Radiographic Evaluation of Osteoporosis Through Detection of Jaw Bone Changes: a Simplified Early Osteoporosis Detection Effort

Osteoporosis has become a worldwide problem and has been known as a silence disease. Nowadays, there are a lot of diagnostic tools for detecting osteoporosis. Eighty eight postmenopausal were included and underwent digital panoramic, digital periapical, and conventional radiography. Ultrasound bone densitometry of os calcis used as gold standard. Correlation between stiffness index (SI) with a digital dental, digital panoramic and conventional dental radiography are 0.170 (p = 0.11), -0382 (p = 0.001) and 0.246 (p = 0.021) respectively. Significant relationship was found between the SI only with digital panoramic and conventional dental. The highest correlation was found between SI values with mandibular Inferior Cortex on digital panoramic (-0.382, Pearson Correlation Tests). Correlation between digital panoramic radiographs and the SI values was the highest of the three radiographic modalities in this study. This indicates that evaluation of cortical bone is more accurate than cancellous bone. Bone quality evaluation in patients at high risk for osteoporosis using panoramic and dental conventional radiograph by dentist, contributes in preventing further occurrence of osteoporosis which in turn could reduce mortality and morbidity of osteoporosis in Indonesia

Cone beam CT of the musculoskeletal system : clinical applications

Objectives: The aim of this pictorial review is to illustrate the use of CBCT in a broad spectrum of musculoskeletal disorders and to compare its diagnostic merit with other imaging modalities, such as conventional radiography (CR), Multidetector Computed Tomography (MDCT) and Magnetic Resonance Imaging. Background: Cone Beam Computed Tomography (CBCT) has been widely used for dental imaging for over two decades. Discussion: Current CBCT equipment allows use for imaging of various musculoskeletal applications. Because of its low cost and relatively low irradiation, CBCT may have an emergent role in making a more precise diagnosis, assessment of local extent and follow-up of fractures and dislocations of small bones and joints. Due to its exquisite high spatial resolution, CBCT in combination with arthrography may be the preferred technique for detection and local staging of cartilage lesions in small joints. Evaluation of degenerative joint disorders may be facilitated by CBCT compared to CR, particularly in those anatomical areas in which there is much superposition of adjacent bony structures. The use of CBCT in evaluation of osteomyelitis is restricted to detection of sequestrum formation in chronic osteomyelitis. Miscellaneous applications include assessment of (symptomatic) variants, detection and characterization of tumour and tumour-like conditions of bone. Teaching Points: Review the spectrum of MSK disorders in which CBCT may be complementary to other imaging techniques. Compare the advantages and drawbacks of CBCT compared to other imaging techniques. Define the present and future role of CBCT in musculoskeletal imaging

Quantitative Digital Subtraction Radiography (DSR) as an approach for evaluating crestal alveolar bone density changes around teeth following orthodontic tooth movement.

Aim: The aim of the present study was to retrospectively evaluate changes in bone density using DSR  at the crestal and subcrestal regions of interproximal bone around posterior teeth (premolars and molars) before and after  orthodontic treatment using digital OPGs. Materials & Method : A total of 14 Pre and Post operative digital image pairs were obtained from the department of Orthodontics and 28 regions were sampled and analyzed. The selected patients were in the age group of 13-18 years. The mean duration of orthodontic treatment was 1.5 years. All pre and post operative radiographs were assessed at baseline and after completion of orthodontic treatment using DSR. All subtracted images were subsequently imported into The Image Tool® software to calculate the average density of Gray levels  in the areas that showed changes in subtraction. Results: Out of 28 test regions 23 regions (82.14%) showed an increase in bone density whereas 5 regions (17.85%) showed a decrease in bone density. The mean bone density of the  ROIs was 151.18 (gray level = 151.18 ± 19.97 SD). A one sample t test for statistical significance was carried out. The difference of the Mean values was found to be 23.18. The obtained p value was <0.001 at 95% confidence interval (15.44 to 30.92) Conclusion: In the present study, we have found that 23 out of 28 regions  (82.14%) showed significant increase in bone density whereas 5 regions (17.85%) showed a decrease in bone density. DSR is a valuable tool to assess subtle radiographic changes that occur in the alveolar bone during and after orthodontic therapy and can be used to monitor the bony changes over treatment period

Use of texture feature maps for the refinement of Information derived from digital Intraoral radiographs of lytic and sclerotic lesions

The aim of this study was to examine whether additional digital intraoral radiography (DIR) image preprocessing based on textural description methods improves the recognition and differentiation of periapical lesions. (1) DIR image analysis protocols incorporating clustering with the k-means approach (CLU), texture features derived from co-occurrence matrices, first-order features (FOF), gray-tone difference matrices, run-length matrices (RLM), and local binary patterns, were used to transform DIR images derived from 161 input images into textural feature maps. These maps were used to determine the capacity of the DIR representation technique to yield information about the shape of a structure, its pattern, and adequate tissue contrast. The effectiveness of the textural feature maps with regard to detection of lesions was revealed by two radiologists independently with consecutive interrater agreement. (2) High sensitivity and specificity in the recognition of radiological features of lytic lesions, i.e., radiodensity, border definition, and tissue contrast, was accomplished by CLU, FOF energy, and RLM. Detection of sclerotic lesions was refined with the use of RLM. FOF texture contributed substantially to the high sensitivity of diagnosis of sclerotic lesions. (3) Specific DIR texture-based methods markedly increased the sensitivity of the DIR technique. Therefore, application of textural feature mapping constitutes a promising diagnostic tool for improving recognition of dimension and possibly internal structure of the periapical lesions

Radiography in Palaeopathology: Where Next?

