OBJECTIVES:To investigate periodontitis combined with carotid artery calcifications on panoramic radiographs in relation to carotid ultrasound findings of atherosclerotic disease among participants in the Malmö Offspring Dental Study. METHODS:In this population-based, cross-sectional cohort study, 410 participants (mean age 53.0±7.8 years) were examined by carotid ultrasound, panoramic and intraoral radiography. The panoramic radiographs were assessed for presence and shape of carotid artery calcifications and marginal bone loss, indicating current or past periodontitis. Groups with and without periodontitis stage III-IV and/or carotid artery calcifications were analyzed for associations to findings of three carotid ultrasound characteristics: total plaque area, number of plaques, and lumen reduction. Adjustments for covariates were performed. RESULTS:Participants with combined periodontitis and carotid artery calcifications (all shapes) had significantly greater total plaque area, number of plaques, and lumen reduction (P < 0.001). The findings for vessel-outlining shape combined with periodontitis was more severe but non-significant. Participants with combined findings had 13.7-times higher probability of having plaques on ultrasound, whereas those with carotid artery calcifications alone had 7.65-times higher probability than participants with no carotid artery calcifications or periodontitis (P < 0.001). CONCLUSIONS:Participants with periodontitis and carotid artery calcifications had more ultrasound findings, indicating more advanced atherosclerotic disease. Dentists should consider recommending patients with these findings to seek medical attention for cardiovascular risk factor evaluation and prevention. ADVANCES IN KNOWLEDGE:This study explore that participants with periodontitis combined with carotid artery calcification on panoramic radiographs have more advanced signs of atherosclerotic disease on ultrasound than participants with carotid artery calcifications but without periodontitis.
OBJECTIVES:This retrospective diagnostic accuracy study compared magnetic resonance imaging and ultrasonography in 98 temporomandibular joints from 49 patients for evaluating disc position, disc configuration, joint effusion, condylar degenerative changes, and bone marrow edema. METHODS:A total of 98 temporomandibular joints from 49 patients who underwent both modalities were retrospectively evaluated by two independent, blinded observers using established classification systems. All imaging was performed prior to the initiation of any specific TMJ treatment. Intra- and inter-observer agreement, the diagnostic accuracy of ultrasonography relative to the magnetic resonance imaging reference standard, diagnostic likelihood ratios, and associations between parameters were analysed statistically. RESULTS:Intra- and inter-observer agreement was good to excellent for both modalities (Kappa 0.71-0.91, p < 0.05). Ultrasonography showed high sensitivity and specificity for disc displacement (94.4-97.4% and 61.5-70.0%) and effusion (87.5-92.3% and 84.0-87.0%), but more limited performance for bone marrow edema, particularly in specificity (60.0-61.1%). On the left side, magnetic resonance imaging identified bone marrow edema in 63.3% of cases compared with 36.7% on ultrasonography (p = 0.015). Folded and convex disc configurations and marked or severe effusion were both associated with displacement without reduction (p ≤ 0.046). CONCLUSIONS:Ultrasonography appears suitable as a first-line screening modality for selected TMJ abnormalities, whereas magnetic resonance imaging remains indispensable whenever bone marrow pathology or complex internal derangement is suspected. ADVANCES IN KNOWLEDGE:This study provides direct, same-patient diagnostic accuracy data comparing ultrasonography with magnetic resonance imaging across multiple temporomandibular joint pathologies, including an indirect ultrasonographic assessment of bone marrow edema via cortical irregularity, clarifying which findings ultrasonography can reliably screen for and which still require magnetic resonance imaging confirmation.
