Oral Radiology最新文献

{"title":"Comparative analysis of clinical image evaluation charts for panoramic radiography.","authors":"Yeonhee Kim, Samsun Lee, Gyudong Jo, Ahyoung Kwon, Juhee Kang, Joeun Kim, Kyunghoe Huh, Wonjin Yi, Minsuk Heo, Soonchul Choi","doi":"10.1007/s11282-024-00765-3","DOIUrl":"10.1007/s11282-024-00765-3","url":null,"abstract":"<p><strong>Objective: </strong>To compare and analyze professional (P chart) and simple (S chart) clinical image evaluation charts for evaluating panoramic radiograph image quality.</p><p><strong>Methods: </strong>Ten evaluators assessed 285 clinical panoramic radiograph images. The evaluators were divided into oral and maxillofacial radiologists (OMFR, n = 5) and general dentist (dentists not specializing in oral and maxillofacial radiology, G, n = 5) groups. For image evaluation, P and S charts provided by the Korean Academy of Oral and Maxillofacial Radiology were used. Scores of items for each evaluation chart were used to compare the reliability, correlation, evaluation scores, evaluation time, and preference, and statistical analyses were performed using IBM SPSS Statistics.</p><p><strong>Results: </strong>The S chart showed similar levels of evaluation scores at shorter evaluation time, as compared to the P chart. In the results for each evaluation chart, all analyzed correlations were statistically significant. Total score, image density/contrast/sharpness, and overall image quality items showed a very high positive correlation in the P chart. While the overall range of correlation coefficients was relatively lower in the S chart than the P chart, the same items showed high correlation coefficients. In the preference evaluation, both the professional and generalist groups preferred the S chart.</p><p><strong>Conclusions: </strong>A comparative analysis with the P chart, revisions, and upgrades are needed for the S chart items that showed low correlations in this study, such as artifacts, coverage area, and patient movement.</p>","PeriodicalId":56103,"journal":{"name":"Oral Radiology","volume":" ","pages":"520-529"},"PeriodicalIF":1.6,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11379777/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141560456","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Accuracy of intraoral ultrasound to evaluate alveolar bone level: an ex vivo study in human cadavers","authors":"Claudiu Corbea, Lawrence H. Le, Neelambar R. Kaipatur, Mengxun Li, Kim Cuong Nguyen, Giseon Heo, Carlos Alberto Figueredo, Paul W. Major, Fabiana T. Almeida","doi":"10.1007/s11282-024-00773-3","DOIUrl":"https://doi.org/10.1007/s11282-024-00773-3","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Objectives</h3><p>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.</p><h3 data-test=\"abstract-sub-heading\">Methods</h3><p>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.</p><h3 data-test=\"abstract-sub-heading\">Results</h3><p>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).</p><h3 data-test=\"abstract-sub-heading\">Conclusion</h3><p>The study demonstrated that intraoral ultrasound is highly reliable and accurate compared to the µCT reference standard for evaluating facial alveolar bone height.</p>","PeriodicalId":56103,"journal":{"name":"Oral Radiology","volume":"42 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142225414","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A cone-beam computed tomography study of canalis sinuosus and its accessory canals in a South African population.","authors":"Michael A Beckenstrater, Mohamed Y Gamieldien, Chane Smit, Glynn D Buchanan","doi":"10.1007/s11282-024-00738-6","DOIUrl":"10.1007/s11282-024-00738-6","url":null,"abstract":"<p><strong>Objectives: </strong>Canalis sinuosus (CS) is a clinically relevant structure in the anterior maxilla. The present study aimed to determine the prevalence and distribution of CS and its accessory canals (ACs) in the South African population and describe its anatomical variations.</p><p><strong>Methods: </strong>In total, 500 cone-beam computed tomography (CBCT) scans of the anterior maxilla were assessed for prevalence, sidedness, diameter, and distribution of CS. The frequency, number, diameter, configuration, and point of termination of ACs were also recorded. Statistical analysis was performed using analysis of variance, Kruskal-Wallis, chi-squared, and Fisher Exact tests with P < 0.05.</p><p><strong>Results: </strong>CS was present in most cases (99.6%), and commonly occurred bilaterally (98.8%). The mean diameter of CS was 1.08 mm (range: 0.50 mm-2.39 mm). Sex, population group, and age had no significant effect on the prevalence or sidedness of CS. Additionally, 535 ACs were observed in 58.8% of the sample, with 42.9% of ACs found bilaterally and 57.1% unilaterally. The mean diameter of the ACs was 0.86 mm on the left and 0.87 mm on the right (range; 0.50 mm-1.52 mm). The majority of ACs maintained a straight vertical configuration (72.3%). ACs most commonly terminated in the anterior palatal region of the maxilla (57.2%). No significant differences were found in any groups mentioned (P > 0.05).