Abstract
Background:
Osteoporosis places a significant strain on the healthcare system and contributes significantly to morbidity and mortality. Digital panoramic radiographs, which are typically taken for routine dental examinations, are quite useful for spotting early low mineral density changes.
Aim:
The aim of the study was to assess the diagnostic efficiency of gonial and antigonial radiographic indices in identifying low bone mineral density in aged women.
Materials and Methods:
A total of 800 panoramic radiographs were assessed from the archives, and 118 radiographic images among controls and study groups were included. Radiomorphometric indicators such as gonial angle (GA), gonial index (GI), antigonial angle (AA), antigonial depth (AD), and antigonial index (AI) were studied.
Results:
A statistically significant higher GA, GI, AA, AD, and AI among control groups were evident compared to study groups.
Conclusion:
In screening for early osteoporotic alterations, all indices evaluated in the present study can be used as radiographic screening methods to identify low bone mineral density among aged women.
Novelty:
The study attempted to evaluate the GA, GI, AA, AD, and AI of the mandible in orthopantomography individually for normal and aged women. Hence, they can be used as an opportunistic screening tool.
Keywords: Antigonial indices, gonial indices, osteoporosis, panoramic radiographs, radiomorphometric indices
Introduction
Low bone mass and microstructural degeneration of bone tissue are characteristics of osteoporosis, the silent pandemic, which increases bone fragility and fracture risk.[1] There are three stages of menopause; initially, perimenopause, is when ovaries gradually produce less estrogen, resulting in irregular menstrual cycles between the ages of 45 and 55 years. Second, menopause is when the ovaries are no longer releasing as much estrogen as required and 4 years on average following the onset of perimenopause. Third, the postmenopause phase starts right after 12 months of menopause. Aged women (those over the age of 45) are more likely to develop osteoporosis than premenopausal women because of decreased estrogen production and the accompanying decline in bone mineral content.[1,2]
There are 200 million women affected worldwide, and the prevalence rises with age.[3,4,5] When compared to the ocular evaluation of the cortex, osteoporosis can be detected utilizing mandibular parameters based on the thickness and shape of the cortex.[6] It is possible for routine dental radiographs, such as orthopantomography (OPG) and periapical X-rays, to serve the dual purposes of dental investigation and low bone mineral density screening due to the growing body of evidence supporting osteoporotic manifestation within the mandible.[7] There have been several techniques investigated, including those that require precise measurements to determine radio morphometric indices, straightforward visual evaluation, and mandibular densitometry.[8,9] However, the gold standard method to identify osteoporosis is dual-energy X-ray absorptiometry.[3,4]
Five radio morphometric indices, such as mental index, panoramic mandibular index, gonial index (GI), antigonial index (AI), and Klemetti index, are routinely used to quantify the thickness or porosity of the mandibular bone on a panoramic radiograph.[10] These indices varied from medium to high in terms of their sensitivity and specificity for osteoporosis.[11] These indices can be applied globally and are repeatable and useful even for less experienced dentists. However, given that there are numerous factors, such as standardization of the technique, the quality of the radiograph, etc., that might affect the detection of low bone mineral density, some studies recommended using the panoramic radiograph in addition to other clinical examinations.[12]
Since low bone mineral density has no symptoms at first, it may eventually grow to a late stage before being recognized, which carries a higher risk of related morbidity and even mortality. The prognosis and quality of life of those with low bone mineral density can, therefore, be enhanced by early detection.[13] However, only a few studies in the literature have focused on the mandibular gonial and AIs to detect low bone mineral density. Hence, the present study was conducted to radiographically evaluate the gonial and AIs in detecting low bone mineral density among young and aged women.
Materials and Methods
The three primary dental care centers, such as Institute of Dental Sciences, Bareilly, Bapuji Dental College and Hospital, Davangere, and Saveetha Dental College, Chennai, pooled the OPGs from archives during a period of 1 year from January 2022 to December 2022. The study protocol was approved by the Institutional Human Ethical Committee of Saveetha Dental College, Chennai (IHEC/SDC/FACULTY/21/PERIO/572, Dated: July 07, 2021). All the other institutes waived the need for ethical clearance and informed consent due to the retrospective nature of the study. The procedures followed were under the ethical standards of the institutional committee on human experimentation and with the Helsinki Declaration of 1975 as revised in 2019.
