Diagnosis of osteoporosis from dental panoramic radiographs using the support vector machine method in a computer-aided system

<p>Abstract</p> <p>Background</p> <p>Early diagnosis of osteoporosis can potentially decrease the risk of fractures and improve the quality of life. Detection of thin inferior cortices of the mandible on dental panoramic radiographs could be useful for identifying postmenopausal women with low bone mineral density (BMD) or osteoporosis. The aim of our study was to assess the diagnostic efficacy of using kernel-based support vector machine (SVM) learning regarding the cortical width of the mandible on dental panoramic radiographs to identify postmenopausal women with low BMD.</p> <p>Methods</p> <p>We employed our newly adopted SVM method for continuous measurement of the cortical width of the mandible on dental panoramic radiographs to identify women with low BMD or osteoporosis. The original X-ray image was enhanced, cortical boundaries were determined, distances among the upper and lower boundaries were evaluated and discrimination was performed by a radial basis function. We evaluated the diagnostic efficacy of this newly developed method for identifying women with low BMD (BMD T-score of -1.0 or less) at the lumbar spine and femoral neck in 100 postmenopausal women (≥50 years old) with no previous diagnosis of osteoporosis. Sixty women were used for system training, and 40 were used in testing.</p> <p>Results</p> <p>The sensitivity and specificity using RBF kernel-SVM method for identifying women with low BMD were 90.9% [95% confidence interval (CI), 85.3-96.5] and 83.8% (95% CI, 76.6-91.0), respectively at the lumbar spine and 90.0% (95% CI, 84.1-95.9) and 69.1% (95% CI, 60.1-78.6), respectively at the femoral neck. The sensitivity and specificity for identifying women with low BMD at either the lumbar spine or femoral neck were 90.6% (95% CI, 92.0-100) and 80.9% (95% CI, 71.0-86.9), respectively.</p> <p>Conclusion</p> <p>Our results suggest that the newly developed system with the SVM method would be useful for identifying postmenopausal women with low skeletal BMD.</p

Panoramic radiograph analyses for early detection of osteoporosis in the population of Northern Norway

Osteoporosis is a chronic disease affecting bone tissue that may lead to fractures from minor accidents. Roughly 20% of females and 6 % of males have osteoporosis after age 50, but the disease might be present at a younger age. Early diagnosis is challenging because the disease has no symptoms. Dental radiography is a frequent examination that might be useful for early osteoporosis screening at dental clinics. This thesis explores the utility of radiomorphometric indices manually measured on panoramic radiographs and the feasibility of fully automated radiomorphometric indices for osteoporosis screening in Norwegian males and females. The data from the seventh survey of the Tromsø study (Tromsø7) were used. Participants aged 40 and older were examined with dental panoramic radiographs and dual-energy x-ray absorptiometry at the femoral neck. Other demographic, health, and lifestyle data were collected in questionnaires. Mandibular cortical width and shape were assessed. Thin ( ≤ 3 mm) and severely eroded cortex could differentiate osteoporotic from non-osteoporotic females. Combining mandibular cortical width and shape with Fracture Risk Assessment (FRAX) score improved their diagnostic efficacy. T-score was the strongest predictor of mandibular cortical morphology among other factors in females. In males, the T-score was weakly associated with cortical shape, while the efficacy estimates for radiomorphometric indices were inconclusive. The reproducibility of the manually measured indices was suboptimal. Nevertheless, developing a fully automated algorithm for measuring MCW was feasible. Its first step, localization of mental foramen, was best performed by EfficientDet neural network with an accuracy of 79%. To conclude, radiomorphometric indices might be as useful as existing risk-factor-based tools for osteoporosis screening in females, and their combination with the FRAX score has superior diagnostic efficacy. Future extensive studies should further explore the performance of fully automated radiomorphometric indices.Osteoporose er en kronisk sykdom som påvirker beinvev og kan føre til brudd fra mindre ulykker. Omtrent 20% av kvinner og 6% av menn har osteoporose etter fylte 50 år, men sykdommen kan også forekomme i en yngre alder. Tidlig diagnose er utfordrende fordi sykdommen ikke har noen symptomer. Tannrøntgenundersøkelse er en vanlig prosedyre på tannklinikk og kan være nyttig for tidlig osteoporosescreening. Denne avhandlingen utforsker nytten av radiomorfometriske indekser som måles manuelt på panoramarøntgen og gjennomførbarheten av fullt automatiserte radiomorfometriske indekser for osteoporosescreening hos norske menn og kvinner. Data fra den sjuende Tromsøundersøkelsen (Tromsø7) ble brukt. Deltakere i alderen 40 år og eldre ble undersøkt med panorarøntgen og dual-energy x-ray absorptiometry ved lårhalsen. Andre demografiske, helse- og livsstils data ble innsamlet gjennom et spørreskjema. Mandibulær kortikal bredde og erosjon ble vurdert. Tynn (≤ 3 mm) og alvorlig erodert korteks kan skille osteoporotiske kvinner fra ikke-osteoporotiske kvinner. Ved å kombinere mandibulær kortikal bredde og erosjon med Fracture Risk Assessment (FRAX) score forbedret deres diagnostiske egenskaper. T-score var den sterkeste prediktoren for mandibulær kortikal morfologi blant andre faktorer hos kvinner. Hos menn var T-score svakt assosiert med kortikal erosjon, mens diagnostiske egenskaper for radiomorfometriske indekser var uklare. Reproduserbarheten til de manuelt målte indeksene var suboptimal. Likevel var det mulig å utvikle en fullt automatisert algoritme for måling av mandibulær kortikal bredde. Det første trinnet, lokalisering av foramen mentale, ble best utført av EfficientDet nevrale nettverk med en nøyaktighet på 79%. For å konkludere kan radiomorfometriske indekser være like nyttige som eksisterende risikofaktorbaserte verktøy for osteoporosescreening hos kvinner, og deres kombinasjon med FRAX-scoren viser bedre diagnostiske egenskaper enn radiomorfometriske indeksene alene. Fremtidige omfattende studier bør ytterligere utforske ytelsen til fullt automatiserte radiomorfometriske indekser

