Radiographs in periodontal disease diagnosis and management

Toward Digital Periodontal Health: Recent Advances and Future Perspectives

Periodontal diseases, ranging from gingivitis to periodontitis, are prevalent oral diseases affecting over 50% of the global population. These diseases arise from infections and inflammation of the gums and supporting bones, significantly impacting oral health. The established link between periodontal diseases and systemic diseases, such as cardiovascular diseases, underscores their importance as a public health concern. Consequently, the early detection and prevention of periodontal diseases have become critical objectives in healthcare, particularly through the integration of advanced artificial intelligence (AI) technologies. This paper aims to bridge the gap between clinical practices and cutting-edge technologies by providing a comprehensive review of current research. We examine the identification of causative factors, disease progression, and the role of AI in enhancing early detection and treatment. Our goal is to underscore the importance of early intervention in improving patient outcomes and to stimulate further interest among researchers, bioengineers, and AI specialists in the ongoing exploration of AI applications in periodontal disease diagnosis.

Comparison of Dental Findings with Computed Tomographic and Clinical Examination in Patients with End-Stage Heart Failure

Background: This study aimed to evaluate the diagnostic value of pre-existing computed tomography (CT) examinations for the detection of dental pathologies compared with clinical dental examination in patients with end-stage heart failure. Methods: For this purpose, 59 patients with end-stage heart failure and pre-existing non-dental CT images of the craniofacial region were included. Virtual orthopantomograms (vOPG) were reconstructed. Dental pathologies were analyzed in vOPG and source-CT images. Imaging and clinical findings less than 6 months apart were compared (n = 24). Results: The subjective image quality of vOPG was more often rated as insufficient than CT (66%; 20%; p < 0.01). Depending on examination (CT, vOPG or clinic), between 33% and 92% of the patients could require dental intervention such as treatment of caries and periodontitis or tooth extraction. vOPG led to a higher (80%) prevalence of teeth requiring treatment than CT (39%; p < 0.01). The prevalence of teeth requiring treatment was similar in CT (29%) and clinic (29%; p = 1.00) but higher in vOPG (63%; p < 0.01). CT (stage 3 or 4: 42%) and vOPG (38%) underestimated the stage of periodontitis (clinic: 75%; p < 0.01). Conclusions: In conclusion, available CT images including the craniofacial region from patients with end-stage heart failure may contain valuable information regarding oral health status. The assessability of vOPGs might be insufficient and must be interpreted with caution.

Accuracy of intraoral ultrasound to evaluate alveolar bone level: an ex vivo study in human cadavers

OBJECTIVES

This study aimed to evaluate the reliability and accuracy of an intraoral ultrasound (US) device to evaluate alveolar bone by comparing it between different raters and to microCT (µCT) measurements.

METHODS

38 teeth distributed across three human cadavers were prepared by placing two notches on the facial enamel surface. The maxillary and mandibular teeth were imaged with a custom-designed intraoral 20 MHz ultrasound and µCT with 0.03 mm voxel size. µCT was considered the reference standard for this study. For each sample, the distance from the inferior border of the most apical notch to the tip of the alveolar bone crest on the facial aspect of the teeth was measured from the US and µCT images. Intraclass correlation coefficient (ICC) and standard deviation were calculated.

RESULTS

The intra-examiner and inter-examiner reliability for both the µCT and US alveolar bone measurements were found to be excellent (intra-examiner ICC was 0.998 for µCT and 0.997 for US, inter-examiner ICC was 0.996 for µCT and between 0.947 and 0.950 for US). The accuracy of the US was found to be good compared to µCT (ICC between 0.885 and 0.894).

CONCLUSION

The study demonstrated that intraoral ultrasound is highly reliable and accurate compared to the µCT reference standard for evaluating facial alveolar bone height.

Early detection of cardiovascular risk markers through non-invasive ultrasound methodologies in periodontitis patients

Objectives

This narrative review aims to update the current evidence and offer insight into the new non-invasive ultrasound techniques used to early identify degenerative vascular changes in subjects with periodontitis and to investigate if these methodologies could be useful to identify subclinical cardiovascular disease (CVD) dysfunction in periodontitis patients and to monitor changes in CVD risk after periodontal treatment.

Methods

Studies examining the assessment of vascular endothelial function through the latest methodologies were analyzed. Systematic reviews, observational studies, and clinical trials in the English language were identified using PubMed, Web of Science, and Google Scholar databases with key search terms such as "periodontitis," "endothelial dysfunction (ED)," "arterial stiffness," and "periodontal therapy."

Results

Several mechanisms are involved in the association between periodontitis and CVD. The key players are periodontal bacteria and their toxins, which can enter the circulation and infiltrate blood vessel walls. The increase in proinflammatory molecules such as interleukins and chemokines, c-reactive protein, fibrinogen, and oxidative stress also plays a decisive role. In addition, an increase in parameters of ED, arterial stiffness, and atherosclerosis, such as carotid intima-media thickness, pulse wave velocity, and flow-mediated dilatation, has been shown in periodontal patients.

Conclusions

The literature today agrees on the association of periodontitis and CVD and the positive role of periodontal therapy on systemic inflammatory indices and cardiovascular outcomes. Hopefully, these non-invasive methodologies could be extended to periodontal patients to provide a comprehensive understanding of the CVD-periodontitis link from the perspective of a personalized medicine approach in periodontology.

Point-of-care diagnostic devices for periodontitis - current trends and urgent need

Point of care (POC) diagnostic devices provide a method for rapid accurate identification of disease through analysis of biologically relevant substances. This review focuses on the utility of POC testing for early detection of periodontitis, a critical factor in treating the disease. Accessing the oral cavity for biological sampling is less invasive when compared to other internal test sites, and oral fluids contain biomarkers indicative of periodontitis. The ease of access makes the mouth an excellent target location for the development of POC devices. In this review, accepted standards in industry by which these devices must adhere, provided by the World Health Organization such as REASSURED and CLIA, are discussed. An overview is provided for many periodontal biomarkers currently being investigated as a means of predicting periodontal disease and its progression. POC devices currently being investigated for the identification and monitoring of periodontal disease such as paper-based and lab-on-a-chip based devices are outlined. Limitations of current POC devices on the market are provided and future directions in leveraging biomarkers as an adjunctive method for oral diagnosis along with AI-based analysis systems are discussed. Here, we present the ESSENCE sensor platform, which combines a porous non-planar electrode with enhanced shear flow to achieve unprecedented sensitivity and selectivity. The combination of the ESENCE chip with an automated platform allows us to meet the WHO's ASSURED criteria. This platform promises to be an exciting POC candidate for early detection of periodontitis.

Auxiliary Diagnosis of Dental Calculus Based on Deep Learning and Image Enhancement by Bitewing Radiographs

In the field of dentistry, the presence of dental calculus is a commonly encountered issue. If not addressed promptly, it has the potential to lead to gum inflammation and eventual tooth loss. Bitewing (BW) images play a crucial role by providing a comprehensive visual representation of the tooth structure, allowing dentists to examine hard-to-reach areas with precision during clinical assessments. This visual aid significantly aids in the early detection of calculus, facilitating timely interventions and improving overall outcomes for patients. This study introduces a system designed for the detection of dental calculus in BW images, leveraging the power of YOLOv8 to identify individual teeth accurately. This system boasts an impressive precision rate of 97.48%, a recall (sensitivity) of 96.81%, and a specificity rate of 98.25%. Furthermore, this study introduces a novel approach to enhancing interdental edges through an advanced image-enhancement algorithm. This algorithm combines the use of a median filter and bilateral filter to refine the accuracy of convolutional neural networks in classifying dental calculus. Before image enhancement, the accuracy achieved using GoogLeNet stands at 75.00%, which significantly improves to 96.11% post-enhancement. These results hold the potential for streamlining dental consultations, enhancing the overall efficiency of dental services.

