{"title":"An attempt to generate panoramic radiographs including jaw cysts using StyleGAN3.","authors":"Motoki Fukuda, Shinya Kotaki, Michihito Nozawa, Kaname Tsuji, Masahiro Watanabe, Hironori Akiyama, Yoshiko Ariji","doi":"10.1093/dmfr/twae044","DOIUrl":"https://doi.org/10.1093/dmfr/twae044","url":null,"abstract":"<p><strong>Objectives: </strong>The purpose of this study was to generate radiographs including dentigerous cysts by applying the latest generative adversarial network (GAN; StyleGAN3) to panoramic radiography.</p><p><strong>Methods: </strong>A total of 459 cystic lesions were selected, and 409 images were randomly assigned as training data and 50 images as test data. StyleGAN3 training was performed for 500 000 images. Fifty generated images were objectively evaluated by comparing them with 50 real images according to four metrics: Fréchet inception distance (FID), kernel inception distance (KID), precision and recall, and inception score (IS). A subjective evaluation of the generated images was performed by three specialists who compared them with the real images in a visual Turing test.</p><p><strong>Results: </strong>The results of the metrics were as follows: FID, 199.28; KID, 0.14; precision, 0.0047; recall, 0.00; and IS, 2.48. The overall results of the visual Turing test were 82.3%. No significant difference was found in the human scoring of root resorption.</p><p><strong>Conclusions: </strong>The images generated by StyleGAN3 were of such high quality that specialists could not distinguish them from the real images.</p>","PeriodicalId":11261,"journal":{"name":"Dento maxillo facial radiology","volume":" ","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142119228","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}
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":"<p><strong>Objectives: </strong>This study aimed to verify the accuracy of clinical protocols for the diagnosis of disc displacement (DD) compared with MRI, considering examiners' calibration.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusion: </strong>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.</p>","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}
{"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":"<p><strong>Objectives: </strong>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).</p><p><strong>Methods: </strong>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).</p><p><strong>Results: </strong>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).</p><p><strong>Conclusions: </strong>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.</p>","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}
Hui Jeong, Sang-Sun Han, Youngjae Yu, Saejin Kim, Kug Jin Jeon
{"title":"How well do large language model-based chatbots perform in oral and maxillofacial radiology?","authors":"Hui Jeong, Sang-Sun Han, Youngjae Yu, Saejin Kim, Kug Jin Jeon","doi":"10.1093/dmfr/twae021","DOIUrl":"10.1093/dmfr/twae021","url":null,"abstract":"<p><strong>Objectives: </strong>This study evaluated the performance of four large language model (LLM)-based chatbots by comparing their test results with those of dental students on an oral and maxillofacial radiology examination.</p><p><strong>Methods: </strong>ChatGPT, ChatGPT Plus, Bard, and Bing Chat were tested on 52 questions from regular dental college examinations. These questions were categorized into three educational content areas: basic knowledge, imaging and equipment, and image interpretation. They were also classified as multiple-choice questions (MCQs) and short-answer questions (SAQs). The accuracy rates of the chatbots were compared with the performance of students, and further analysis was conducted based on the educational content and question type.</p><p><strong>Results: </strong>The students' overall accuracy rate was 81.2%, while that of the chatbots varied: 50.0% for ChatGPT, 65.4% for ChatGPT Plus, 50.0% for Bard, and 63.5% for Bing Chat. ChatGPT Plus achieved a higher accuracy rate for basic knowledge than the students (93.8% vs. 78.7%). However, all chatbots performed poorly in image interpretation, with accuracy rates below 35.0%. All chatbots scored less than 60.0% on MCQs, but performed better on SAQs.</p><p><strong>Conclusions: </strong>The performance of chatbots in oral and maxillofacial radiology was unsatisfactory. Further training using specific, relevant data derived solely from reliable sources is required. Additionally, the validity of these chatbots' responses must be meticulously verified.</p>","PeriodicalId":11261,"journal":{"name":"Dento maxillo facial radiology","volume":" ","pages":"390-395"},"PeriodicalIF":2.9,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11358622/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141287874","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}
