Background: Postmenopausal women exhibit reduced bone mineralization, which causes bone resorption, including that of alveolar bone. Parathyroid hormone has been shown to play a role in alveolar bone resorption. Objective: This study aims to analyze relationships between parathyroid hormone and other factors that may contribute to alveolar bone resorption in postmenopausal women. Methods: This cross-sectional study included 82 postmenopausal women aged 50–74 years, who resided in Central and East Jakarta, Indonesia. Subjects' data were obtained through questionnaires, dental examinations, and blood collection for the examination of parathyroid hormone levels by enzyme-linked immunosorbent assay and using panoramic radiography to measure bone resorption. Results: Spearman correlation analysis showed a significant correlation between parathyroid hormone level (p = 0.005) and extent of alveolar bone resorption, but age (p = 0.292), menopausal duration (p = 0.244), and number of missing teeth (p = 0.517) were not significantly correlated with the extent of alveolar bone resorption. Conclusion: Various factors play a role in the mechanism of bone resorption, so knowing the role of each factor is expected to reduce the effects of alveolar bone resorption that occurs in postmenopause. Among the factors investigated in this study, the parathyroid hormone was the sole factor correlated with postmenopausal alveolar bone resorption.

Background/Objective: Early periodontitis diagnosis is challenging due to varying staging and grading systems. While clinical parameters like bleeding on probing (BoP) and pocket depth (PD) are commonly used, periapical radiographs provide valuable information about bone loss and periodontal ligament changes. However, a clear definition of early periodontitis, particularly regarding alveolar bone crest changes, remains elusive. Methods: This cross-sectional study involved 21 participants aged 20–30 with clinical signs of periodontitis and radiographic evidence of alveolar bone changes and periodontal ligament widening. Four dentists assessed 40 cases for BoP, 40 for PD, and 40 for periapical radiographs. Results: Statistical analysis revealed that the pocket depth measurement was the most significant factor in diagnosing early periodontitis (Fisher’s exact test, p-value = 0.000). Additionally, the irregularity of the alveolar crest proved to be a significant marker compared to periodontal ligament width (Fisher’s exact test, p-value = 0.000). A Kendall Tau_b test (p-value = 0.000, r = 1.000) confirmed pocket depth to be the most influential parameter among the assessed factors. Conclusions: While this study highlights the importance of clinical and radiographic assessments in early periodontitis detection, integrating these findings into a definitive diagnosis can be complex. The standardization of diagnostic techniques and the development of advanced radiographic interpretation methods are crucial to improve accuracy. Further research is needed to refine diagnostic criteria and explore additional tests for early periodontitis detection.

The purpose of this study is to evaluate the relationship between radiomorphometric indices and fractal dimension (FD) analysis in jawbone radiographic density using Cone-Beam Computed Tomography (CBCT). The study included 87 CBCT datasets from dental patients aged 50–79. Four radiomorphometric indices (Computed Tomography Cortical Index (CTCI), Computed Tomography Mental Index (CTMI), Computed Tomography Index-Superior (CTI-S), and Computed Tomography Index-Inferior (CTI-I)) along with age, gender, remaining teeth, and mandibular bone height were evaluated. FD was assessed in trabecular bone near the mental foramen (ROI 1) and on the mandibular cortical bone (ROI 2). Relationships between indices and variables were analyzed using Pearson chi-square, Fisher’s exact, one-way ANOVA, Kruskal–Wallis, and Spearman’s rho tests. ANOVA showed significant differences in mandibular bone height (p = .004) and FD at ROI 2 (p = .000) across three mandibular cortex types (C1, C2, C3). Spearman’s rho indicated significant correlations between FD at ROI 2 and CTMI, CTI-S, CTI-I (p = .000), and between mandibular bone height and CTMI (p = .010). The correlations of FD at ROI 2 ranged from strongest to weakest with CTCI, CTMI, CTI-S, and CTI-I. High-risk osteoporosis radiomorphometric indices are associated with FD analysis of cortical bone.

This study aimed to evaluate the correlation between the Osteoporosis Self-Assessment Tool for Asians (OSTA) and three panoramic indices in relation to z-score and t-score values using quantitative ultrasound (QUS) bone densitometry. The sensitivity, specificity, and area under the curve (AUC) of the OSTA index were also measured using the QUS tool to evaluate the method’s performance in identifying people at risk of osteoporosis. The study employed a cross-sectional design with 387 participants (190 men, 197 women). Patients’ mandibular cortical indexes (MCI), mandibular cortical widths (MCW), and panoramic mandibular indexes (PMI) were measured from panoramic images. The sensitivity, specificity, and AUC were calculated using an OSTA index cutoff of ≤−1 and a t-score of ≤−1.0 for the QUS bone densitometry. The coefficient correlation of the OSTA index with the z-score (r = −0.563, p < 0.001) and t-score (r = −0.740, p < 0.001) shows a higher value than the MCI, MCW, and PMI, per the QUS. The sensitivity, specificity, and AUC values with a cutoff t-score of ≤−1.0 per the QUS in men was 90%, 50%, and 0.812, and in women, 96.8%, 30%, and 0.862. The OSTA index is a simple method that can be used in general dental practice.

Background: Periodontal disease is the second most common tooth and mouth disease in Indonesia. Moreover, radiographic examination is the most useful tool to evaluate alveolar bone loss and diagnose periodontal diseases. This study aimed to analyze radiographically the relationship between alveolar bone loss and age among patients with chronic periodontitis. Methods: A total of 192 digital periapical images of patients aged 25–40 years were collected. Four regions were selected, including the maxillary and mandibular central incisors and maxillary and mandibular first molars. Alveolar bone loss was measured in the mesial and distal surfaces. Results: The mean and standard deviation for alveolar bone loss in age categories 1 (age 25–32 years) and 2 (age 33–40 years) were 4.03 ± 1.46 and 5.23 ± 2.5 (mm), respectively. Alveolar bone loss demonstrated a significant relationship with patient’s age (p < 0.001, Mann–Whitney U test). Conclusions: The mean and standard deviation of alveolar bone loss reduction in patients with chronic periodontitis was 4.87 ± 0.2 (mm). The alveolar bone loss on the mandibular central incisors’ mesial surface is the highest among other regions.

Cone-beam computed tomography (CBCT) is becoming more widely used in the field of dentomaxillofacial radiography, but its utility for bone quality assessment is still limited. This study was conducted to describe the use of radiomorphometric examination and fractal dimensions (FDs) for osteoporosis risk detection through CBCT in elderly patients. Medical databases (PubMed, Scopus, Elsevier, and Directory of Open Access Journals (DOAJ)) were searched using the keywords osteoporosis, radiomorphometric, fractal dimension, and fractal analysis. The search limits applied were available full-text articles, publication years 2012-2021, and articles published available in English. Then, the articles included were systematically reviewed following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses. A total of four studies were included in this review. Seven radiomorphometric indices were used, and most indices were adopted from panoramic radiographs, such as the computed tomographycortical index, computed tomography mental index, computed tomography index, and four other indices along the mandible, which are the S (symphysis), A (anterior), M (molar), and P (posterior) indices. All of the radiomorphometric studies show similar results. These indices can identify osteoporosis-related changes and are useful as osteoporosis screening tools on CBCT. However, all FD studies show different methods and discover heterogeneous results. Radiomorphometric measurement methods in CBCT can be used to detect patients at risk for osteoporosis. The FD analysis method still finds heterogeneous research results, so it is recommended to standardize the method in terms of the shape, size, and location of the region of interest.