Intraoral Ultrasonography for the Exploration of Periodontal Tissues: A Technological Leap for Oral Diagnosis

INTRODUCTION

Periodontal disease is an infectious syndrome presenting inflammatory aspects. Radiographic evaluation is an essential complement to clinical assessment but has limitations such as the impossibility of assessing tissue inflammation. It seems essential to consider new exploration methods in clinical practice. Ultrasound of periodontal tissues could make it possible to visualize periodontal structures and detect periodontal diseases (periodontal pocket measurement and the presence of intra-tissue inflammation). Clinical Innovation Report: An ultrasound probe has been specially developed to explore periodontal tissues. The objective of this clinical innovation report is to present this device and expose its potential.

DISCUSSION

Various immediate advantages favor using ultrasound: no pain, no bleeding, faster execution time, and an image recording that can be replayed without having to probe the patient again. Ultrasound measurements of pocket depth appear to be as reliable and reproducible as those obtained by manual probing, as do tissue thickness measurements and the detection of intra-tissue inflammation.

CONCLUSIONS

Ultrasound seems to have a broad spectrum of indications. Given the major advances offered by ultrasound imaging as a complementary aid to diagnosis, additional studies are necessary to validate these elements and clarify the potential field of application of ultrasound imaging in dentistry.

Radiographic diagnosis of periodontal diseases - Current evidence versus innovations

Accurate diagnosis of periodontal and peri-implant diseases relies significantly on radiographic examination, especially for assessing alveolar bone levels, bone defect morphology, and bone quality. This narrative review aimed to comprehensively outline the current state-of-the-art in radiographic diagnosis of alveolar bone diseases, covering both two-dimensional (2D) and three-dimensional (3D) modalities. Additionally, this review explores recent technological advances in periodontal imaging diagnosis, focusing on their potential integration into clinical practice. Clinical probing and intraoral radiography, while crucial, encounter limitations in effectively assessing complex periodontal bone defects. Recognizing these challenges, 3D imaging modalities, such as cone beam computed tomography (CBCT), have been explored for a more comprehensive understanding of periodontal structures. The significance of the radiographic assessment approach is evidenced by its ability to offer an objective and standardized means of evaluating hard tissues, reducing variability associated with manual clinical measurements and contributing to a more precise diagnosis of periodontal health. However, clinicians should be aware of challenges related to CBCT imaging assessment, including beam-hardening artifacts generated by the high-density materials present in the field of view, which might affect image quality. Integration of digital technologies, such as artificial intelligence-based tools in intraoral radiography software, the enhances the diagnostic process. The overarching recommendation is a judicious combination of CBCT and digital intraoral radiography for enhanced periodontal bone assessment. Therefore, it is crucial for clinicians to weigh the benefits against the risks associated with higher radiation exposure on a case-by-case basis, prioritizing patient safety and treatment outcomes.

The repeatability of periodontal imaging with intraoral ultrasound scanning

OBJECTIVE

Ultrasound is a non-invasive and low-cost diagnostic tool widely used in medicine. Recent studies have demonstrated that ultrasound imaging might have the potential to be used intraorally to assess the periodontium by comparing it to current imaging methods. This study aims to characterize the repeatability of intraoral periodontal ultrasound imaging.

MATERIALS AND METHODS

Two hundred and twenty-three teeth were scanned from fourteen volunteers participating in this study. One operator conducted all the scans in each tooth thrice with a 20 MHz intraoral ultrasound. The repeatability of three measurements, alveolar bone crest to the cementoenamel junction (ABC-CEJ), gingival thickness (GT), and alveolar bone thickness (ABT), was calculated with intercorrelation coefficient (ICC). Measurements were also compared with mean absolute deviation (MAD), repeatability coefficient (RC), and descriptive statistics.

RESULTS

ICC scores for intra-rater repeatability were 0.917(0.897,0.933), 0.849(0.816,0.878), and 0.790(0.746,0.898), MAD results were 0.610 mm (± 0.508), 0.224 (± 0.200), and 0.067 (± 0.060), and RC results were 0.648, 0.327, and 0.121 for ABC-CEJ, GT, and ABT measurements, respectively.

CONCLUSION

Results of the present study pointed towards good or excellent repeatability of ultrasound as a measurement tool for periodontal structures.

CLINICAL RELEVANCE

Clinicians could benefit from the introduction of a novel chairside diagnostic tool. Ultrasound is a non-invasive imaging assessment tool for the periodontium with promising results in the literature. Further validation, establishment of scanning protocols, and commercialization are still needed before ultrasound imaging is available for clinicians.

Use of ultrasound imaging for assessment of the periodontium: A systematic review

The objective of this study was to systematically review the literature regarding diagnostic applications of ultrasound imaging for evaluation of the periodontium in humans. The search was conducted on Medline, EMBASE, Web of Science, Scopus, Cochrane, and PubMed up to April 3, 2023. The studies included were exclusively human studies that assessed the periodontium with ultrasound (US) imaging (b-mode). Outcomes measured included alveolar bone level, alveolar bone thickness, gingival thickness, and blood flow quantification. References were imported to Covidence. Two reviewers conducted phases 1 and 2. The JBI risk assessment tool for cross-sectional studies was used. Extracted data included the transducer and measurements used and the study's outcomes. The search yielded 4892 studies after removing duplicates. From these, 25 studies were included and selected for extraction. Included studies retrieved outcomes from US examinations of the periodontal tissues. From the selected studies, 15 used US on natural teeth, 4 used US on implants, 2 used US on edentulous ridges, and 4 used color flow/power in US to evaluate the blood flow. The results of the present systematic review suggest that US might be a feasible and valuable diagnostic tool for the periodontium, with the potential to complement shortfalls of current radiographic technologies.

Artificial intelligence models for diagnosing gingivitis and periodontal disease: A systematic review

STATEMENT OF PROBLEM

Artificial intelligence (AI) models have been developed for periodontal applications, including diagnosing gingivitis and periodontal disease, but their accuracy and maturity of the technology remain unclear.

PURPOSE

The purpose of this systematic review was to evaluate the performance of the AI models for detecting dental plaque and diagnosing gingivitis and periodontal disease.

MATERIAL AND METHODS

A review was performed in 4 databases: MEDLINE/PubMed, World of Science, Cochrane, and Scopus. A manual search was also conducted. Studies were classified into 4 groups: detecting dental plaque, diagnosis of gingivitis, diagnosis of periodontal disease from intraoral images, and diagnosis of alveolar bone loss from periapical, bitewing, and panoramic radiographs. Two investigators evaluated the studies independently by applying the Joanna Briggs Institute critical appraisal. A third examiner was consulted to resolve any lack of consensus.

