Dento maxillo facial radiology最新文献

{"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":"<p><strong>Introduction: </strong>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.</p><p><strong>Methods: </strong>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.).</p><p><strong>Results: </strong>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.</p><p><strong>Conclusions: </strong>PSMA PET-CT is useful to differentiate between MRONJ and jaw metastasis.</p>","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}

{"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":"<p><strong>Objectives: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusions: </strong>HP and SQ can be considered confounding variables in IT examination of the temporomandibular region.</p>","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}

{"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":"<p><strong>Objectives: </strong>This study aimed to evaluate the impact of 3D-printed mannequins on the training of predoctoral students.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusions: </strong>3D printing is an option for producing simulators for pre-clinical training in Oral Radiology, reducing student stress and increasing confidence during clinical care.</p>","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}

{"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":"<p><strong>Objectives: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusions: </strong>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.</p>","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}

{"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":"<p><strong>Objectives: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusions: </strong>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.</p>","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}

{"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":"<p><strong>Objectives: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusions: </strong>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.</p>","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}

{"title":"In vitro early proximal caries detection using trilateral short-wave infrared reflection at 1050 and 1550 nm.","authors":"Katrin Heck, Nils Werner, Lea Hoffmann, Falk Schwendicke, Friederike Litzenburger","doi":"10.1093/dmfr/twae049","DOIUrl":"https://doi.org/10.1093/dmfr/twae049","url":null,"abstract":"<p><strong>Objectives: </strong>This in vitro study evaluated the diagnostic potential of short-wave infrared reflection (SWIRR) at 1050 and 1550 nm for proximal caries detection from the occlusal, buccal and lingual surfaces of posterior teeth under clinically relevant conditions. Bitewing radiography (BWR) was the alternative index test and micro-computed tomography (μCT) the reference standard.</p><p><strong>Methods: </strong>250 proximal surfaces of extracted human teeth were examined using SWIRR at 1050 and 1550 nm and BWR. SWIRR, BWR and μCT findings were evaluated twice by two trained examiners. SWIRR images were evaluated from occlusal and trilateral (occlusal, buccal and lingual combined) views. Sensitivity, specificity and AUC were calculated. Reliability assessment was performed using κ statistics.</p><p><strong>Results: </strong>SWIRR (1050 nm) showed sensitivity of 0.44 for occlusal and 0.55 for trilateral assessment, paired with specificity of 0.96 and 0.90, whereas SWIRR (1550 nm) showed sensitivity of 0.73 and 0.85 paired with specificity of 0.76 and 0.59. Compared to occlusal view, trilateral SWIRR view revealed ≈10% higher sensitivity and lower specificity. BWR revealed lowest sensitivity (0.30) and highest specificity (0.99). Over-and underestimation of caries demonstrated opposite trends: from 1050-1550 nm, overestimation of trilateral SWIRR increased (0.08-0.29), while underestimation decreased (0.15-0.06).</p><p><strong>Conclusion: </strong>Trilateral SWIRR has higher sensitivity and lower specificity for proximal caries, than occlusal SWIRR. 1050 nm are more suitable for trilateral SWIRR and 1550 nm for occlusal examinations. A combination of SWIRR at 1050 and 1550 nm may exhibit a balanced sensitivity and specificity for proximal caries.</p>","PeriodicalId":11261,"journal":{"name":"Dento maxillo facial radiology","volume":" ","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142343505","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}

{"title":"The impact of CBCT on outcomes associated with endodontic access cavity preparation: a controlled human analogue study using 3D printed first maxillary molars.","authors":"Margarete B McGuigan, Henry F Duncan, Gabriel Krastl, Julia Ludwig, Bahman Honari, Keith Horner","doi":"10.1093/dmfr/twae048","DOIUrl":"https://doi.org/10.1093/dmfr/twae048","url":null,"abstract":"<p><strong>Objectives: </strong>To identify if supplemental preoperative CBCT imaging could improve outcomes related to endodontic access cavity preparation, using 3D-printed maxillary first molars (M1Ms) in a rigorously simulated, controlled human analogue study.</p><p><strong>Methods: </strong>18 operators with three experience-levels took part in two simulated clinical sessions, one with and one without the availability of CBCT imaging, in a randomised order and with an intervening 8-week washout period. Operators attempted location of all four root canals in each of three custom-made M1Ms (two non-complex and one complex mesiobuccal canal anatomy). Primary outcome was tooth volume removed. Secondary outcomes were linear cavity dimensions, canals located, and procedural time. Operator confidence and 'helpfulness' of available imaging were recorded. Statistical analysis of data included: paired t-tests, Fishers Exact test, linear mixed effect modelling and Mann-Whitney U test, with an alpha level of .05 for all.</p><p><strong>Results: </strong>When supplemental preoperative CBCT was available, there were significant reductions in volume of the access cavity and procedural times, with significantly increased mesiobuccal-2 (MB2) canal location, but only for teeth with non-complex anatomies and for more experienced operators. Linear mixed-effect modelling identified image type and operator experience as significant predictors of tooth volume removed and procedural time. There was significantly lower confidence in canal location and perceived 'helpfulness\" (all experience groups) when conventional imaging only was used compared with when CBCT was available.</p><p><strong>Conclusions: </strong>Supplemental preoperative CBCT had several beneficial impacts on access cavity preparation, although this only applied to teeth with non-complex anatomy and for more experienced operators.</p>","PeriodicalId":11261,"journal":{"name":"Dento maxillo facial radiology","volume":" ","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142343506","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}

