placement of temporary skeletal anchorage devices using cone-beam computed tomography (CBCT). The secondary objectives were to assess sex differences and correlate the MC position with various factors.
Methods: This prospective, observational study was conducted on 90 patients, divided into 3 groups based on the sagittal pattern: skeletal Class I, Class II, and Class III.
J Imaging
December 2024
Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), 76131 Karlsruhe, Germany.
In recent years, synthetic Computed Tomography (CT) images generated from Magnetic Resonance (MR) or Cone Beam Computed Tomography (CBCT) acquisitions have been shown to be comparable to real CT images in terms of dose computation for radiotherapy simulation. However, until now, there has been no independent strategy to assess the quality of each synthetic image in the absence of ground truth. In this work, we propose a Deep Learning (DL)-based framework to predict the accuracy of synthetic CT in terms of Mean Absolute Error (MAE) without the need for a ground truth (GT).
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