Mandibular cortical shape index in non-standardised panoramic radiographs for identifying patients with osteoporosis as defined by the German Osteology Organization

Association of Osteoporosis with Tooth Loss and Dental Radiomorphometric Indices

Background/Objectives: Osteoporosis is a systemic disease associated with reduced bone mass, impaired bone microarchitecture, and thus an increased risk of bone fractures. Moreover, patients with osteoporosis are more likely to experience periodontal diseases and tooth loss. Some indices have been proposed to detect osteoporosis on dental panoramic radiographs. The aim of our retrospective study was to investigate the association between osteoporosis and the loss of alveolar bone and teeth and to evaluate the validity of several dental radiomorphometric indices for assessing osteoporosis. Methods: In patients with and without osteoporosis, tooth loss, alveolar bone loss, the panoramic mandibular index (PMI), mental index (MI), and mandibular cortical index (MCI) were determined. Results: Compared with the non-osteoporotic group, patients with osteoporosis showed more tooth loss and more severe alveolar bone loss. PMI and MI were lower in patients with osteoporosis than in the non-osteoporotic group. Analysis of MCI showed that category C3 (cortical layer forms strong endosteal cortical residues and is clearly porous) was significantly more common in patients with osteoporosis. Conclusions: Osteoporosis is associated with more tooth and alveolar bone loss. Furthermore, various dental radiomorphometric indices are altered in osteoporosis and could thus help to better assess osteoporosis of the jaw.

Radiomorphometric indices and fractal dimension of the mandible in individuals with osteogenesis imperfecta: a matched cross-sectional study

OBJECTIVE

The objective was to analyze radiomorphometric indices (RMIs) of mandibular cortical bone and fractal dimension (FD) of trabecular bone of individuals with osteogenesis imperfecta (OI) and compare the findings to those of individuals without OI.

METHODS

Digital panoramic radiographs of 20 individuals with OI (case group) and 40 individuals without OI (control group) were examined. The RMIs of mandibular cortical index (MCI) and mandibular cortical thickness (MCT) were analyzed. FD of mandibular trabecular bone was calculated bilaterally in 3 regions. The chi-squared test and paired t test were used to compare the significance of differences between the groups. The effect size and minimal clinically important difference (MCID) were also determined. Significance was established at P < .05.

RESULTS

Categories C2 and C3 of the MCI were more frequent in individuals with OI (P < .001). The Mean MCT was 2.08 ± 0.79 in the OI case group and 2.91 ± 0.60 in the control group (P < .001). Mean FD in the condylar region was significantly lower in the OI case group (P = .002). The effect size for these 2 measures was large, and the difference between groups was greater than the MCID.

CONCLUSION

Radiographs of individuals with OI exhibited more porosity and diminished thickness of the mandibular cortical bone and lower FD values in the condylar trabecular bone.

Identification of osteoporosis using ensemble deep learning model with panoramic radiographs and clinical covariates

Osteoporosis is becoming a global health issue due to increased life expectancy. However, it is difficult to detect in its early stages owing to a lack of discernible symptoms. Hence, screening for osteoporosis with widely used dental panoramic radiographs would be very cost-effective and useful. In this study, we investigate the use of deep learning to classify osteoporosis from dental panoramic radiographs. In addition, the effect of adding clinical covariate data to the radiographic images on the identification performance was assessed. For objective labeling, a dataset containing 778 images was collected from patients who underwent both skeletal-bone-mineral density measurement and dental panoramic radiography at a single general hospital between 2014 and 2020. Osteoporosis was assessed from the dental panoramic radiographs using convolutional neural network (CNN) models, including EfficientNet-b0, -b3, and -b7 and ResNet-18, -50, and -152. An ensemble model was also constructed with clinical covariates added to each CNN. The ensemble model exhibited improved performance on all metrics for all CNNs, especially accuracy and AUC. The results show that deep learning using CNN can accurately classify osteoporosis from dental panoramic radiographs. Furthermore, it was shown that the accuracy can be improved using an ensemble model with patient covariates.