Sample size evaluation
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Analysis: A priori: Compute required sample size
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Input: Tail (s) = One
Ratio var1/var0 = 1.5
α err prob = 0.05
Power (1-β err prob) = 0.95
-
Output: Lower critical χ² = 160.9148
Upper critical χ² = 160.9148
Df = 133
Total sample size = 236
Actual power = 0.9505880.
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A power analysis was established by G*power, version 3.0.1 (Franz Faul Universitat, Kiel, Germany). A sample size of 236 patients (118 patients in each group) would yield 95% power to detect significant differences, with an effect size of 1.5 (derived from the article Bajoria, et al.,[14]) and a significance level of 0.05.
A single trained expert oral radiologist who was blinded for the research groups reviewed 800 OPG taken for diverse diagnostic purposes. Out of which, 118 OPG each from aged women over the age of 45 years formed the study group, and healthy participants between the age group of 18 and 44 years made up the control group. Male patients with fully edentulous arches, jaw pathologies, bone-destructive lesions, artifacts, and those with dental implants were excluded from the study.
Before the initiation of the study, the examiner underwent standardization and calibration overseen by a consultant from the department of oral medicine, diagnosis, and radiology. This procedure was implemented to ensure consistent interpretations and uniform examinations, achieving a kappa value of 1.00. All radiographs were taken using a digital orthopantomograph (PM2002cc Proline), with exposure parameters set at 65–70 kVp and 8 mA, and Kodak T-Mat, speed-E films were utilized. The radiographs underwent a subjective evaluation to confirm patient positioning, head alignment, film density, and contrast, meeting the predefined quality standards of the reviewer. Linear and angular measurements were subsequently manually traced using marker pens, vernier caliper, protractors, and scales. The structures of interest were outlined on transparencies. Following this, each image was cropped into right and left sides and appropriately labeled.
The study included various radiomorphometric indices[14,15] for evaluation:
Gonial angle (GA) was calculated on each side by drawing a line parallel to the border of the mandible and another parallel to the posterior borders of the ramus and condyle [Figure 1]
GI measurement of the mandibular cortical thickness taken at the angle formed by tangent lines to the bottom of the mandible and posterior border of the ramus [Figure 2]
Antigonial angle (AA) is measured by drawing two lines in the antigonial region that are parallel to the lower cortical boundary and then measuring the angle at the deepest point of the antigonial notch [Figure 3]
Antigonial depth (AD) is measured as the distance along an angle between the mandible’s inferior cortical border and the deepest point of the antigonial notch concavity [Figure 4]
AI measured the cortical width by extending a line of best fit along the anterior mandibular border, in the area anterior to the gonial [Figure 5].
Figure 1.
Cropped orthopantomography showing the measurement of gonial angle
Figure 2.
Cropped orthopantomography showing the measurement of gonial index
Figure 3.
Line diagram depicting the measurement of antigonial angle. AGA: Antigonial angle
Figure 4.
Line diagram depicting the measurement of antigonial depth. AGD: Antigonial depth
Figure 5.
Line diagram depicting the measurement of antigonial index. AGI: Antigonial index
The mentioned indices were evaluated in every OPG of both study and control groups using Image J software, and the data were entered in a Microsoft Excel sheet for statistical analysis.
Statistical analysis
All the data were analyzed using the Statistical Package for the Social Sciences software, version 17.0 (IBM, Chicago, Illinois, USA). The test of normality was prepared by the Kolmogorov–Smirnov and Shapiro–Wilk tests. As the data were not normally distributed, a nonparametric test was used for the analysis. Descriptive statistics and cross-tabulations were evaluated with the Mann–Whitney U test and were computed with the statistical significance set at P < 0.05. A pairwise comparison between the radiomorphometric indices used among both groups was accomplished by the Dunn–Bonferroni test.