{"title":"The relationship between the uptake of alveolar bone inflammation and of cervical lymph nodes on fluoro-2-deoxy-D-glucose positron emission tomography.","authors":"Masafumi Oda, Hirofumi Koga, Shota Kataoka, Shinji Yoshii, Susumu Nishina, Toshihiro Ansai, Yasuhiro Morimoto","doi":"10.1093/dmfr/twae019","DOIUrl":"10.1093/dmfr/twae019","url":null,"abstract":"<p><strong>Objectives: </strong>To elucidate the relationships between the maximum standardized uptake value (SUVmax) of alveolar bone and those of lymph nodes (LNs) around the neck on 18F-fluoro-2-deoxy-D-glucose (18F-FDG) positron emission tomography (PET).</p><p><strong>Methods: </strong>The SUVmax values of alveolar bone and of level IA, level IB, and level IIA LNs of 174 patients, including those with and without active odontogenic inflammation, on PET/CT performed for a health check were retrospectively evaluated. The upper and lower jaws were divided into four blocks (right maxilla, left maxilla, right mandible, and left mandible). The SUVmax values of each block and of the LNs were calculated. The differences in the SUVmax of each LN level between patients with and without odontogenic inflammation, and the relationship between the SUVmax values of alveolar bone and of the LNs were analysed statistically.</p><p><strong>Results: </strong>Significant differences in SUVmax values of bilateral level IB and IIA LNs were found between patients with and without odontogenic inflammation (Mann-Whitney U test: right level IB, P = .008; left level IB, P = .006; right level IIA, P < .001; left level IIA, P = .002), but not in bilateral level IA LNs (Mann-Whitney U test: right level IA, P = .432; left level IA, P = .549). The inflammatory site with the highest SUVmax in level IB LNs was the ipsilateral mandible (multivariate analysis: right, beta = 0.398, P < .001; left, beta = 0.472, P < .001), and the highest SUVmax in level IIA LNs was the ipsilateral maxilla (multivariate analysis: right, beta = 0.223, P = .002; left, beta = 0.391, P < .001).</p><p><strong>Conclusions: </strong>The SUVmax values of level IB and IIA LNs were associated with a tendency towards a higher SUVmax value of alveolar bone on 18F-FDG-PET.</p>","PeriodicalId":11261,"journal":{"name":"Dento maxillo facial radiology","volume":" ","pages":"372-381"},"PeriodicalIF":2.9,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11358638/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141086130","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}
Kai Liu, Kai Li, Xudong Wang, Jiuai Sun, Steve G F Shen
{"title":"Facial vascular visualization enhancement based on optical detection technology.","authors":"Kai Liu, Kai Li, Xudong Wang, Jiuai Sun, Steve G F Shen","doi":"10.1093/dmfr/twae020","DOIUrl":"10.1093/dmfr/twae020","url":null,"abstract":"<p><strong>Objective: </strong>This study aims to develop a facial vascular enhancement imaging system and analyze vascular distribution in the facial region to assess its potential in preventing unintended intravascular injections during cosmetic facial filling procedures.</p><p><strong>Methods: </strong>A facial vascular enhancement imaging system based on optical detection technology was designed, and volunteers were recruited. The system was utilized to detect and analyze vascular distribution in various anatomical regions of the faces. The vascular visualization-enhanced (VVE) images generated by the system were compared with visible light images to validate the vascular visualization capability of the system. Additionally, the reliability of vascular visualization was assessed by comparing the observed vascular patterns in the VVE images with those in near-infrared light images.</p><p><strong>Results: </strong>Thirty volunteers were recruited. The VVE images produced by the system demonstrated a significant capacity to identify vascular morphology and yielded a higher vessel count compared to visible light images, particularly in the frontal, orbital, perioral, mental, temporal, cheek, and parotid masseter regions (P < .05). The temporal region exhibited the highest vascular density, followed by the cheek region and then the frontal region. Reliability analysis of vascular visualization enhancement indicated that the system's imaging of facial vasculature not only demonstrated reliability but also enhanced physicians' visual perception.</p><p><strong>Conclusion: </strong>Blood vessel distribution varies across facial regions. The facial vascular enhancement imaging system facilitates real-time and clear visualization of facial vasculature, offering immediate visual feedback to surgeons. This innovation holds promise for enhancing the safety and effectiveness of facial filling procedures.</p>","PeriodicalId":11261,"journal":{"name":"Dento maxillo facial radiology","volume":" ","pages":"382-389"},"PeriodicalIF":2.9,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11358639/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141075701","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}