Clinical guidelines for the application of panoramic radiographs in screening for osteoporosis

Osteoporotic fractures are associated with an increased risk of subsequent fractures, a higher rate of mortality, and incremental medical costs. Incidental findings, which include some measurements related to the mandibular inferior cortex and the alveolar trabecular bone pattern of the mandible determined on panoramic radiographs, are considered to be a useful tool for identifying asymptomatic individuals at risk of having osteoporosis and/or fragility fractures. We undertook a worldwide literature survey and present the following clinical recommendations. Postmenopausal female dental patients with a mandibular inferior cortical width of less than 3 mm on panoramic radiographs may be at risk of having low skeletal bone mineral density (BMD) or osteoporosis, but not fragility fractures. In addition, those with a severely eroded mandibular inferior cortex may have an increased risk of having low skeletal BMD, osteoporosis, and fragility fractures. The alveolar trabecular bone pattern of the mandible might be useful for identifying female dental patients at risk of having fragility fractures, although further investigation is necessary to confirm this possibility. These incidental findings on panoramic radiographs, when used for identifying asymptomatic postmenopausal female patients at risk of having osteoporosis in general dental practice, may be helpful in reducing the incidence of first fractures, with a consequent reduction in the secondary fractures, medical costs, and mortality associated with osteoporotic fragility fractures, without incurring any additional cost.

Automatic computation of mandibular indices in dental panoramic radiographs for early osteoporosis detection

AIM

A new automatic method for detecting specific points and lines (straight and curves) in dental panoramic radiographies (orthopantomographies) is proposed, where the human knowledge is mapped to the automatic system. The goal is to compute relevant mandibular indices (Mandibular Cortical Width, Panoramic Mandibular Index, Mandibular Ratio, Mandibular Cortical Index) in order to detect the thinning and deterioration of the mandibular bone. Data can be stored for posterior massive analysis.

METHODS

Panoramic radiographies are intrinsically complex, including: artificial structures, unclear limits in bony structures, jawbones with irregular curvatures and intensity levels, irregular shapes and borders of the mental foramen, irregular teeth alignments or missing dental pieces. An intelligent sequence of linked imaging segmentation processes is proposed to cope with the above situations towards the design of the automatic segmentation, making the following contributions: (i) Fuzzy K-means classification for identifying artificial structures; (ii) adjust a tangent line to the lower border of the lower jawbone (lower cortex), based on texture analysis, grey scale dilation, binarization and labelling; (iii) identification of the mental foramen region and its centre, based on multi-thresholding, binarization, morphological operations and labelling; (iv) tracing a perpendicular line to the tangent passing through the centre of the mental foramen region and two parallel lines to the tangent, passing through borders on the mental foramen intersected by the perpendicular; (v) following the perpendicular line, a sweep is made moving up the tangent for detecting accumulation of binary points after applying adaptive filtering; (vi) detection of the lower mandible alveolar crest line based on the identification of inter-teeth gaps by saliency and interest points feature description.

RESULTS

The performance of the proposed approach was quantitatively compared against the criteria of expert dentists, verifying also its validity with statistical studies based on the analysis of deterioration of bone structures with different levels of osteoporosis. All indices are computed inside two regions of interest, which tolerate flexibility in sizes and locations, making this process robust enough.

CONCLUSIONS

The proposed approach provides an automatic procedure able to process with efficiency and reliability panoramic X-Ray images for early osteoporosis detection.

Evaluation of Transfer Learning with Deep Convolutional Neural Networks for Screening Osteoporosis in Dental Panoramic Radiographs

: Dental panoramic radiographs (DPRs) provide information required to potentially evaluate bone density changes through a textural and morphological feature analysis on a mandible. This study aims to evaluate the discriminating performance of deep convolutional neural networks (CNNs), employed with various transfer learning strategies, on the classification of specific features of osteoporosis in DPRs. For objective labeling, we collected a dataset containing 680 images from different patients who underwent both skeletal bone mineral density and digital panoramic radiographic examinations at the Korea University Ansan Hospital between 2009 and 2018. Four study groups were used to evaluate the impact of various transfer learning strategies on deep CNN models as follows: a basic CNN model with three convolutional layers (CNN3), visual geometry group deep CNN model (VGG-16), transfer learning model from VGG-16 (VGG-16_TF), and fine-tuning with the transfer learning model (VGG-16_TF_FT). The best performing model achieved an overall area under the receiver operating characteristic of 0.858. In this study, transfer learning and fine-tuning improved the performance of a deep CNN for screening osteoporosis in DPR images. In addition, using the gradient-weighted class activation mapping technique, a visual interpretation of the best performing deep CNN model indicated that the model relied on image features in the lower left and right border of the mandibular. This result suggests that deep learning-based assessment of DPR images could be useful and reliable in the automated screening of osteoporosis patients.