Results
The mean age in the study population was found to be 59 years and approximately 30 years in the control group. The mean ± standard deviation of various radiomorphometric index in control and study group among GA was 131.18 ± 2.75 and 107.06 ± 6.08, in GI was 1.30 ± 0.11 and 0.89 ± 0.12, in AA was 161.80 ± 2.48 and 147.85 ± 6.46, in AD was 1.65 ± 0.11 and 1.20 ± 0.15, and in AI was 3.41 ± 0.20 and 2.48 ± 0.19, respectively. Upon comparison of radiomorphometric indices among the control and study groups showed a statistically significant difference with P < 0.001 [Table 1]. However, the intercomparison of the control and study groups with various radiomorphometric indices also showed a statistically significant difference with P < 0.001 [Table 2]. A Dunn–Bonferroni test was used to pairwise compare all the various radiomorphometric indices among controls and study groups [Table 3], which showed a statistically significant difference with P < 0.001.
Table 1.
Comparison of radiomorphometric indices among control and study groups
| Radiomorphometric indices | Groups | Mean±SD | P |
|---|---|---|---|
| GA (°) | Control | 131.18±2.75 | 0.001* |
| Study | 107.06±6.08 | ||
| GI (mm) | Control | 1.30±0.11 | 0.001* |
| Study | 0.89±0.12 | ||
| AA (°) | Control | 161.80±2.48 | 0.001* |
| Study | 147.85±6.46 | ||
| AD (mm) | Control | 1.65±0.11 | 0.001* |
| Study | 1.20±0.15 | ||
| AI (mm) | Control | 3.41±0.20 | 0.001* |
| Study | 2.48±0.19 |
*Statistical significance set at 0.05. SD: Standard deviation; AI: Antigonial index; AD: Antigonial depth; AA: Antigonial angle; GI: Gonial index; GA: Gonial angle
Table 2.
Intercomparison of control and study groups with various radiomorphometric indices
| Groups | Radiomorphometric indices | Mean±SD | P |
|---|---|---|---|
| Control | GA (°) | 131.18±2.75 | 0.001* |
| GI (mm) | 1.30±0.11 | ||
| AA (°) | 161.80±2.48 | ||
| AD (mm) | 1.65±0.11 | ||
| AI (mm) | 3.41±0.20 | ||
| Study | GA (°) | 107.06±6.08 | 0.001* |
| GI (mm) | 0.89±0.12 | ||
| AA (°) | 147.85±6.46 | ||
| AD (mm) | 1.20±0.15 | ||
| AI (mm) | 2.48±0.19 |
*Statistical significance set at 0.05. SD: Standard deviation; AI: Antigonial index; AD: Antigonial depth; AA: Antigonial angle; GI: Gonial index; GA: Gonial angle
Table 3.
Pairwise intracomparison of radiomorphometric indices among control and study groups
| Radiomorphometric indices | P-value in control groups | P-value in study groups |
|---|---|---|
| GA - GI | 0.001 | 0.001 |
| GA - AA | 0.001 | 0.001 |
| GA - AD | 0.001 | 0.001 |
| GA - AI | 0.001 | 0.001 |
| GI - AA | 0.001 | 0.001 |
| GI - AD | 0.001 | 0.001 |
| GI - AI | 0.001 | 0.001 |
| AA - AD | 0.001 | 0.001 |
| AA - AI | 0.001 | 0.001 |
| AD - AI | 0.001 | 0.001 |
AI: Antigonial index; AD: Antigonial depth; AA: Antigonial angle; GI: Gonial index; GA: Gonial angle
Discussion
The impact of low bone mineral density on public health is enormous. Menopausal osteoporosis is the term used to describe the condition, which is most frequently encountered in elderly women.[16,17] Since the jawbone serves as the supporting framework for teeth and dental implants, it must be of the highest quality in dental practice. As a result, low bone mineral density has been the subject of substantial research in this field.[18] Investigating if low bone mineral density has any consequences on the jawbone is crucial. In addition, given the huge number of people who undergo dental treatments, dental imaging methods may be used as opportunistic low-bone mineral density screening tools.[19]
The present study aimed to assess the diagnostic efficiency of gonial and AIs to diagnose low bone mineral density in aged women and intercompare the indices used among themselves in both the control and study groups and showed a statistical difference in the indices used and also among the two groups. Similarly, Palaskar and Ambildhok[20] conducted a cross-sectional study on 325 OPGs and showed the average age of the participants was 23.5 ± 2.5 years. Females, in comparison with males, displayed much lower mental index (MI), panoramic mandibular index (PMI), and AI parameters.