OBJECTIVE:This study aimed to evaluate the structural characteristics of mandibular alveolar bone in patients with Type 1 diabetes mellitus (T1DM), Type 2 diabetes mellitus (T2DM), and systemically healthy controls using panoramic radiography-based radiomic analysis combined with machine learning algorithms. MATERIALS AND METHODS:A total of 225 panoramic radiographs (75 T1DM, 75 T2DM, 75 healthy controls) were retrospectively analyzed. ROIs were segmented from eight anatomical mandibular segments per subject, and 107 radiomic features were extracted using PyRadiomics. Interobserver reliability was confirmed by two-way random-effects ICC (≥0.85). A leakage-free pipeline was applied. Four machine learning algorithms were evaluated: Random Forest, ExtraTrees, SVM-RBF, and Logistic Regression. RESULTS:Significant differences were identified in age (Kruskal-Wallis p = 0.0003) and sex (χ²=17.857, p = 0.0001). The best single-segment performance was achieved in the left mandibular corpus with Logistic Regression (Accuracy=0.833, F1=0.832, AUC=0.958). All segments showed significant radiomic differences (FDR q < 0.001). Sensitivity of 1.000 was achieved for T1DM and AUC=1.000 for T2DM. The feature glszm_SizeZoneNonUniformityNormalized showed the strongest discriminative power (H = 86.928, ε²=0.578). CONCLUSION:Panoramic radiography-based radiomic analysis demonstrates high diagnostic performance in non-invasively distinguishing mandibular bone alterations among T1DM, T2DM, and healthy individuals, with potential as a clinical bone monitoring tool.
OBJECTIVES:To compare the diagnostic performance of three multimodal AI chatbots on oral and maxillofacial radiographic images and to examine how additional information, delivery mode, and user-suggested diagnoses affect accuracy. METHODS:Three AI chatbots (GPT-5.1, Gemini 3 Flash, Claude Opus 4.7) were tested on 90 cases comprising normal controls, osteomyelitis, and benign jaw lesions. Inputs were combinations of a panoramic image, a cropped panoramic image, an axial CBCT image or a text-based cue. Inputs were delivered all at once or sequentially. Accuracy was scored at category and specific-diagnosis levels using non-parametric tests with false-discovery-rate correction. RESULTS:With the panoramic image alone, accuracy for diseased cases was low (0-60%) but rose to as high as 38-92% in each model's best condition with added information. A cropped image was the most consistently beneficial additional visual input, whereas an axial CBCT image provided less improvement. GPT-5.1 recognised normal cases well but missed lesions, Gemini 3 was sensitive but less specific, and Claude 4.7 defaulted to benign diagnoses. Correct verbal cues increased accuracy, whereas a misleading cue caused decline. Gemini 3 accepted a false benign suggestion in 96% of cases it had initially classified as normal. For benign lesions, specific-diagnosis accuracy was almost half of category-level accuracy. CONCLUSIONS:Accuracy was strongly affected by model choice, information type and user-suggested diagnoses, but no model reached a level that would be acceptable for clinical use. ADVANCES IN KNOWLEDGE:This multi-model comparison isolates the effects of information type, delivery mode, and sycophancy in oral and maxillofacial radiology.
OBJECTIVES:Developing methods that minimize radiation exposure in skeletal age assessment for orthodontic planning and growth monitoring in pediatric populations is a priority. This study aimed to evaluate the diagnostic efficacy of ultrasonography as a non-ionizing alternative in bone age estimation and to analyze the correlation between ultrasonographic skeletal maturation and chronological age. METHODS:In this cross-sectional study, the left hand-wrist region of 131 individuals aged 8-18 years was evaluated simultaneously using digital radiography and ultrasonography. Skeletal maturation was analyzed based on the epiphysis-diaphysis relationship of the phalanges and radius, the presence of sesamoid bone, and bone age estimation based on the Greulich-Pyle atlas. In addition, the ossification ratios (o/O) of the distal radius and ulna were calculated. Friedman, Wilcoxon signed-rank, McNemar tests, and regression analyses were used to compare the data. RESULTS:A strong correlation was found between chronological age, ultrasonographic age, and radiographic age. Statistically significant differences were found between ultrasonography and radiography measurements in all middle phalanges (MP2-MP5), the distal phalanx of the fourth finger (DP4), the distal and proximal phalanges of the first finger (DP1, PP1), proximal phalanges of the second finger (PP2) and the radius (p < 0.05). A high correlation (r = 0.862) was observed between the two methods used to detect sesamoid bones. A strong positive correlation (rs ≈ 0.70) was observed between chronological age and ultrasonographic ossification rates; the explanatory power of radius and ulna measurements on age was 54%. CONCLUSIONS:Ultrasonography shows a strong correlation with both chronological and radiographic age and demonstrates high efficacy in detecting sesamoid bones and monitoring ossification rates. Statistically significant differences have been found between radiographic examination and ultrasonography in evaluating the epiphysis-diaphysis relationship of the phalanges. ADVANCES IN KNOWLEDGE:This research demonstrates that ultrasonography is a reliable, non-ionizing method for skeletal age assessment and shows significant diagnostic consistency across anatomical regions, similar to that of conventional radiography. Furthermore, it supports the clinical utility of ultrasonography as a reliable, radiation-free method and contributes to ongoing efforts to establish standardized, non-invasive assessment methods.