Comparison of skeletal changes related to patients with chronic kidney disease and healthy individuals in digital panoramic radiography

Background

Chronic kidney disease (CKD) is a prevalent condition affecting bone metabolism. Bone changes in CKD patients also known as renal osteodystrophy happen due to disorders in the regulation of water and electrolytes caused by the disease. The aim of this study is to investigate the bone changes of CKD stages 3-5 patients without dialysis using digital panoramic radiography.

Materials and Methods

In this cross-sectional study, panoramic radiographs were obtained from 30 patients with CKD stages 3-5 and 30 age and gender matched healthy individuals. The mean values of quantitative parameters such as mental index (MI), panoramic mandibular index (PMI), and antegonial index (AI) were measured and qualitative parameters such as mandibular cortical index (MCI) and trabecular bone pattern (TP) were recorded based on Kelemetti and Lindh calcifications, respectively. Statistical analysis was performed using t-test, Chi-square, and Mann-Whitney test (α = 0.05).

Results

The mean values of MI, PMI, and AI in the two groups were not statistically significant (P > 0.05). MCI and TP were significantly different between the two groups. MCI showed more defects in mandibular cortex of CKD patients (6.7% of patients vs. 0% of control group were C₃, P = 0.038), and TP showed more porosity in mandibular bone of CKD patients (10% of patients vs. 0% of control group were sparse, P = 0.001).

Conclusion

The amount of MI, PMI, and AI were not related to CKD. While MCI and TP were significant parameters that showed mandibular cortical situation and trabecular bone pattern, they assess osteoporosis level in a more reliable manner in CKD stages 3-5 patients without dialysis.

Mandibular radiomorphometric assessment of bone mineral density in survivors of pediatric hematopoietic stem-cell transplantation

OBJECTIVE

Hematopoietic stem-cell transplantation (HSCT) childhood survivors of hematologic malignancies are prone to develop late osteopenia and osteoporosis. The purpose of this retrospective study was to quantitatively and qualitatively assess bone mineral density (BMD) in HSCT childhood survivors and to compare the effectiveness of both qualitative and quantitative assessment methods.

METHODS

DESIGN BMD assessment using panoramic radiographs of childhood HSCT survivors aged 3.69-18.88 years using two radiomorphometric indexes. Case-control double-blinded comparison of panoramic radiographic images from childhood HSCT survivors and age- and sex-matched healthy controls. Quantitative assessment was performed by measuring the cortical bone width bilaterally at the mental foramen level. Qualitative assessment was performed using the mandibular cortical index bilaterally on all panoramic images.

RESULTS

Radiographs were taken 6.59-83.95 months after bone marrow transplantation [median±SD=25.92±24.9 months]. Fifty-two panoramic radiographic images were analyzed: 21 from HSCT survivors and 31 from healthy controls aged 3.69-25.1 years [mean±SD=11.89±5.28 years]. The mandibular cortical bone width was 17% smaller in childhood HSCT survivors than in healthy controls (case group: 2.420, control group: 3.307; p=0.00617). Qualitative analysis revealed an increased frequency of severe mandibular cortical erosion in childhood HSCT survivors, although no significant difference was observed (case group: 1.540, control group: 1.490; p=0.32). The interobserver agreement was 85% (Kappa index).

CONCLUSIONS

HSCT childhood survivors exhibit quantitative and qualitative mandibular bone impairments. Further studies are needed to establish an association between mandibular cortical bone impairment and osteoporosis.

