Dento maxillo facial radiology最新文献

Objectives: The aim of this study was to investigate whether any feature of carotid artery calcification (CAC) detected on panoramic radiographs (PRs) is associated with more severe signs of cardiovascular disease (CVD), as assessed by carotid ultrasound (CUS) including multi-view assessment of carotid intima media thickness (cIMT).

Methods: The present investigation was a retrospective sub-study of the randomized controlled trial visualization of asymptomatic atherosclerotic disease for optimum cardiovascular prevention (VIPVIZA), which included 60-, 50-, and 40-year-old inhabitants of Västerbotten County, each of whom underwent CUS. The present sub-study included 135 participants who had undergone PR for odontological indications within 18 months before or after CUS examination. Findings of CAC on PR were compared with CUS findings of cIMT and carotid plaque. CAC features were categorized into 4 types: single, scattered, vessel width-defining, or vessel-outlining.

Results: Compared to participants without CAC on PR, those with any CAC type on PR exhibited significantly more carotid plaque (80.9% vs 43.2%, P < .001) and a higher average cIMT score (0.83 vs 0.77 mm, P = .013) on CUS. The vessel-outlining CAC group exhibited the most pronounced cIMT and carotid plaque occurrence (P = .011).

Conclusions: All CAC types detected on PR were associated with CVD on CUS, and vessel-outlining CAC indicated more severe CVD. By detecting CAC on PR, especially vessel-outlining CACs, dentists could contribute to the early identification of patients with asymptomatic CVD, and recommend that these patients seek medical attention for preventive treatment.

Advances in knowledge: All types of CAC detected on PR-particularly the vessel-outlining type-are associated with carotid ultrasound findings, including carotid intima media thickness, indicating CVD and increased risk of stroke and myocardial infarction. Thus, dentists can identify patients at increased risk of cardiovascular events by detecting CAC  on PR, with higher diagnostic reliability in cases with vessel-outlining calcification.

Objectives: The aim of this study is to provide an overview of current cone beam CT (CBCT) practices in European dental clinics.

Methods: From February to May 2023, 186 European EADMFR members were invited to complete an online survey. Participants were asked: (1) to provide exposure settings for 4 diagnostic scenarios; (2) if and how they adjust for age and body type; (3) whether they follow established protocols when selecting settings; and (4) if the Dose Area Product (DAP) is registered for CBCT scans.

Results: A total of 59 (32%) eligible responses were received. There was a large variation in exposure parameters among clinicians within the same diagnostic scenario. Across scenarios, only voxel size and field of view (FOV) differed significantly (P < .05), with smaller settings being chosen for endodontic diagnostics and larger parameters for full-jaw imaging for implant planning. For young patients, most respondents reduced FOV (70%), mA (67%), and exposure time (59%). For larger patients, most increased mA (54%) and kV (52%). Written protocols were more frequently employed than manufacturer-recommended settings (75% vs 50% reported "most of the time" or "always"). More frequent usage of manufacturer-recommended settings correlated with larger FOV settings (P < .05). 90% reported registering the DAP.

Conclusions: CBCT exposure parameter selection lacks consistency. Only FOV and voxel size were consistently adjusted for the indication. New guidelines providing guidance on the selection of CBCT settings could reduce variation between clinicians and enhance the uniformity of the quality of care.

Advances in knowledge: Lack of uniformity in CBCT parameter selection highlights the need for updated, indication-oriented, and patient-specific guidelines.

Objective: Intraoral ultrasonography (US) is known for its high accuracy in evaluating the depth of invasion (DOI) in tongue squamous cell carcinoma (SCC). However, measurement discrepancies, such as overestimation or underestimation, can occur in certain cases. This study aimed to identify factors affecting the measurement accuracy of intraoral US.

Methods: A total of 96 cases were included in this study. Patients who underwent imaging diagnosis for primary tongue SCC by oral and maxillofacial radiologists, followed by surgical resection by oral surgeons at our institution between April 2014 and March 2022, were included in the study. Cases were classified according to their clinical and histopathological characteristics, including clinical growth pattern, maximum pathological tumour diameter, pathological T classification, and pattern of invasion (Yamamoto-Kohama classification). Measurement accuracy was evaluated using Spearman's rank correlation coefficient and Bland-Altman analysis.