OBJECTIVES:The current study aimed to quantify the diagnostic accuracy of commonly utilized chatbots including Gemini, Copilot, Claude, and specialized architectures like Manus in the detection and differential diagnosis of various jaw lesions, while concurrently evaluating the clinical safety and fidelity of the information they provide. MATERIALS AND METHODS:Cone beam computed tomography (CBCT) dataset from 97 patients presented with jaw lesions were collected and anonymized. Panoramic 2D views were reconstructed from Digital Imaging and Communication in Medicine (DICOM) of all cases using Bluesky Plan software and provided to 4 chatbots (Gemini 2.5 Pro, Copilot, Claude and Manus). Moreover, the DICOM data was provided to Manus followed by prompting. The reports generated were evaluated for accuracy, relevance and feasibility. RESULTS:Statistically significant differences were detected between the chatbots in all measured parameters. In all evaluated parameters Manus CBCT showed the most accurate results (95% of lesions were detected and correctly diagnosed,). Gemini 2.5 pro ranked second where 80% of lesions were detected and 56% were correctly diagnosed. Manus Pan showed less accurate results. The least accurate results were detected in Copilot and Claude. CONCLUSION:Significant discrepancies exist among artificial intelligence (AI) chatbots regarding their diagnostic accuracy in reporting jaw lesions. Notably, the integration of raw 3-dimensional CBCT data substantially optimizes chatbot performance in lesion detection and diagnosis, as demonstrated by Manus architecture.
OBJECTIVE:To evaluate the impact of exposure setting variations on contrast and spatial resolution (SR) in CMOS and direct-conversion CMOS (DC-CMOS) intraoral sensors. METHODS:Ten images of a DDQA phantom were acquired for each assessed condition using three sensors (CMOS-I, CMOS-S, DC-CMOS) and two X-ray units (HH: handheld; WM: wall-mounted). HH was set at 60kVp/2.5mA, and WM was set at 60kVp/7mA and 70kVp/7mA. Each combined sensor-x-ray unit condition was exposed at 0.02, 0.04, 0.05, 0.08, 0.10, 0.16, 0.20, 0.25, 0.32, 0.40, 0.50, 0.63, 0.80, and 1.00s. One observer selected 2 × 2 mm ROIs from the third and fifth steps of the DDQA step-wedge and measured their mean gray values using Fiji macro. Contrast was calculated by subtracting the mean gray value of the third step from the fifth step for each group. SR was determined by identifying the line pair with the highest value, in which five peaks and four valleys were distinguishable. Descriptive statistics were calculated for SR and three-way ANOVA and Tukey's post-hoc tests for contrast (α = 0.05). RESULTS:Across all exposure parameters, CMOS-I exhibited the highest mean contrast, followed by DC-CMOS and CMOS-S (p < 0.001). HH yielded the highest mean contrast, which was significantly greater than WM (p < 0.001). CMOS-S exhibited the highest SR, and DC-CMOS the lowest, although SR remained constant for DC-CMOS across all exposure times. CONCLUSION:Sensor type, x-ray unit, and exposure time influenced image contrast and spatial resolution, while variations in kVp had minimal impact on these image quality parameters.
