Dento maxillo facial radiology最新文献_第6页

Automatic classification and segmentation of multiclass jaw lesions in cone-beam CT using deep learning. 利用深度学习对锥形束计算机断层扫描中的多类颌骨病变进行自动分类和分割。

IF 2.9 2区医学

Dento maxillo facial radiology Pub Date : 2024-10-01 DOI: 10.1093/dmfr/twae028

Wei Liu, Xiang Li, Chang Liu, Ge Gao, Yutao Xiong, Tao Zhu, Wei Zeng, Jixiang Guo, Wei Tang

{"title":"Automatic classification and segmentation of multiclass jaw lesions in cone-beam CT using deep learning.","authors":"Wei Liu, Xiang Li, Chang Liu, Ge Gao, Yutao Xiong, Tao Zhu, Wei Zeng, Jixiang Guo, Wei Tang","doi":"10.1093/dmfr/twae028","DOIUrl":"10.1093/dmfr/twae028","url":null,"abstract":"Objectives: To develop and validate a modified deep learning (DL) model based on nnU-Net for classifying and segmenting five-class jaw lesions using cone-beam CT (CBCT).Methods: A total of 368 CBCT scans (37 168 slices) were used to train a multi-class segmentation model. The data underwent manual annotation by two oral and maxillofacial surgeons (OMSs) to serve as ground truth. Sensitivity, specificity, precision, F1-score, and accuracy were used to evaluate the classification ability of the model and doctors, with or without artificial intelligence assistance. The dice similarity coefficient (DSC), average symmetric surface distance (ASSD), and segmentation time were used to evaluate the segmentation effect of the model.Results: The model achieved the dual task of classifying and segmenting jaw lesions in CBCT. For classification, the sensitivity, specificity, precision, and accuracy of the model were 0.871, 0.974, 0.874, and 0.891, respectively, surpassing oral and maxillofacial radiologists (OMFRs) and OMSs, approaching the specialist. With the model's assistance, the classification performance of OMFRs and OMSs improved, particularly for odontogenic keratocyst (OKC) and ameloblastoma (AM), with F1-score improvements ranging from 6.2% to 12.7%. For segmentation, the DSC was 87.2% and the ASSD was 1.359 mm. The model's average segmentation time was 40 ± 9.9 s, contrasting with 25 ± 7.2 min for OMSs.Conclusions: The proposed DL model accurately and efficiently classified and segmented five classes of jaw lesions using CBCT. In addition, it could assist doctors in improving classification accuracy and segmentation efficiency, particularly in distinguishing confusing lesions (eg, AM and OKC).","PeriodicalId":11261,"journal":{"name":"Dento maxillo facial radiology","volume":" ","pages":"439-446"},"PeriodicalIF":2.9,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141466868","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Enhanced multistage deep learning for diagnosing anterior disc displacement in the temporomandibular joint using MRI. 利用磁共振成像诊断颞下颌关节前椎间盘移位的增强型多级深度学习。

IF 2.9 2区医学

Dento maxillo facial radiology Pub Date : 2024-10-01 DOI: 10.1093/dmfr/twae033

Chang-Ki Min, Won Jung, Subin Joo

{"title":"Enhanced multistage deep learning for diagnosing anterior disc displacement in the temporomandibular joint using MRI.","authors":"Chang-Ki Min, Won Jung, Subin Joo","doi":"10.1093/dmfr/twae033","DOIUrl":"10.1093/dmfr/twae033","url":null,"abstract":"Objectives: This study aimed to propose a new method for the automatic diagnosis of anterior disc displacement of the temporomandibular joint (TMJ) using MRI and deep learning. By using a multistage approach, the factors affecting the final result can be easily identified and improved.Methods: This study introduces a multistage automatic diagnostic technique using deep learning. This process involves segmenting the target from MR images, extracting distance parameters, and classifying the diagnosis into 3 classes. MRI exams of 368 TMJs from 204 patients were evaluated for anterior disc displacement. In the first stage, 5 algorithms were used for the semantic segmentation of the disc and condyle. In the second stage, 54 distance parameters were extracted from the segments. In the third stage, a rule-based decision model was developed to link the parameters with the expert diagnosis results.Results: In the first stage, DeepLabV3+ showed the best result (95% Hausdorff distance, Dice coefficient, and sensitivity of 6.47 ± 7.22, 0.84 ± 0.07, and 0.84 ± 0.09, respectively). This study used the original MRI exams as input without preprocessing and showed high segmentation performance compared with that of previous studies. In the third stage, the combination of SegNet and a random forest model yielded an accuracy of 0.89 ± 0.06.Conclusions: An algorithm was developed to automatically diagnose TMJ-anterior disc displacement using MRI. Through a multistage approach, this algorithm facilitated the improvement of results and demonstrated high accuracy from more complex inputs. Furthermore, existing radiological knowledge was applied and validated.","PeriodicalId":11261,"journal":{"name":"Dento maxillo facial radiology","volume":" ","pages":"488-496"},"PeriodicalIF":2.9,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141723233","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The diagnostic value of prostate-specific membrane antigen PET-CT in differentiating medication-related osteonecrosis of the jaw and metastasis to the jawbone. PSMA PET-CT 在鉴别药物性颌骨骨坏死和颌骨转移方面的诊断价值。