YesRadiography has frequently been used during palaeopathological research, and plays an important role in the differential diagnosis of many diseases, including Paget¿s disease and carcinomas. Traditionally, radiographs were taken in hospitals with clinical equipment. However industrial radiography techniques have gradually become more commonly used, as their superior image quality and improved potential for diagnoses become recognised. The introduction of radiographic scanners has facilitated the digitisation of these images for dissemination and publication. However this is not all that radiographic digitisation can offer the researcher. Digital image processing (DIP) allows the researcher to focus on an area of interest and to adjust the brightness and contrast of the captured image. This allows the investigation of areas of high radio-opacity and radio-lucency, providing detailed images of the internal structures of bone and pathological lesions undetectable by the naked eye. In addition 3D effects, edge enhancement and sharpening algorithms, available through commonly used image processing software, can be very effective in enhancing the visibility of specific features. This paper will reveal how radiographic digitisation and manipulation can enhance radiographic images of palaeopathological lesions and potentially further our understanding of the bony manifestations of disease

Is panoramic radiography really a key examination before chemo-radiotherapy treatment for oropharyngeal cancer?

Aim: To evaluate the diagnostic accuracy of panoramic radiography (PAN) for the identification of infectious foci of the tooth and periradicular bone before definitive chemo-radiotherapy treatment for oropharyngeal cancer, using multislice spiral computed tomography (MSCT) imaging as the reference standard. Materials and methods: 50 patients with oropharyngeal cancer who had performed both pre-treatment MSCT and PAN were retrospectively evaluated. Pre-radiotherapy MSCT showed 65 deep caries, 37 root remnants, 143 stage III periodontal diseases, and 77 apical periodontitis, for a total of 322 infectious foci. The same number of healthy teeth (control group) was selected via MSCT to be analysed by PAN. Sensitivity, specificity, positive and negative predictive values, and diagnostic accuracy for PAN images with respect to MSCT imaging were examined. Results: PAN showed sensitivity, negative predictive value, and diagnostic accuracy of 100% for deep caries, root remnants, and stage III periodontal disease, whereas there were 46.8%, 64.7%, and 72.1% apical periodontitis respectively. Conclusions: PAN did not show great diagnostic accuracy in the assessment of apical periodontitis, and therefore maxillofacial MSCT carried out before chemo-radiotherapy treatment should always be examined to identify dental and jaw diseases. Deep caries, root remnants, and stage III periodontal disease were perfectly detected on PAN

A comprehensive artificial intelligence framework for dental diagnosis and charting

Background: The aim of this study was to develop artificial intelligence (AI) guided framework to recognize tooth numbers in panoramic and intraoral radiographs (periapical and bitewing) without prior domain knowledge and arrange the intraoral radiographs into a full mouth series (FMS) arrangement template. This model can be integrated with different diseases diagnosis models, such as periodontitis or caries, to facilitate clinical examinations and diagnoses. Methods: The framework utilized image segmentation models to generate the masks of bone area, tooth, and cementoenamel junction (CEJ) lines from intraoral radiographs. These masks were used to detect and extract teeth bounding boxes utilizing several image analysis methods. Then, individual teeth were matched with a patient’s panoramic images (if available) or tooth repositories for assigning tooth numbers using the multi-scale matching strategy. This framework was tested on 1240 intraoral radiographs different from the training and internal validation cohort to avoid data snooping. Besides, a web interface was designed to generate a report for different dental abnormalities with tooth numbers to evaluate this framework’s practicality in clinical settings. Results: The proposed method achieved the following precision and recall via panoramic view: 0.96 and 0.96 (via panoramic view) and 0.87 and 0.87 (via repository match) by handling tooth shape variation and outperforming other state-of-the-art methods. Additionally, the proposed framework could accurately arrange a set of intraoral radiographs into an FMS arrangement template based on positions and tooth numbers with an accuracy of 95% for periapical images and 90% for bitewing images. The accuracy of this framework was also 94% in the images with missing teeth and 89% with restorations. Conclusions: The proposed tooth numbering model is robust and self-contained and can also be integrated with other dental diagnosis modules, such as alveolar bone assessment and caries detection. This artificial intelligence-based tooth detection and tooth number assignment in dental radiographs will help dentists with enhanced communication, documentation, and treatment planning accurately. In addition, the proposed framework can correctly specify detailed diagnostic information associated with a single tooth without human intervention