Do metal artifact reduction algorithms influence the detection of implant-related injuries to the inferior alveolar canal in CBCT images?

BACKGROUND: The routine application of dental implants for replacing missing teeth has revolutionized restorative and prosthetic dentistry. However, cone beam computed tomography (CBCT) evaluations of structures adjacent to the implants are limited by metal artifacts. There are several methods for reducing metal artifacts, but this remains a challenging task. This study aimed to examine the effectiveness of metal artifact reduction (MAR) algorithms in identifying injuries of implants to the inferior alveolar canal in CBCT images. METHOD: In this in vitro study, mono-cortical bone windows were created and the inferior alveolar canal was revealed. Using 36 implants, pilot drill and penetration damage of the implant tip into the canal was simulated and compared to the control implants with distance from the canal. CBCT images were evaluated by four experienced observers with and without the MAR algorithm and compared to direct vision as the gold standard. The values of accuracy, sensitivity, and specificity were obtained and compared by receiver operating characteristic (ROC) curve (α = 0.05). RESULT: The area under the ROC curve values for detection of pilot drill injuries varied between 0.840-0.917 and 0.639-0.854 in the active and inactive MAR conditions, respectively. The increase in ROC area was only significant for one of the observers (P = 0.010). For diagnosing penetrative injuries, the area under the ROC curve values was between 0.990-1.000 and 0.722-1.000 in the active and inactive MAR conditions, respectively. The improvement of ROC curve values in active MAR mode was only significant for one of the observers (P = 0.006). CONCLUSION: Activation of MAR improved the diagnostic values of CBCT images in detecting both types of implant-related injuries to the inferior alveolar canal. However, for most observers, this increase was not statistically significant.

Evaluation of accuracy of deep learning and conventional neural network algorithms in detection of dental implant type using intraoral radiographic images: A systematic review and meta-analysis.

STATEMENT OF PROBLEM: With the growing importance of implant brand detection in clinical practice, the accuracy of machine learning algorithms in implant brand detection has become a subject of research interest. Recent studies have shown promising results for the use of machine learning in implant brand detection. However, despite these promising findings, a comprehensive evaluation of the accuracy of machine learning in implant brand detection is needed. PURPOSE: The purpose of this systematic review and meta-analysis was to assess the accuracy, sensitivity, and specificity of deep learning algorithms in implant brand detection using 2-dimensional images such as from periapical or panoramic radiographs. MATERIAL AND METHODS: Electronic searches were conducted in PubMed, Embase, Scopus, Scopus Secondary, and Web of Science databases. Studies that met the inclusion criteria were assessed for quality using the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool. Meta-analyses were performed using the random-effects model to estimate the pooled performance measures and the 95% confidence intervals (CIs) using STATA v.17. RESULTS: Thirteen studies were selected for the systematic review, and 3 were used in the meta-analysis. The meta-analysis of the studies found that the overall accuracy of CNN algorithms in detecting dental implants in radiographic images was 95.63%, with a sensitivity of 94.55% and a specificity of 97.91%. The highest reported accuracy was 99.08% for CNN Multitask ResNet152 algorithm, and sensitivity and specificity were 100.00% and 98.70% respectively for the deep CNN (Neuro-T version 2.0.1) algorithm with the Straumann SLActive BLT implant brand. All studies had a low risk of bias. CONCLUSIONS: The highest accuracy and sensitivity were reported in studies using CNN Multitask ResNet152 and deep CNN (Neuro-T version 2.0.1) algorithms.

Long-Term Clinical Outcomes of Single Crowns or Short Fixed Partial Dentures Supported by Short (≤6 mm) Dental Implants: A Systematic Review.