OBJECTIVES:Although deep learning for periodontitis diagnosis on panoramic radiographs has advanced rapidly, most studies use single-vendor data and cross-vendor generalization is rarely evaluated. Therefore, we evaluate the cross-vendor robustness of a hybrid CNN-CAD framework for automated four-stage periodontitis classification. METHODS:Five hundred panoramic radiographs were retrospectively collected from three vendors (Instrumentarium, n=400; Vatech, n=50; PointNix, n=50). The framework extends a previously published hybrid pipeline by adding a YOLO-based CNN for missing-teeth quantification, enabling four-stage classification according to the 2017 World Workshop criteria. Three dataset configurations were evaluated: pooled multi-vendor training and two leave-one-device-out (LODO) splits. We compared segmentation backbones (U-Net, Dense U-Net, SegNet, Mask R-CNN) and YOLO detector variants. Agreement with three oral and maxillofacial radiologists (3, 5 and 10 years of experience) was assessed using mean absolute difference (MAD), Pearson and intraclass correlation, Bland-Altman, and Passing-Bablok analyses. RESULTS:Under pooled multi-vendor training, Mask R-CNN achieved Dice coefficients of 0.96, 0.92 and 0.94 for periodontal bone level, cemento-enamel junction level and teeth/implants respectively; CNNv4-tiny reached a mean AP of 0.86 for missing teeth. The MAD between automated and expert staging was 0.31, overall image-level ICC was 0.93 (95% CI 0.86-0.97; p<0.01), and Bland-Altman bias against the most experienced radiologist was 0.007. Under LODO, Dice coefficient dropped to 0.75-0.86 (all p<0.001 versus pooled), quantifying substantial vendor-induced domain shift. CONCLUSIONS:The hybrid framework achieves expert-level agreement under pooled multi-vendor training but degrades in held-out vendors, providing a quantitative reference for vendor-induced domain shift in panoramic radiograph AI and motivating vendor-aware training or domain adaptation in future clinical deployments. ADVANCES IN KNOWLEDGE:This work provides, to our knowledge, the first cross-vendor benchmark for deep-learning-based periodontitis staging on panoramic radiographs and quantifies vendor-induced domain shift directly addressing the external-validation gap recently identified in this journal.
Objectives Accurate image registration is essential for successful digital dental implant planning. Surface-based registration, commonly used in clinical software, is sensitive to cone-beam CT (CBCT) artifacts and relies on manual landmark selection, potentially reducing accuracy. Marker-based registration offers improved precision but is underused due to its technical complexity and time demands. The purpose of this ex-vivo study was to evaluate the accuracy of a novel marker-based registration method using limited-view CBCT reconstructions derived from 2 orthogonal projection images and to compare it with a conventional surface-based registration method.Methods An ex-vivo model consisting of a maxillary arch with removable 3D-printed teeth and a radiographic guide containing radiographic markers was used to simulate 5 metal artifact conditions. Full-view CBCT scans were acquired for each condition. For the conventional method, 3 examiners independently performed dual-scan registrations using user-defined surface landmarks on full CBCT reconstructions. For the proposed method, examiners selected orthogonal projection images where markers were clearly visible and limited-view reconstructions were generated to identify marker centroids. Registration error was measured as the point-to-point distance between corresponding surface reference points, standardized to a common frame of reference. Inter-rater reliability was also assessed.Results Both methods maintained consistent performance across all artifact conditions. The proposed method demonstrated greater accuracy, with lower point-to-point registration errors and less spatial variation. Inter-rater reliability was excellent for the proposed method and good for the conventional approach.Conclusion The proposed marker-based registration method using orthogonal projection images and limited-view CBCT reconstructions showed higher accuracy than conventional surface-based registration under controlled ex-vivo conditions. Although the workflow currently requires additional examiner input, it may improve precision in dual-scan protocols for implant planning. Future clinical studies and software developments are required to support clinical implementation.
