Dento maxillo facial radiology最新文献

{"title":"A pilot study on the detection of proximal caries in permanent anterior human teeth using lateral short-wave infrared transillumination at 1300 nm.","authors":"Leander Benz, Friederike Litzenburger, Elias Walter, Falk Schwendicke, Katrin Heck","doi":"10.1093/dmfr/twaf064","DOIUrl":"10.1093/dmfr/twaf064","url":null,"abstract":"<p><strong>Objectives: </strong>This pilot study aimed to evaluate the diagnostic performance of short-wave infrared transillumination at 1300 nm for detecting proximal caries lesions in permanent anterior teeth, compared with digital radiography.</p><p><strong>Methods: </strong>Seventeen extracted human permanent anterior teeth were examined using short-wave infrared transillumination from both labial and oral directions. Images were acquired using a 1300-nm light-emitting diode and a short-wave infrared camera. Radiographs were obtained using a standard digital radiography setup. Micro-CT served as the reference standard. Two calibrated examiners independently assessed the presence or absence of caries lesions. Statistical analysis included sensitivity, specificity and overall accuracy. Inter-examiner agreement was assessed using kappa statistics.</p><p><strong>Results: </strong>Proximal surfaces were analysed. Short-wave infrared transillumination demonstrated higher diagnostic accuracy from oral (86%), labial (79%), and combined (90%) views compared to radiography (66%). The combined approach yielded a sensitivity of 86% and a specificity of 93%. In contrast, radiography achieved a sensitivity of 29% and a specificity of 100%. Inter-examiner agreement was substantial to almost perfect for all methods.</p><p><strong>Conclusion: </strong>This pilot study shows that short-wave infrared transillumination at 1300 nm provides significantly greater diagnostic accuracy than radiography for detecting proximal caries in anterior teeth and may serve as a radiation-free adjunct in clinical diagnostics.</p><p><strong>Advances in knowledge: </strong>This is the first pilot study to demonstrate that combining labial and oral short-wave infrared transillumination enables accurate detection of proximal caries in anterior teeth and offers potential as a novel diagnostic tool.</p>","PeriodicalId":11261,"journal":{"name":"Dento maxillo facial radiology","volume":" ","pages":"99-105"},"PeriodicalIF":2.9,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145091384","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":"Cephalometric tracing: comparing artificial intelligence and augmented intelligence on online platforms.","authors":"Edna Alejandra Gallardo-Lopez, Lucila Massu Yoshizaki Akinaga Moreira, Murilo Henrique Cruz, Núbia Rafaelle Oliveira Meneses, Suelen Cavalcante Ferreira Schumiski, Daniela Miranda Richarte de Andrade Salgado, Edgard Michel-Crosato, Claudio Costa","doi":"10.1093/dmfr/twaf045","DOIUrl":"10.1093/dmfr/twaf045","url":null,"abstract":"<p><strong>Objective: </strong>This research aimed to evaluate the results of cephalometric analyses obtained by artificial intelligence (AI) from the RadioCef, EasyCeph, and WebCeph platforms, and their variability due to modifications made by the user.</p><p><strong>Methods: </strong>In this cross-sectional observational study, seventy cephalometric radiographs were analysed using the AI of the platforms. Subsequently, four examiners with different areas of expertise and levels of experience examined each landmark, correcting its location if necessary.</p><p><strong>Results: </strong>The Pog, L1 tip, B, and Go landmarks on the RadioCef; Pn, Me, Pog, U1 tip, and UL on the EasyCeph; and Pog, Me, and B on the WebCeph showed a modification equal to or greater than 90%. More experienced examiners modified a greater number of landmarks. The repeated measures ANOVA test reported statistically significant differences concerning the SNA, SNB, ANB, SN-GoGn, FMIA, FMA, and IMPA angles (P < .05) for fully automated and semi-automated analyses. ICC values reported intra-observer agreement levels from poor (ICC = 0.27) to perfect (ICC = 1), and inter-observer agreement showed good to excellent reliability (ICC = 0.88-0.99).</p><p><strong>Conclusions: </strong>Fully automated cephalometric analysis presents variations according to modifications made by the examiners. This represents a challenge to the knowledge of the orthodontist, influencing the diagnosis and treatment planning. Therefore, the use of augmented intelligence in cephalometric analysis is still suggested based on the results obtained for each platform.</p><p><strong>Advances in knowledge: </strong>Cephalometric AI platforms show variability in landmark location accuracy. User modifications significantly impact automated analysis results.