IF 2.9 2区医学

Dento maxillo facial radiology Pub Date : 2024-10-01 DOI: 10.1093/dmfr/twae034

Karin Kur, Erofili Papadopoulou, Meital Nidam, Michal Fertouk, Omer Binyamini, Silvina Friedlander Barenboim, Towy Sorel Lazarovitci, Liran Domachevsky, Noam Yarom

{"title":"The diagnostic value of prostate-specific membrane antigen PET-CT in differentiating medication-related osteonecrosis of the jaw and metastasis to the jawbone.","authors":"Karin Kur, Erofili Papadopoulou, Meital Nidam, Michal Fertouk, Omer Binyamini, Silvina Friedlander Barenboim, Towy Sorel Lazarovitci, Liran Domachevsky, Noam Yarom","doi":"10.1093/dmfr/twae034","DOIUrl":"10.1093/dmfr/twae034","url":null,"abstract":"Introduction: Medication-related osteonecrosis of the jaw (MRONJ) and jaw metastasis might share similar clinical and radiographic characteristics, with both demonstrating F-18 fluorodeoxyglucose (FDG) uptake on PET-CT. Prostate-specific membrane antigen (PSMA) PET-CT is used to demonstrate prostate cancer dissemination. Unlike FDG PET-CT, PSMA PET-CT is more specific to cancer than to inflammation. Therefore, we hypothesized that it might be a useful tool to differentiate between MRONJ and jaw metastasis.Methods: All files of prostate cancer patients diagnosed with MRONJ and with available PSMA PET-CT studies were retrieved. A similar number of solid cancer patients with MRONJ and with available FDG PET-CT studies served as a second study group. All studies were reviewed by 2 blinded co-investigators (L.D. and M.F.).Results: Seventeen patients who underwent PSMA PET-CT (24 studies) and 15 patients who underwent FDG PET-CT (29 studies) met the inclusion criteria. All patients with FDG PET-CT studies showed pathological uptake at the site of MRONJ in at least one of their studies versus only 23.5% of patients in the PSMA PET-CT group (P < .001). FDG PET-CT studies showed pathological uptake in 89.6% of the studies compared with only 20.8% in the PSMA PET-CT group (P < .001). The mean standardized uptake value (SUVmax) and the mean uptake volume in the FDG PET-CT group were significantly higher compared with the PSMA PET-CT group (P < .001 and P < .005, respectively). The interclass correlation coefficient for all parameters was higher than 0.95.Conclusions: PSMA PET-CT is useful to differentiate between MRONJ and jaw metastasis.","PeriodicalId":11261,"journal":{"name":"Dento maxillo facial radiology","volume":" ","pages":"497-500"},"PeriodicalIF":2.9,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141859319","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Hypervigilance to pain and sleep quality are confounding variables in the infrared thermography examination of the temporomandibular joint and temporal and masseter muscles. 对疼痛的过度警觉和睡眠质量是颞下颌关节、颞肌和颌下肌红外热成像检查的干扰变量。

IF 2.9 2区医学

Dento maxillo facial radiology Pub Date : 2024-10-01 DOI: 10.1093/dmfr/twae032

Erasmo Freitas de Souza Junior, Camila Maia Vieira Pereira, Jussara da Silva Barbosa, Maria Jacinta Arêa Leão Lopes Araújo Arruda, Daniela Pita de Melo, Patrícia Meira Bento