OBJECTIVE:To develop and validate an artificial intelligence model capable of identifying the presence of the palatoglossal airway in panoramic radiographs, a factor that may impair diagnostic image quality, thereby providing an intermediate technical evaluation tool prior to diagnostic image analysis. MATERIALS AND METHODS:A total of 456 panoramic radiographs were selected from a radiographic database containing approximately 10,000 images and independently classified by three evaluators into control (tongue positioned on the palate) and test (tongue not positioned on the palate) groups, used to establish the gold standard for comparison with the algorithm's classification. The AI model was developed using YOLOv11n architecture detection for training, validation, and testing, respectively. The model's performance was evaluated using the metrics of sensitivity, specificity, accuracy, recall, precision, and F1 score. RESULTS:The AI model achieved 89.3% accuracy in detecting the presence of a palatoglossal airway associated with the classification of compromised image quality, demonstrating balanced sensitivity and specificity (both 89.47%) and excellent agreement with the reference standard (Kappa index = 1.0). CONCLUSION:The proposed AI-based model demonstrated high accuracy and robustness in detecting tongue-to-palate malposition in panoramic radiographs, a frequent error associated with the palatoglossal airway space that compromises diagnostic image quality. CLINICAL RELEVANCE:The developed algorithm is available through the website, where it is possible to obtain an instant technical analysis of the panoramic image, capable of preventing errors in subsequent diagnostic interpretation.
OBJECTIVE:To determine category-specific supracrestal tissue attachment (STA) dimensions and apply these values to calibrate high-frequency ultrasound-derived measurements to match clinical probing depth (PD), and to examine the reliability of ultrasound landmark annotation in healthy and diseased cohorts. METHODS:Intraoral high-frequency ultrasound (40 MHz) imaging was performed to acquire images from 34 subjects (20 healthy and 14 with stage II-IV periodontitis). Four trained raters annotated 955 teeth for the gingival margin (GM), cemento-enamel junction (CEJ), and alveolar bone crest (ABC). The image-based gingival height (iGH) was defined as the distance from the gingival margin to the average bone crest. Ultrasound assessment is in terms of distances to the bone crest, whereas probing depth is measured to the supracrestal tissue attachment. Ultrasound measurements were calibrated using category-specific STA values to estimate probing depth. Method agreement between iPD and clinical PD was evaluated via Bland-Altman analysis using a ±1 mm clinical acceptance limit. This prospective calibration-validation study (34 subjects; 955 annotated tooth-surface observations) compared high-frequency ultrasound-derived measurements with conventional clinical periodontal probing depth measurements. The dataset was partitioned into a calibration set (721 observations, 27 subjects) and an independent validation set (234 observations, 7 subjects). RESULTS:Inter- and intra-rater reliability was high, with correlation coefficients ranging from 0.894 to 0.998. Calibrated STA values ranged from 1.349 mm for molar-buccal to 2.970 mm for anterior-buccal teeth, yielding an overall mean of 2.162±0.549 mm that falls within established histological reference ranges. Validation analysis (n = 234 teeth) demonstrated 80.8% agreement between iPD and clinical PD within ±1 mm, with a mean bias of -0.137 mm and limits of agreement of -1.718 to + 1.443 mm. CONCLUSIONS:Category-specific STA-calibrated high-frequency intraoral ultrasound enables clinically acceptable PD estimation across tooth types and surfaces without ionizing radiation or probe-induced discomfort. The observed level of agreement lies within the reported inter-examiner variability of conventional periodontal probing. ADVANCES IN KNOWLEDGE:This study represents the initial comprehensive characterization of supracrestal tissue attachment for all tooth types and surfaces by means of high-frequency ultrasound, which illustrates that calibration for each of these tooth type groups is essential for accurate estimation of probing depth. This approach may provide a non-invasive adjunct to periodontal probing assessment.