Usefulness of measuring radiographic density of axis vertebra in patients at risk of osteoporosis: A cone-beam computed tomography study

Objective:

Using cone-beam computed tomography (CBCT) images, the aim of the study was to evaluate the usefulness of measuring radiographic density of the axis vertebra (RDAV) in patients at risk of osteoporosis.

Materials and Methods:

Two hundred and forty-seven old patients (109 males and 138 females) aged between 50 and 80 years (mean age: 59.68 ± 7.27) were examined by CBCT. Using InVivoDental, v. 5.0 (Anatomage Inc., San Jose, CA), RDAV and mental index (MI) were measured twice and correlated using Pearson's correlation coefficients. Patients were divided into two categories: high risk and low risk of osteoporosis using 3.1 mm of MI as a cutoff value, and the mean value of RDAV was compared and correlated using independent samples’ t-test and regression analysis. Receiver-operating characteristic (ROC) curve analysis was also used to examine the predictive power of RDAV.

Results:

The mean value of RDAV was moderately correlated with MI (r = 0.32), and in patients at low risk of osteoporosis, the mean value of RDAV was significantly higher than in patients at high risk of osteoporosis. In multivariate binary logistic regression, the odds of being at risk of osteoporosis decreased by 1% with one unit increase in RDAV (odds ratio = 0.988, 95% confidence interval: 0.983–0.993; P < 0.005). ROC analysis showed that the mean value of RDAV had a high predictive power for predicting patients at risk of osteoporosis (area under the curve = 0.761 for females and 0.649 for males).

Conclusions:

Measuring RDAV is considered useful in predicting patients at risk of osteoporosis.

Decrease in Mandibular Cortical in Patients With Type 1 Diabetes Mellitus Combined with Poor Glycemic Control

In this study we analyzed the mandibular cortical bone of patients with type 1 diabetes mellitus (T1DM) and non-diabetic. Fifty patients with T1DM and 100 non-diabetic ones paired by age and gender were analyzed. Two double-blinded observers evaluated 150 digital panoramic images of both groups. The mandibular cortical bone was analyzed using the Mandibular Cortical Index (MCI), Mental Index (MI), Gonial Index (GI), Antegonial Index (AI) and Upper and Lower Panoramic Mandibular Indexes (UPMI and LPMI), with the aid of RADIOIMP® software. Influence of T1DM in the morphology of the mandibular cortical bone was studied based on obtaining data related to T1DM diagnosis time, blood glucose level, T1DM control and the presence of chronic complications. Collected data were submitted to descriptive (mean and standard deviation) and inferential analyzes (Pearson's chi-squared test and Fisher's exact test) (p≤0.05). According to the MCI, individuals with T1DM had higher frequencies of mandibular cortical alterations, in both sexes and all age groups (p<0.01). For quantitative indexes, MI, GI, AI, UPMI and LPMI, female patients showed statistically significant differences for GI and AI, while male patients had statistically significant differences for all indexes (p<0.05), presenting the individuals with TDM1 inferior measures. Individuals with poor T1DM control showed significantly higher frequency of mandibular cortical alteration (92.3%), with lower means for MI, GI, AI and LPMI (p≤0.05). In conclusion, patients with T1DM showed decrease in the mandibular cortical bone when compared to non-diabetic ones, indicating that poor disease control is associated with these alterations.

Osteoporosis detection in panoramic radiographs using a deep convolutional neural network-based computer-assisted diagnosis system: a preliminary study

OBJECTIVES

To evaluate the diagnostic performance of a deep convolutional neural network (DCNN)-based computer-assisted diagnosis (CAD) system in the detection of osteoporosis on panoramic radiographs, through a comparison with diagnoses made by oral and maxillofacial radiologists.

METHODS

Oral and maxillofacial radiologists with >10 years of experience reviewed the panoramic radiographs of 1268 females {mean [± standard deviation (SD)] age: 52.5 ± 22.3 years} and made a diagnosis of osteoporosis when cortical erosion of the mandibular inferior cortex was observed. Among the females, 635 had no osteoporosis [mean (± SD) age: 32.8 ± SD 12.1 years] and 633 had osteoporosis (72.2 ± 8.5 years). All panoramic radiographs were analysed using three CAD systems, single-column DCNN (SC-DCNN), single-column with data augmentation DCNN (SC-DCNN Augment) and multicolumn DCNN (MC-DCNN). Among the radiographs, 200 panoramic radiographs [mean (± SD) patient age: 63.9 ± 10.7 years] were used for testing the performance of the DCNN in detecting osteoporosis in this study. The diagnostic performance of the DCNN-based CAD system was assessed by receiver operating characteristic (ROC) analysis.

