Radiographic assessment of the mandible to diagnose women with osteoporosis—a literature review

Introduction

Background

Osteoporosis is a bone disease causing significant morbidity and mortality worldwide (1). It is characterized by reduced bone mass and deterioration of bone microarchitecture leading to an increased risk of bone fracture (2). Nearly half of the postmenopausal women in India are more likely to develop osteoporosis (3). According to estimates, osteoporosis affects more than 200 million individuals worldwide at the moment. The International Osteoporosis Foundation has released figures showing that 1 in 3 women over 50 and 1 in 5 men may have an osteoporotic fracture over their lifetimes (4). Osteoporosis is frequently underdiagnosed since it may not show any clinical symptoms until a fracture occurs (5). In order to prevent fractures early diagnosis is essential. Though there are different imaging modalities available to detect bone mineral density (BMD), dual-energy X-ray absorptiometry (DEXA) is the preferred method across the world due to its accuracy and minimal radiation exposure exceptionally low radiation dose to patients, short scan times, high resolution images, good precision and inherent stability of calibration (6). World Health Organization (WHO) has defined osteoporosis based on DEXA BMD as T-score ≤−2.5. Osteopenia is a state of low bone mass defined by a BMD T-score between −1 and −2.5 (7). DEXA of the femoral neck is found to have a precision of 2–5% while DEXA of the spine have a precision of 0.5–1% (8). On the contrary, DEXA is unsuitable for widespread use due to its low availability and high price, making it difficult to detect and treat osteoporosis (9). So, cheaper alternative approach to assess skeletal condition is required for screening purposes (10). Dental radiographs are affordable, and a considerable portion of the total population already has them done regularly. As a result, dental radiographs might have a lot of potential as an osteoporosis screening tool. Several review studies explore the utilization of dental radiographs for the diagnosis of osteoporosis. Jaw bone mass is diminished in osteoporotic patients which puts dentists in a potentially beneficial position for patient screening for indications of osteoporosis given that dental radiography may be effective as a rapid way to screen patients for the disease (11). Dentists may also be among the first health professionals to recognize a patient who has osteoporosis but is yet to be diagnosed or a patient who is at risk of developing osteoporosis later in life (12).

Evidence in the literature indicates that the mandibular indices in combination with surveys on the risk of fracture can help in early osteoporosis detection (13). Systematic reviews have investigated the possibility of cone-beam computed tomography (CBCT) for screening patients with low BMD and concluded that CBCT has high accuracy in predicting osteoporosis and strong sensitivity and specificity (14,15). The current literature review focuses on the utility of orthopantomogram (OPG), CBCT, and periapical radiographs in diagnosing women with osteoporosis.

Rationale and knowledge gap

Osteoporosis affects the mandibular bone mass at a rate similar to that of the skeletal bone mass. BMD of the mandible has been linked morphologically, densitometrically, and architecturally to the BMD of the lumbar spine and femoral neck (16). Consequently, dentists play a crucial role in the early detection of osteoporosis. Several methods have been attempted to be used as an alternative to DEXA. Oral indices such as the number of teeth present, resorption of alveolar bone, mandibular BMD, lamina dura width, mandibular cortical thickness and morphology of the mandibular inferior cortex measured in dental radiographs like OPG, CBCT and intraoral periapical radiograph (IOPA) have been used to predict low BMD. If the radiographic indices are found reliable in identifying patients with low BMD, then dentists may use dental radiographs as a screening technique to refer the patient for a bone densitometry test.

Objective

This literature review aimed to analyze the evidence available in the literature to provide a reliable alternative method to diagnose osteoporosis in women using dental radiographs. We present this article in accordance with the Narrative Review reporting checklist (available at https://fomm.amegroups.com/article/view/10.21037/fomm-23-33/rc).

Methods

Search strategy

Articles related to the diagnosis of osteoporosis in women and mandibular bone changes were searched in the PubMed database using keywords like ((bone) OR (mandible) OR (jaw)) AND ((dental radiograph) OR (orthopantomography) OR (CBCT)) AND (Osteoporosis). The database was last searched on the month of December 2022.

Study selection

Observational studies related to osteoporosis in women and bone changes of the Mandible published for a period of 11 years, from 2011 to 2021, in the English language were selected for the study. The following were excluded from consideration: articles written in languages other than English, those lacking the full text, not related to dental radiographs and osteoporosis in men, articles that did not use DEXA as a reference test, articles that included patients with other systemic diseases, other oral conditions like periodontal disease, implants and patients under medication. Studies that used artificial intelligence, computed-based automated systems and machine learning were also eliminated. Case studies, review papers, letters to the editor, systematic reviews, questionnaire studies and conference proceedings were not considered. Two authors (S.R., B.D.) independently screened the articles and included them in the review process based on the inclusion and exclusion criteria. The decision of the third author (V.V.) was considered in case of discrepancies between the two authors.