</p>","PeriodicalId":11261,"journal":{"name":"Dento maxillo facial radiology","volume":" ","pages":"667-673"},"PeriodicalIF":2.9,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144076820","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":"Oriented tooth detection: a CBCT image processing method integrated with RoI transformer.","authors":"Ziyi Zhao, Bo Wu, Sha Su, Dongdong Liu, Zejie Wu, Runtao Gao, Nan Zhang","doi":"10.1093/dmfr/twaf049","DOIUrl":"10.1093/dmfr/twaf049","url":null,"abstract":"<p><strong>Objectives: </strong>Cone beam computed tomography (CBCT) has revolutionized dental imaging due to its high spatial resolution and ability to provide detailed 3-dimensional reconstructions of dental structures. This study introduces an innovative CBCT image processing method using an oriented object detection approach integrated with a Region of Interest (RoI) transformer.</p><p><strong>Methods: </strong>This study addresses the challenge of accurate tooth detection and classification in PAN derived from CBCT, introducing an innovative oriented object detection approach, which has not been previously applied in dental imaging. This method better aligns with the natural growth patterns of teeth, allowing for more accurate detection and classification of molars, premolars, canines, and incisors. By integrating RoI transformer, the model demonstrates relatively acceptable performance metrics compared to conventional horizontal detection methods while also offering enhanced visualization capabilities. Furthermore, post-processing techniques, including distance and greyscale value constraints, are employed to correct classification errors and reduce false positives, especially in areas with missing teeth.</p><p><strong>Results: </strong>The experimental results indicate that the proposed method achieves an accuracy of 98.48%, a recall of 97.21%, an F1 score of 97.21%, and an mean average precision (mAP) of 98.12% in tooth detection.</p><p><strong>Conclusions: </strong>The proposed method enhances the accuracy of tooth detection in CBCT-derived PAN by reducing background interference and improving the visualization of tooth orientation.</p>","PeriodicalId":11261,"journal":{"name":"Dento maxillo facial radiology","volume":" ","pages":"695-705"},"PeriodicalIF":2.9,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144612067","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":"Dental imaging in Singapore: a survey of 2D radiographic techniques and CBCT practices.","authors":"Almond Y Q Ng, Clement W M Lai, Clarissa X H Ho, Li Zhen Lim","doi":"10.1093/dmfr/twaf033","DOIUrl":"10.1093/dmfr/twaf033","url":null,"abstract":"<p><strong>Objectives: </strong>This survey was conducted to identify dental radiography practices and knowledge gaps among dentists in Singapore with respect to both 2D and 3D imaging.</p><p><strong>Methods: </strong>This was a cross-sectional survey conducted via an electronic platform from May to June 2023. All Singapore Dental Council-registered dentists were eligible to participate. We gathered data on demographics, intraoral (IO) radiography usage, cone-beam CT (CBCT) training, current CBCT usage, and interpretation.</p><p><strong>Results: </strong>Three-hundred and five out of 2605 registered dentists completed the online survey (11.7% response rate). Radiograph positioning holders, digital imaging, and round collimation were used by most respondents for IO radiography (85.6%, 88.9%, and 89.2%, respectively). One-hundred and forty-two participants (46.6%) underwent CBCT training, and most lacked training in image acquisition. Dentists expressed interest in CBCT interpretation and the use of viewing software; 219 dentists (71.8%) are CBCT users. Most (74.9%) took 0-5 CBCT scans monthly. Implant planning was the most common indication (24.8%). Among CBCT users, 85.9% report some or all their own scans while 70.7% would engage a reporting service if available.</p><p><strong>Conclusions: </strong>This survey provides insights in dental imaging that require increased educational efforts in Singapore. For IO radiography, there should be greater emphasis on rectangular collimation. With CBCT, there is potential for training in image acquisition, interpretation, and the use of viewing software.</p><p><strong>Advances in knowledge: </strong>Identifying knowledge and training gaps in dental imaging is critical to ensure the safe use of ionizing radiation on patients.