{"title":"Hypervigilance to pain and sleep quality are confounding variables in the infrared thermography examination of the temporomandibular joint and temporal and masseter muscles.","authors":"Erasmo Freitas de Souza Junior, Camila Maia Vieira Pereira, Jussara da Silva Barbosa, Maria Jacinta Arêa Leão Lopes Araújo Arruda, Daniela Pita de Melo, Patrícia Meira Bento","doi":"10.1093/dmfr/twae032","DOIUrl":"10.1093/dmfr/twae032","url":null,"abstract":"Objectives: Verify whether hypervigilance to pain (HP) and sleep quality (SQ) are confounding variables in the infrared thermography (IT) examination of the temporomandibular joint and temporal and masseter muscles.Methods: A cross-sectional and analytical study was conducted, collecting HP and SQ data from 80 participants without temporomandibular disorders (TMD), performing their IT and another 40 participants with TMD. For the selection of participants with and without TMD, the TMD Pain Screener questionnaire and axis I of the Diagnostic Criteria for Temporomandibular Disorders were applied. SQ was verified using the Pittsburgh Sleep Quality Index (PSQI) questionnaire. For the HP assessment the Pain Vigilance and Awareness Questionnaire (PVAQ) was applied. And the IT was performed through a FLIR infrared sensor camera, model T650 Infrared.Results: No significant correlations were found between SQ and the temperatures of the areas of interest (P > .05), and regarding HP, a statistically significant positive correlation was found with the dimensionless (ρ = 0.289) and non-dimensionless (ρ = 0.223) asymmetries of temporal muscle temperatures. In the temperature comparisons between the participants without TMD and the participants with TMD, significant differences were found (P < .05), also when the group without TMD was controlled according to both HP and SQ (P < .05), with higher temperatures found in the TMD group.Conclusions: HP and SQ can be considered confounding variables in IT examination of the temporomandibular region.","PeriodicalId":11261,"journal":{"name":"Dento maxillo facial radiology","volume":" ","pages":"478-487"},"PeriodicalIF":2.9,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141589906","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

New scenarios for training in oral radiology: clinical performance and predoctoral students' perception of 3D-printed mannequins. 口腔放射学培训的新场景：三维打印人体模型的临床表现和博士预科生的感知。

IF 2.9 2区医学

Dento maxillo facial radiology Pub Date : 2024-10-01 DOI: 10.1093/dmfr/twae035

Wislem Miranda de Mello, Vinícius Dutra, Lucas Machado Maracci, Gleica Dal' Ongaro Savegnago, Geraldo Fagundes Serpa, Gabriela Salatino Liedke

{"title":"New scenarios for training in oral radiology: clinical performance and predoctoral students' perception of 3D-printed mannequins.","authors":"Wislem Miranda de Mello, Vinícius Dutra, Lucas Machado Maracci, Gleica Dal' Ongaro Savegnago, Geraldo Fagundes Serpa, Gabriela Salatino Liedke","doi":"10.1093/dmfr/twae035","DOIUrl":"10.1093/dmfr/twae035","url":null,"abstract":"Objectives: This study aimed to evaluate the impact of 3D-printed mannequins on the training of predoctoral students.Methods: Two 3D-printed training models were developed: a traditional model that simulates a sound adult patient and a customized model with pathological and physiological changes (impacted third molar and edentulous region). Students accomplished their pre-clinical training divided into a control group (CG, n = 23), which had access to the traditional model, and a test group (TG, n = 20), which had access to both models. Afterward, they performed a full mouth series on patients and filled out a perception questionnaire. Radiographs were evaluated for technical parameters. Descriptive statistics and the Mann-Whitney test were used to compare the groups.Results: Students provided positive feedback regarding the use of 3D printing. The TG reported a more realistic training experience than the CG (P = .037). Both groups demonstrated good clinical performance (CG = 7.41; TG = 7.52), and no significant differences were observed between them.Conclusions: 3D printing is an option for producing simulators for pre-clinical training in Oral Radiology, reducing student stress and increasing confidence during clinical care.","PeriodicalId":11261,"journal":{"name":"Dento maxillo facial radiology","volume":" ","pages":"501-508"},"PeriodicalIF":2.9,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141632904","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