Improvement of region of interest extraction and scanning method of computer-aided diagnosis system for osteoporosis using panoramic radiographs

ObjectivesPatients undergoing osteoporosis treatment benefit greatly from early detection. We previously developed a computer-aided diagnosis (CAD) system to identify osteoporosis using panoramic radiographs. However, the region of interest (ROI) was relatively small, and the method to select suitable ROIs was labor-intensive. This study aimed to expand the ROI and perform semi-automatized extraction of ROIs. The diagnostic performance and operating time were also assessed.MethodsWe used panoramic radiographs and skeletal bone mineral density data of 200 postmenopausal women. Using the reference point that we defined by averaging 100 panoramic images as the lower mandibular border under the mental foramen, a 400x100-pixel ROI was automatically extracted and divided into four 100x100-pixel blocks. Valid blocks were analyzed using program 1, which examined each block separately, and program 2, which divided the blocks into smaller segments and performed scans/analyses across blocks. Diagnostic performance was evaluated using another set of 100 panoramic images.ResultsMost ROIs (97.0%) were correctly extracted. The operation time decreased to 51.4% for program 1 and to 69.3% for program 2. The sensitivity, specificity, and accuracy for identifying osteoporosis were 84.0, 68.0, and 72.0% for program 1 and 92.0, 62.7, and 70.0% for program 2, respectively. Compared with the previous conventional system, program 2 recorded a slightly higher sensitivity, although it occasionally also elicited false positives.ConclusionsPatients at risk for osteoporosis can be identified more rapidly using this new CAD system, which may contribute to earlier detection and intervention and improved medical care

Computer-aided diagnosis system for osteoporosis based on quantitative evaluation of mandibular lower border porosity using panoramic radiographs

Objectives: A new computer-aided screening system for osteoporosis using panoramic radiographs was developed. The conventional system could detect porotic changes within the lower border of the mandible, but its severity could not be evaluated. Our aim was to enable the system to measure severity by implementing a linear bone resorption severity index (BRSI) based on the cortical bone shape. Methods: The participants were 68 females (>50 years) who underwent panoramic radiography and lumbar spine bone density measurements. The new system was designed to extract the lower border of the mandible as region of interests and convert them into morphological skeleton line images. The total perimeter length of the skeleton lines was defined as the BRSI. 40 images were visually evaluated for the presence of cortical bone porosity. The correlation between visual evaluation and BRSI of the participants, and the optimal threshold value of BRSI for new system were investigated through a receiver operator characteristic analysis. The diagnostic performance of the new system was evaluated by comparing the results from new system and lumbar bone density tests using 28 participants. Results: BRSI and lumbar bone density showed a strong negative correlation (p < 0.01). BRSI showed a strong correlation with visual evaluation. The new system showed high diagnostic efficacy with sensitivity of 90.9%, specificity of 64.7%, and accuracy of 75.0%. Conclusions: The new screening system is able to quantitatively evaluate mandibular cortical porosity. This allows for preventive screening for osteoporosis thereby enhancing clinical prospects

