Imaging Science in Dentistry最新文献

Purpose: Haller cells (HCs) represent an anatomical variation in the maxillofacial region, frequently linked to sino-nasal pathologies. Numerous regional studies have reported the prevalence of HCs using various imaging modalities. This systematic review aims to evaluate the prevalence of HCs as reported in the existing literature.

Materials and methods: A comprehensive literature search was carried out across multiple databases, including ScienceDirect, PubMed, Scopus, Dentistry and Oral Sciences (EBSCO), Ovid, and LILACS. Different keyword combinations employing Boolean logic were used to identify relevant studies. Data extraction procedures adhered closely to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The quality of studies was assessed using the Critical Appraisal Skills Program (CASP) checklist for cross-sectional studies.

Results: After data extraction, 9 studies qualified for critical analysis. The highest reported prevalence of HCs was 66.84%, whereas the lowest was 16%. Across these 9 studies, the average prevalence was 32.40%. Unilateral HCs predominated in most reported studies. Four studies provided details regarding the shapes of HCs, while size information was available in three studies. Eight of the 9 included studies demonstrated strong evidence quality according to the CASP checklist.

Conclusion: Approximately one-third of radiographic scans analyzed in published studies revealed the presence of HCs. Unilateral HCs were found to be more common than bilateral HCs. The most frequently reported shapes were round, ovoid, and teardrop, with the majority measuring between 2 and 4 mm.

Purpose: This study aimed to establish an expert consensus on a set of principles for radiation protection in oral and maxillofacial radiology in Korea. Although national and international guidelines exist, their practical application to dental radiology remains limited, with key clinical components not subject to mandatory enforcement. Therefore, guidelines tailored specifically to dental radiology are necessary to ensure consistent and effective radiation safety.

Materials and methods: A modified Delphi method was utilized, involving 20 experts-7 specialists in oral and maxillofacial radiology and 13 in medical radiology. A Guideline Development Committee initially drafted the principles, which were refined over 3 rounds of email-based surveys. Panelists evaluated each principle using a 9-point Likert scale, with quantitative scores and qualitative feedback informing the revision process.

Results: Consensus was reached on 10 principles, addressing radiographic justification, imaging scope limitations, pregnancy considerations, pediatric optimization, portable radiography, radiation dose monitoring and equipment operation. Final agreement scores approached 9.0, with standard deviations ≤0.7, confirming strong expert consensus.

Conclusion: The finalized principles constitute a structured, evidence-based guideline aligned with international standards while addressing specific challenges unique to oral and maxillofacial radiology. They offer practical strategies to enhance patient safety and standardize radiographic decision-making. Further research should investigate their clinical implementation and recommend periodic updates to reflect evolving technologies.

Purpose: This study aimed to evaluate artefact expression and volumetric distortion of endodontic obturation materials with varying radiopacity in root canal-treated teeth using cone-beam computed tomography (CBCT).

Material and methods: The radiopacity test was performed according to ANSI/ADA standards for AH Plus sealer, Bio-C Sealer, and conventional and bioceramic cones. Upper incisors were selected and instrumented with WaveOne Gold files (45/05). Teeth were individually positioned into empty sockets of a human jaw, and CBCT scans were initially performed (control group). Each tooth was subsequently filled with different combinations of root filling materials. Mean dentin gray values, image noise, and filling material volumes were measured and segmented. Data comparisons among groups were conducted using analysis of variance and the paired t-test (α=0.05).

Results: The conventional cone and AH Plus demonstrated the highest radiopacity. CBCT images exhibited significantly higher mean gray values, noise, and volumetric distortion for groups with conventional cones and AH Plus sealer (P<0.05).

Conclusion: Bioceramic materials, which had lower radiopacity, generated fewer artefacts and less volumetric distortion compared to conventional gutta-percha cones and AH Plus sealer.

Purpose: This study assessed the effectiveness of an educational video in reducing tongue positioning errors on panoramic radiographs.

Materials and methods: An educational video instructing patients on proper tongue positioning during panoramic radiograph acquisition was sent via WhatsApp (WhatsApp Inc., Menlo Park, CA, USA) at the time of appointment scheduling. Patients were instructed to view the video again before their appointment. Collected data included patients' sex, age, scheduling method, educational background, the necessity for panoramic radiograph retake, and the reason for retake. The frequency of retakes due to tongue positioning errors was compared with retrospective data from patients who did not receive the video, resulting in the evaluation of 1,088 panoramic radiographs. Descriptive data analyses were conducted, and simple and multiple logistic regression models were applied with a significance level of 5%.