In vitro evaluation of the accuracy of electronic apex locators and cone-beam CT in the detection of oblique root fractures. 体外评估电子牙尖定位仪和锥形束计算机断层扫描在检测斜牙根骨折方面的准确性。

IF 2.9 2区医学

Dento maxillo facial radiology Pub Date : 2024-10-01 DOI: 10.1093/dmfr/twae037

Simay Koç, Hatice Harorlı, Alper Kuştarcı

{"title":"In vitro evaluation of the accuracy of electronic apex locators and cone-beam CT in the detection of oblique root fractures.","authors":"Simay Koç, Hatice Harorlı, Alper Kuştarcı","doi":"10.1093/dmfr/twae037","DOIUrl":"10.1093/dmfr/twae037","url":null,"abstract":"Objectives: This study aimed to compare the accuracy of cone-beam CT (CBCT) scanning and 3 different electronic apex locators (EALs) in the detection of simulated oblique root fractures (ORF) in different localizations.Methods: The study utilised a total of 80 human maxillary incisors, which were categorised into two groups based on the location of the ORF (apical and middle third of the root) formed on the buccal side of the root surface. The measurement of the distance between the incisal edge and the intersection of the ORF with the root canal was conducted using a stereomicroscope. This measurement is referred to as the actual working length (AWL). Additionally, three EALs-Dentaport ZX, EndoRadar Pro, and Propex II-were utilised to determine the electronic working length (EWL). Furthermore, CBCT images were employed to assess the distance, known as the CBCT working length (CWL). The differences were determined by subtracting AWL from EWL and CWL.Results: Based on the accuracy of the devices, there were no significant differences observed among Dentaport ZX, EndoRadar, Propex II, and CBCT measures in both the apical and middle third ORF groups, within the acceptable range of 0.5 and 1 mm.Conclusions: The accuracy of Dentaport ZX, Propex II, and CBCT was higher in the middle third ORF group compared to the apical third ORF group, with a tolerance of 0.5 mm. However, there were no significant differences seen among the devices.","PeriodicalId":11261,"journal":{"name":"Dento maxillo facial radiology","volume":" ","pages":"509-514"},"PeriodicalIF":2.9,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141747727","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An artificial intelligence grading system of apical periodontitis in cone-beam computed tomography data. 锥束计算机断层扫描数据中根尖牙周炎的人工智能分级系统。

IF 2.9 2区医学

Dento maxillo facial radiology Pub Date : 2024-10-01 DOI: 10.1093/dmfr/twae029

Tianyin Zhao, Huili Wu, Diya Leng, Enhui Yao, Shuyun Gu, Minhui Yao, Qinyu Zhang, Tong Wang, Daming Wu, Lizhe Xie

{"title":"An artificial intelligence grading system of apical periodontitis in cone-beam computed tomography data.","authors":"Tianyin Zhao, Huili Wu, Diya Leng, Enhui Yao, Shuyun Gu, Minhui Yao, Qinyu Zhang, Tong Wang, Daming Wu, Lizhe Xie","doi":"10.1093/dmfr/twae029","DOIUrl":"10.1093/dmfr/twae029","url":null,"abstract":"Objectives: In order to assist junior doctors in better diagnosing apical periodontitis (AP), an artificial intelligence AP grading system was developed based on deep learning (DL) and its reliability and accuracy were evaluated.Methods: One hundred and twenty cone-beam computed tomography (CBCT) images were selected to construct a classification dataset with four categories, which were divided by CBCT periapical index (CBCTPAI), including normal periapical tissue, CBCTPAI 1-2, CBCTPAI 3-5, and young permanent teeth. Three classic algorithms (ResNet50/101/152) as well as one self-invented algorithm (PAINet) were compared with each other. PAINet were also compared with two recent Transformer-based models and three attention models. Their performance was evaluated by accuracy, precision, recall, balanced F score (F1-score), and the area under the macro-average receiver operating curve (AUC). Reliability was evaluated by Cohen's kappa to compare the consistency of model predicted labels with expert opinions.Results: PAINet performed best among the four algorithms. The accuracy, precision, recall, F1-score, and AUC on the test set were 0.9333, 0.9415, 0.9333, 0.9336, and 0.9972, respectively. Cohen's kappa was 0.911, which represented almost perfect consistency.Conclusions: PAINet can accurately distinguish between normal periapical tissues, CBCTPAI 1-2, CBCTPAI 3-5, and young permanent teeth. Its results were highly consistent with expert opinions. It can help junior doctors diagnose and score AP, reducing the burden. It can also be promoted in areas where experts are lacking to provide professional diagnostic opinions.","PeriodicalId":11261,"journal":{"name":"Dento maxillo facial radiology","volume":" ","pages":"447-458"},"PeriodicalIF":2.9,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141497424","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Automatic deep learning detection of overhanging restorations in bitewing radiographs. 深度学习自动检测咬翼X光片中的悬垂修复体。

