Mandibular inferior cortex erosion as a sign of elevated total serum calcium in elderly people: a 9-year follow-up study

Three panoramic indices for identification of healthy older people at a high risk of osteoporosis

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Three panoramic indices could be used to detect the risk of osteoporosis.

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Severely eroded mandibular cortex as a potent marker of osteoporosis.

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Low bone density may occur in older people under 65 years.

Background

This study aimed to identify whether healthy older adults are at a high risk of osteoporosis based on the association between the T-score values of bone mineral density (BMD) and three panoramic indices.

Materials and methods

All participants (50–64 years old) underwent calcaneal quantitative ultrasound (QUS) bone densitometry. In total, 371 panoramic images were included in the analysis. The mandibular cortical width (MCW), mandibular cortical index (MCI), and panoramic mandibular index (PMI) were the three parameters assessed. The data were examined using one-way analysis of variance or Kruskal–Wallis H and post hoc tests. Spearman’s rho was used to measure correlation coefficients.

Results

T-score distributions in the normal, osteopenia, and osteoporosis categories were 80 (21.6%), 236 (63.6%), and 55 (14.8%), respectively. T-scores were significantly related to age, MCW, PMI, and MCI (p < 0.001). Participants with osteopenia and a risk of progression to osteoporosis had an average MCW value of < 3.38 mm, a PMI of < 0.31, and an MCI class 2 and 3 distribution in 211 (56.9%) participants. The highest to lowest correlation coefficients with a significant relationship to the T-score were for age (r = -0.844), MCI (r = 0.456), MCW (r = 0.359), sex (r = 0.354), and PMI value (r = 0.292).

Conclusions

This study found that healthy older people with Class 3 MCI, an MCW < 3 mm, and a PMI ratio < 0.3 had a significant association with lower BMD T-scores on QUS and were at higher risk of osteoporosis.

Automatic detection of osteoporosis based on hybrid genetic swarm fuzzy classifier approaches

OBJECTIVES

This study proposed a new automated screening system based on a hybrid genetic swarm fuzzy (GSF) classifier using digital dental panoramic radiographs to diagnose females with a low bone mineral density (BMD) or osteoporosis.

METHODS

The geometrical attributes of both the mandibular cortical bone and trabecular bone were acquired using previously developed software. Designing an automated system for osteoporosis screening involved partitioning of the input attributes to generate an initial membership function (MF) and a rule set (RS), classification using a fuzzy inference system and optimization of the generated MF and RS using the genetic swarm algorithm. Fivefold cross-validation (5-FCV) was used to estimate the classification accuracy of the hybrid GSF classifier. The performance of the hybrid GSF classifier has been further compared with that of individual genetic algorithm and particle swarm optimization fuzzy classifiers.

RESULTS

Proposed hybrid GSF classifier in identifying low BMD or osteoporosis at the lumbar spine and femoral neck BMD was evaluated. The sensitivity, specificity and accuracy of the hybrid GSF with optimized MF and RS in identifying females with a low BMD were 95.3%, 94.7% and 96.01%, respectively, at the lumbar spine and 99.1%, 98.4% and 98.9%, respectively, at the femoral neck BMD. The diagnostic performance of the proposed system with femoral neck BMD was 0.986 with a confidence interval of 0.942-0.998. The highest mean accuracy using 5-FCV was 97.9% with femoral neck BMD.

CONCLUSIONS

The combination of high accuracy along with its interpretation ability makes this proposed automatic system using hybrid GSF classifier capable of identifying a large proportion of undetected low BMD or osteoporosis at its early stage.