Dento maxillo facial radiology最新文献

Objectives: To conduct a systematic review evaluating the performance of deep learning (DL) tools in osteoporosis screening using dental imaging and to assess whether these models have been implemented in dental practice.

Methods: Search was performed across 7 electronic databases and 2 sources of grey literature. Included studies applied DL algorithms to dental radiographs or CT in adults diagnosed with osteoporosis, using dual-energy X-ray absorptiometry (DXA) or expert assessment as the reference standard. Risk of bias was assessed using the QUADAS-2 (Quality Assessment of Diagnostic Accuracy Studies 2) tool, alongside an AI-specific checklist and GRADE to evaluate certainty of evidence.

Results: Thirteen studies met the inclusion criteria. DXA was the most common reference standard (n = 08), and panoramic radiography was the predominant imaging modality (n = 12). Accuracy was the most frequently reported metric (n = 12). Most models used pretrained convolutional neural networks, such as VGG16, GoogleNet, ResNet, and AlexNet. ResNet and EfficientNet architectures showed superior performance, particularly when combined with ensemble techniques and clinical covariates. However, no study reported external validation or implementation in dental practice, limiting their applicability.

Conclusions: All DL models demonstrated potential as supportive tools for osteoporosis screening in dentistry. However, the absence of external validation and clinical integration limits their real-world use. Future research should focus on standardization and development of accessible, validated systems.

Advances in knowledge: This systematic review is the first to show that, despite advancements in DL for osteoporosis screening, clinical applicability remains limited. It underscores the need for robust, user-friendly interfaces to facilitate integration into routine dental practice.

Background: The aim of this study is to determine the prevalence, distribution, and follow-up recommendations of incidental findings in cone beam computed tomography (CBCT) scans acquired for endodontic treatment.

Methods: This was a retrospective review of limited field-of-view (FOV) CBCT images for endodontic evaluation obtained at the Stony Brook University School of Dental Medicine between 2018 and 2022. All scans were reviewed by 1 oral and maxillofacial radiology (OMR) resident and all incidental findings were corroborated with the radiology report approved by 1 of 2 board-certified OMRs. Data extracted for each case included age, gender, and reason for scan; and location, diagnosis, and recommended follow-up for each incidental finding. The recommended follow-up consisted of 5 categories: no recommendation, radiographic monitoring, dental specialty evaluation, medical evaluation, or immediate evaluation.

Results: Data was obtained from 565 CBCT scans with 219 males and 346 females. The mean age was 55.4 ± 18.38. There were 349 maxillary and 216 mandibular scans. The most common incidental finding was mild to moderate mucosal disease (21.4%), then periradicular/periapical odontogenic pathology unrelated to the indication for the scan (15.2%). The most common location for an incidental finding was the gnathic bones (62.2%), then the sino-nasal complex (32.5%). The most common follow-up recommendation was dental specialty evaluation (46.2%). Twenty-five findings (2.3%) were subject to immediate follow-up recommendation.

Conclusions: Incidental findings were found in 90.5% of CBCT scans acquired for endodontic purposes. Medical evaluation or immediate evaluation was recommended for a combined 6.4% of incidental findings. Together, these findings highlight the importance of a thorough review of the entire scan by a trained specialist.

Objectives: Positron emission tomography (PET) images are reconstructed using computed tomography (CT)-based attenuation correction, which may cause artefactual errors due to CT artefacts. This study aimed to investigate the effects of metallic dental prostheses and metal artefacts on the incidence of nodular overcorrection in PET/CT images of the oral cavity in patients with head and neck tumours.

Methods: We retrospectively reviewed the F-18 fluorodeoxyglucose PET/CT images of 27 and 20 patients using silicon photomultiplier (SiPM) and photomultiplier tube (PMT) PET, respectively. We evaluated the presence or absence of overcorrection of tumour-like nodular uptake, number of metallic dental prostheses, number of metallic prosthetic blocks, mean CT values, bright-band artefact area/ratio, and dark-band artefact area/ratio.

Results: There was no significant difference in the incidence of overcorrections between SiPM and PMT PET; however, overcorrections in the former were significantly smaller in size than those in the latter. Overcorrection in PMT PET was more likely to occur when the number of metallic dental prostheses, number of metallic dental prosthetic blocks, mean CT value, and bright-band artefact area/ratio were high. However, there was no significant difference in SiPM PET overcorrection between the positive and negative overcorrection groups for the above conditions.