Results: Of the 1,088 panoramic radiographs evaluated, 69 displayed tongue positioning errors. Of these, 53 radiographs were from patients without access to the educational video, whereas only 16 were from patients who had received the video (P<0.05). Patients without video access were 2.07 times more likely to exhibit tongue positioning errors than those who had access. The other variables assessed (sex, age, scheduling method, and educational background) did not significantly influence tongue positioning errors (P>0.05).

Conclusion: Providing patients with an educational video on proper tongue positioning significantly reduced tongue positioning errors on panoramic radiographs.

Purpose: Classifying cervical vertebral maturation (CVM) stages aids in determining the peak period of growth and in predicting growth rates and patterns. This study aimed to develop a multistage framework for the automated classification of CVM.

Materials and methods: The dataset consisted of 2325 lateral cephalograms. Two orthodontists independently classified these images into 6 categories. One object detection model (Faster RCNN) and 2 classification models (ResNet 101) were implemented using the Python programming language and the PyTorch library. The first classification model divided images into 2 primary groups (CS1-CS3 and CS4-CS6) based on the morphology of the C4 vertebra. The second model subsequently classified each primary group into their respective subcategories. Each classification model was trained and evaluated using a 10-fold cross-validation strategy. The learning process of the models was visualized with gradient-weighted class activation maps.

Results: The overall framework achieved an accuracy of 82.96%. Object detection for region-of-interest extraction reached mAP50 and mAP75 values of 100%. The first classification model demonstrated an accuracy of 99.10% on the hold-out test set. The classifier for CS1-CS3 images showed higher accuracy than the classifier for CS4-CS6 images (86.49% vs. 82.80%).

Conclusion: The accuracy achieved by this fully automated framework was promising.

Purpose: This study analyzed cone-beam computed tomography images of 27 patients with multiple myeloma at different disease stages to identify jawbone destruction patterns and assess their associations with clinical data.

Materials and methods: In this cross-sectional study, 2 trained examiners performed standardized, consensus-based image analyses. Lesions were classified into 4 distinct bone destruction patterns: diffuse, multilocular, unilocular, and punched-out. Clinical data were collected from medical records.

Results: The sample included 51.8% male and 48.2% female patients, predominantly between 42 and 60 years old. All cases exhibited diffuse bone destruction affecting both jaws. Multilocular and unilocular patterns were observed in 51.9% and 29.6% of cases, respectively, while no punched-out lesions were identified. The unilocular pattern was significantly associated with cases classified as International Staging System stage I and Durie-Salmon stage IIIA.

Conclusion: Among the studied cases of multiple myeloma, the most frequently observed bone destruction patterns were diffuse and multilocular. The absence of punched-out lesions may be attributable to the use of 3-dimensional imaging. A clear association was identified between the unilocular pattern and disease staging.

Purpose: This study aimed to evaluate the influence of different cone-beam computed tomography (CBCT) image reconstruction parameters (slice thickness, noise filter application and orthogonal plane) on the calculation of bone fractal dimension and, based on those findings, to determine the optimal protocol for this type of assessment.

Materials and methods: The sample consisted of 18 patients who underwent CBCT scans of the mandible and bone densitometry examinations. Four mandibular regions of interest were selected from the scans, with various image reconstruction parameters applied. Fractal dimension was calculated using the box-counting method. Two independent observers performed the evaluations, and all analyses were conducted with a significance level of 5%.

Results: The retromolar triangle and mandibular body regions did not demonstrate statistically significant differences when different tomographic reconstruction parameters were applied (P>0.05). The mandibular base did not display a consistent pattern that could define the influence of these parameters on its evaluation. The symphysis region showed improved performance in fractal analysis when using sagittal plane images with a 1 mm slice thickness.

Conclusion: Operator-dependent parameters inherent to navigation software can influence fractal dimension analysis, with variations depending on the region of interest. The most appropriate parameters for this evaluation were identified as the sagittal plane with a 1 mm slice thickness. Among the regions assessed, the mandibular body was found to be the most suitable for fractal dimension analysis in CBCT.

Purpose: This study was conducted to develop and evaluate a deep learning-based super-resolution approach for enhancing the quality of cone-beam computed tomography (CBCT) images in dentomaxillofacial imaging.