Literature screening

A preliminary review was performed based on the full title and abstract, before proceeding to full-text review. Data like radiographs used, parameters analyzed, observation and inference were extracted from each of the included studies and qualitative analysis was performed. The review was performed by three reviewers. After the individual reviews of the three reviewers were finished, a group discussion ensued. When one of the reviewers disagreed, the other two assessed the circumstance and considered whether or not the majority of the group agreed with the data. A summary of the search strategy has been provided in Table 1.

Quality assessment

The Joanna Briggs Institute (JBI) Critical Appraisal Tool was used to evaluate the quality of the papers (17). There are 10 quality indicators in the JBI checklist for diagnostic test accuracy. These quality indicators were converted to a score of 100%, with a score of >80% being classified as high quality, 60–80% as medium quality, and 60% as low quality. Two authors conducted the quality assessment, while a third author handled the discrepancy between the two assessors.

Discussion

A total of 269 articles were screened in PubMed those were within the time period of 2011–2021, out of which 172 articles were excluded as they were not related to dental radiographs and osteoporosis based on title and abstracts. 75 articles were excluded based on exclusion criteria like review articles [12], systematic reviews [8], questionnaires [2], articles in languages other than English [2], articles that did not have full texts [5], articles that didn’t consider DEXA as a standard method [2], articles that included combination OPG and IOPA or CBCT [4], studies done on male population [5], articles with patients having Implants [7], Periodontitis [5], edentulous dental arch [1], other systemic diseases [9] or those under medication [5], articles that evaluated Temporomandibular joints or Condyles [3], articles with machine learning, artificial intelligence, computer-based automated system [6] were all excluded. Post excluding all the articles that did not fulfill the criterion, a total of 20 papers were included for review.

OPG

Twelve studies that evaluated the changes in the mandible based on OPG, of which four were from India (5,16,18,19), two from Saudi Arabia (20,21), two from Iran (22,23), two from Brazil (24,25) and one from Japan (3) and Korea (26). The mean sample size in the studies was 118.7±110.91 with a range of 40–431. In all the articles, the population was classified as normal or osteoporotic based on DEXA. DEXA of the lumbar spine was used as a standard in 10 studies, the femur in 8, and the hip in one of the studies. Among them, in 6 studies DEXA of both lumbar spine and femur were done. The mean age of the participants included in the studies was 56.88±12.24 years. Mandibular cortical width (MCW) of mandible was studied in 9 articles (75%), mandibular cortical index (MCI) in 6 (50%), and fractal dimension (FD) in 3 (25%) articles. The other parameters evaluated were panoramic mandibular index (PMI), trabecular bone area (TBA), mandibular ratio (M/M ratio), gonial index, antegonial index (AI), and bone resorption severity index (BRSI). Three thresholds were determined for MCW with varying sensitivity and specificity. The cut-off for MCW was obtained as 4.29 mm in an Iranian study with 81.4% sensitivity and 58.3% specificity, compared to 3.35 mm in an Indian study with 55% sensitivity and 93.3% specificity. The MCW threshold for osteoporosis diagnosis was found to be 4.1 mm in a Saudi Arabian study, with a 60.2% sensitivity and 68.4% specificity. Three (25%) of the articles were considered to be of high quality, and nine (75%) were of medium quality (Table 2).

CBCT

Out of seven studies, two from Syria (27,28), two from Brazil (29,30) and one each from Egypt (31), Turkey (32) and Korea (8) evaluated the alterations in the mandible using CBCT. The sample size ranged from 38 to 120, with a mean of 62.57. Six studies used DEXA of the lumbar spine as the standard, four used the femur, one used the hip and one did not specify the area. Among them, four studies investigated both the lumbar spine and the femur, one lumbar and the hip, and one lumbar alone. The study participants were 58.82 years old on average. There were four articles that evaluated computed tomography mental index (CTMI), four on computed tomography mandibular index (CTI) and two on computed tomography cortical index (CTCI). In addition to FD, histogram analysis, MCW, cortical quality and radiographic density (RD) were also examined in various papers. Another study used BoneJ-ImageJ to measure connection density, trabecular thickness (Tb.Th), trabecular separation (Tb.S), bone volume fraction (BV/TV), specific bone surface (BS/TV), and bone volume fraction. In one article, a novel CBCT-driven osteoporosis index (3D MOI) was established. Age-related CBCT measurements revealed sensitivity and specificity levels of over 74.0% (Table 3). When employing RD, the threshold for lumbar vertebrae was 867–900 while that for the femoral neck was 829–838. Two (29%) were of low quality and 5(71%) were medium-quality articles.