RESULTS

Twenty-four articles were included: 2 studies developed AI models for detecting plaque, resulting in accuracy ranging from 73.6% to 99%; 7 studies assessed the ability to diagnose gingivitis from intraoral photographs reporting an accuracy between 74% and 78.20%; 1 study used fluorescent intraoral images to diagnose gingivitis reporting 67.7% to 73.72% accuracy; 3 studies assessed the ability to diagnose periodontal disease from intraoral photographs with an accuracy between 47% and 81%, and 11 studies evaluated the performance of AI models for detecting alveolar bone loss from radiographic images reporting an accuracy between 73.4% and 99%.

CONCLUSIONS

AI models for periodontology applications are still in development but might provide a powerful diagnostic tool.

Increased odds for COVID-19 infection among individuals with periodontal disease

OBJECTIVES

Periodontal disease has been linked to multiple systemic conditions, but the relationship with COVID-19 still needs to be elucidated. We hypothesized that periodontal disease may be associated with COVID-19 infection.

MATERIALS AND METHODS

This study utilized cross-sectional data to establish the strength of the association between periodontal disease and COVID-19 infection. The University of Florida Health Center's i2b2 patient's registry was used to generate patient counts through ICD-10 diagnostic codes. Univariate descriptive statistics of the patient population and logistic regression to estimate odds ratios of associations between periodontal disease and COVID-19 infection were used for analysis.

RESULTS

Patients with periodontal disease were 4.4 times more likely to be positively diagnosed with COVID-19 than patients without PD. Associations remained similar and robust (P value < 0.0001) after adjustment for age (OR = 4.34; 95% CI, 3.68-5.09), gender (OR = 4.46; 95% CI, 3.79-5.23), and smoking status (OR = 4.77; 95% CI, 4.04-5.59). Associations were smaller but remained robust (P value < 0.0001) after adjusting for race (OR = 2.83; 95% CI, 2.40-3.32), obesity (OR = 2.53; 95% CI, 2.14-2.98), diabetes (OR = 3.32; 95% CI, 2.81-3.90), and cardiovascular disease (OR = 2.68; 95% CI, 2.27-3.14).

CONCLUSIONS

Periodontal disease is significantly associated with increased odds for COVID-19 infection.

CLINICAL RELEVANCE

With the caveat of a cross-sectional study design, these results suggest that periodontal disease may increase the odds for COVID-19 infection.

Estimation of Cancellous Changes Using Fractal Analysis in Patients with Periodontitis

Periodontal disease is a broad term given when the periodontium is affected by inflammation. There are several methods to diagnose periodontitis, but no method to quantify the cancellous bone is presently used. For this purpose, a non-invasive tool that is efficient in analyzing bone quality called fractal analysis can be employed. The objective of the study was to utilize fractal dimension (FD) to evaluate cancellous patterns of interproximal alveolar bone using a digital intraoral periapical radiograph (IOPAR) in different clinical presentations of periodontitis classified according to the latest classification by the World Workshop for Periodontal and Peri-Implant Diseases and Conditions, 2017 (WWDC, 2017). The study aimed to numerically calculate the periodontitis changes in the cancellous bone around the affected tooth on an IOPAR using fractal analysis and to provide an additional criterion for the staging of periodontitis. In this cross-sectional observational study, 75 patients were selected and equally allotted to five groups based on the staging system proposed by the WWDC, 2017. The region of interest was selected on the IOPA radiograph of the tooth with the site having the most significant clinical attachment loss, and FD was calculated using Image J analysis. The association of gender and age with stages of periodontitis was studied using the chi-square test of independence. A comparison of % bone loss and fractal dimension among stages was studied by using the non-parametric Kruskal Wallis test. The relationship between % bone loss and fractal dimension within stages and gender was studied by using the Karl Pearson correlation. A receiver operating characteristic (ROC) curve analysis was performed for FD value as a marker of periodontitis patients. We demonstrated that the FD values decreased significantly with the increase in stages (p < 0.0001). The overall relationship between % bone loss and FD showed a significantly strong negative correlation of -0.739 (p < 0.0001), except for stages III and IV. FD can be utilized as a quantitative method for detecting cancellous bone changes in different stages of periodontitis, aiding in diagnosing periodontitis.

Early Implant Bone Loss in the Preprosthetic Phase: A Retrospective Study

Initiation of the inflammatory response begins with the surgical placement of an implant that stimulates bone remodeling. The occurrence of crestal bone loss during submerged healing affects the prognosis of an implant. Hence, this study was conducted to estimate the early implant bone loss during the preprosthetic phase on bone level implants placed equicrestally. This retrospective observational study included evaluation of crestal bone loss around 271 two-piece implants placed in 149 patients from the archived postsurgical (P1) and preprosthetic (P2) digital orthopantomographic records using MicroDicom software. The outcome was categorized based on (1) sex (male or female), (2) time of implant placement (immediate [I] vs conventional [D]), (3) duration of healing period before loading (conventional [T1] vs delayed [T2]), (4) region of implant placement (maxilla [M1] vs mandible [M2]), and (5) site of implant placement (anterior [A] vs posterior [P]). To find the significant difference between the bivariate samples in the independent groups, an unpaired sample t test was used. The average marginal bone loss during the healing phase was 0.56 ± 0.573 mm in the mesial region and 0.44 ± 0.549 mm in the distal region of the implant, with a statistically significant difference (P < .01). There was no statistically significant difference in crestal bone level with the (1) sex of the patient (male or female), (2) type of implant placement (I or D), (3) time of implant loading (T1 or T2), (4) region of implant placement (M1 or M2), or (5) site of implant in the arch (A or P) (P > .05). An average of 0.50 mm crestal bone loss occurred in the peri-implant region during the preprosthetic phase. We found that the delayed placement of an implant and a delay in the healing period would further increase the early implant bone loss. The difference in the healing period did not alter the outcome of the study.

Multi-modal deep learning for automated assembly of periapical radiographs

OBJECTIVES

Periapical radiographs are oftentimes taken in series to display all teeth present in the oral cavity. Our aim was to automatically assemble such a series of periapical radiographs into an anatomically correct status using a multi-modal deep learning model.

METHODS

4,707 periapical images from 387 patients (on average, 12 images per patient) were used. Radiographs were labeled according to their field of view and the dataset split into a training, validation, and test set, stratified by patient. In addition to the radiograph the timestamp of image generation was extracted and abstracted as follows: A matrix, containing the normalized timestamps of all images of a patient was constructed, representing the order in which images were taken, providing temporal context information to the deep learning model. Using the image data together with the time sequence data a multi-modal deep learning model consisting of two residual convolutional neural networks (ResNet-152 for image data, ResNet-50 for time data) was trained. Additionally, two uni-modal models were trained on image data and time data, respectively. A custom scoring technique was used to measure model performance.

RESULTS

Multi-modal deep learning outperformed both uni-modal image-based learning (p<0.001) and time-based learning (p<0.05). The multi-modal deep learning model predicted tooth labels with an F1-score, sensitivity and precision of 0.79, respectively, and an accuracy of 0.99. 37 out of 77 patient datasets were fully correctly assembled by multi-modal learning; in the remaining ones, usually only one image was incorrectly labeled.

CONCLUSIONS

Multi-modal modeling allowed automated assembly of periapical radiographs and outperformed both uni-modal models. Dental machine learning models can benefit from additional data modalities.