Materials and methods: A deep learning-based super-resolution method using the MIRNet-v2 model was developed to enhance CBCT image quality. The study used a dataset comprising 6,961 anonymized axial slices from 15 CBCT scans. High-resolution images served as ground truth, while low-resolution versions were created through artificial degradation, including downscaling, blurring, and noise addition. The model was evaluated using a 5-fold cross-validation strategy, employing peak signal-to-noise ratio (PSNR) and structural similarity index measure (SSIM) as metrics. Qualitative assessments conducted by 2 experienced radiologists involved criteria such as noise, sharpness, spatial resolution, and diagnostic quality, scored using a CBCT evaluation chart.

Results: The model significantly improved degraded CBCT images across all evaluation metrics. Enhanced images demonstrated mean PSNR values exceeding 35 dB and SSIM values over 0.85, with the highest performance achieved for blurred images (PSNR: 43.86±1.61, SSIM: 0.98±0.01). Subjective assessments indicated improvements in diagnostic quality, noise reduction, and spatial resolution, with outputs comparable to the original images in several degradation scenarios. Interobserver reliability was fair (Cohen kappa: 0.335). Notable improvements were observed for noise and artifact reduction in specific degradation groups, suggesting improved diagnostic utility.

Conclusion: Deep learning-based super-resolution demonstrates considerable potential for enhancing CBCT image quality, especially in scenarios involving blur and downscaling. These results suggest possible applications in low-dose imaging protocols and improved clinical decision-making.

Purpose: Temporomandibular joint osteoarthritis (TMJOA) is a significant subtype of temporomandibular joint disorders (TMDs). The purpose of this study was to comprehensively summarize the current literature on the use of artificial intelligence (AI) technologies in the diagnosis and management of TMJOA using cone-beam computed tomography (CBCT).

Materials and methods: This systematic review was pre-registered in the PROSPERO database (PROSPERO CRD42024509772). Up to December 2023, research was conducted using Google Scholar, Embase, MEDLINE, and Web of Science databases to identify studies evaluating the use of AI technologies in the management and diagnosis of TMJOA via CBCT. The search strategy included MeSH terms, keywords, and their combinations. Risk of bias was assessed using the ROBINS-I tool.

Results: Out of 2,543 articles retrieved, a total of 9 studies were included in this systematic review. All included studies were observational and employed AI models based on convolutional neural networks, including SVA, SSD, LightGBM, XGBoost, and YOLO. The performance of these models varied, with accuracy ranging from 73.5% to 99% and F1-scores between 0.80 and 0.86. Among these, YOLO demonstrated the highest accuracy for the assessment and diagnosis of TMJOA using CBCT scans.

Conclusion: AI algorithms developed for the automated diagnosis of TMJOA can be utilized by clinicians as decision-support tools. Incorporating diverse input data types, such as electronic medical records, radiomics features, and biomarkers, alongside diagnostic imaging may further increase the diagnostic accuracy for TMDs.

Purpose: This retrospective study aimed to evaluate the accuracy of facial scan (FS) to cone-beam computed tomography (CBCT) registration by comparing superimpositions on full-cranium and reduced field-of-view (FOV) CBCT, with the goal of assessing its potential to reduce radiation exposure without compromising diagnostic quality.

Materials and methods: CBCT scans from 50 patients were analyzed, integrating FS data obtained via 3D laser scanning. FSs were registered to both full-cranium and reduced FOV CBCT using landmark-based matching and a best-fit algorithm. Accuracy was evaluated by calculating the point-to-point surface distance between FS and CBCT soft-tissue renderings. The metrics used were root mean square distance (RMSD), Hausdorff distance (HD), and median distance (MD). Registration of FS onto full FOV CBCT served as the ground truth. Statistical analysis employed the Mann-Whitney U test to compare registration performance on both the overall surface and the facial midline.

Results: There was no significant difference in HD (P=0.288) between the 2 methods. However, median RMSD and MD were significantly lower for full-cranium CBCT (P=0.019). Midline alignment between FS and reduced FOV CBCT showed no visual discrepancies, with an MD of 0.35 mm along the midsagittal plane.

Conclusion: FS registration to reduced FOV CBCT provides clinically acceptable accuracy, particularly in the midline region, while substantially reducing radiation exposure. This approach is promising for a range of dental applications, especially in pediatric cases and situations prioritizing facial aesthetics. Further research is warranted to optimize this technique for diverse clinical contexts.