IOPA

A study from Indonesia (33), evaluated the alterations in the mandible based on IOPA. The sample size was 31. Based on DEXA, the population was divided into three categories: normal, osteopenic and osteoporotic. The study used standard DEXA procedure on the lumbar and femur. The average age of the participants was 65.2±7.5 years. Trabecular structural analysis was performed with BoneJ and ImageJ—Parameters used bone area fraction (BA/TA) and 2D Tb.Th. The article was of medium quality (Table 4).

Key findings

The DEXA method is an advance in non-invasive BMD determination which provides a lower absorbed radiation dose, improved spatial resolution and faster scan times. Despite being the best diagnostic method now available, DEXA is expensive and labor-intensive to screen osteoporotic patients. Although BMD can be assessed everywhere on the body, two areas—the lumbar spine and the proximal femur—have been identified as more reliable and representative (25). Osteoporosis can occasionally progress asymptomatically. Instead of having all patients tested for BMD, dentists may use dental radiographs as a screening technique to refer the patient for a bone densitometry test. Given the cost, it is not recommended for every patient to have a DEXA scan if they are unaware that they are at risk or have the disease since they can be assessed with pre-existing dental radiographs. Furthermore, DEXA can be used for further validation and risk management in people who are at risk. Hence, the current study aimed to evaluate the usefulness of existing dental radiographs for the diagnosis of osteoporosis in women. In the majority of the studies included in our review, DEXA of the lumbar spine or femur has been considered a standard reference test to determine the diagnostic efficacy of dental radiographs in diagnosing osteoporosis.

OPG has been a critical component of radiographic dental diagnostics for more than 40 years. Several parameters have been employed to measure and quantify mandibular bone mass as well as to detect symptoms of resorption using OPGs.

• MCW or cortical width index or mental index (MI) is the mandibular cortical thickness (MCT) measured at the line A line perpendicular to the base of the mandible and passing through the middle of the mental foramen.
• PMI is the ratio of MCT and the distance between the inferior mandibular cortex and mental foramen.
• Klemetti index or MCI or cortical erosion is a three-graded system used to assess the changes in the inferior mandibular cortex. It classifies the cortex as normal when the endosteal margin of the cortex is even and sharp on both sides, mild to moderately eroded cortex when the endosteal margin shows semilunar defects, or severely eroded cortex when the cortical layer forms heavy endosteal cortical residue and is clearly porous.
• M/M ratio refers to total mandibular height divided by the height from the center of the mental foramen to the inferior mandibular border.
• Gonion index (GI) is the mandibular cortical thickness at the angle of the mandible (gonion).
• AI refers to the cortical width, anterior to the gonion, at a point corresponding to the line of fit on the anterior border of the ascending ramus, down to the lower border of the mandible (antegonial region).
• FD is a value that indicates how completely a fractal appears to fill space.

Among these parameters, MCW and MCI have been commonly employed in most of the studies suggesting their possible use as a predictor test of osteoporosis in postmenopausal women. GI and AI are difficult to determine and less frequently used in the literature.

One of the major limitations of DEXA is that it assesses the BMD rather than the microarchitecture of the bone which is far more crucial in identifying the etiology of osteoporosis. The bone microarchitecture is clinically assessed by high-resolution CT and Q-CT (20). CBCT is a preferred investigation due to its relatively low cost and reduced radiation dose. CT indices have been derived based on modified Ledgerton’s classification on OPG images (23).

• CTI (superior) [CTI (S)] is the ratio of the inferior cortical width to the distance from the superior margin of the mental foramen to the inferior border of the mandible.
• CTI (inferior) [CTI (I)] is the ratio of the inferior cortical width to the distance from the inferior margin of the mental foramen to the inferior border of the mandible.
• CTMI, is the inferior cortical width of the mandible.
• CTCI, which was the type of the inferior mandibular cortex.