CLINICAL SIGNIFICANCE

Like humans, deep learning models may profit from multiple data sources for decision-making. We demonstrate how multi-modal learning can assist assembling periapical radiographs into an anatomically correct status. Multi-modal learning should be considered for more complex tasks, as clinically a wealth of data is usually available and could be leveraged.

Automatic recognition of teeth and periodontal bone loss measurement in digital radiographs using deep-learning artificial intelligence

Background/purpose

Artificial Intelligence (AI) can optimize treatment approaches in dental healthcare due to its high level of accuracy and wide range of applications. This study seeks to propose a new deep learning (DL) ensemble model based on deep Convolutional Neural Network (CNN) algorithms to predict tooth position, detect shape, detect remaining interproximal bone level, and detect radiographic bone loss (RBL) using periapical and bitewing radiographs.

Materials and methods

270 patients from January 2015 to December 2020, and all images were deidentified without private information for this study. A total of 8000 periapical radiographs with 27,964 teeth were included for our model. AI algorithms utilizing the YOLOv5 model and VIA labeling platform, including VGG-16 and U-Net architecture, were created as a novel ensemble model. Results of AI analysis were compared with clinicians' assessments.

Results

DL-trained ensemble model accuracy was approximately 90% for periapical radiographs. Accuracy for tooth position detection was 88.8%, tooth shape detection 86.3%, periodontal bone level detection 92.61% and radiographic bone loss detection 97.0%. AI models were superior to mean accuracy values from 76% to 78% when detection was performed by dentists.

Conclusion

The proposed DL-trained ensemble model provides a critical cornerstone for radiographic detection and a valuable adjunct to periodontal diagnosis. High accuracy and reliability indicate model's strong potential to enhance clinical professional performance and build more efficient dental health services.

Pre-Chemotherapy Dental Screening: Is There Additional Diagnostic Value for a Panoramic Radiograph?

BACKGROUND

The oral cavity is a potential source of infectious complications in patients treated with myelosuppressive chemotherapy (CT). Pre-chemotherapy oral examination to identify foci of infection is recommended, but it is unclear whether this should include panoramic radiography. The present study aimed to evaluate the additional diagnostic merit of panoramic radiography as part of pre-CT oral screening.

METHODS

Patients with solid tumors scheduled to receive a myelosuppressive CT were eligible. The foci definition followed the guidelines of the Dutch Association of Maxillofacial Surgery. Oral foci assessed by clinical evaluation and panoramic radiography were compared.

RESULTS

In 33 out of 93 patients (35.5%), one or more foci were identified by clinical examination, whereas in 49.5% of patients, panoramic radiography showed pathology. In 19 patients, an oral focus was missed by clinical examination only, whereas in 11 patients, panoramic radiography indicated periodontal bone loss, but advanced periodontitis was not substantiated by clinical examination.

CONCLUSIONS

Panoramic radiographs complement clinical examinations and have additional diagnostic value. Nevertheless, the additional merit seems small, and the clinical relevance may vary depending on the anticipated risk of developing oral complications and the need for detailed diagnosis and rigorous elimination of oral foci prior to the start of cancer therapy.

Development and validation of intraoral periapical radiography-based machine learning model for periodontal defect diagnosis

Radiographic determination of the bone level is useful in the diagnosis and determination of the severity of the periodontal disease. Various two- and three-dimensional imaging modalities offer choices for imaging pathologic processes that affect the periodontium. In recent years, innovative computer techniques, especially artificial intelligence (AI), have begun to be used in many areas of dentistry and are helping increase treatment and diagnostic performance. This study was aimed at developing a machine-learning (ML) model and assessing the extent to which it was capable of classifying periodontal defects on 2D periapical images. Eighty-seven periapical images were examined as part of this research. The existence or absence of periodontal defects in the aforementioned images were evaluated by a human observer. The evaluations were subsequently repeated using a radiomics platform. A comparison was made of all data acquired through human observation and ML techniques by SVM analysis. According to the study findings the ability of human observers and the ML model to detect periodontal defects was significantly different in comparison to the gold standard. However, ML and human observers performed similarly for the detection of periodontal defects without a significant difference. This study reveals that the prediction of periodontal defects can be achieved by combining particular radiomic features with image variables. The proposed machine leaning model can be utilized for supporting clinical practitioners and eventually substitute evaluations conducted by human observers while enhancing future levels of performance.

Intra-Oral Photograph Analysis for Gingivitis Screening in Orthodontic Patients

This study aimed to confirm the presence of gingival inflammation through image analysis of the papillary gingiva using intra-oral photographs (IOPs) before and after orthodontic treatment and to confirm the possibility of using gingival image analysis for gingivitis screening. Five hundred and eighty-eight (n  =  588) gingival sites from the IOPs of 98 patients were included. Twenty-five participants who had completed their orthodontic treatments and were aged between 20 and 37 were included. Six points on the papillary gingiva were selected in the maxillary and mandibular anterior incisors. The red/green (R/G) ratio values were obtained for the selected gingival images and the modified gingival index (GI) was compared. The change in the R/G values during the orthodontic treatment period appeared in the order of before orthodontic treatment (BO), mid-point of orthodontic treatment (MO), three-quarters of the way through orthodontic treatment (TO), and immediately after debonding (IDO), confirming that it was similar to the change in the GI. The R/G value of the gingiva in the image correlated with the GI. Therefore, it could be used as a major index for gingivitis diagnosis using images.

Ultrasound Imaging of the Periodontium Complex: A Reliability Study

Background

Ultrasonography is a noninvasive, low-cost diagnostic tool widely used in medicine. Recent studies have demonstrated that ultrasound imaging might have the potential to be used intraorally to assess periodontal biomarkers.

Objectives

To evaluate the reliability of interlandmark distance measurements on intraoral ultrasound images of the periodontal tissues.

Materials and Methods

Sixty-four patients from the graduate periodontics (n = 33) and orthodontics (n = 31) clinics were recruited. A 20 MHz handheld intraoral ultrasound transducer was used to scan maxillary and mandibular incisors, canines, and premolars. Distances between the alveolar bone crest and cementoenamel junction (ABC-CEJ), gingival thickness (GT), and alveolar bone thickness (ABT) were measured by 3 raters. The intercorrelation coefficient (ICC) and mean absolute deviation (MAD) were calculated among and between the raters. Raters also scored images according to quality.

Results

The ICC scores for intrarater reliability were 0.940 (0.932-0.947), 0.953 (0.945-0.961), and 0.859 (0.841-0.876) for ABC-CEJ, GT, and ABT, respectively. The intrarater MAD values were 0.023 (±0.019) mm, 0.014 (±0.005) mm, and 0.005 (±0.003) mm, respectively. The ICC scores for interrater reliability were 0.872 (95% CI: 0.836-0.901), 0.958 (95% CI: 0.946-0.968), and 0.836 (95% CI: 0.789-0.873) for ABC-CEJ, GT, and ABT, respectively. The interrater MAD values were 0.063 (±0.029) mm, 0.023 (±0.018) mm, and 0.027 (±0.012) mm, respectively.

Conclusions

The present study showed the high reliability of ultrasound in both intrarater and interrater assessments. Results suggest there might be a potential use of intraoral ultrasound to assess periodontium.

Factors affecting interpretation of dental radiographs

OBJECTIVES

To identify the factors influencing errors in the interpretation of dental radiographs.