</p>","PeriodicalId":11261,"journal":{"name":"Dento maxillo facial radiology","volume":" ","pages":"649-658"},"PeriodicalIF":2.9,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12653774/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143986347","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 performance of large language models in dentomaxillofacial radiology: a systematic review.","authors":"Zekai Liu, Andrew Nalley, Jing Hao, Qi Yong H Ai, Andy Wai Kan Yeung, Ray Tanaka, Kuo Feng Hung","doi":"10.1093/dmfr/twaf060","DOIUrl":"10.1093/dmfr/twaf060","url":null,"abstract":"<p><strong>Objectives: </strong>This study aimed to systematically review the current performance of large language models (LLMs) in dento-maxillofacial radiology (DMFR).</p><p><strong>Methods: </strong>Five electronic databases were used to identify studies that developed, fine-tuned, or evaluated LLMs for DMFR-related tasks. Data extracted included study purpose, LLM type, images/text source, applied language, dataset characteristics, input and output, performance outcomes, evaluation methods, and reference standards. Customized assessment criteria adapted from the TRIPOD-LLM reporting guideline were used to evaluate the risk-of-bias in the included studies specifically regarding the clarity of dataset origin, the robustness of performance evaluation methods, and the validity of the reference standards.</p><p><strong>Results: </strong>The initial search yielded 1621 titles, and 19 studies were included. These studies investigated the use of LLMs for tasks including the production and answering of DMFR-related qualification exams and educational questions (n = 8), diagnosis and treatment recommendations (n = 7), and radiology report generation and patient communication (n = 4). LLMs demonstrated varied performance in diagnosing dental conditions, with accuracy ranging from 37% to 92.5% and expert ratings for differential diagnosis and treatment planning between 3.6 and 4.7 on a 5-point scale. For DMFR-related qualification exams and board-style questions, LLMs achieved correctness rates between 33.3% and 86.1%. Automated radiology report generation showed moderate performance with accuracy ranging from 70.4% to 81.3%.</p><p><strong>Conclusions: </strong>LLMs demonstrate promising potential in DMFR, particularly for diagnostic, educational, and report generation tasks. However, their current accuracy, completeness, and consistency remain variable. Further development, validation, and standardization are needed before LLMs can be reliably integrated as supportive tools in clinical workflows and educational settings.</p>","PeriodicalId":11261,"journal":{"name":"Dento maxillo facial radiology","volume":" ","pages":"613-631"},"PeriodicalIF":2.9,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12653761/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144834414","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":"Machine learning algorithms enhance the accuracy of radiographic diagnosis of dental caries: a comparative study.","authors":"Shwetha Hegde, Jinlong Gao, Stephen Cox, Shanika Nanayakkara, Rena Logothetis, Rajesh Vasa","doi":"10.1093/dmfr/twaf053","DOIUrl":"10.1093/dmfr/twaf053","url":null,"abstract":"<p><strong>Objectives: </strong>This study evaluated the influence of cognitive aids, including machine learning (ML) algorithms and checklists, on the diagnostic accuracy and confidence of dental students in detecting dental caries on bitewing radiographs.</p><p><strong>Methods: </strong>Fifty-two third-year dental students were randomly assigned to control, ML, or checklist groups. The participants recorded their caries diagnoses (charting) on 10 bitewing radiographs and rated their confidence. Diagnostic accuracy and reliability were compared between groups for caries detection (present/absent). The inter-rater reliability for International Caries Detection and Assessment System II (ICDAS II) caries grading was assessed using weighted kappa. Participants also completed questionnaires on their perceptions of cognitive aids.</p><p><strong>Results: </strong>ML group showed the highest diagnostic accuracy and confidence levels. For caries detection, the ML group achieved the highest sensitivity (79%) and diagnostic odds ratio (20.3), while the checklist group had the highest specificity (90.9%) (P < .001). The control group showed moderate sensitivity (67.9%) but outperformed the checklist group in this metric. Inter-rater agreement for caries detection was highest in the ML group (κ = 0.702, 95% CI: 0.692-0.713; P < .001), followed by the checklist group. The ML group also had the highest weighted kappa for ICDAS II grading (κ = 0.520, P < .001). Confidence levels differed significantly between groups (P < .001), with the ML group reporting the highest confidence.</p><p><strong>Conclusion: </strong>ML algorithms may enhance diagnostic accuracy and confidence, possibly by reducing cognitive load. While standardizing the diagnostic process, checklists were less effective, likely due to their lack of flexibility and clinical context. Further research is needed to better understand our findings and translate them into clinical workflows.