Ziang Wu, Xinbo Yu, Yizhou Chen, Xiaojun Chen, Chun Xu
{"title":"Deep learning in the diagnosis of maxillary sinus diseases: a systematic review.","authors":"Ziang Wu, Xinbo Yu, Yizhou Chen, Xiaojun Chen, Chun Xu","doi":"10.1093/dmfr/twae031","DOIUrl":"10.1093/dmfr/twae031","url":null,"abstract":"<p><strong>Objectives: </strong>To assess the performance of deep learning (DL) in the detection, classification, and segmentation of maxillary sinus diseases.</p><p><strong>Methods: </strong>An electronic search was conducted by two reviewers on databases including PubMed, Scopus, Cochrane, and IEEE. All English papers published no later than February 7, 2024, were evaluated. Studies related to DL for diagnosing maxillary sinus diseases were also searched in journals manually.</p><p><strong>Results: </strong>Fourteen of 1167 studies were eligible according to the inclusion criteria. All studies trained DL models based on radiographic images. Six studies applied to detection tasks, one focused on classification, two segmented lesions, and five studies made a combination of two types of DL models. The accuracy of the DL algorithms ranged from 75.7% to 99.7%, and the area under curves (AUC) varied between 0.7 and 0.997.</p><p><strong>Conclusion: </strong>DL can accurately deal with the tasks of diagnosing maxillary sinus diseases. Students, residents, and dentists could be assisted by DL algorithms to diagnose and make rational decisions on implant treatment related to maxillary sinuses.</p>","PeriodicalId":11261,"journal":{"name":"Dento maxillo facial radiology","volume":" ","pages":"354-362"},"PeriodicalIF":2.9,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11358632/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141598885","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}
Yuri Iwamoto, Hiroaki Shimamoto, Doaa Felemban, Tomoyuki Terai, Sven Kreiborg, Sanjay M Mallya, Fan-Pei Gloria Yang, Chihiro Tanikawa, Shumei Murakami
{"title":"MRI susceptibility artefacts caused by orthodontic wire.","authors":"Yuri Iwamoto, Hiroaki Shimamoto, Doaa Felemban, Tomoyuki Terai, Sven Kreiborg, Sanjay M Mallya, Fan-Pei Gloria Yang, Chihiro Tanikawa, Shumei Murakami","doi":"10.1093/dmfr/twae023","DOIUrl":"10.1093/dmfr/twae023","url":null,"abstract":"<p><strong>Objectives: </strong>To evaluate magnetic susceptibility artefacts produced by orthodontic wires on MRI and the influence of wire properties and MRI image sequences on the magnitude of the artefact.</p><p><strong>Methods: </strong>Arch form orthodontic wires [four stainless steels (SS), one cobalt chromium (CC) alloy, 13 titanium (Ti) alloys] were embedded in a polyester phantom, and scanned using a 1.5-T superconducting magnet scanner with an eight-channel phased-array coil. All wires were scanned with T1-weighted spin echo (SE) and gradient echo (GRE) sequences according to the American Society for Testing and Materials (ASTM) F2119-07 standard. The phantom also scanned other eight sequences. Artefacts were measured using the ASTM F2119-07 definition and OsiriX software. Artefact volume was analysed according to metal composition, wire length, number of wires, wire thickness, and imaging sequence as factors.</p><p><strong>Results: </strong>With SE/GRE, black/white artefacts volumes from all SS wires were significantly larger than those produced by CC and Ti wires (P < .01). With the GRE, the black artefacts volume was the highest with the SS wires. With the SE, the black artefacts volume was small, whereas white artefacts were noticeable. The cranio-caudal extent of the artefacts was significantly longer with SS wires (P < .01). Although a direct relationship of wire length, number of wires, and wire thickness with artefact volume was noted, these factors did not influence artefact extension in the cranio-caudal direction.</p><p><strong>Conclusions: </strong>Ferromagnetic/paramagnetic orthodontic wires create artefacts due to local alteration of magnetic field homogeneity. The SS-type wires produced the largest artefacts followed by CC and Ti.</p>","PeriodicalId":11261,"journal":{"name":"Dento maxillo facial radiology","volume":" ","pages":"396-406"},"PeriodicalIF":2.9,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11358636/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141317074","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}
Juha Koivisto, Jan Wolff, Ruben Pauwels, Touko Kaasalainen, Anni Suomalainen, Patricia Stoor, Jani Horelli, Juho Suojanen