METHODS

A protocol was registered on Prospero. All studies published until May 2022 were included in this review. The search of the electronic databases spanned Ovid Medline, PubMed, EMBASE, Web of Science and Scopus. The quality of the studies was assessed using the MMAT tool. Due to the heterogeneity of the included studies, a meta-analysis was not conducted.

RESULTS

The search yielded 858 articles, of which eight papers met the inclusion and exclusion criteria and were included in the systematic review. These studies assessed the factors influencing the accuracy of the interpretation of dental radiographs. Six factors were identified as being significant that affected the occurrence of interpretation errors. These include clinical experience, clinical knowledge, and technical ability, case complexity, time pressure, location and duration of dental education and training and cognitive load.

CONCLUSIONS

The occurrence of interpretation errors has not been widely investigated in dentistry. The factors identified in this review are interlinked. Further studies are needed to better understand the extent of the occurrence of interpretive errors and their impact on the practice of dentistry.

Automatic Segmentation of Periodontal Tissue Ultrasound Images with Artificial Intelligence: A Novel Method for Improving Dataset Quality

This research aimed to evaluate Mask R-CNN and U-Net convolutional neural network models for pixel-level classification in order to perform the automatic segmentation of bi-dimensional images of US dental arches, identifying anatomical elements required for periodontal diagnosis. A secondary aim was to evaluate the efficiency of a correction method of the ground truth masks segmented by an operator, for improving the quality of the datasets used for training the neural network models, by 3D ultrasound reconstructions of the examined periodontal tissue.

METHODS

Ultrasound periodontal investigations were performed for 52 teeth of 11 patients using a 3D ultrasound scanner prototype. The original ultrasound images were segmented by a low experienced operator using region growing-based segmentation algorithms. Three-dimensional ultrasound reconstructions were used for the quality check and correction of the segmentation. Mask R-CNN and U-NET were trained and used for prediction of periodontal tissue's elements identification.

RESULTS

The average Intersection over Union ranged between 10% for the periodontal pocket and 75.6% for gingiva. Even though the original dataset contained 3417 images from 11 patients, and the corrected dataset only 2135 images from 5 patients, the prediction's accuracy is significantly better for the models trained with the corrected dataset.

CONCLUSIONS

The proposed quality check and correction method by evaluating in the 3D space the operator's ground truth segmentation had a positive impact on the quality of the datasets demonstrated through higher IoU after retraining the models using the corrected dataset.

"New Normal" Radiology

COVID-19, the most recent and globally impactful zoonotic viral pandemic in the last 20 years, has now entered its third year. As the global dental profession returns to providing as full a range of services as possible, in addition to embedding the new infection-control processes that were developed for this pandemic, it should also take full advantage of digital conventional radiology (intraoral, extraoral, and panoramic radiography) and cone-beam computed tomography. Regardless of vaccinations, new or yet-to-manifest variants, and testing, some dentists may be working in communities where the asymptomatic but potentially infectious patient poses a real risk. This needs to be met with not only the whole COVID-19 panoply the dentist is already too familiar with but also the need to minimise aerosol generation production by dental radiography. A flowchart and a table that compares the attributes of the above modalities are included.

Impact of the presence of partially erupted third molars on the local radiographic bone condition

The decision on retaining or prophylactically removing asymptomatic lower third molars is still discussed in the literature. This study aimed to verify the association between asymptomatic lower third molars and local bone conditions through periapical radiographs. Based on sample size calculations, 288 radiographs were required. Dependent variables were alveolar bone crest status and radiolucency between the distal aspect of the third molar crown and the ascending mandibular ramus. Independent variables were sex, age, Pell and Gregory and Winter’s classification, angulation and distance between second and third molars, third molar side. Advanced ages (OR 1.15; CI 1.08–1.24; p < 0.001) and greater third molar angulations (OR 1.03; CI 1.01–1.04; p < 0.001) significantly increased the chance of radiographic alterations in the bone crest between second and third molars. Radiolucency distal to third molars was solely impacted by patient’s age (OR 1.05; CI 1.01–1.11; p = 0.036). Older patients and lower third molars with greater angulations about adjacent second molar should be evaluated for third molar removal because of the increased chance of alveolar bone crest alterations. Older patients should also be monitored for wider radiolucent pericoronal spaces distal to lower third molars and its consequences.

Application of Fractal Analysis in Detecting Trabecular Bone Changes in Periapical Radiograph of Patients with Periodontitis

Introduction

Evaluation of detailed features of the supporting bone is an important step in diagnosis and treatment planning for teeth with clinical attachment loss. Fractal analysis can be used as a method for evaluating the complexity of trabecular bone structures. The aim of this study was to evaluate the trabecular bone changes in periapical radiographs of patients with different stages of periodontitis using fractal analysis.

Methods

This comparative cross-sectional study was performed on patients with and without clinical attachment loss in mandibular first molars. Teeth with clinical attachment loss were divided into mild, moderate, and severe periodontitis groups. Digital periapical radiographs were obtained from the mandibular first molars using the same exposure parameters. DICOM file of the radiographs was exported to ImageJ software for fractal analysis. Three regions of interest (ROIs) were considered in each radiograph: two proximal ROIs mesial and distal to the mandibular first molar and one apical ROI. Fractal dimension (FD) values were calculated using the fractal box counting approach. Statistical analysis was performed using the chi-square test, Mann–Whitney test, intraclass correlation coefficient, and ANOVA (α = 0.05).

Results

FD values were significantly different between moderate and severe periodontitis and healthy periodontal bone (P < 0.05), except for the distal ROI for moderate periodontitis cases (P=0.280). However, FD values of the supporting bone in periodontally healthy teeth and teeth with mild periodontitis did not show a statistically significant difference (P > 0.05).

Conclusion

Fractal analysis is a useful tool for evaluation of bone alterations in moderate and severe periodontitis, but was not able to detect the most initial radiographic bone signs of mild periodontitis.

Automated description of the mandible shape by deep learning

PURPOSE

The shape of the mandible has been analyzed in a variety of fields, whether to diagnose conditions like osteoporosis or osteomyelitis, in forensics, to estimate biological information such as age, gender, and race or in orthognathic surgery. Although the methods employed produce encouraging results, most rely on the dry bone analyses or complex imaging techniques that, ultimately, hamper sample collection and, as a consequence, the development of large-scale studies. Thus, we proposed an objective, repeatable, and fully automatic approach to provide a quantitative description of the mandible in orthopantomographies (OPGs).

METHODS

We proposed the use of a deep convolutional neural network (CNN) to localize a set of landmarks of the mandible contour automatically from OPGs. Furthermore, we detailed four different descriptors for the mandible shape to be used for a variety of purposes. This includes a set of linear distances and angles calculated from eight anatomical landmarks of the mandible, the centroid size, the shape variations from the mean shape, and a group of shape parameters extracted with a point distribution model.

RESULTS

The fully automatic digitization of the mandible contour was very accurate, with a mean point to the curve error of 0.21 mm and a standard deviation comparable to that of a trained expert. The combination of the CNN and the four shape descriptors was validated in the well-known problems of forensic sex and age estimation, obtaining 87.8% of accuracy and a mean absolute error of 1.57 years, respectively.

CONCLUSION

The methodology proposed, including the shape model, can be valuable in any field that requires a quantitative description of the mandible shape and a visual representation of its changes such as clinical practice, surgery management, dental research, or legal medicine.