RESULTS

The area under the curve (AUC) values obtained using SC-DCNN, SC-DCNN (Augment) and MC-DCNN were 0.9763, 0.9991 and 0.9987, respectively.

CONCLUSIONS

The DCNN-based CAD system showed high agreement with experienced oral and maxillofacial radiologists in detecting osteoporosis. A DCNN-based CAD system could provide information to dentists for the early detection of osteoporosis, and asymptomatic patients with osteoporosis can then be referred to the appropriate medical professionals.

Craniofacial Manifestations of Systemic Disorders: CT and MR Imaging Findings and Imaging Approach

Many systemic diseases or conditions can affect the maxillofacial bones; however, they are often overlooked or incidentally found at routine brain or head and neck imaging performed for other reasons. Early identification of some conditions may significantly affect patient care and alter outcomes. Early recognition of nonneoplastic hematologic disorders, such as thalassemia and sickle cell disease, may help initiate earlier treatment and prevent serious complications. The management of neoplastic diseases such as lymphoma, leukemia, or Langerhans cell histiocytosis may be different if diagnosed early, and metastases to the maxillofacial bones may be the first manifestation of an otherwise occult neoplasm. Endocrinologic and metabolic disorders also may manifest with maxillofacial conditions. Earlier recognition of osteoporosis may alter treatment and prevent complications such as insufficiency fractures, and identification of acromegaly may lead to surgical treatment if there is an underlying growth hormone-producing adenoma. Bone dysplasias sometimes are associated with skull base foraminal narrowing and subsequent involvement of the cranial nerves. Inflammatory processes such as rheumatoid arthritis and sarcoidosis may affect the maxillofacial bones, skull base, and temporomandibular joints. Radiologists should be familiar with the maxillofacial computed tomographic and magnetic resonance imaging findings of common systemic disorders because these may be the first manifestations of an otherwise unrevealed systemic process with potential for serious complications. Online supplemental material is available for this article. ^©RSNA, 2018.

IDIOS: An innovative index for evaluating dental imaging-based osteoporosis screening indices

Purpose

The goal of this study was to develop a new index as an objective reference for evaluating current and newly developed indices used for osteoporosis screening based on dental images. Its name; IDIOS, stands for Index of Dental-imaging Indices of Osteoporosis Screening.

Materials and Methods

A comprehensive PubMed search was conducted to retrieve studies on dental imaging-based indices for osteoporosis screening. The results of the eligible studies, along with other relevant criteria, were used to develop IDIOS, which has scores ranging from 0 (0%) to 15 (100%). The indices presented in the studies we included were then evaluated using IDIOS.

Results

The 104 studies that were included utilized 24, 4, and 9 indices derived from panoramic, periapical, and computed tomographic/cone-beam computed tomographic techniques, respectively. The IDIOS scores for these indices ranged from 0 (0%) to 11.75 (78.32%).

Conclusion

IDIOS is a valuable reference index that facilitates the evaluation of other dental imaging-based osteoporosis screening indices. Furthermore, IDIOS can be utilized to evaluate the accuracy of newly developed indices.

Osteoporosis and jawbones in women

Osteoporosis is a major health problem affecting one in three women over the age of 50 and may not be detected until fractures occur. Since osteoporotic fractures are a health burden worldwide, identifying subjects with a high risk of osteoporosis and preventing osteoporosis-related mortality and morbidity are a very important health strategy. Women show an estrogen-related bone loss starting at menopause, predominantly occurring in trabecular bone. Diagnosis of osteoporosis is usually based on the bone mineral density measurement, but this is not a practical and economical technique for early detection. Therefore, investigators are interested in the possibility of detecting osteoporosis from the panoramic radiographs. Mandibular cortical bone undergoes resorptive activity in osteoporotic patients, leading to a decreased thickness and more porous inferior border. Therefore, studies have demonstrated the usefulness of cortical width and shape, determined from panoramic radiographs, in identifying elderly individuals with undetected osteoporosis, especially postmenopausal women. In conclusion, postmenopausal women with C3 category, Mental Index (MI) <3 mm, and panoramic mandibular index (PMI) <0.3 may be considered for further osteoporosis investigation.