Periapical radiographs are relatively inexpensive exams that are frequently available in dental offices. Since the trabecular bone can be easily visualized in periapical radiographs, it is likely that, similar to other parts of the skeleton, this may contain significant information about the bone condition on a microstructural level. It is possible to check for early signs of osteoporosis using standard mandibular periapical radiography.

Strengths and limitations

Dentists are well-positioned to screen patients for osteoporosis and may be the first medical professionals to encounter people who have the condition but have not yet received a diagnosis or who are at a high risk of developing it in the future. By lending a helping hand in the early detection of the affected persons, which further results in timely care to avoid further complications, they might further assist the healthcare practitioners as well as the osteoporotic patients. The density of the jaw bone can be measured using intraoral radiography, but the measurements may vary depending on the method of analysis, patient positioning, non-standard imaging positions, and changes in anatomical structures. The other major limitation is the reproducibility of the various indices since some of the studies have involved direct digital OPG while in some studies software to manipulate the images. Also, there are inherent inaccuracies and observer variability when taking measurements from OPG. The quality of radiographs and the diagnostic performance of various parameters vary among the studies. Another drawback is that most of the studies involved postmenopausal women, who are not the appropriate representative of the normal population. Some of the studies included normal and osteoporotic women, but not osteopenic women. It is questionable if osteopenic and osteoporotic women can be distinguished using the same method, given the likelihood that the difference between these two groups may be smaller than the diagnostic ability of the method. The key difficulties encountered in the studies with IOPA were that there were very few studies done utilizing them, therefore it could not be clearly stated whether they are of greater value or not. Although results have shown that they can be used to predict osteoporosis in women, more research is still required to substantiate the findings. Patients with localized inflammation, other bone diseases, patients under medication, and radiotherapy may have altered bone density which should not be confused with osteoporosis. In the majority of the studies, these were considered as the exclusion criteria. General dental practitioners should always consider this while evaluating dental radiographs.

Comparison with similar researches and explanations of findings

Beginning in the third decade of life, the density and porosity of human bones start to change. After menopause, this loss of bone mass is increased in women (16). According to estimates, women lose between 0.5% and 1% of their bone mass year after menopause (34). Hence, most of the included studies involved postmenopausal women. There is evidence that the key factor influencing the risk of hip fracture is BMD as determined by DEXA, particularly at the proximal femur (16). It has been shown that there is a strong association between BMD measurements at the femur and lumbar spine and panoramic mandibular indices (35-37). Though the bone mineral density in the spine has a higher area, the MCW is found to predict the rate of BMD better in the femur than in the lumbar spine (23).

A group of researchers from five European institutions began the OSTEODENT project in 2003 aimed to determine the most reliable radiography index for diagnosing osteoporosis in 671 postmenopausal women in the age range of 45 to 70 years of age. MCW was found to be superior to MCI (38). Over time, studies have demonstrated that the MCW has lower diagnostic validity when compared to the osteoporosis index of risk (OSIRIS)—age, weight, current estrogen therapy, and history of low trauma fracture (39).

MCW, TBA, and age were combined by Kathirvelu et al. to diagnose individuals with low BMD using OPG. MCW was found to better predict low BMD when compared to TBA which could be due to the diverse trabecular pattern of jaws (18). In cases of localized inflammation, the trabecular bone in the jaws is easily resorbed and/or sclerosed (40). However, the combinational approach performed better suggesting the importance of age in predicting the BMD. The performance of MCW in screening for osteoporosis was further improved by combining it with other parameters like FD. A CAD system was also used to analyze MCW by Kavitha et al. MCW was found to independently distinguish the groups better than other textural features. The mean FD decreased in osteoporotic (1.38) patients compared to normal (1.41) subjects. The combination of textural features like FD and grey-level co-occurrence matrix and MCW exhibited better diagnostic efficacy (26). Oliveira et al. showed that FD and pixel intensity (PI) were effective in detecting osteoporotic changes. The right side of the body did not show significant changes in PI which could be attributed to anatomical variations unilateral chewing or positioning errors (24). In a study by Roberts et al., when the machine learning method to evaluate the texture of the mandible, FD was a less effective texture feature. They have concluded that despite being clearly observable at the population level, the association between the FD of the mandibular cortex and osteoporosis at other bone locations only generates low specificity when used to determine an individual’s osteoporotic state (41).