The Chairside Periodontal Diagnostic Toolkit: Past, Present, and Future

Periodontal diseases comprise a group of globally prevalent, chronic oral inflammatory conditions caused by microbial dysbiosis and the host immune response. These diseases specifically affect the tooth-supporting tissues (i.e., the periodontium) but are also known to contribute to systemic inflammation. If left untreated, periodontal diseases can ultimately progress to tooth loss, lead to compromised oral function, and negatively impact the overall quality of life. Therefore, it is important for the clinician to accurately diagnose these diseases both early and accurately chairside. Currently, the staging and grading of periodontal diseases are based on recording medical and dental histories, thorough oral examination, and multiple clinical and radiographic analyses of the periodontium. There have been numerous attempts to improve, automate, and digitize the collection of this information with varied success. Recent studies focused on the subgingival microbiome and the host immune response suggest there is an untapped potential for non-invasive oral sampling to assist clinicians in the chairside diagnosis and, potentially, prognosis. Here, we review the available toolkit available for diagnosing periodontal diseases, discuss commercially available options, and highlight the need for collaborative research initiatives and state-of-the-art technology development across disciplines to overcome the challenges of rapid periodontal disease diagnosis.

Quality and Findings of Bitewing Radiographs among Twenty-Year-Old Conscripts in Finland

Objectives

Bitewing radiographs are mainly used to confirm clinical findings in caries diagnostics. The objective here was to investigate the quality of bitewing radiographs after short brush-up training and additional findings besides caries in a low-caries population.

Methods

The material of this cross-sectional study comprised 377 pairs of bitewing radiographs of 19- to 20-year-olds taken by dentists. Radiography was considered indicated if one dentinal caries lesion was present on clinical examination. A senior oral radiologist evaluated quality and diagnosed the findings afterwards unaware of clinical status. The association between variables was analysed using cross tabulation and chi-squared testing.

Results

Almost half of the images were of compromised quality (44.1%). Dentinal caries lesions were detected in 82.3% and enamel lesions in 73.5% of the subjects. On average, the subjects had 1.7 (SD 0.52) dentinal lesions. Fillings were found in 81.8%, fractures/cracks in 11.7%, and attrition in 7.4% of the subjects. Signs of excessive bite force were recorded in 19.4%, whereas marginal bone loss was detected in 6.4%. No significant correlation was detected between fractures, attrition, and excessive bite forces.

Conclusions

Effort must be taken to ensure high quality of bitewing radiographs. In addition to caries detection, bitewing radiographs offer additional value, such as detecting excessive bite forces, tooth wear, and marginal bone loss among young adults.

A Wolf in Sheep's clothing: A case report series of oral manifestations of multiple myeloma

Multiple myeloma is the most common haematological malignancy accounting for 10 % of all haematological cancers. Treatment of myeloma has evolved in recent years leading to improved survival. Lesions related to myeloma are frequently observed within the oral cavity and jawbone. In addition, many of the therapeutic agents have side effects with implications for provision of dental treatment. This case series aims to highlight some of these presentations to remind dental practitioners to be vigilant. Observation of suspicious lesions within the oral cavity or jawbone might warrant further investigation.

Alveolar bone loss, platelet and glycosylated haemoglobin levels in 239 patients. A clinical study

Background

The relation between periodontal disease and systemic pathologies is still not widespread among general practitioners. The aim of our study is to evaluate whether or not periodontal radiological diagnosis can aid the detection of blood alterations associated with acquired systemic diseases.

Material and Methods

This is a cross sectional study. All of the participants underwent a panoramic radiograph and a complete blood test. Morphological bone loss was considered as positive in those patients who showed radiographically more than 1 tooth with bone loss greater than or equal to the middle third of the root. The statistical analysis was performed by comparing the variables using the ANOVA or U-Mann-Whitney tests for independent samples with normal conditions. The correlation coefficient was analysed using the Pearson test.

Results

239 patients were included in our study (96 men and 143 women) with an average age of 64.40 years. 59.04% of the patients were determined as morphological bone loss positive and had on average 4 teeth less than negative patients (p <0.0001). Also the average platelet levels in positive patients were lower (p = 0.024) and mean levels of HBA1c (p = 0.009) were higher.

Conclusions

Morphological bone loss parameter can be useful both for dentists and general practitioners to refer, subsequently, to periodontal specialist.

Key words:Periodontal diseases, blood chemical analysis, blood platelets, alkaline phosphatase, glycosylated haemoglobin A, alveolar bone loss.

Diagnosing periodontal and dental indicators with horizontal and vertical bitewing radiographs

OBJECTIVE

The aim of this study is to compare information provided by the 2 orientations of bitewing radiographs, horizontal (HBW) and vertical (VBW) taken in a dental school.

METHODS AND MATERIALS

Radiographic records were reviewed at Tufts University School of Dental Medicine (TUSDM) for patients showing posterior bone loss who had both HBW and VBW. 320 records were reviewed with 6 criteria: visibility of crestal bone from the distal of the cuspids to the distal of the most posterior tooth, visibility of horizontal or angular bone loss, the crestal density of bone, visibility of interproximal contact areas, visibility of the entire anatomical crown, and visibility of furcations.

RESULTS

Significantly higher number of VBW compared with HBW (P < 0.0001) showed the levels of alveolar bone loss (52.81% vs. 3.75%), the type of loss (angular or horizontal) (50.94% vs. 3.75%), the crestal bone density (28.75% vs. 0.63%), the contact areas (20.63% vs. 14.38%), and the furcations (43.44% vs. 1.25%). A greater number of HBW showed the entire anatomical crown compared with VBW. No significant difference was detected in the number of radiographs taken per HBW and VBW set.

CONCLUSION

For patients with alveolar bone loss, VBW are superior to HBW when assessing bone levels, density, morphology, tooth furcations, and evaluating interproximal contact areas for caries. It is recommended that the vertical bitewing technique be taught as a standard in dental, dental hygiene, and dental assisting schools for adult patients showing evidence of posterior interdental bone loss.

Qualitative and Quantitative Assessment of Alveolar Bone Destruction in Adult Rats Using CBCT

Cone-beam computed tomography (CBCT) has strong potential to be utilized in various aspects of veterinary dentistry. Using ex vivo rat maxillary bone and teeth, the purpose of this study was to compare gray value, surface area, and volumetric measurements of teeth with and without experimental periodontitis by CBCT. Periodontitis was induced in 36 molar teeth, while 36 teeth with a healthy periodontium served as control. Images of each specimen along with teeth were obtained using CBCT. The following measurements for each tooth with periodontitis (n = 36) were recorded: gray value measurement, width, height, depth, surface area, and volume of the alveolar bone loss. For the control group (n = 36), gray value measurement, surface area, and volume of the alveolar bone were recorded. All measurements were repeated after 3 weeks. As the gold standard, the rat maxillas were decalcified and paraffin-embedded for further immunocytochemical study. One-way analysis of variance (ANOVA) was used. Significance level was set at P < .05. Correlation values for gray value, width, height, depth, surface area, and volume measurements were 0.983, 0.966, 0.962, 0.880, 0.998, and 0.999, respectively, for the first and second measurements. One way ANOVA showed statistically significant differences between teeth with and without alveolar bone destruction conducted for gray value, surface area, and volume measurements (P = .000). Mean gray value, surface area, and volume measurements decreased 56.46%, 81.89%, and 78.56%, respectively, for teeth with alveolar bone destruction in comparison to healthy teeth. Cone-beam computed tomography provided useful qualitative and quantitative information regarding induced periodontitis in the rat maxilla.