</p>","PeriodicalId":11261,"journal":{"name":"Dento maxillo facial radiology","volume":" ","pages":"632-641"},"PeriodicalIF":2.9,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12653770/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144599691","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":"Artificial intelligence-based metal artefact correction algorithm for radiotherapy patients with dental hardware in head and neck CT: towards precise imaging.","authors":"Xiaoli Yu, Sihua Zhong, Guozhi Zhang, Jinlong Du, Guangyu Wang, Jiang Hu","doi":"10.1093/dmfr/twaf038","DOIUrl":"10.1093/dmfr/twaf038","url":null,"abstract":"<p><strong>Objectives: </strong>To investigate the clinical efficiency of an artificial intelligence-based metal artefact correction algorithm (AI-MAC) for reducing dental metal artefacts in head and neck CT, compared to conventional interpolation-based metal artefact correction (MAC).</p><p><strong>Methods: </strong>We retrospectively collected 41 patients with non-removal dental hardware who underwent non-contrast head and neck CT prior to radiotherapy. All images were reconstructed with the standard reconstruction algorithm (SRA) and were additionally processed with both conventional MAC and AI-MAC. The image quality of SRA, MAC, and AI-MAC was compared by qualitative scoring on a 5-point scale, with scores ≥ 3 considered interpretable. This was followed by a quantitative evaluation, including signal-to-noise ratio (SNR) and artefact index (Idxartefact). Organ contouring accuracy was quantified via calculating the dice similarity coefficient (DSC) and hausdorff distance (HD) for the oral cavity and teeth, using the clinically accepted contouring as reference. Moreover, the treatment planning dose distribution for the oral cavity was assessed.</p><p><strong>Results: </strong>AI-MAC yielded superior qualitative image quality as well as quantitative metrics, including SNR and Idxartefact, to SRA and MAC. The image interpretability significantly improved from 41.46% for SRA and 56.10% for MAC to 92.68% for AI-MAC (P < .05). Compared to SRA and MAC, the best DSC and HD for both oral cavity and teeth were obtained on AI-MAC (all P < .05). No significant differences for dose distribution were found among the 3 image sets.</p><p><strong>Conclusion: </strong>AI-MAC outperforms conventional MAC in metal artefact reduction, achieving superior image quality with high image interpretability for patients with dental hardware undergoing head and neck CT. Furthermore, the use of AI-MAC improves the accuracy of organ contouring while providing consistent dose calculation against metal artefacts in radiotherapy.</p><p><strong>Advances in knowledge: </strong>AI-MAC is a novel deep learning-based technique for reducing metal artefacts on CT. This in vivo study demonstrated its capability of reducing metal artefacts while preserving organ visualization, as compared with conventional MAC.</p>","PeriodicalId":11261,"journal":{"name":"Dento maxillo facial radiology","volume":" ","pages":"659-666"},"PeriodicalIF":2.9,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143969465","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":"Detection of jaw orthogonal plane and dental arch curve from cone beam CT images.","authors":"Benxiang Jiang, Songze Zhang, Hongjian Shi","doi":"10.1093/dmfr/twaf047","DOIUrl":"10.1093/dmfr/twaf047","url":null,"abstract":"<p><strong>Objectives: </strong>This research focuses on detecting the orthogonal plane to the jaw and the dental arch curve on this plane so that high-quality panoramic images can be reconstructed from cone beam CT images.</p><p><strong>Methods: </strong>The movement trajectory of panoramic reconstruction, known as the dental arch curve, determines the quality of the reconstructed panoramic image. In traditional methods, the dental arch curve is detected on 1 transversal slice using interpolation methods. However, these methods may fail to capture the actual dental arch since the jaw is not usually perpendicular to the transversal slice and the interpolation methods tend to ignore local anatomical information of the jaw and teeth. To improve detection of the actual dental arch, we define the jaw orthogonal plane by establishing a relationship between the plane variables and the jaw's left-to-right and the anterior-and-posterior tilts. On this plane, the dental arch curve is first initialized and then moved to match the actual dental arch.</p><p><strong>Results: </strong>Experimental results demonstrate that our method accurately detects dental arch curves. Panoramic images reconstructed using these curves effectively display the true anatomical features of the jaw and teeth with less distortion compared to those reconstructed by traditional methods.