Balto et al. observed that PMI and M/M ratio are of low significance in detecting osteoporosis in postmenopausal Saudi women when compared to MCW. However, MCW had the worst repeatability when compared to PMI, M/M ratio, and number of mandibular teeth (20). The diagnostic threshold for MCW for referring females for bone densitometry has been determined to be 3 mm or less by some of the investigators (42,43). However, the threshold differed in various study populations. Carmo et al. suggested that the cut-off threshold of MCW of 3 mm might not be as appropriate for multi-ethnic young Brazilian postmenopausal women as it was for Asian, Greek, and Caucasian ethnicities (25). This could be due to the difference in the sizes of their mandibles (44). Nagi R et al. reported that the threshold of MCW <3.35 mm exhibited low sensitivity but very high specificity. They also found that MCW negatively correlated with age, and BMI and positively correlated with femoral BMD (16). The MCW cut-off for osteoporosis was determined to be 4.1 mm in a Saudi Arabian study, while the cut-off for osteopenia was 4.6 mm (20). In a study conducted in Iran, the threshold for osteoporosis diagnosis was determined to be 4.29 mm (22). It could be speculated that the threshold of MCW for identifying osteoporosis in one population could not be used directly for another (44).

Pallagatti et al. also validated that MCI can be employed for early detection of osteoporosis (5). Carmo et al. diagnosed osteoporosis in 10% of the patients and osteopenia in 50% of the patients using MCI (25). MCI showed good results with 100% sensitivity in a study by Gaur et al. However, their sample size was too low to come to a conclusion (19). Alam et al. corroborated that along with MCI, aging is a risk factor for osteoporosis. Other variables including MCW, PMI, M/M ratio, and FD were not indicative of osteoporosis (21). Similarly, Yasar and Akgunlu came to the conclusion that MCI was easy to assess, while MCW and PMI did not lend themselves to the diagnosis of osteoporosis (45). The specificity of MCW was also found to be lower than that of MCI in identifying low BMD which indicates that MCI can identify more subjects with normal BMD (22).

Nakamoto et al. developed a BRSI for CAD diagnosis based on the shape of the linear resorption of the mandibular marginal cortical bone on panoramic radiographs. BRSI quantitatively evaluated the mandibular cortical porosity with a threshold of 2,198 (3).

Koh et al. observed that there were significant differences in CTI (S) and CTI (I) between the normal and osteoporotic groups, while no significant difference was observed for CTMI (8). Brasileiro et al. suggested that CTMI thinner than 3 mm at the mental foramen region may be considered a threshold value when predicting low spinal and femoral BMD (29). CBCT images were for the calculation of Radiographic density (RD), mean voxel gray values, and cortical bone percentage using software provided by the manufacturer and it was found that RD for the whole bony area had the greatest ability to predict osteoporosis in both the femoral neck and the lumbar vertebrae. There are some inaccuracies in the determination of grey values in CBCT, which are related to the lack of water path calibration contrary to conventional CT (27). Güngör et al. radiomorphometric index measurements, CT value, and the histogram analysis (HA) and FD methods were used to evaluate jaw bones on CBCT images (32). CT values, HA, and FD measurements in osteoporosis patients were significantly lower than measurements in osteopenia patients and control subjects (11). In contrast, the study by Mostafa et al. observed lower FD values in the control group when compared to the osteoporosis group (31). de Castro et al. introduced a new CBCT index for assessing osteoporosis called as three-dimensional mandibular osteoporosis index (3D MOI) which is 3 measurements: two quantitative measures evaluating MCW on panoramic reconstruction images (3D MOI PR) and on cross-sectional images (3D MOI CS), and one qualitative measure assessing cortical bone quality (3D MOI CQ). For qualitative and quantitative evaluation of the mandibular cortex, the 3D mandibular osteoporosis index (MOI) has shown sensitivity and specificity in differentiating osteoporosis from normal bone mass density, with good predictive value. Postmenopausal women with osteoporosis presented with a mandibular cortex with C3 classification and a mandibular cortical width below 2.75 mm (30).

OSTEOSYR project was launched after the drop in the economy of Syria due to the civil war and aimed to provide treatment at the lowest possible costs with available medical records. In this project, Barngkgei et al. concluded that as determined by CBCT, osteoporosis has no effect on the trabecular bone structure of the mandible and maxilla. However, a high diagnostic accuracy was observed for trabecular bone analysis of dens, which is the odontoid process of the second cervical vertebra (28). It is debatable whether CBCT measurements of the mandible can be used to assess bone mineral density, as it usually has a low resolution (0.3–0.4 mm), causing blur in trabecular structures, which typically have a bone thickness of around 0.1 mm. To identify patients with osteoporosis, CBCT in conjunction with DEXA may be beneficial in cases where dentists prescribe CBCT for other dental reasons.