Extractions in Patients with Periodontal Diseases and Clinical Decision-Making Process

Objectives

To investigate the professional aspects and clinical and radiographic evidence that influences the decision for the extraction of teeth among periodontologists and general dentists.

Material and methods

The sample consisted of 150 (n=106 females and 44 males) dentists (n=103 general dentists and 47 periodontologists) that responded to a questionnaire designed to retrieve cross-sectional information related mainly to their level of training and time of experience in practice, as well as their personal decision for managing four patients with periodontal disease. Bivariate analyses were performed to test the association between the clinical decisions and the professional information collected from the dentists.

Results

In specific cases, periodontologists decided to maintain more teeth than general dentists (p<0.05). In other cases, dentists with more years of experience in practice decided to opt for more extractions (p<0.05). The level of periodontal disease (50-92%), poor oral hygiene (42.6-67.3%) and lack of alveolar bone structure (43.2-79.3%) were the most prevalent reasons behind the decision for extractions.

Conclusions

An advanced level of training in Dentistry, especially Periodontology, and more years of experience in practice may lead to more well-founded decisions on whether extracting teeth or not in case-specific scenarios.

Comparison of closed root planing with versus without concurrent doxycycline hyclate or clindamycin hydrochloride gel application for the treatment of periodontal disease in dogs

OBJECTIVE To compare improvements in values for periodontal disease indices in dogs following treatment with closed root planing (CRP) alone, CRP with concurrent 8.5% doxycycline hyclate gel application, and CRP with concurrent 2% clindamycin hydrochloride reverse-polymer hydrogel application. DESIGN Randomized, blinded, controlled clinical trial. ANIMALS 34 client-owned dogs with periodontal pockets measuring 3.5 to 5.5 mm deep. PROCEDURES Dogs were randomly assigned to receive 1 of 3 treatments: CRP alone (n = 10) or CRP plus 8.5% doxycycline hyclate (12) or 2% clindamycin hydrochloride (12) gel applied within the periodontal pockets. Indices of periodontal disease severity were recorded before and 12 weeks after treatment, and outcomes were compared among treatment groups. RESULTS Except for gingivitis index, no significant differences were identified among the 3 treatment groups in the amount of improvement observed in values for periodontal disease indices following treatment. A minor but clinically unimportant improvement in mean gingivitis index values was identified for dogs treated with CRP plus doxycycline gel, which differed significantly from improvements in the other 2 groups. Teeth that were initially more severely affected (pocket depths, 5.0 to 5.5 mm) had the greatest amount of improvement, whereas teeth with only mildly high initial pocket depths (3.5 to 4.0 mm) had less improvement. CONCLUSIONS AND CLINICAL RELEVANCE Overall, addition of doxycycline or clindamycin gel application to CRP for the treatment of periodontal disease in dogs yielded no clinically relevant benefit over CRP during the 12-week follow-up period.

Comparison of cone-beam computed tomography with bitewing radiography for detection of periodontal bone loss and assessment of effects of different voxel resolutions: an in vitro study

OBJECTIVE

The aim of the study was to compare intraoral radiographs and CBCT images for detection of horizontal periodontal bone loss, and to investigate the diagnostic effect of different voxel resolutions in CBCT imaging.

METHODS

A total of 240 sites with horizontal bone loss were measured on the buccal, lingual, mesial, and distal surfaces of 60 posterior teeth in four maxillary and six mandibular bones obtained from cadavers (dry skulls). Direct measurements on the dry skulls were accepted as the gold standard values. Measurements on CBCT images at two different voxel resolutions (0.250 and 0.160 mm³) and intraoral bitewing radiographs were compared with one another and with the gold standard values.

RESULTS

The measurements on the CBCT images at two voxel resolutions and bitewing radiographs did not differ significantly (p > 0.05) from the direct measurements on the dry skulls. No significant difference was found between the bitewing radiographs and CBCT images for measurements in the mesial and distal regions (p > 0.05). There was no significant difference between the measurements on the buccal and lingual surfaces at the two different voxel resolutions (p > 0.05).

CONCLUSIONS

CBCT scans are recommended for evaluation of buccal and lingual bone loss to avoid intraoral radiographs that exceed routine examination of interproximal alveolar bone loss. Furthermore, instead of basing the voxel size on the required CBCT scans, it is recommended to select the smallest possible field of view to reduce the dose of radiation.

Imaging of Odontogenic Infections

Odontogenic infections represent a common clinical problem in patients of all ages. The presence of teeth enables the direct spread of inflammatory products from dental caries, trauma, and/or periodontal disease into the maxilla and mandible. The radiographic changes seen depend on the type and duration of the inflammatory process and host body response. Imaging plays a central role in identifying the source of infection and the extent of the disease spread and in detecting any complications. Many different imaging modalities can be used. The radiographic features associated with acute and chronic inflammatory processes are discussed.

Optimizing the reconstruction filter in cone-beam CT to improve periodontal ligament space visualization: An in vitro study

Purpose

Evaluation of alveolar bone is important in the diagnosis of dental diseases. The periodontal ligament space is difficult to clearly depict in cone-beam computed tomography images because the reconstruction filter conditions during image processing cause image blurring, resulting in decreased spatial resolution. We examined different reconstruction filters to assess their ability to improve spatial resolution and allow for a clearer visualization of the periodontal ligament space.

Materials and Methods

Cone-beam computed tomography projections of 2 skull phantoms were reconstructed using 6 reconstruction conditions and then compared using the Thurstone paired comparison method. Physical evaluations, including the modulation transfer function and the Wiener spectrum, as well as an assessment of space visibility, were undertaken using experimental phantoms.

Results

Image reconstruction using a modified Shepp-Logan filter resulted in better sensory, physical, and quantitative evaluations. The reconstruction conditions substantially improved the spatial resolution and visualization of the periodontal ligament space. The difference in sensitivity was obtained by altering the reconstruction filter.

Conclusion

Modifying the characteristics of a reconstruction filter can generate significant improvement in assessments of the periodontal ligament space. A high-frequency enhancement filter improves the visualization of thin structures and will be useful when accurate assessment of the periodontal ligament space is necessary.

Comparison of periodontal evaluation by cone-beam computed tomography, and clinical and intraoral radiographic examinations

OBJECTIVES

Cone-beam computed tomography (CBCT) has been widely used in many fields of dentistry. However, little is known about the accuracy of CBCT for evaluation of periodontal status. The objective of this study was to compare and correlate periodontal assessments among CBCT, clinical attachment loss (CAL) measurement, and periapical (PA)/bitewing (BW) radiography.

METHODS

Eighty patients (28 males, 52 females; age range, 19-84 years) from the University of Texas School of Dentistry at Houston were evaluated retrospectively. Measurements were taken on the central incisors, canines, and first molars of the right maxilla and left mandible. CAL was extracted from periodontal charts. The radiographic distance from the cementum-enamel junction (CEJ) to the alveolar crest was measured for tooth mesial and distal sites on PA/BW and CBCT images using MiPacs software and Anatomage Invivo software, respectively. One-way ANOVA and Pearson analysis were performed for statistical analyses.