{"title":"Assessment of cone-beam CT technical image quality indicators and radiation dose for optimal STL model used in visual surgical planning.","authors":"Juha Koivisto, Jan Wolff, Ruben Pauwels, Touko Kaasalainen, Anni Suomalainen, Patricia Stoor, Jani Horelli, Juho Suojanen","doi":"10.1093/dmfr/twae026","DOIUrl":"10.1093/dmfr/twae026","url":null,"abstract":"<p><strong>Objectives: </strong>The aim of this study was to identify cone-beam computed tomography (CBCT) protocols that offer an optimal balance between effective dose (ED) and 3D model for orthognathic virtual surgery planning, using CT as a reference, and to assess whether such protocols can be defined based on technical image quality metrics.</p><p><strong>Methods: </strong>Eleven CBCT (VISO G7, Planmeca Oy, Helsinki, Finland) scan protocols were selected out of 32 candidate protocols, based on ED and technical image quality measurements. Next, an anthropomorphic RANDO SK150 phantom was scanned using these 11 CBCT protocols and 2 CT scanners for bone quantity assessments. The resulting DICOM (Digital Imaging and Communications in Medicine) files were converted into Standard Tessellation Language (STL) models that were used for bone volume and area measurements in the predefined orbital region to assess the validity of each CBCT protocol for virtual surgical planning.</p><p><strong>Results: </strong>The highest CBCT bone volume and area of the STL models were obtained using normal dose protocol (F2) and ultra-low dose protocol (J13), which resulted in 48% and 96% of the mean STL bone volume and 48% and 95% of the bone area measured on CT scanners, respectively.</p><p><strong>Conclusions: </strong>The normal dose CBCT protocol \"F2\" offered optimal bone area and volume balance for STL. The optimal CBCT protocol can be defined using contrast-to-noise ratio and modulation transfer function values that were similar to those of the reference CT scanners'. CBCT scanners with selected protocols can offer a viable alternative to CT scanners for acquiring STL models for virtual surgical planning at a lower effective dose.</p>","PeriodicalId":11261,"journal":{"name":"Dento maxillo facial radiology","volume":" ","pages":"423-433"},"PeriodicalIF":2.9,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11358642/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141445830","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}
Layrlla Kateriny Moura Oliveira Lopes, Rodolfo Ramos Castelo Branco, Rafaela Pequeno Reis Sousa, Elisa Diniz de Lima, Diego Filipe Bezerra Silva, Daniela Pita de Melo
{"title":"The influence of different cheek and lip retractors and emissivity on intraoral infrared thermography.","authors":"Layrlla Kateriny Moura Oliveira Lopes, Rodolfo Ramos Castelo Branco, Rafaela Pequeno Reis Sousa, Elisa Diniz de Lima, Diego Filipe Bezerra Silva, Daniela Pita de Melo","doi":"10.1093/dmfr/twae025","DOIUrl":"10.1093/dmfr/twae025","url":null,"abstract":"<p><strong>Objectives: </strong>To assess the influence of two conventional and one adapted cheek and lip retractors and three emissivity setting values on intraoral infrared thermography (IT) temperature values.</p><p><strong>Methods: </strong>The sample was composed by 50 volunteers. Three cheek and lip retractors were tested: Group 1-flex retractor (FR); Group 2-FR adapted with Styrofoam; Group 3-U-type retractor (UR) for cheek and lip. All thermograms were acquired using FLIR T650 infrared camera. A set of three thermograms in frontal norm were acquired for each lip and cheek retractor at 0.91, 0.96, and 0.98ε, with an interval of 15 min between each set of images to avoid thermal interference. All images were assessed by two observers. The ROIs' mean temperature of the four upper incisors was recorded. Two-way ANOVA and Sidak post-test were used for data assessment with a significance level of 5%.</p><p><strong>Results: </strong>Group 3 showed higher mean temperature than Groups 1 and 2 at all emissivity settings for all assessed teeth (P < .05). 0.91ε showed higher temperature than 0.96ε and 0.98ε for all assessed variables (P < .01). Contralateral teeth assessed using Group 3 at 0.91ε showed statistical differences between each other (P < .05). No statistical difference was observed between contralateral teeth assessed using Groups 1 and 2 at 0.96ε and 0.98ε (P > .05).</p><p><strong>Conclusions: </strong>The choice of cheek and lip retractor and emissivity setting can interfere on intraoral IT temperature values. U-type cheek and lip retractor and 0.91ε setting should not be used for IT image acquisition when assessing dental tissues.</p>","PeriodicalId":11261,"journal":{"name":"Dento maxillo facial radiology","volume":" ","pages":"417-422"},"PeriodicalIF":2.9,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11358626/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141174832","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}