The mandibular trabecular structures of postmenopausal women was assessed using periapical radiography in the study by Diba et al. Trabecular thickness measurements was used as an initial test for bone quality since the loss of trabeculae structure was more severe in osteoporotic postmenopausal women. As a result, using dental radiography, such as periapical radiographs, to screen for bone quality can be a relatively simple and economically viable procedure (33). In a study by Licks et al., the specificity (100%) and sensitivity (81%) of the trabecular morphologic analysis using IOPA, resulted in a total accuracy of 88.3%, making it a crucial factor in the diagnosis of low bone mass (46). The authors were unable to distinguish between individuals with normal and low bone density when the clinical and radiographic components were looked at separately since age is a crucial clinical criterion for osteoporosis.

Implications and actions needed

The available evidence suggests that dental radiographs can be used to detect changes in osteoporotic women. More clinical trials are needed to assess the risk of osteoporosis in early postmenopausal women, since the dental radiograph may not detect small changes in the mandibular microarchitecture. Though the aforementioned studies have come to the conclusion that OPG, and CBCT might be utilized as an alternative approach for assessing BMD, additional research is needed to determine which parameter could be more dependable and accurate to do so. The majority of investigations have been conducted on healthy individuals; however, people with various other systemic illnesses might be the focus of future research. It is also recommended to validate the thresholds for each CBCT device that best predicts the bone microarchitecture. The general dental practitioners should be aware of the changes that are seen in the dental radiographs of individuals with low BMD, so as to refer them to perform DEXA.

Conclusions

Mandibular indices evaluated from OPG, used in combination, can be used to detect changes in the mandible of osteoporotic women. It is questionable if CBCT can be used independently to evaluate the BMD provided the scarcity of CBCT studies in the literature. CBCT in conjunction with DEXA can be effective. Also, there is a dearth of studies evaluating the use of IOPA as an alternative to DEXA for evaluating BMD.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the Narrative Review reporting checklist. Available at https://fomm.amegroups.com/article/view/10.21037/fomm-23-33/rc

Peer Review File: Available at https://fomm.amegroups.com/article/view/10.21037/fomm-23-33/prf

Funding: None.

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://fomm.amegroups.com/article/view/10.21037/fomm-23-33/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