RESULTS

The CEJ-crest distances for CBCT, PA/BW, and CAL were 2.56 ± 0.12, 2.04 ± 0.12, and 2.08 ± 0.17 mm (mean ± SD), respectively. CBCT exhibited larger values than the other two methods (p < 0.05). There were highly significant positive correlations among CBCT, PA/BW, and CAL measurements at all examined sites (p < 0.001). The Pearson correlation coefficient was higher for CBCT with CAL relative to PA/BW with CAL, but the difference was not significant (r = 0.64 and r = 0.55, respectively, p > 0.05).

CONCLUSIONS

This study validates the suitability of CBCT for periodontal assessment. Further studies are necessary to optimize the measurement methodology with CBCT.

A Retrospective Analysis of Radiographic Jaw Findings in Young Women; Prevalence and Predictors

AIMS AND OBJECTIVES

To determine the prevalence and types of jaw pathologic findings as detected in panoramic radiographs of a sample of young women attending a teaching hospital in Al Madinah Al Munawarah, Saudi Arabia, and to determine the most important factors that predict the occurrence of jaw pathologic findings.

MATERIALS AND METHODS

The electronic clinical files of a representative sample of female patients who attended the outpatient dental clinics were retrieved. Patients were aged 18 to 25 years. Types of pathologic radiographic jaw findings and their prevalence were determined through screening of panoramic radiographs. Data were analyzed using the statistical analysis software [SPSS version 21 (IBM Corp.)]. Multiple linear regression was used to explore the significance of some types of dental lesions as predictor variables for the occurrence of jaw pathologic findings.

RESULTS

A total of 190 patients (mean age, 22.4 ± 2.46 years) were included in the study. Periapical lesions, retained roots, and alveolar bone loss were detected in 53.6%, 24.8%, and 17.4% of the participants, respectively. Other odontogenic abnormalities such as supernumerary and impacted teeth (6.4% and 33.7%, respectively) were also detected. Patients' age was found to be a good predictor for alveolar bone loss and number of periapical lesions (P ≤ 0.05).

CONCLUSIONS

A high prevalence of periapical lesions, retained roots, and alveolar bone loss was found among a sample of young female dental attendees, as shown by their panoramic radiographs. Further studies are needed to explore potential risk factors for such a noticeable trend of poor oral health, and the needed strategies to counteract this trend.

An endodontic conundrum: the association between pulpal infection and periodontal disease

This paper reviews the classification of periodontal-endodontic lesions and considers the pathways through which inflammatory lesions or bacteria may communicate between the pulp and the periodontium. Such communications have previously underpinned the classification of periodontal-endodontic lesions but a more up-to-date approach is to focus specifically on those lesions that originate concurrently as pulpal infection (and necrosis) and periodontal disease on the affected teeth. In doing so, both conventional periodontal and endodontic treatments are indicated for the affected teeth, although more complex management strategies may occasionally be indicated.

Risk factors for the progression of periodontal disease in a Greek adult population

AIM

The purpose of the present study was to investigate the progression risk factors of periodontal disease by individual characteristics at baseline in a Greek adult population.

METHODS

The study sample consisted of 854 individuals. All participants were clinically examined and answered questions regarding sex, smoking status, socioeconomic status, low educational level, frequency of dental follow up, and oral hygiene habits. Serum levels of disease markers were investigated, and attachment levels were clinically recorded. For the assessment of periodontal disease progression, additional clinical attachment loss (CAL) was used if one or more sites showed a 3 mm or more increase in probing attachment level over a 2-year period. Statistical analysis was performed by using a modified multiple Poisson's analysis model.

RESULTS

A total of 74% of the participants exhibited additional CAL over a 2-year period. Significant associations were observed between additional CAL and smoking (relative risk [RR] = 0.78, 95% confidence level [CI] = 0.65-0.92), attachment level of 5 mm or more at baseline (RR = 0.89, 95% CI = 0.75-1.05), educational level (RR = 0.90, 95% CI = 0.76-1.07), socioeconomic status (RR = 0.86, 95% CI = 0.59-1.14), and irregular dental follow up (RR = 1.23, 95% CI = 1.04-1.45).

CONCLUSIONS

Smoking, baseline attachment level of 5 mm or more, low educational level, low socioeconomic status, and irregular dental follow up could be considered risk factors for further CAL.

A six-site method for the evaluation of periodontal bone loss in cone-beam CT images

OBJECTIVES

In contrast to two-dimensional planar images, a measuring point is hardly repeatedly determined in a CBCT image when alveolar bone loss is assessed. Thus, the aim of the present study was to propose a six-site measuring method, which is closely related to anatomical structure, for the evaluation of alveolar bone loss in CBCT images.

METHODS

150 measuring points in 11 molars and 14 premolars from 6 patients (2 males and 4 females) were included. CBCT images of the teeth were acquired prior to periodontal surgery. Four observers measured the distances between cemento-enamel junctions and the apical bases of the periodontal bone defect at the mesio-buccal, mid-buccal, disto-buccal, mesio-lingual/palatal, mid-lingual/palatal and disto-lingual/palatal sites in CBCT images. Direct measurements of the six sites were correspondingly obtained in the subsequent periodontal surgeries. Differences between the distances measured in the CBCT images and during the surgery were analysed. Interobserver and intraobserver variances were tested.

RESULTS

No statistically significant difference was found between the surgical and CBCT measurements (p = 0.84). Diagnostic coincidence rates of four observers were 86.7%, 87.3%, 88.7% and 88.0%, respectively. The interobserver (p = 0.95) and intraobserver (p = 0.30) variances were not significant.

CONCLUSIONS

The six-site measuring method validated in the present study may be a useful three-dimensional measuring method for the evaluation of periodontal disease.

Evaluation of diagnostic accuracy of conventional and digital periapical radiography, panoramic radiography, and cone-beam computed tomography in the assessment of alveolar bone loss

Background:

To evaluate the diagnostic accuracy of different radiographic methods in the assessment of proximal alveolar bone loss (ABL).

Materials and Methods:

ABL, the distance between cement-enamel junction and alveolar bone crest, was measured in 70 mandibular human teeth – directly on the mandibles (control), using conventional periapical radiography with film holders (Rinn XCP and Han-Shin), digital periapical radiography with complementary metal-oxide semiconductor sensor, conventional panoramic, and cone-beam computed tomography (CBCT). Three programs were used to measure ABL on the images: Image tool 3.0 (University of Texas Health Sciences Center, San Antonio, Texas, USA), Kodak Imaging 6.1 (Kodak Dental Imaging 6.1, Carestream Health^®, Rochester, NY, USA), and i-CAT vision 1.6.20. Statistical analysis used ANOVA and Tukey's test at 5% significance level.

Results:

The tomographic images showed the highest means, whereas the lowest were found for periapical with Han-Shin. Controls differed from periapical with Han-Shin (P < 0.0001). CBCT differed from panoramic (P = 0.0130), periapical with Rinn XCP (P = 0.0066), periapical with Han-Shin (P < 0.0001), and digital periapical (P = 0.0027). Conventional periapicals with film holders differed from each other (P = 0.0007). Digital periapical differed from conventional periapical with Han-Shin (P = 0.0004).

Conclusions:

Conventional periapical with Han-Shin film holder was the only method that differed from the controls. CBCT had the closest means to the controls.