Results: A total of 76 cases were analysed. Intraoral US demonstrated high diagnostic accuracy across various tumour characteristics. However, greater DOI and larger maximum tumour diameter were associated with increased variability in measurements. Exophytic lesions were more likely to be overestimated, whereas lesions with diffuse infiltration tended to be underestimated.

Conclusion: Although intraoral US provides high accuracy in the preoperative evaluation of tongue SCC, clinicians should be aware of specific tumour characteristics that may influence measurement precision, leading to potential overestimation or underestimation.

Objectives: 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.

Methods: 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.

Results: 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.

Conclusion: 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.

Advances in knowledge: 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.

Objectives: Panoramic radiographs (PANs) are a commonly used dental imaging modality and are complex to evaluate. This study aimed to use mouse-tracking technology to identify the visualization characteristics of experienced Oral & Maxillofacial Radiology (OMR) faculty when reviewing PANs and to assess relationships with detection accuracy.

Methods: Seventeen OMR faculty in U.S. dental schools with 5 to 38 years of experience were recruited. Participants were shown 17 PANs (5 "Normal" and 12 "Pathology") over Zoom and instructed to move their mouse cursor in sync with their eye movements. Data collection was based on video recordings with X, Y coordinates auto-detected using mouse-tracking algorithms. Parameters collected included detection accuracy, time taken, completeness of search coverage, revisits and search patterns used.

Results: Most common search patterns were Dental to Periphery (41.5%) and Periphery to Dental (37.7%). The mean accuracy score for all cases with pathology was 84.6%. Except for 2 cases with subtle findings (condylar fracture and fibrous dysplasia), mean accuracy scores ranged from 76.5% to 100%. There were no associations between search patterns and detection accuracy. Participants took longer durations and performed more complete searches with more revisits on "Normal" cases. They were more likely to use shorter search times with smaller coverage and perform single searches when correctly detecting lesions.

Conclusions: Experienced OMRs were able to detect lesions without scanning the entire PAN and within a single search, regardless of the search pattern used.

Advances in knowledge: This is the first study using mouse-tracking algorithms to evaluate visualization patterns on PANs. Experienced OMRs can conduct efficient and accurate reviews of PANs regardless of search strategy.

Objectives: This study proposes a deep convolutional neural network model that integrates B-mode and D-mode ultrasound images to classify metastatic lymph nodes in patients with oral squamous cell carcinoma.

Methods: A shared backbone network incorporating a cross-attention mechanism was employed to enhance feature-level interactions between dual-input ultrasound images. A total of six convolutional neural network architectures (VGG16, SqueezeNet, ResNet50, EfficientNet B3, ConvNext, DenseNet121) were implemented within a shared backbone framework to investigate optimal performance. For each network, diagnostic performance was compared between dual-input and single-input ultrasound. In addition, model performance was evaluated against human observers with different levels of experience.

Results: The model using DenseNet121 as a shared backbone with an integrated cross-attention layer (LNM-Net) achieved the highest classification accuracy (85.3%) when utilizing dual-input images, surpassing the diagnostic performance of residents. The cross-attention module improved feature fusion, reducing false positives by suppressing modality-specific noise.

Conclusion: LNM-Net demonstrates strong potential as a clinical decision-support tool for preoperative lymph node metastasis assessment in oral squamous cell carcinoma. Despite current limitations such as dataset size and cross-institutional variability, the model offers a promising supplementary aid, particularly in settings with limited radiological expertise.

Advances in knowledge: This study develops a novel cross-attentive network using dual-input B- and D-mode ultrasound images to classify metastatic lymph nodes in oral squamous cell carcinoma.

Objective: 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.

Methods: 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.

Results: 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).

Conclusions: 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.

Advances in knowledge: Cephalometric AI platforms show variability in landmark location accuracy. User modifications significantly impact automated analysis results.

Objectives: 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.

Methods: 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.

Results: 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.

Conclusions: The proposed method enhances the accuracy of tooth detection in CBCT-derived PAN by reducing background interference and improving the visualization of tooth orientation.

Objectives: This survey was conducted to identify dental radiography practices and knowledge gaps among dentists in Singapore with respect to both 2D and 3D imaging.

Methods: 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.

Results: 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.

Conclusions: 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.

Advances in knowledge: Identifying knowledge and training gaps in dental imaging is critical to ensure the safe use of ionizing radiation on patients.

Objectives: This study aimed to systematically review the current performance of large language models (LLMs) in dento-maxillofacial radiology (DMFR).

Methods: 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.

Results: 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%.

Conclusions: 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.