Details

Autor(en) / Beteiligte

• Tanaka, Ray
• Tanaka, Tatsurou
• Yeung, Andy Wai Kan
• Taguchi, Akira
• Katsumata, Akitoshi
• Bornstein, Michael M

Titel

Mandibular Radiomorphometric Indices and Tooth Loss as Predictors for the Risk of Osteoporosis using Panoramic Radiographs

Ist Teil von

• Oral health & preventive dentistry, 2020-09, Vol.18, p.773

Ort / Verlag

Germany

Erscheinungsjahr

2020

Quelle

MEDLINE

Beschreibungen/Notizen

• To assess the mandibular cortical width (MCW) and morphology of the mandibular inferior cortex (MIC) on panoramic views from a large sample of males and females in various age groups by using an automated morphometric grading system for assisting osteoporosis screening. Furthermore, possible predictors and concrete cut-off values to identify the risk for osteoporosis were evaluated. MCW, MIC, tooth loss (TL), and alveolar bone loss (ABL) were retrospectively evaluated in 700 panoramic images from dental patients in Hong Kong using commercially available software. To estimate possible predictors for identifying the risk of osteoporosis, age, TL, and ABL were evaluated with the receiver operating characteristic (ROC) curves for each gender separately. The age groups 60s (sixties), 70s and 80s showed statistically significant gender differences. For example, a smaller MCW and more MIC Class 3 were found in females. Furthermore, females exhibited a statistically significant increase in TL in the age groups 50 years and above. In males, age, TL or ABL did not correlate with MCW, whereas in females it statistically significantly did. Meanwhile, the correlation between ABL and MCW and MIC was weak for both genders. Concrete cut-off values to identify patients at risk of osteoporosis were 60.15 years and 3.5 missing teeth in females, and 72.55 years in males. Age and tooth loss were related to MCW and MIC in the population investigated. An age of ≥60 as well as more than 3.5 teeth lost seem to be indicators for a risk of osteoporosis in Chinese females based on panoramic views using artificial-intelligence-based software.