Year: 2013
Type: article
Study design: Observational Study
Abstract: Objectives: The purposes of this study were to determine 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 gender and age on bone mineral density distribution.Methods: Sixty six clinical CBCT images from patients (36 females and 30 males) were identified.Three age groups (40, 50, and 60 years) were identified for male and female patients.Alveolar bone (AB) and basal cortical bone regions were digitally isolated.A histogram of gray levels, which are equivalent to degrees of bone mineralization, was obtained from each region of the CBCT images.Mean, standard deviation (SD), coefficient of variation (COV), fifth percentile low (Low 5 ) and high (High 5 ) of gray levels were obtained.Percentage differences of gray level parameters between alveolar and basal cortical bones were computed.Results: The alveolar bone region had significantly higher SD and COV, but significantly lower Mean, Low 5 and High 5 than the basal cortical bone region for all CBCT images (p<0.001).Significantly higher percentage differences of SD, COV, and Low 5 were observed when the over 50 years old female group was compared to the male group of the same age (p<0.042).iii Conclusions: Significant gender differences in gray level variability observed within the postmenopausal age group suggested that the current approach to oral bone mineral density assessment using 3D clinical CBCT images can provide additional information for early diagnosis of postmenopausal osteoporosis. CHAPTER 1assessment using the 3D clinical CBCT images can provide additional information for early diagnosis of postmenopausal osteoporosis.
Author: Jie Liu
Institution: The Ohio State University
Language: English
Subfield: Oral Surgery
Field: Dentistry
Domain: Health Sciences
Open Access status: green
Funder: Delta Dental Foundation
OpenAlex ID: W2610278367