ArticleOral health & preventive dentistry2020
Mandibular Radiomorphometric Indices and Tooth Loss as Predictors for the Risk of Osteoporosis using Panoramic Radiographs.
Article in Oral health & preventive dentistry, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
11 citing papers in PubMed, 1 synthesis or guideline pooled it, 20 citations in OpenAlex.
- Mandibular Radiographic Assessment in Sickle Cell Disease: A Systematic Review of Radiomorphometric Indices and Fractal Dimension.Special care in dentistry : official publication of the American Association of Hospital Dentists, the Academy of Dentistry for the Handicapped, and the American Society for Geriatric DentistryPooled it
- The performance of radiomorphometric indices in sex differentiation compared to the W index.European oral research · 2026Article
- Radiomorphometric indices for measuring mandibular bone quality in oncologic patients.Oral radiology · 2025Article
- Association of Osteoporosis with Tooth Loss and Dental Radiomorphometric Indices.Biomedicines · 2024Article
- Application of Panoramic Radiography in the Detection of Osteopenia and Osteoporosis-Current State of the Art.Current osteoporosis reports · 2023Review
- Machine Learning in Dentistry: A Scoping Review.Journal of clinical medicine · 2023Article
- Overview on postmenopausal osteoporosis and periodontitis: The therapeutic potential of phytoestrogens against alveolar bone loss.Frontiers in pharmacology · 2023Review
- Content Analysis of YouTube Videos on Radiographic Anatomy on Dental Panoramic Images.Healthcare (Basel, Switzerland) · 2022Article
- Mandibular cortical bone structure as risk indicator in fractured and non-fractured 80-year-old men and women.BMC oral health · 2021Article
- Dentists' knowledge about osteoporosis and their ability to identify the disease.Advances in rheumatology (London, England) · 2021Article
- Clinical guidelines for the application of panoramic radiographs in screening for osteoporosis.Oral radiology · 2021Review
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeTo 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. MATERIALS AND
methodsMCW, 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.
resultsThe 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.
conclusionAge 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.
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