Conclusion: Overcorrection was associated with metallic dental prostheses and CT artefacts; however, the conditions may have scanner-specific characteristics.

Advances in knowledge: Small tumour-like overcorrections appear on SiPM PET, which should be noted because it is more difficult to notice overcorrections. It is important to analyse the images while checking the pre-attenuation correction PET.

Objectives: To evaluate the influence of the battery level of a handheld X-ray device on the objective image quality of radiographs.

Methods: An acrylic-block was radiographed using a SnapShot solid-state sensor and an Eagle handheld X-ray device set at 60 kVp and 0.88 mAs, with the battery at ten different levels (ranging from fully charged to 10%). Six radiographs were acquired at each level. Mean grey values and standard deviations were collected using ImageJ software to assess image brightness, noise, and uniformity. Additionally, an aluminium step-wedge was radiographed under the same conditions for contrast evaluation. Image quality parameters were compared across different battery levels using analysis of variance (ANOVA) with Tukey's post-hoc test (α = 0.05).

Results: Images obtained with a 100% battery level showed higher brightness than those at 50% (P < 0.0001); the battery level did not affect image noise (P = 0.091); uniformity at 20% battery level differed from all other levels (P < 0.0001); and contrast was highest at 90% battery compared to all other levels (P < 0.0001). Overall, the values remained consistent across different battery levels.

Conclusions: Despite some significant differences, the objective image quality remained stable throughout the entire battery charge cycle of the tested handheld X-ray device.

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.

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: 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.

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: This study aimed to conduct a comprehensive evaluation of general-purpose multimodal large language model (LLM) chatbots in oral radiology.

Methods: Ninety text- and image-based oral radiology questions from a Korean dental university were extracted and categorized into six educational contents and two question types. ChatGPT-4o and Gemini 2.0 Flash were evaluated with following items: accuracy with group differences across six contents (using Fisher's exact test with Bonferroni correction, p < 0.0167), answer consistency across ten repeated outputs (evaluated as the mean agreement and Fleiss' kappa coefficient), and hallucination (evaluated as the mean of the 5-point Global Quality Score assigned by two oral radiologists).

Results: Multimodal AI chatbots (ChatGPT-4o and Gemini 2.0 Flash) achieved excellent performance on text-based questions with over 80% accuracy but showed limited performance on image-based tasks, with accuracy under 30%. Additionally, image-based tasks exhibited high response variability, and hallucinations were frequently observed, providing incorrect information. These findings suggest that AI chatbots are not yet suitable for reliable use in oral radiology.

Conclusions: This study provided timely insights into the capabilities and limitations of general-purpose multimodal LLM chatbots in the oral radiology, and will serve as a foundation for more safe and effective applications of AI chatbots in the oral radiology field in the future.

Advances in knowledge: This is the first study to comprehensively assess multimodal LLM chatbots in oral radiology. It provides key insights into the performance benchmarks for AI chatbots in oral radiology, promoting the responsible and transparent integration of AI into dental education.

Objectives: The objective was to assess the accuracy of different AI tools in providing the right responses for multiple choice questions (MCQs) and the time taken to complete the responses.

Methods: The study included 80 MCQs, each with four options and a correct answer related to oral radiology used to assess the knowledge and skill across 5 different domains. The accuracy levels of ChatGPT, ChatGPT-4o (4o), Microsoft Co-pilot, DeepSeek, Gemini, and Meta AI were assessed and compared using the Chi-Square test. In addition, One-way ANOVA was used to compare the response time between different AI chatbots.

Results: Overall, Microsoft Co-pilot and ChatGPT-4o had the highest accuracy. ChatGPT had the fastest response time. Microsoft Co-pilot and DeepSeek, though not significant, had the highest accuracy for knowledge-based and skill-based queries. For accuracy on 5 domains, Microsoft Co-pilot and ChatGPT-4o had an accuracy of 100% for radiographic safety and DeepSeek was more accurate for radiographic diagnosis. Students took more time to respond than the collective time taken by AI chatbots.

Conclusion: Microsoft Co-pilot had an overall higher accuracy, responded more accurately for knowledge-based questions, and was 100% accurate for queries related to radiographic safety. ChatGPT-4o had the second highest accuracy and DeepSeek served better for radiographic diagnosis.

Advances in knowledge: This study is the first to systematically compare the accuracy and response time of multiple AI-driven tools in answering domain-specific MCQs in oral radiology. It highlights significant variability in performance across platforms, offering novel insights into the suitability of AI chatbots for educational use in dentistry.