OBJECTIVES:This study aimed to evaluate pediatric dentists' knowledge and clinical practices regarding dentomaxillofacial imaging, with particular emphasis on guideline-consistent indication selection, radiation protection, and dose optimization principles, in accordance with established international guidelines (EAPD, AAPD, and DIMITRA). METHODS:A structured cross-sectional questionnaire was distributed to pediatric dentists from eight countries (Egypt, Jordan, Mexico, Pakistan, Poland, Saudi Arabia, Türkiye, and the USA) through a convenience and snowball sampling approach. The survey assessed knowledge of radiation protection, radiographic parameters, cone-beam computed tomography (CBCT) indications and resolution selection, and routine clinical practices. Descriptive and comparative analyses were performed. RESULTS:A total of 488 pediatric dentists participated, with a mean knowledge score of 39.9 ± 4.7, and 75.8% demonstrated moderate knowledge. Awareness of dose-reduction strategies was limited, as 41.6% identified rectangular collimation as the most effective radiation protection measure and 17.7% recognized its impact on radiation dose. Knowledge of dose-optimization principles varied: 68.0% of respondents demonstrated knowledge of the ALARA/ALADA principle, whereas 46.5% demonstrated knowledge of the ALADAIP concept. Clinical practices showed patterns that were partially consistent with guideline recommendations. Regarding CBCT, 57.4% had not received formal training, 43.6% were uncertain about appropriate field-of-view selection, and 91.0% reported fewer than five scans per month. CONCLUSIONS:Pediatric dentists demonstrated moderate radiation knowledge but inconsistent application of radiation protection principles. These findings indicate a gap between theoretical knowledge and clinical practice. Targeted, practice-oriented education is needed to improve dose optimization and CBCT-related decision-making. Findings should be interpreted with caution due to the non-probability sampling design. ADVANCES IN KNOWLEDGE:This multinational study highlights persistent gaps in pediatric dental imaging practices and supports the need for standardized, competency-based training to improve radiation safety.
Aims This study investigated whether antiresorptive drug (ARD) therapy is associated with lamina dura (LD) thickening, defined as a radiographic increase in the thickness of the normally thin, radiopaque cortical line surrounding the tooth root. It further evaluated whether LD thickening serves as a radiographic marker and risk indicator for medication-related osteonecrosis of the jaw (MRONJ). Methods Panoramic radiographs from 65 ARD-treated patients (University Hospital Leuven) and 65 age- and sex-matched controls were analyzed. Inclusion criteria were prior oncological diagnosis, high-dose intravenous ARD, and radiographs before and after therapy. Three blinded oral and maxillofacial radiologists categorized LD appearance into 4 grades: (0) not/barely visible, (1) normal, (2) mild thickening, and (3) marked thickening. Group differences and longitudinal changes were evaluated using appropriate non-parametric and time-to-event analyses. Results Among 130 participants, LD thickness remained stable in controls but increased in ARD-treated patients (P < .001). Within the ARD group, LD thickening changed over time (P < .001): 30.6% showed no change, 55.4% developed mild thickening, and 13.8% marked thickening. Controls showed minimal change (P = .011), with 9.2% developing mild thickening. Kaplan-Meier analysis estimated a median time to LD thickening of 27 months, with a higher thickening probability in ARD-treated patients than controls (P < .001). Lamina dura thickening was not directly associated with MRONJ (P = .39). Conclusion Lamina dura thickening is strongly associated with long-term ARD exposure and shows progressive changes. Although not directly associated with MRONJ in this cohort, it may still represent a potential risk indicator, warranting confirmation in further studies.