References

1. Vijay G, Chitroda PK, Katti G, et al. Prediction of osteoporosis using dental radiographs and age in females. J Midlife Health 2015;6:70-5. [Crossref] [PubMed]
2. Thakur P, Kuriakose C, Cherian KE, et al. Knowledge gap regarding osteoporosis among medical professionals in Southern India. J Eval Clin Pract 2020;26:272-80. [Crossref] [PubMed]
3. Nakamoto T, Hatsuta S, Yagi S, et al. Computer-aided diagnosis system for osteoporosis based on quantitative evaluation of mandibular lower border porosity using panoramic radiographs. Dentomaxillofac Radiol 2020;49:20190481. [Crossref] [PubMed]
4. Sözen T, Özışık L, Başaran NÇ. An overview and management of osteoporosis. Eur J Rheumatol 2017;4:46-56. [Crossref] [PubMed]
5. Pallagatti S, Parnami P, Sheikh S, et al. Efficacy of Panoramic Radiography in the Detection of Osteoporosis in Post-Menopausal Women When Compared to Dual Energy X-Ray Absorptiometry. Open Dent J 2017;11:350-9. [Crossref] [PubMed]
6. Blake GM, Fogelman I. Technical principles of dual energy x-ray absorptiometry. Semin Nucl Med 1997;27:210-28. [Crossref] [PubMed]
7. Ayub N, Faraj M, Ghatan S, et al. The Treatment Gap in Osteoporosis. J Clin Med 2021;10:3002. [Crossref] [PubMed]
8. Koh KJ, Kim KA. Utility of the computed tomography indices on cone beam computed tomography images in the diagnosis of osteoporosis in women. Imaging Sci Dent 2011;41:101-6. [Crossref] [PubMed]
9. Alkhader M, Aldawoodyeh A, Abdo N. Usefulness of measuring bone density of mandibular condyle in patients at risk of osteoporosis: A cone beam computed tomography study. Eur J Dent 2018;12:363-8. [Crossref] [PubMed]
10. Grocholewicz K, Janiszewska-Olszowska J, Aniko-Włodarczyk M, et al. Panoramic radiographs and quantitative ultrasound of the radius and phalanx III to assess bone mineral status in postmenopausal women. BMC Oral Health 2018;18:127. [Crossref] [PubMed]
11. White SC. Oral radiographic predictors of osteoporosis. Dentomaxillofac Radiol 2002;31:84-92. [Crossref] [PubMed]
12. Dervis E. Oral implications of osteoporosis. Oral Surg Oral Med Oral Pathol Oral Radiol Endod 2005;100:349-56. [Crossref] [PubMed]
13. López-López J, Estrugo-Devesa A, Jane-Salas E, et al. Early diagnosis of osteoporosis by means of orthopantomograms and oral x-rays: a systematic review. Med Oral Patol Oral Cir Bucal 2011;16:e905-13. [Crossref] [PubMed]
14. Isayev A, Velieva N, Isedisha L, et al. Cone-Beam Computed Tomography as a Prediction Tool for Osteoporosis in Postmenopausal Women: A Systematic Literature Review. Diagnostics (Basel) 2023;13:1027. [Crossref] [PubMed]
15. Guerra ENS, Almeida FT, Bezerra FV, et al. Capability of CBCT to identify patients with low bone mineral density: a systematic review. Dentomaxillofac Radiol 2017;46:20160475. [Crossref] [PubMed]
16. Nagi R, Devi B K Y, Rakesh N, et al. Relationship between femur bone mineral density, body mass index and dental panoramic mandibular cortical width in diagnosis of elderly postmenopausal women with osteoporosis. J Clin Diagn Res 2014;8:ZC36-40. [Crossref] [PubMed]
17. Whiting PF, Rutjes AW, Westwood ME, et al. QUADAS-2: a revised tool for the quality assessment of diagnostic accuracy studies. Ann Intern Med 2011;155:529-36. [Crossref] [PubMed]
18. Kathirvelu D, Anburajan M. Prediction of low bone mass using a combinational approach of cortical and trabecular bone measures from dental panoramic radiographs. Proc Inst Mech Eng H 2014;228:890-8. [Crossref] [PubMed]
19. Gaur B, Chaudhary A, Wanjari PV, et al. Evaluation of panoramic Radiographs as a Screening Tool of Osteoporosis in Post Menopausal Women: A Cross Sectional Study. J Clin Diagn Res 2013;7:2051-5. [PubMed]
20. Balto KA, Gomaa MM, Feteih RM, et al. Dental Panoramic Radiographic Indices as a Predictor of Osteoporosis in Postmenopausal Saudi Women. J Bone Metab 2018;25:165-73. [Crossref] [PubMed]
21. Alam T, AlShahrani I, Assiri KI, et al. Evaluation of Clinical and Radiographic Parameters as Dental Indicators for Postmenopausal Osteoporosis. Oral Health Prev Dent 2020;18:499-504. [PubMed]
22. Khojastehpour L, Afsa M, Dabbaghmanesh MH. Evaluation of Correlation between Width and Morphology of Mandibular Inferior Cortex in Digital Panoramic Radiography and Postmenopausal Osteoporosis. Iran Red Crescent Med J 2011;13:181-6. [PubMed]
23. Navabi N, Motaghi R, Rezazadeh M, et al. Relationship between Two Panoramic Radiography Indices and Bone Mineral Density of Postmenopausal Women with Osteopenia and Osteoporosis. J Dent (Shiraz) 2018;19:181-8. [PubMed]
24. Oliveira ML, Pedrosa EF, Cruz AD, et al. Relationship between bone mineral density and trabecular bone pattern in postmenopausal osteoporotic Brazilian women. Clin Oral Investig 2013;17:1847-53. [Crossref] [PubMed]