Computer-aided detection in musculoskeletal projection radiography: A systematic review

This is the author accepted manuscript. The final version is available from WB Saunders via the DOI in this record.Objectives To investigated the accuracy of computer-aided detection (CAD) software in musculoskeletal projection radiography via a systematic review. Key findings Following selection screening, eligible studies were assessed for bias, and had their study characteristics extracted resulting in 22 studies being included. Of these 22 three studies had tested their CAD software in a clinical setting; the first study investigated vertebral fractures, reporting a sensitivity score of 69.3% with CAD, compared to 59.8% sensitivity without CAD. The second study tested dental caries diagnosis producing a sensitivity score of 68.8% and specificity of 94.1% with CAD, compared to sensitivity of 39.3% and specificity of 96.7% without CAD. The third indicated osteoporotic cases based on CAD, resulting in 100% sensitivity and 81.3% specificity. Conclusion The current evidence reported shows a lack of development into the clinical testing phase; however the research does show future promise in the variation of different CAD systems

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

Automatic detection of the mental foramen for estimating mandibular cortical width in dental panoramic radiographs: the seventh survey of the Tromsø Study (Tromsø7) in 2015-2016

Objective To apply deep learning to a data set of dental panoramic radiographs to detect the mental foramen for automatic assessment of the mandibular cortical width. Methods Data from the seventh survey of the Tromsø Study (Tromsø7) were used. The data set contained 5197 randomly chosen dental panoramic radiographs. Four pretrained object detectors were tested. We randomly chose 80% of the data for training and 20% for testing. Models were trained using GeForce RTX 2080 Ti with 11 GB GPU memory (NVIDIA Corporation, Santa Clara, CA, USA). Python programming language version 3.7 was used for analysis. Results The EfficientDet-D0 model showed the highest average precision of 0.30. When the threshold to regard a prediction as correct (intersection over union) was set to 0.5, the average precision was 0.79. The RetinaNet model achieved the lowest average precision of 0.23, and the precision was 0.64 when the intersection over union was set to 0.5. The procedure to estimate mandibular cortical width showed acceptable results. Of 100 random images, the algorithm produced an output 93 times, 20 of which were not visually satisfactory. Conclusions EfficientDet-D0 effectively detected the mental foramen. Methods for estimating bone quality are important in radiology and require further development

Identifying individuals at risk of fragility fractures in a dental setting

Introduction: The increasing life expectancy is only positive if the added years are healthy years. Fragility fractures are most common in older adults, and they can result in lowered quality of life and high costs for the society. About one-half of Swedish women and one-fourth of the men are expected to sustain at least one fragility fracture during their lifetime, so identifying the high-risk individuals would be favorable. Regular dental check-ups offer a possibility to identify individuals with a high risk of having a disease or condition outside the oral cavity. Features of the mandibular bone shown on dental radiographs have been found to reflect the bone density of the skeleton. Low Bone Mineral Density (BMD) is a risk factor for fragility fractures. Low physical performance is also a risk factor as a fall often precedes a fracture. FRAX is a tool commonly used in primary care to assess the ten-year risk of sustaining a fragility fracture. Aim: The aim of the thesis was to study different methods of identifying individuals with a high risk of fragility fracture, methods that could be used in a dental setting. Material and methods: In the first three studies, we used the unique REBUS cohort, a stratified random sample of the Stockholm population, where 32,183 men and women between the ages of 18-65 received a postal questionnaire in 1969-70. A smaller sample of the cohort had a dental assessment including intraoral radiographs. We acquired data concerning fractures during 1970-2016 from the National Patient Register. In study I, we assessed the trabecular pattern of mandibular bone in intraoral radiographs with two methods, one visual, and one semi-automated. We followed 837 individuals 18-65 years old for 47 years. In study II, we studied the association between questions of physical health and mobility for 16,766 participants 26-65 years, and hip fractures during 20-35 years of follow-up. In study III, we studied the association between questions about alcohol consumption for 27,766 participants, 18-65 years old, and hip fractures during 47 years of follow-up. We also studied diagnoses indicating high alcohol consumption before a fracture and the relationship to hip fractures. In study IV, a qualitative study, we interviewed patients at the Stockholm Public Dental Services about their thoughts about doing a FRAX assessment of ten-year fracture risk in a dental setting. Results: In study I, we found no fracture predictive value in the two methods of assessing the trabecular pattern of the mandibular bone. In study II, questions of physical health and mobility could predict a 2.69 (CI 1.85-3.90) – 3.30 (CI 1.51-7.23) increase in hip fractures. This was true for all men, 26-65 years old at the study start and followed for 20-35 years until they were 61-85 years old, but for women only for those who were 26-45 years old and followed for 35 years, until 61-80 years old. In study III, the questions about alcohol consumption had no fracture predictive value. A hospitalization event with a diagnosis indicating high levels of alcohol consumption resulted in a significantly elevated subhazard ratio (SHR) for hip fractures in men (3.29, CI 1.80-5.98) and women (2.73, CI 1.37-5.42), but only in the youngest age group who were age 18-25 at the start of the study and 65-72 years old at the end of the study. This was interpreted as an indication that high alcohol consumption has a predictive ability for hip fractures that occur at an early age, for both men and women. In study IV, the interviewed participants were mostly positive about doing a FRAX assessment of the ten-year fracture risk, but they expressed concerns that need to be considered before introducing FRAX in a dental setting. Conclusion: We found no evidence of fracture predictive ability using the semi-automated method. The visual method may not be suitable to use for all ages and both sexes. Questions about physical health and mobility, and high alcohol consumption need to be further developed and studied. Using FRAX may be a feasible way to identify high fracture risk, but further studies are needed