IF 2.9 2区医学

Dento maxillo facial radiology Pub Date : 2024-10-01 DOI: 10.1093/dmfr/twae036

Guldane Magat, Ali Altındag, Fatma Pertek Hatipoglu, Omer Hatipoglu, İbrahim Sevki Bayrakdar, Ozer Celik, Kaan Orhan

{"title":"Automatic deep learning detection of overhanging restorations in bitewing radiographs.","authors":"Guldane Magat, Ali Altındag, Fatma Pertek Hatipoglu, Omer Hatipoglu, İbrahim Sevki Bayrakdar, Ozer Celik, Kaan Orhan","doi":"10.1093/dmfr/twae036","DOIUrl":"10.1093/dmfr/twae036","url":null,"abstract":"Objectives: This study aimed to assess the effectiveness of deep convolutional neural network (CNN) algorithms for the detecting and segmentation of overhanging dental restorations in bitewing radiographs.Methods: A total of 1160 anonymized bitewing radiographs were used to progress the artificial intelligence (AI) system for the detection and segmentation of overhanging restorations. The data were then divided into three groups: 80% for training (930 images, 2399 labels), 10% for validation (115 images, 273 labels), and 10% for testing (115 images, 306 labels). A CNN model known as You Only Look Once (YOLOv5) was trained to detect overhanging restorations in bitewing radiographs. After utilizing the remaining 115 radiographs to evaluate the efficacy of the proposed CNN model, the accuracy, sensitivity, precision, F1 score, and area under the receiver operating characteristic curve (AUC) were computed.Results: The model demonstrated a precision of 90.9%, a sensitivity of 85.3%, and an F1 score of 88.0%. Furthermore, the model achieved an AUC of 0.859 on the receiver operating characteristic (ROC) curve. The mean average precision (mAP) at an intersection over a union (IoU) threshold of 0.5 was notably high at 0.87.Conclusions: The findings suggest that deep CNN algorithms are highly effective in the detection and diagnosis of overhanging dental restorations in bitewing radiographs. The high levels of precision, sensitivity, and F1 score, along with the significant AUC and mAP values, underscore the potential of these advanced deep learning techniques in revolutionizing dental diagnostic procedures.","PeriodicalId":11261,"journal":{"name":"Dento maxillo facial radiology","volume":" ","pages":"468-477"},"PeriodicalIF":2.9,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11440037/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141723287","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Influence of examiner calibration on clinical and MRI diagnosis of temporomandibular joint disc displacement: a systematic review and meta-analysis. 检查者校准对颞下颌关节椎间盘移位的临床和 mri 诊断的影响：系统回顾和荟萃分析。

IF 2.9 2区医学

Dento maxillo facial radiology Pub Date : 2024-09-01 DOI: 10.1093/dmfr/twae027

Lucas Machado Maracci, Gleica Dal Ongaro Savegnago, Raquel Pippi Antoniazzi, Mariana Marquezan, Tatiana Bernardon Silva, Gabriela Salatino Liedke