Long-term clinical outcomes of short dental implants (≤6 mm) supporting single crowns or short fixed partial dentures have been reported differently in different studies and need more clarification. This systematic study evaluated the rate of bone loss (BL), the durability of implants equal to or shorter than 6 mm supporting single crowns or short fixed partial dentures, and prosthetic-related side effects during 5 years of follow-up. Five databases (PubMed, MEDLINE, Scopus, Google Scholar, and Cochrane) were electronically and manually searched for longitudinal studies with a follow-up period of 5 years or more until January 2023. The study question was, "Does the implant equal to or shorter than 6 mm affect BL and survival rate of the implant-supported prosthesis after 5 years of follow-up?". From 752 identified articles, nine studies were selected for further evaluation. After 5 years of follow-up, most studies had more than 90% survival rate and the maximum BL was 0.54 mm. Still, in internal and external connections, these changes were not substantial. For example, screw loosening was the most common problem with implanted prostheses. Implants of 6 mm or shorter are a suitable treatment option in atrophic ridges with good durability and fewer side effects during a follow-up period of more than 5 years.

Soft tissue simulant materials in X-ray-based imaging in dentomaxillofacial radiology: a scoping review.

INTRODUCTION: In in-vitro dental radiographic research, simulation of soft tissue is required to replicate the clinical condition as close as possible. This study aimed to find out which soft tissue simulation material have been studied to use in dentomaxillofacial radiology and showed similarity in radiodensity to the soft tissues of the maxillofacial region. METHODS: In this scoping review, Web of Science, Embase, Scopus, Google scholar and PubMed databases were searched on April 9, 2023, considering the following PICOS: Population: soft tissue simulants, Intervention: X-ray-based imaging, Comparison: -, Outcome: properties of the soft tissue simulants, Study design: in-vitro studies. Screening, study selection, and data extraction were performed by two independent researchers. A third team member was consulted in the case of disagreement. Quality assessment of the included studies was made using Quality Assessment Tool For In-Vitro Studies (QUIN Tool). RESULTS: Of the initial 1172 articles retrieved in the database search, 13 studies were included in the review. Seven studies had a low risk of bias. In 8 studies, computed tomography (CT) or cone beam computed tomography (CBCT), in 4 studies intraoral radiography, and in 2 studies panoramic radiography was used (one study has used CT/CBCT and panoramic radiography). The studies varied in the radiographic modality, acquisition parameters, selected outcomes, and gold standard. In the majority of the studies (n = 10, 77%), acrylic resin derivatives were used in the soft tissue simulant formula alone or as a major component. Wax was used in the simulant material in 8 studies (62%). In addition, in 3 studies (23%) ice/water was used as the main simulant. CONCLUSION: Ballistic gelatin, expanded 2-cm thick polystyrene with or without 1-cm utility wax, and 0.5 cm of acrylic resin were shown to have a radiographic density similar to soft tissue in standardized studies employing CBCT scanning. For intraoral radiographs, using self-polymerizing acrylic resin, utility wax, and wood, as well as a polymethylmethacrylate box filled with water in thicknesses ranging from 4 to 45 mm, provides suitable radiographic contrast. However, for 4 and 8 mm of wax and 4 mm of water, the radiographic contrast is not appropriate. In addition, 13-17 mm wax and 14.5 mm acrylic resin showed acceptable soft tissue densities in intraoral radiography. Further studies using different imaging modalities with standardized conditions and objective metrics are required to confirm the most appropriate soft tissue simulant material for in-vitro dental radiographic research.

Stress Analysis of Endodontically Treated Tooth-Implant Different Connectors Designs in Maxillary Posterior Region: A Finite Element Analysis.