{"title":"Development and validation of a CT-based deep learning radiomics signature to predict lymph node metastasis in oropharyngeal squamous cell carcinoma: a multicenter study.","authors":"Tianzi Jiang, Hexiang Wang, Jie Li, Tongyu Wang, Xiaohong Zhan, Jingqun Wang, Ning Wang, Pei Nie, Shiyu Cui, Xindi Zhao, Dapeng Hao","doi":"10.1093/dmfr/twae051","DOIUrl":"https://doi.org/10.1093/dmfr/twae051","url":null,"abstract":"<p><strong>Objectives: </strong>Lymph node metastasis (LNM) is a pivotal determinant that influences the treatment strategies and prognosis for oropharyngeal squamous cell carcinoma (OPSCC) patients. This study aims to establish and verify a deep learning (DL) radiomics model for the prediction of LNM in OPSCCs using contrast-enhanced computed tomography (CECT).</p><p><strong>Methods: </strong>A retrospective analysis included 279 OPSCC patients from three institutions. CECT images were used for handcrafted (HCR) and DL feature extraction. Dimensionality reduction for HCR features used recursive feature elimination and least absolute shrinkage and selection operator algorithms, whereas DL feature dimensionality reduction used variance-threshold and recursive feature elimination algorithms. Radiomics signatures were constructed using support vector machine, decision tree, random forest, k-nearest neighbor, gaussian naive bayes classifiers and light gradient boosting machine. A combined model was then constructed using the screened DL, HCR, and clinical features. The area under the receiver operating characteristic curve (AUC) served to quantify the model's performance, and calibration curves were utilized to assess its calibration.</p><p><strong>Results: </strong>The combined model exhibited robust performance, achieving AUC values of 0.909 (95% CI: 0.861-0.957) in the training cohort, 0.884 (95% CI: 0.800-0.968) in the internal validation cohort, and 0.865 (95% CI: 0.791-0.939) in the external validation cohort. It outperformed both the clinical model and best-performing radiomics model. Moreover, calibration was deemed satisfactory.</p><p><strong>Conclusions: </strong>The combined model based on CECT demonstrates the potential to predict LNM in OPSCCs preoperatively, offering a valuable tool for more precise and tailored treatment strategies.</p><p><strong>Advances in knowledge: </strong>This study presents a novel combined model integrating clinical factors with deep learning radiomics, significantly enhancing preoperative LNM prediction in OPSCC.</p>","PeriodicalId":11261,"journal":{"name":"Dento maxillo facial radiology","volume":" ","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142281917","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}

{"title":"Peracetic Acid Efficacy on Disinfection of Photostimulable Phosphor Plates.","authors":"Débora Costa Ruiz, Thaís Santos Cerqueira Ocampo, Eduardo Martinelli Franco, Iago Filipe Correia-Dantas, Renata de Oliveira Mattos-Graner, Francisco Haiter-Neto, Deborah Queiroz Freitas","doi":"10.1093/dmfr/twae046","DOIUrl":"https://doi.org/10.1093/dmfr/twae046","url":null,"abstract":"<p><strong>Objectives: </strong>To evaluate the antimicrobial efficacy of white vinegar, acetic acid and peracetic acid on photostimulable phosphor (PSP) plates disinfection, and to assess the disinfectant influence on the radiographic quality.</p><p><strong>Methods: </strong>Eight PSP plates (Express system) were contaminated with Streptococcus mutans and Candida albicans. These plates were wiped with tissues without any substance, with white vinegar, acetic acid, and peracetic acid, followed by an agar imprint. Number of microbial colonies formed was recorded. Afterwards, the quality of radiographs was tested using the more efficient disinfectant. Before disinfection and after every five disinfections, two radiographs of an acrylic-block and two radiographs of an aluminum step-wedge were acquired for each plate. Density, noise, uniformity, and contrast were analyzed. Three oral radiologists evaluated the images for the presence of artifacts. One-way Analysis of Variance compared changes on gray values among the disinfections (α = 0.05). Intra- and inter-examiner agreement for the presence of artifacts was calculated by weighted Kappa.</p><p><strong>Results: </strong>Peracetic acid was the only one that eliminated both microorganisms. Density and uniformity decreased after 100 disinfections, and contrast changed without a pattern in the course of disinfections (P ≤ 0.05). Small artifacts were observed after 30 disinfections. Intra- and inter-examiner agreements were almost perfect.</p><p><strong>Conclusions: </strong>Disinfection with peracetic acid eliminated both microorganisms. However, it also affected density, uniformity and contrast of radiographs, and led to the formation of small artifacts.</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":"142105392","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}