25. Carmo JZB, Medeiros SF. Mandibular Inferior Cortex Erosion on Dental Panoramic Radiograph as a Sign of Low Bone Mineral Density in Postmenopausal Women. Rev Bras Ginecol Obstet 2017;39:663-9. [Crossref] [PubMed]
26. Kavitha MS, An SY, An CH, et al. Texture analysis of mandibular cortical bone on digital dental panoramic radiographs for the diagnosis of osteoporosis in Korean women. Oral Surg Oral Med Oral Pathol Oral Radiol 2015;119:346-56. [Crossref] [PubMed]
27. Barngkgei I, Al Haffar I, Khattab R. Osteoporosis prediction from the mandible using cone-beam computed tomography. Imaging Sci Dent 2014;44:263-71. [Crossref] [PubMed]
28. Barngkgei I, Al Haffar I, Shaarani E, et al. Assessment of jawbone trabecular bone structure amongst osteoporotic women by cone-beam computed tomography: the OSTEOSYR project. J Investig Clin Dent 2016;7:332-40. [Crossref] [PubMed]
29. Brasileiro CB, Chalub LLFH, Abreu MHNG, et al. Use of cone beam computed tomography in identifying postmenopausal women with osteoporosis. Arch Osteoporos 2017;12:26. [Crossref] [PubMed]
30. de Castro JGK, Carvalho BF, de Melo NS, et al. A new cone-beam computed tomography-driven index for osteoporosis prediction. Clin Oral Investig 2020;24:3193-202. [Crossref] [PubMed]
31. Mostafa RA, Arnout EA, Abo El-Fotouh MM. Feasibility of cone beam computed tomography radiomorphometric analysis and fractal dimension in assessment of postmenopausal osteoporosis in correlation with dual X-ray absorptiometry. Dentomaxillofac Radiol 2016;45:20160212. [Crossref] [PubMed]
32. Güngör E, Yildirim D, Çevik R. Evaluation of osteoporosis in jaw bones using cone beam CT and dual-energy X-ray absorptiometry. J Oral Sci 2016;58:185-94. [Crossref] [PubMed]
33. Diba SF, Gracea RS, Shantiningsih RR, et al. Analysis of mandible trabecular structure using digital periapical radiographs to assess low bone quality in postmenopausal women. Saudi Dent J 2021;33:997-1003. [Crossref] [PubMed]
34. Kavitha MS, Asano A, Taguchi A, et al. Diagnosis of osteoporosis from dental panoramic radiographs using the support vector machine method in a computer-aided system. BMC Med Imaging 2012;12:1. [Crossref] [PubMed]
35. White SC, Taguchi A, Kao D, et al. Clinical and panoramic predictors of femur bone mineral density. Osteoporos Int 2005;16:339-46. [Crossref] [PubMed]
36. Bodade PR, Mody RN. Panoramic radiography for screening postmenopausal osteoporosis in India: a pilot study. Oral Health Dent Manag 2013;12:65-72. [PubMed]
37. Taguchi A, Suei Y, Ohtsuka M, et al. Usefulness of panoramic radiography in the diagnosis of postmenopausal osteoporosis in women. Width and morphology of inferior cortex of the mandible. Dentomaxillofac Radiol 1996;25:263-7. [Crossref] [PubMed]
38. Devlin H, Karayianni K, Mitsea A, et al. Diagnosing osteoporosis by using dental panoramic radiographs: the OSTEODENT project. Oral Surg Oral Med Oral Pathol Oral Radiol Endod 2007;104:821-8. [Crossref] [PubMed]
39. Karayianni K, Horner K, Mitsea A, et al. Accuracy in osteoporosis diagnosis of a combination of mandibular cortical width measurement on dental panoramic radiographs and a clinical risk index (OSIRIS): the OSTEODENT project. Bone 2007;40:223-9. [Crossref] [PubMed]
40. Taguchi A. Triage screening for osteoporosis in dental clinics using panoramic radiographs. Oral Dis 2010;16:316-27. [Crossref] [PubMed]
41. Roberts MG, Graham J, Devlin H. Image texture in dental panoramic radiographs as a potential biomarker of osteoporosis. IEEE Trans Biomed Eng 2013;60:2384-92. [Crossref] [PubMed]
42. Lee K, Taguchi A, Ishii K, et al. Visual assessment of the mandibular cortex on panoramic radiographs to identify postmenopausal women with low bone mineral densities. Oral Surg Oral Med Oral Pathol Oral Radiol Endod 2005;100:226-31. [Crossref] [PubMed]
43. Devlin H, Horner K. Mandibular radiomorphometric indices in the diagnosis of reduced skeletal bone mineral density. Osteoporos Int 2002;13:373-8. [Crossref] [PubMed]
44. Taguchi A, Ohtsuka M, Tsuda M, et al. Risk of vertebral osteoporosis in post-menopausal women with alterations of the mandible. Dentomaxillofac Radiol 2007;36:143-8. [Crossref] [PubMed]
45. Yaşar F, Akgünlü F. The differences in panoramic mandibular indices and fractal dimension between patients with and without spinal osteoporosis. Dentomaxillofac Radiol 2006;35:1-9. [Crossref] [PubMed]
46. Licks R, Licks V, Ourique F, et al. Development of a prediction tool for low bone mass based on clinical data and periapical radiography. Dentomaxillofac Radiol 2010;39:224-30. [Crossref] [PubMed]