Tofangchiha et al.[6] compared the panoramic radiographs of 49 aged women with decreased bone mineral density and 42 unaffected controls. The results showed the sensitivity and positive predictive value of mental and AI were superior to those of specificity. However, the morphological index and a straightforward visual assessment of cortical thickness revealed the reverse. Furthermore, it was found that radiomorphometric indices and morphology are more reliable than a straightforward visual assessment of cortical thickness in the diagnosis of low bone mineral density. This was in parallel with the present study that radiomorphometric indices can be used as adjuvant methods for screening low bone mineral density on OPG.
Bajoria et al.[14] measured the radiomorphometric indices and the correlation between the indices and the patient’s age and sex was discovered. The findings revealed a considerable level of 78.26% agreement between AI and MI. Contrarily, when comparing GI with PMI, MI, and AI, respectively, agreement of 30.43%, 52.17%, and 56.52% was seen, which was in partial agreement with the present study. This difference could be attributed to the different indices considered in the study.
Gaur et al.[21] evaluated various radiomorphometric indices[22] in 40 randomly selected aged women aged 40–69 years and were subjected to dental panoramic radiography. Mean GI differences were discovered to be statistically significant (P = 0.000). However, AI failed to reach statistical significance. This result partially matched the current investigation. The methodological issue of locating the line that “best fits” the anterior border of the ascending ramus, the interaction between dental status and AI, and the dearth of data linking this index to BMD values were among the arguments put forth to demonstrate that AI was a poor index to use for a radiographic low bone mineral density assessment.
Ghosh et al.[23] analyzed changes in the antigonial region concerning age, gender, and dental status in a total of thousand panoramic radiographs. Both males and females showed a trend with age toward a decrease in AA and an increase in AD. In addition, there were discrepancies between the right and left AA s and depths, with the left having a larger angle and the right having a larger depth. When the dentition status changed from entire dentition to partially edentulous and from partially dentulous to completely edentulous, there was a considerable decrease in AA and an increase in AD.
Asha and Kaimal[24] evaluated the accuracy of radiomorphometric indices of panoramic radiographs, such as the AI and GI in identifying low bone mineral density. Statistically significant differences were noted among AI and GI indices, supporting the results of the present study.
According to Leite et al.,[25] AIs and GAs cannot be utilized as low bone mineral density predictors, which contrasts with the results of the present study. The sample population employed and the alternative radiomorphometric indices used may be the cause. The left side’s AI had a nonsignificant value, according to Mahl et al.[26] The comparison of each side independently using a distinct assessment approach could be the cause.
In the present study, all the radiomorphometric indices showed statistically significant differences. Furthermore, the results demonstrated that the gonial and antigonial regions undergo remodeling with advancing age. So further, it could be abridged that all these indices could be used as screening tools in detecting low bone mineral density using panoramic radiographs at the earlier stages.
Limitations
In this initial study, low bone mineral density was screened using radiomorphometric indicators of the gonial and antigonial regions only. Further, a large sample size with several additional indices should be used to more precisely predict osteoporotic changes in bone using panoramic radiographs. Further validation of the results with dual-energy X-ray absorptiometry (DXA) needs to be considered.
Future prospective
Independent studies to compare indices from the right and left sides can help in assessing the symmetry of the jaw, which could augment in detecting low bone mineral density at first. As a result, it is crucial that the dentist considers the likelihood of getting these indices and can assess their impact on other health outcomes.
Conclusion
Antigonial and gonial indices of the mandible, computed from panoramic radiographs, are the straightforward technique in low bone mineral density screening of dental patients, delivering the most advantage of being radiographed. These indicators for low bone mineral density detection on panoramic radiographs are trustworthy, reproducible, and advantageous for dental patients. As a result, when interpreting panoramic radiographs, dentists should be aware of these indices.
Conflicts of interest
There are no conflicts of interest.
Funding Statement
Nil.
References
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