</p><p><strong>Conclusions: </strong>Our detected dental arch curve on the jaw orthogonal plane is more accurately located in the middle of the jaw and teeth. Anatomic information of the jaw and teeth around the detected dental curve is rightly employed to reconstruct high-quality panoramic images.</p>","PeriodicalId":11261,"journal":{"name":"Dento maxillo facial radiology","volume":" ","pages":"682-689"},"PeriodicalIF":2.9,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143997034","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":"Usability of shear wave elastography in the quantitative evaluation of masseter muscle stiffness in adolescents with bruxism.","authors":"Emire Aybüke Erdur, Mehmet Öztürk, Nurullah Dağ, Ömer Erdur, Ali Altındağ","doi":"10.1093/dmfr/twaf012","DOIUrl":"10.1093/dmfr/twaf012","url":null,"abstract":"<p><strong>Objectives: </strong>To investigate the correlation between elastography values, age, and duration of bruxism by quantitatively measuring masseter muscle (MM) stiffness with shear wave elastography (SWE) in adolescents with bruxism.</p><p><strong>Methods: </strong>This prospective study evaluated 132 MMs from 66 adolescents: 33 controls and 33 with bruxism. The thickness and stiffness of the MM were measured. The SWE values (metres/second; m/s) and kilopascals (kPa) of the patient and control groups were quantitatively compared.</p><p><strong>Results: </strong>The elastic and velocity values of the MM in both closed and open positions were higher in bruxism patients compared to controls (P < .001, for each). No significant difference existed in MM thickness (P = .904). The receiver operating characteristic analysis for different SWE values found a sensitivity and specificity at baseline of 0.81 kPa, 0.60 m/s and 0.76 kPa, 0.67 m/s with the mouth closed. The values found with the mouth open were 0.76 kPa, 0.64 m/s and 0.76 kPa, 0.61 m/s.</p><p><strong>Conclusions: </strong>Adolescents with bruxism had higher MM hardness values in closed and open positions compared to the control group. SWE can be used as an effective imaging method to measure MM hardness. No relationship existed between SWE values and the patient's age or duration of bruxism.</p>","PeriodicalId":11261,"journal":{"name":"Dento maxillo facial radiology","volume":" ","pages":"642-648"},"PeriodicalIF":2.9,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144157399","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":"3D-printed model for preclinical training in oral radiology: anatomic and pathological conditions.","authors":"Ana Carvalho de Christo, Wislem Miranda de Mello, Vinícius Dutra, Lucas Machado Maracci, Gleica Dal' Ongaro Savegnago, Gabriela Salatino Liedke","doi":"10.1093/dmfr/twaf046","DOIUrl":"10.1093/dmfr/twaf046","url":null,"abstract":"<p><strong>Objective: </strong>The aim of this study was to evaluate the impact of a 3D-printed model with simulated oral changes on the teaching of radiographic evaluation.</p><p><strong>Method: </strong>A model of an adult patient with several simulated alterations was designed, including impacted teeth, dentigerous cyst, mesiodens, coronal fractures, periodontal resorptions, periapical lesions, and exostoses. The radiographic images obtained were evaluated by postgraduate students using a questionnaire. The data obtained were analysed with descriptive and inferential statistics.</p><p><strong>Results: </strong>The 3D model produced satisfactory images for the simulation of the proposed alterations. The general perception of the participants was positive, but there were significant differences between master's and doctoral students regarding the clinical-radiographic relationship of the simulated changes in general (P = .037) and the radiographic image of impacted canine (P = .032).</p><p><strong>Conclusions: </strong>The 3D model was positively evaluated in most of the simulated alterations, demonstrating its potential as a pedagogical tool. These results reinforce the feasibility of 3D printing for producing models for radiographic assessment, offering image quality and versatility for the development of complex training.</p><p><strong>Advances in knowledge: </strong>This is the first study to develop and evaluate a 3D-printed model with complex anatomical and pathological alterations for preclinical training in Oral and Maxillofacial Radiology.</p>","PeriodicalId":11261,"journal":{"name":"Dento maxillo facial radiology","volume":" ","pages":"674-681"},"PeriodicalIF":2.9,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144076819","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}