</p><p><strong>Conclusions: </strong>A high prevalence of CS as well as ACs were observed in the sample population. Due to their clinical significance, surgical planning with the aid of high quality CBCT scans of the anterior maxilla is advisable.</p>","PeriodicalId":56103,"journal":{"name":"Oral Radiology","volume":" ","pages":"367-374"},"PeriodicalIF":2.2,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11180635/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139713452","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluation of the thickness of masticatory muscles in patients with chronic periodontitis by ultrasonography.","authors":"Berkhas Tumani Üstdal, Burcu Evlice, Damla Soydan Çabuk, Hazal Duyan Yüksel, İmran Güner Akgül, Bahar Alkaya, Gökçe Arçay","doi":"10.1007/s11282-024-00746-6","DOIUrl":"10.1007/s11282-024-00746-6","url":null,"abstract":"<p><strong>Objectives: </strong>Periodontitis is one of the most common chronic inflammatory diseases. It causes changes in the biting abilities of individuals. However, periodontal treatment has positive effects on masticatory function. The aim of this study is to determine the effect of periodontitis and periodontal treatment on masticatory abilities by measuring masseter and temporal muscle thicknesses with ultrasonography before and after periodontal treatment in chronic periodontitis patients.</p><p><strong>Methods: </strong>The patients included in the study were determined by clinical and radiological examination. The thickness of the masseter and temporal muscles of the patients were measured by ultrasonography. Periodontal measurements and treatments of the patients were completed by a single physician. IBM SPSS 20.0 (IBM Corp., Armonk, NY) statistical program was used for statistical analysis.</p><p><strong>Results: </strong>A statistically significant difference was found between the values of periodontal measurements before and after treatment (p<0.05). In the ultrasonography measurements of the thickness of masseter and anterior temporal muscles, a statistically significant increase was observed in both rest and contraction values at all time intervals (p<0.05). Muscle thicknesses of male patients were higher than female patients.</p><p><strong>Conclusions: </strong>Periodontitis negatively affects the masticatory performance of individuals. Chronic periodontitis patients should be referred for periodontal treatment without wasting time.</p>","PeriodicalId":56103,"journal":{"name":"Oral Radiology","volume":" ","pages":"402-408"},"PeriodicalIF":2.2,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140337766","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Artificial intelligence for caries detection: a novel diagnostic tool using deep learning algorithms.","authors":"Yiliang Liu, Kai Xia, Yueyan Cen, Sancong Ying, Zhihe Zhao","doi":"10.1007/s11282-024-00741-x","DOIUrl":"10.1007/s11282-024-00741-x","url":null,"abstract":"<p><strong>Objectives: </strong>The aim of this study was to develop an assessment tool for automatic detection of dental caries in periapical radiographs using convolutional neural network (CNN) architecture.</p><p><strong>Methods: </strong>A novel diagnostic model named ResNet + SAM was established using numerous periapical radiographs (4278 images) annotated by medical experts to automatically detect dental caries. The performance of the model was compared to the traditional CNNs (VGG19, ResNet-50), and the dentists. The Gradient-weighted Class Activation Mapping (Grad-CAM) technique shows the region of interest in the image for the CNNs.</p><p><strong>Results: </strong>ResNet + SAM demonstrated significantly improved performance compared to the modified ResNet-50 model, with an average F1 score of 0.886 (95% CI 0.855-0.918), accuracy of 0.885 (95% CI 0.862-0.901) and AUC of 0.954 (95% CI 0.924-0.980). The comparison between the performance of the model and the dentists revealed that the model achieved higher accuracy than that of the junior dentists. With the assist of the tool, the dentists achieved superior metrics with a mean F1 score of 0.827 and the interobserver agreement for dental caries is enhanced from 0.592/0.610 to 0.706/0.723.</p><p><strong>Conclusions: </strong>According to the results obtained from the experiments, the automatic assessment tool using the ResNet + SAM model shows remarkable performance and has excellent possibilities in identifying dental caries. The use of the assessment tool in clinical practice can be of great benefit as a clinical decision-making support in dentistry and reduce the workload of dentists.