Objective: To validate the diagnostic sufficiency of a low-dose (LD) cone-beam CT (CBCT) protocol for dental implant assessment by comparing it to a standard-dose (SD) protocol in a clinical setting. The study evaluated linear measurement accuracy, subjective clarity of anatomical landmarks, and the impact on bone microarchitecture assessment. Methods: This retrospective study analyzed preoperative (SD) and postoperative (LD) CBCT scans from 37 patients (37 SD and 37 LD scans for both maxillary and mandibular sites). The LD protocol achieved a 76.7% dose reduction by decreasing tube current and exposure time. The diagnostic utility was assessed: (1) subjective clarity scoring of the mandibular canal and maxillary sinus floor; (2) objective linear measurements of key anatomical dimensions; and (3) quantitative analysis of bone microstructural parameters (trabecular number [Tb.N], trabecular separation [Tb.Sp], trabecular thickness [Tb.Th], bone volume fraction [BV/TV]). Reliability assessment was also performed for clarity scoring and quantitative measurements. Statistical comparisons were performed using Chi-square and paired-samples t-tests. Results: No statistically significant differences were found between the LD and SD protocols in the subjective clarity of anatomical structures (P > .05) or in the accuracy of linear measurements (P > .05). However, all 4 bone microstructural parameters showed statistically significant differences between the 2 protocols in both the maxilla and mandible (P < .05 for all). Intra- and inter-examiner assessments demonstrated substantial to good consistency across all qualitative (weighted Kappa >0.611) and quantitative (intra-class correlation coefficient [ICC] >0.702) parameters. Conclusion: This study provides clinical evidence that for the specific CBCT unit tested, the optimized LD CBCT protocol reduces patient radiation exposure by over 76.7% for dental implant assessment without compromising the diagnostic accuracy required for linear measurements and visualization of key anatomical landmarks. Therefore, for the tested model, the LD protocol is sufficient for preoperative CBCT scanning in implant dentistry. This offers a clinically validated method for enhancing patient safety in this specific context, effectively applying the As Low As Diagnostically Acceptable, Indication-oriented, and Patient-specific (ALADAIP) principle.
Objectives To compare the diagnostic accuracy of a new wireless direct-conversion digital intraoral sensor to current indirect-conversion complementary metal-oxide semiconductor (CMOS) and photostimulable storage phosphor (PSP) sensors for detecting proximal caries. Methods The sample in this ex vivo study were 28 human premolars with 21 micro-CT verified non-cavitated proximal dental carious lesions. Images were obtained using 3 digital intraoral systems: a wireless direct-conversion sensor, a wired indirect-conversion CMOS sensor, and a PSP sensor. A custom phantom was constructed providing a limited dental arch segment comprising a molar, first premolar, and canine. The premolar was substituted and the phantom imaged using each intraoral system with (filtered) and without (raw) the application of a manufacturer-recommended enhancements, providing 168 images. Eight oral radiologists assessed the images using a 5-point scale. Receiver operating characteristic analysis was performed to calculate sensitivity, specificity, and the area under the curve (AUC) and compared across modalities using 2-way analysis of variance (ANOVA) with post hoc Tukey's test at an a priori level of significance of 0.05. Results The AUC ranged from 0.58 to 0.73 (sensitivity range: 0.21-0.68, specificity range: 0.69-0.92). The wireless direct-conversion sensor (0.72 +/- 0.06) showed diagnostic performance comparable to CMOS (0.72 +/- 0.06) and superior to PSP (0.58 +/- 0.07) for raw images (P < .001). The direct-conversion sensor without image enhancement (0.68 +/- 0.18) demonstrated the highest sensitivity, whereas the PSP without image enhancement (0.21 +/- 0.09) had the lowest sensitivity. Application of image enhancement improved PSP performance (0.48 +/- 0.16), approximating that of the other systems. Conclusions Based on this ex vivo study, the wireless direct-conversion and CMOS sensors demonstrated similar diagnostic performance, superior to PSP in unfiltered conditions. These findings should be interpreted in light of the ex vivo design and modest sample size.
Objective To evaluate the methodological quality of dental cone-beam CT (CBCT) diagnostic reference levels (DRLs) studies and reports, identify factors that limit DRL comparison, assess the level and methods of dose optimization, and clarify obstacles, both in dose optimization and DRL establishment.Methods A systematic search was applied across 5 databases and gray literature with International Atomic Energy Agency (IAEA) member countries contacted, to identify dental CBCT DRL studies and national reports. Studies/reports containing DRL establishment procedures, insufficient methodological detail, and adopted DRLs were excluded. Methodological quality was assessed using a modified Effective Public Health Practice Project tool, aligned with a checklist developed in accordance with International Commission on Radiological Protection (ICRP) 135.Results Of 320 reports screened, 19 were included. Diagnostic reference levels were clinical indication or field of view (FOV) based, using dose/kerma-area-product (DAP/KAP) metrics. Overall, 63% of studies had moderate methodological quality; DRL comparability was limited due to gaps or inconsistencies in reporting of exposure parameters, FOV, and heterogeneous indication grouping. Substantial dose variability was observed within the same clinical indications (2- to 10-fold) and FOV categories (3- to 10-fold), reflecting routine use of large FOVs irrespective of indication, reliance on manufacturer default protocols, limited understanding/education/training of exposure settings or optimization strategies, non-standardized system FOV settings, and unauthorized CBCT operators.Conclusions The majority of CBCT DRL studies are not of high quality. Improving DRL reporting quality requires interdisciplinary collaboration; digitized-dose recording with robust retrospective management of protocols, dose, indications; national dose registries for periodic dose audit; improved clinician education/engagement, strengthened regulatory oversight, and potentially international standardized frameworks.