System of gender identification and age estimation from radiography: a review

Under extreme conditions postmortem, dental radiography examinations can play an essential role in individual identification. In forensic odontology, individual identification traditionally compares antemortem dental records radiographs with those obtained on postmortem examination. As such, these traditional methods are vulnerable to oversights or mistakes in the individual identification of unidentified bodies. Digital technology can develop forensic odontology well. An automatic individual identification system is needed to support the forensic odontology process more easily and quickly because there are still opportunities to be created. We aimed to review the complete range of recent developments in identifying individuals from panoramic radiographs. We study methods in gender identification, age estimation, radiographic segmentation, performance analysis, and promising future directions

파노라마방사선영상의 하악 피질골 두께를 이용한 한국 여성의 골다공증 스크리닝 프로그램 개발과 유용성 평가

학위논문 (박사)-- 서울대학교 대학원 치의학대학원 치의과학과, 2017. 8. 허민석.Purpose The purpose of this study was to develop and evaluate a screening program for Korean osteoporotic women using mandibular cortical width (MCW), which has been used for bone mineral density (BMD) assessment on panoramic radiographs. Materials and Methods A computer-based program was developed in order to measure the MCW automatically on panoramic radiographs. To identify changes in the MCW value according to the head position, panoramic radiographs were taken with 5 different vertical angulations using a head phantom. Normality test was performed among the MCW values measured from the panoramic radiographs of 250 young women. After a normal distribution was confirmed, the threshold corresponding to −2.5 standard deviations (SDs) was determined. The determined value was applied to the panoramic radiographs of 70 female subjects with a known femur BMD value, and the sensitivity, specificity, and accuracy were calculated. Additionally, a cut-off value for screening was obtained from a receiver operating characteristic (ROC) based on the data from these 70 female subjects. Results There was no statistically significant difference in the MCW with a change of vertical angle of the head phantom (Kruskal-Wallis test, P=0.406). Analysis of the MCW in the panoramic radiographs of young females showed a normal distribution (P=0.074). The threshold value corresponding to −2.5 SD was 2.46 mm. When this value was applied to patients with a known femur BMD value, the sensitivity, specificity, and accuracy were 60.0%, 96.7%, and 91.4%, respectively. The area under the ROC curve was 0.947 (95% confidence interval 0.894-0.999, P=0.000). The cut-off value obtained from the ROC curve was 3.32 mm. Conclusion In conclusion, it is suggested that the developed computer-based screening program for osteoporosis may have a validity in Korean women. If the cut-off value would be obtained from a big-data study, it could be used to screen for osteoporosis in patients who have undergone panoramic radiographic imaging in dental clinics.I. Introduction II. Materials and Methods III. Result IV. Discussion V. Conclusion VI. References Abstract (Korean)Docto