{"title":"Influence of examiner calibration on clinical and MRI diagnosis of temporomandibular joint disc displacement: a systematic review and meta-analysis.","authors":"Lucas Machado Maracci, Gleica Dal Ongaro Savegnago, Raquel Pippi Antoniazzi, Mariana Marquezan, Tatiana Bernardon Silva, Gabriela Salatino Liedke","doi":"10.1093/dmfr/twae027","DOIUrl":"10.1093/dmfr/twae027","url":null,"abstract":"Objectives: This study aimed to verify the accuracy of clinical protocols for the diagnosis of disc displacement (DD) compared with MRI, considering examiners' calibration.Methods: PubMed, Cochrane (Central), Scopus, Web of Science, LILACS, Embase, Science Direct, Google Scholar, and DANS EASY Archive databases were searched. Two reviewers independently screened and selected the studies. A meta-analysis was conducted using the R Statistical software. Results are shown using sensitivity and specificity, and 95% confidence intervals.Results: Of the 20 studies included in the systematic review, only three were classified as low risk of bias. Seventeen studies were included in the meta-analysis. Compared to MRI, clinical protocols showed overall sensitivity and specificity of 0.75 (0.63-0.83) and 0.73 (0.59-0.84) for DD diagnosis, respectively. For DD with reduction, sensitivity was 0.64 (0.48-0.77) and specificity was 0.72 (0.48-0.87). For DD without reduction, sensitivity was 0.58 (0.39-0.74) and specificity 0.93 (0.83-0.97). Only 8 studies reported examiner calibration when performing clinical and/or MRI evaluation; nevertheless, calibration showed a tendency to improve the diagnosis of DD.Conclusion: The sensitivity and specificity of clinical protocols in the diagnosis of DD are slightly below the recommended values, as well as the studies lack calibration of clinical and MRI examiners. Examiner calibration seems to improve the diagnosis of DD.","PeriodicalId":11261,"journal":{"name":"Dento maxillo facial radiology","volume":" ","pages":"341-353"},"PeriodicalIF":2.9,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11358637/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141544722","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Comparison of quantitative radiomorphometric predictors of healthy and MRONJ-affected bone using panoramic radiography and cone-beam CT. 使用全景 X 射线照相术和锥形束 CT 对健康骨和 MRONJ 受影响骨的放射形态定量预测指标进行比较。

IF 2.9 2区医学

Dento maxillo facial radiology Pub Date : 2024-09-01 DOI: 10.1093/dmfr/twae024

Elif Aslan, Erinc Onem, Ali Mert, B Guniz Baksi

{"title":"Comparison of quantitative radiomorphometric predictors of healthy and MRONJ-affected bone using panoramic radiography and cone-beam CT.","authors":"Elif Aslan, Erinc Onem, Ali Mert, B Guniz Baksi","doi":"10.1093/dmfr/twae024","DOIUrl":"10.1093/dmfr/twae024","url":null,"abstract":"Objectives: To determine the most distinctive quantitative radiomorphometric parameter(s) for the detection of MRONJ-affected bone changes in panoramic radiography (PR) and cone-beam CT (CBCT).Methods: PR and sagittal CBCT slices of 24 MRONJ patients and 22 healthy controls were used for the measurements of mandibular cortical thickness (MCT), fractal dimension (FD), lacunarity, mean gray value (MGV), bone area fraction (BA/TA), trabecular thickness (Tb.Th), trabecular separation (Tb.Sp), trabecular number (Tb.N). MCT was measured in the mental foramen region. While FD and lacunarity were measured on mandibular trabecular and cortical regions-of-interest (ROIs), the remaining parameters were measured on trabecular ROIs. The independent samples t-test was used to compare the measurements between the MRONJ and control groups for both imaging modalities (P = .05).Results: MCT was the only parameter that differentiated MRONJ-affected bone in both PR and CBCT (P < .05). None of the remaining parameters revealed any difference for MRONJ-affected bone in CBCT (P > .05). FD, lacunarity, MGV, BA/TA, and Tb.Sp could distinguish MRONJ-affected trabecular bone in PR (P < .05). The correspondent ROI for both imaging methods that was reliable for detecting MRONJ-affected bone was the trabecular bone distal to the mental foramen above the inferior alveolar canal (ROI-3).Conclusions: MCT is a reliable parameter for the discrimination of MRONJ-affected bone in both PR and CBCT images. PR may be used to detect MRONJ-affected trabecular bone using FD, lacunarity, MGV, BA/TA, and Tb.Sp measurements as well.","PeriodicalId":11261,"journal":{"name":"Dento maxillo facial radiology","volume":" ","pages":"407-416"},"PeriodicalIF":2.9,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11358619/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141174831","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0