OBJECTIVES:This study aimed to investigate cranial base and clival morphology using cone-beam computed tomography (CBCT) in patients with obstructive sleep apnoea (OSA) and matched controls, with particular emphasis on angular measurements and anatomical variations of the clivus and surrounding structures. METHODS:CBCT scans of 73 OSA patients and 73 age- and sex-matched controls were retrospectively evaluated. The skull base angle (SBA) and clivus angle (CA) were measured, and anatomical variants, including sphenoid sinus pneumatization types, sella turcica morphology, fossa navicularis magna (FNM), canalis basilaris medianus (CBM), and craniopharyngeal canal (CPC), were assessed. Group comparisons and regression analyses were performed to identify associations between these parameters and apnoea-hypopnea index (AHI). RESULTS:Compared with controls, patients with OSA exhibited a significantly smaller SBA and a significantly larger CA (both p < 0.001). The distribution of sphenoid sinus pneumatization patterns differed significantly between the groups (p = 0.018). Presellar sphenoid sinus pneumatization was more frequent in the OSA group. Post-sellar pneumatization was the predominant pattern in both groups and was more frequent in controls. No significant differences were observed in sella turcica morphology, CBM, or FNM between groups. The CPC was not detected in any participant. CONCLUSION:CBCT-based evaluation demonstrated that adults with OSA had a smaller cranial base angle, a larger clivus angle, and more frequent sphenoid sinus pneumatization anterior to the sella turcica compared with matched controls. Although these findings should be interpreted within a multifactorial framework, their assessment may provide complementary anatomical information in the radiologic evaluation of OSA. ADVANCES IN KNOWLEDGE:This study presents a CBCT-based assessment of cranial base characteristics in adults with OSA, identifying angular features and anatomical variants that may be associated with upper airway narrowing. These findings suggest a potential role for cranial base configuration in OSA risk assessment, particularly in patients without overt maxillofacial abnormalities.
OBJECTIVES:Temporomandibular disorders (TMDs) are frequently associated with internal derangement (ID) of the temporomandibular joint (TMJ), and MRI is the gold standard for diagnosis. However, most studies focus on sagittal disc position, neglecting coronal mediolateral displacement, while traditional quantitative methods have limitations. This study aimed to validate a novel dual-circle method for assessing coronal mediolateral disc displacement. METHODS:Thirty-eight asymptomatic volunteers (76 TMJs) underwent 3.0 T MRI. Two observers measured mediolateral displacement using both the classical Schmitter method and the dual-circle method. Inter-observer reliability was evaluated via intraclass correlation coefficient (ICC) and Cronbach's α, with correlation and diagnostic efficacy analyzed using Spearman's coefficient and McNemar's test. RESULTS:Results showed the dual-circle method detected 15 (19.7%) disc displacements versus 7 (9.2%) via the conventional method, with significantly higher sensitivity (P < .05). Measurements of the 2 methods were strongly positively correlated (r = 0.868, P < .05). All dual-circle parameters achieved excellent inter-observer reliability (ICC = 0.715-0.965), markedly superior to the conventional method (partial ICC = 0.525) with better consistency. CONCLUSIONS:The dual-circle method offers intuitive, accurate quantification of mediolateral disc displacement, reducing misdiagnoses. It is recommended as a practical option for coronal MRI analysis of TMJ disc position, with the potential to optimize TMD diagnosis and advance understanding of the morphological diversity of the TMJ disc.