Value of intra- and post-operative cone beam computed tomography (CBCT) for positioning control of a sphenopalatine ganglion neurostimulator in patients with chronic cluster headache

INTRODUCTION

The objective of this study was to determine whether postoperative control of the neurostimulator placement within the pterygopalatine fossa (PPF) by means of 3-dimensional (3D) cone beam computed tomography (CBCT) was of therapeutic relevance compared to intraoperative CBCT imaging alone.

MATERIAL AND METHODS

Immediately after implantation of the sphenopalatine ganglion (SPG) neurostimulator, intraoperative CBCT datasets were generated in order to visualize the position of the probe within the PPF. Postoperatively, all patients received a CBCT for comparison with intraoperatively acquired radiographs.

RESULTS

Twenty-four patients with cluster headache (CH) received an SPG neurostimulator. In 4 patients, postoperative CBCT images detected misplacement not found in intraoperative CBCT. In 3 cases, electrode tips were misplaced into the maxillary sinus and in 1 case into the apex of the PPF superior to the suspected location of the SPG. Immediate revision with successful repositioning within 3 days was done in 2 patients and a deferred reimplantation in 1 patient within 6 months. One patient declined revision.

CONCLUSION

We were able to demonstrate the clinical value of postoperative dental CBCT imaging with a wide region of interest (ROI) due to a superior image quality compared with that achieved with intraoperative medical CBCT. Although intraoperative 3D CBCT imaging of electrode placement is helpful in the acute surgical setting, resolution is, at present, too low to safely exclude misplacement, especially in the maxillary sinus. High-resolution postoperative dental CBCT allows rapid detection and revision of electrode misplacement, thereby avoiding readmission and recurrent tissue trauma.

Panoramic measures for oral bone mass in detecting osteoporosis: a systematic review and meta-analysis

Different quantitative and qualitative indices calculated on oral panoramic radiographs have been proposed as useful tools to screen for reduced skeletal bone mineral density (BMD). Our aim was to systematically review the literature on linear and qualitative panoramic measures and to assess the accuracy of these indices by performing a meta-analysis of their sensitivity and specificity. The Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) statement was followed. Fifty studies were included in the qualitative appraisal and 19 were considered for meta-analysis. The methodological quality of the retrieved studies, assessed with the QUADAS-2 tool, was on average low. Three indices were reported by most of the studies: mandibular cortical width, panoramic mandibular index, and the Klemetti index. Mandibular cortical width presented with a better accuracy in excluding osteopenia/osteoporosis (specificity), since patients with a cortical width more than 4 mm had a normal BMD in 90% of the cases. Almost all studies used a cutoff of 0.3 for the panoramic mandibular index, resulting in an estimated sensitivity and specificity in detecting reduced BMD, respectively, of 0.723 (SE 0.160; 95% confidence interval [CI], 0.352-0.926) and 0.733 (SE 0.066; 95% CI, 0.587-0.841). The presence of any kind of mandibular cortical erosion gave an estimated sensitivity and specificity in detecting reduced BMD, respectively, of 0.789 (SE 0.031; 95% CI, 0.721-0.843) and 0.562 (SE 0.047; 95% CI, 0.47-0.651) and a sensitivity and specificity in detecting osteoporosis, respectively, of 0.806 (SE 0.105; 95% CI, 0.528-0.9200) and 0.643 (SE 0.109; 95% CI, 0.417-0.820). The mandibular cortical width, panoramic mandibular index, and Klemetti index are overall useful tools that potentially could be used by dentists to screen for low BMD. Their limitations are mainly related to the experience/agreement between different operators and the different image quality and magnification of the panoramic radiographs.