OBJECTIVES: Using finite element analysis (FEA), this study aimed to determine the effect of nonrigid connectors (NRCs) and their position on the success of tooth and implant-supported fixed prostheses in the maxillary posterior region. MATERIALS AND METHODS: Three three-dimensional FEA models were designed, presuming maxillary second premolar and first molar to be extracted. Implant (replacing first molar), abutment, bone (spongious and cortical), first premolar (containing dentin, root cement, gutta-percha, and casting post and core), periodontal ligament, and three three-unit cemented porcelain-fused-to-metal prostheses (a rigid one and two nonrigid) were modeled. The NRC was once on the tooth side and once on the implant side. The prostheses were loaded twice. The first molar (180 N) and premolars (120 N) teeth were subjected to progressive vertical and oblique (12-degree) loads, and maximum von Mises stress and strain in teeth and connectors were calculated for each model. RESULTS: The findings of the current study showed evidence that tooth-implant design with an NRC has significantly increased the average stress in the tooth. The average stress in dentin was 769.02 for the mesial connector and 766.95 for the distal connector, and this was only 731.59 for rigid connector. Furthermore, it was observed that rigid connector has considerably minimized the stress within the tooth-implant-supported fixed partial denture. The average stress for the crown and metal frame is 346.22 and 526.41 in rigid connector, while it is 1,172.9 and 2,050.9 for the nonrigid mesial connector. CONCLUSION: Although distal NRC was more efficient than mesial NRC, using NRC will only reduce the stress applied to cortical bone and is not recommended in the posterior region of the maxilla.

Protective Role of Angiotensin II Type 1 Receptor Blocker on Short Time Effect of Oleic Acid Induced Lung and Kidney Injury.

BACKGROUNDS: Acute respiratory distress syndrome (ARDS) causes high mortality rate in clinic, and the pathogenesis of this syndrome may interact with renin angiotensin system (RAS) components. The main objective of this study was to determine the protective role of AT1R antagonist (losartan) on oleic acid (OA) induced ARDS and kidney injury. METHODS: The animal model of ARDS was performed by intravenous administration of 250 µl/kg oleic acid (OA). Male and female rats were subjected to received intravenously vehicle (saline, groups 1 and 4), OA (groups 2 and 5), or losartan (10 mg/kg) plus OA (groups 3 and 6), and six hour later, the measurements were performed. RESULTS: Co-treatment of OA and losartan increased the serum levels of blood urea nitrogen significantly (P < 0.05) and creatinine insignificantly in both gender. However, the OA induced kidney damage was decreased by losartan significantly in male (P < 0.05) and insignificantly in female rats. In addition, co-treatment of OA and losartan decreased lung water content significantly in male rats (P < 0.05). Based on tissue staining, no significant difference in lung tissue damages were observed between the groups, however some exudate were observed in lung male rats treated with OA alone which were abolished by losartan. CONCLUSIONS: Losartan may protect the kidney and lung against OA induced tissue injury in male rats. This protective action is not certain in female rats.

Science Mapping Analysis of COVID-19 Articles Published in Dental Journals.

The Coronavirus disease 2019 (COVID-19) pandemic is an ongoing global health crisis with unmatched outcomes and effects. This pandemic has caused an infodemic of article publication in scientific journals. Dental journals have been active in the publication of COVID-19 related articles from the beginning of the pandemic. In this cross-sectional survey, we present an analysis of the scientific output of dental journals on COVID-19. The PubMed COVID-19 database was searched with the "Dental Journals" filter. Data including journal name, country, month of publication and number of citations were recorded. Science mapping analysis of the most used keywords was also performed. The search retrieved a total of 659 articles, of which 28 were excluded. Oral Diseases has published the most COVID-19 articles (15.1%), followed by the British Journal of Oral and Maxillofacial Surgery (8.6%) and the Journal of Dental Education (7.9%). Most of the articles were from researchers from the United States (168), United Kingdom (120) and Brazil (83). The number of citations of the published articles ranged from 0 to 406, with most articles (64.2%) having no citations. Science Mapping analysis revealed that the most used keywords were coronavirus infections, pandemics and humans. The dental community has been active in the publication of COVID-19 articles from the beginning of the pandemic. The papers published by dental journals explore issues such as the management of clinical practices during the outbreak, infection control in the dental setting, signs and symptoms of COVID-19 affecting the oral cavity, and the impact of the COVID-19 pandemic on educational and clinical programs.