</p>","PeriodicalId":56103,"journal":{"name":"Oral Radiology","volume":" ","pages":"375-384"},"PeriodicalIF":2.2,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140159660","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Convolutional neural networks combined with classification algorithms for the diagnosis of periodontitis.","authors":"Fang Dai, Qiangdong Liu, Yuchen Guo, Ruixiang Xie, Jingting Wu, Tian Deng, Hongbiao Zhu, Libin Deng, Li Song","doi":"10.1007/s11282-024-00739-5","DOIUrl":"10.1007/s11282-024-00739-5","url":null,"abstract":"<p><strong>Objectives: </strong>We aim to develop a deep learning model based on a convolutional neural network (CNN) combined with a classification algorithm (CA) to assist dentists in quickly and accurately diagnosing the stage of periodontitis.</p><p><strong>Materials and methods: </strong>Periapical radiographs (PERs) and clinical data were collected. The CNNs including Alexnet, VGG16, and ResNet18 were trained on PER to establish the PER-CNN models for no periodontal bone loss (PBL) and PBL. The CAs including random forest (RF), support vector machine (SVM), naive Bayes (NB), logistic regression (LR), and k-nearest neighbor (KNN) were added to the PER-CNN model for control, stage I, stage II and stage III/IV periodontitis. Heat map was produced using a gradient-weighted class activation mapping method to visualize the regions of interest of the PER-Alexnet model. Clustering analysis was performed based on the ten PER-CNN scores and the clinical characteristics.</p><p><strong>Results: </strong>The accuracy of the PER-Alexnet and PER-VGG16 models with the higher performance was 0.872 and 0.853, respectively. The accuracy of the PER-Alexnet + RF model with the highest performance for control, stage I, stage II and stage III/IV was 0.968, 0.960, 0.835 and 0.842, respectively. Heat map showed that the regions of interest predicted by the model were periodontitis bone lesions. We found that age and smoking were significantly related to periodontitis based on the PER-Alexnet scores.</p><p><strong>Conclusion: </strong>The PER-Alexnet + RF model has reached high performance for whole-case periodontal diagnosis. The CNN models combined with CA can assist dentists in quickly and accurately diagnosing the stage of periodontitis.</p>","PeriodicalId":56103,"journal":{"name":"Oral Radiology","volume":" ","pages":"357-366"},"PeriodicalIF":2.2,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139934491","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Accessory lingual mental foramen: A case report of a rare anatomic variation.","authors":"Arjun Kumar Tallada, Junaid Ahmed, Nanditha Sujir, Nandita Shenoy, Shubham M Pawar, Archana Muralidharan, Sanjay Mallya","doi":"10.1007/s11282-024-00747-5","DOIUrl":"10.1007/s11282-024-00747-5","url":null,"abstract":"<p><strong>Introduction: </strong>The mandibular nerve and the mental foramen have occasionally shown variations in its anatomy. This report aims to present a case of lingual mental foramen recognised on three-dimensional cone beam computed tomographic imaging (CBCT).</p><p><strong>Case report: </strong>Routine Orthopantomogram (OPG) and CBCT images were evaluated to assess the status of impact third molars in a 31-year-old female who had visited the dental clinics in our institution. The OPG image failed to reveal any anatomic variation in the position of the mental foramen. On tracing the course of the mandibular canal in CBCT images, two foramina were traced at the region of premolar. One opened towards the buccal cortical plate at the normal position of the mental foramen and an accessory lingual mental foramen had an opening on the lingual cortical bone at the same level as the mental foramen.</p><p><strong>Conclusion: </strong>Understanding variations of the mental foramen is extremely essential in dentistry to carry out successful anaesthetic or surgical interventions and to avoid complications such as nerve damage or excessive bleeding.</p>","PeriodicalId":56103,"journal":{"name":"Oral Radiology","volume":" ","pages":"410-414"},"PeriodicalIF":1.6,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140208363","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Temporomandibular joint degenerative changes following mandibular fracture: a computed tomography-based study on the role of condylar involvement.","authors":"Chun-Lin Su, An-Chi Su, Chih-Chen Chang, Arthur Yen-Hung Lin, Chih-Hua Yeh","doi":"10.1007/s11282-024-00742-w","DOIUrl":"10.1007/s11282-024-00742-w","url":null,"abstract":"<p><strong>Objectives: </strong>This study assessed the incidence of postfracture radiological temporomandibular joint (TMJ) degeneration in patients with different types of mandibular fractures, focusing on the impact of condylar fractures.</p><p><strong>Methods: </strong>This retrospective review included patients diagnosed as having mandibular fractures from 2016 to 2020 who had undergone initial computed tomography (CT) and a follow-up CT scan at least 1-month postfracture. Patient demographics, fracture details, treatment methods, and radiological signs of TMJ degeneration on CT were analyzed to identify risk factors for postfracture TMJ degeneration, with a focus on condylar head fracture and non-head (condylar neck or base) fractures.</p><p><strong>Results: </strong>The study included 85 patients (mean age: 38.95 ± 17.64 years). The per-patient analysis indicated that the incidence of new radiologic TMJ degeneration on CT was significantly the highest (p < 0.001) in patients with condylar head fractures (90.91%), followed by those with non-head condylar fractures (57.14%), and those without condylar involvement (24.49%). The per-joint analysis indicated nearly inevitable degeneration (93.94%) in 33 TMJs with ipsilateral condylar head fractures. For the remaining 137 TMJs, multivariate logistic regression revealed that other patterns (ipsilateral non-head, contralateral, or both) of condylar fractures (odds ratio (OR) = 3.811, p = 0.007) and the need for open reduction and internal fixation (OR = 5.804, p = 0.005) significantly increased the risk of TMJ degeneration.</p><p><strong>Conclusions: </strong>Ipsilateral non-head condylar fractures and contralateral condylar fractures are associated with a high risk of postfracture TMJ degeneration. Indirect trauma plays a vital role in postfracture TMJ degeneration.</p>","PeriodicalId":56103,"journal":{"name":"Oral Radiology","volume":" ","pages":"385-393"},"PeriodicalIF":2.2,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139991969","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Accuracy of machine learning in the diagnosis of odontogenic cysts and tumors: a systematic review and meta-analysis.","authors":"Priyanshu Kumar Shrivastava, Shamimul Hasan, Laraib Abid, Ranjit Injety, Ayush Kumar Shrivastav, Deborah Sybil","doi":"10.1007/s11282-024-00745-7","DOIUrl":"10.1007/s11282-024-00745-7","url":null,"abstract":"<p><strong>Background: </strong>The recent impact of artificial intelligence in diagnostic services has been enormous. Machine learning tools offer an innovative alternative to diagnose cysts and tumors radiographically that pose certain challenges due to the near similar presentation, anatomical variations, and superimposition. It is crucial that the performance of these models is evaluated for their clinical applicability in diagnosing cysts and tumors.</p><p><strong>Methods: </strong>A comprehensive literature search was carried out on eminent databases for published studies between January 2015 and December 2022. Studies utilizing machine learning models in the diagnosis of odontogenic cysts or tumors using Orthopantomograms (OPG) or Cone Beam Computed Tomographic images (CBCT) were included. QUADAS-2 tool was used for the assessment of the risk of bias and applicability concerns. Meta-analysis was performed for studies reporting sufficient performance metrics, separately for OPG and CBCT.</p><p><strong>Results: </strong>16 studies were included for qualitative synthesis including a total of 10,872 odontogenic cysts and tumors. The sensitivity and specificity of machine learning in diagnosing cysts and tumors through OPG were 0.83 (95% CI 0.81-0.85) and 0.82 (95% CI 0.81-0.83) respectively. Studies utilizing CBCT noted a sensitivity of 0.88 (95% CI 0.87-0.88) and specificity of 0.88 (95% CI 0.87-0.89). Highest classification accuracy was 100%, noted for Support Vector Machine classifier.</p><p><strong>Conclusion: </strong>The results from the present review favoured machine learning models to be used as a clinical adjunct in the radiographic diagnosis of odontogenic cysts and tumors, provided they undergo robust training with a huge dataset. However, the arduous process, investment, and certain ethical concerns associated with the total dependence on technology must be taken into account. Standardized reporting of outcomes for diagnostic studies utilizing machine learning methods is recommended to ensure homogeneity in assessment criteria, facilitate comparison between different studies, and promote transparency in research findings.</p>","PeriodicalId":56103,"journal":{"name":"Oral Radiology","volume":" ","pages":"342-356"},"PeriodicalIF":1.6,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140295378","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prone position magnetic resonance imaging for the mandibular bone: enhancing image quality to perform texture analysis for medication-related osteonecrosis of the jaw and carcinoma of the lower gingiva","authors":"Takahiro Otani, Hirokazu Yoshida, Daichi Sugawara, Yu Mori, Naoko Mori","doi":"10.1007/s11282-024-00754-6","DOIUrl":"https://doi.org/10.1007/s11282-024-00754-6","url":null,"abstract":"","PeriodicalId":56103,"journal":{"name":"Oral Radiology","volume":"235 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140826980","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}