Search Results (144)

Background: Periodontitis is a multifactorial disease leading to the loss of clinical attachment and alveolar bone. The diagnosis of periodontitis involves a clinical examination and radiographic evaluation, including panoramic images. Panoramic radiographs are cost-effective methods widely used in periodontitis classification. The remaining bone height (RBH) is a parameter used to assess the alveolar bone level. Large language models are widely utilized in the medical sciences. ChatGPT, the leading conversational model, has recently been extended to process visual data. The aim of this study was to assess the effectiveness of the ChatGPT models 4.5, o1, o3 and o4-mini-high in RBH measurement and tooth counts in relation to dental professionals’ evaluations. Methods: The analysis was based on 10 panoramic images, from which 252, 251, 246 and 271 approximal sites were qualified for the RBH measurement (using the models 4.5, o1, o3 and o4-mini-high, respectively). Three examiners were asked to independently evaluate the RBH in approximal sites, while the tooth count was achieved by consensus. Subsequently, the results were compared with the ChatGPT outputs. Results: ChatGPT 4.5, ChatGPT o3 and ChatGPT o4-mini-high achieved substantial agreement with clinicians in the assessment of tooth counts (κ = 0.65, κ = 0.66, κ = 0.69, respectively), while ChatGPT o1 achieved moderate agreement (κ = 0.52). In the context of RBH values, the ChatGPT models consistently exhibited a positive mean bias compared with the clinicians. ChatGPT 4.5 was reported to provide the lowest bias (+12 percentage points (pp) for the distal surfaces, width of the 95% CI for limits of agreement (LoAs) ~60 pp; +11 pp for the mesial surfaces, LoA width ~54 pp). Conclusions: ChatGPT 4.5 and ChatGPT o3 show potential in the assessment of tooth counts on a panoramic radiograph; however, their present level of accuracy is insufficient for clinical use. In the current stage of development, the ChatGPT models substantially overestimated the RBH values; therefore, they are not applicable for classifying periodontal disease. Full article

Background/Objectives: Amelogenesis imperfecta (AI) represents a heterogeneous group of inherited disorders affecting the quality and quantity of dental enamel, making clinical diagnosis challenging. This study aimed to identify genetic variants in Slovenian patients with non-syndromic AI and to evaluate enamel morphology using radiographic parameters. Methods: Whole exome sequencing (WES) was performed on 24 AI patients and their families. Panoramic radiographs (OPTs) were analyzed using Fiji ImageJ to assess crown dimensions, enamel angle (EA), dentine angle (DA), and enamel–dentine mineralization ratio (EDMR) in lower second molar buds, compared to matched controls (n = 24). Two observers independently assessed measurements, and non-parametric tests compared EA, DA, and EDMR in patients with and without disease-causing variants (DCVs). Statistical models, including bootstrap-validated random forest and logistic regression, assessed variable influences. Results: DCVs were identified in ENAM (40% of families), AMELX (15%), and MMP20 (10%), including four novel variants. AI patients showed significant enamel deviations with high reproducibility, particularly in hypomineralized and hypoplastic regions. DA and EDMR showed significant correlations with DCVs (p < 0.01). A bootstrap-validated random forest model yielded a 90% (84.0–98.0%) AUC-estimated predictive power. Conclusions: These findings highlight a novel and reproducible radiographic approach for detecting developmental enamel defects in AI and support its diagnostic potential. Full article

Background: Radiographic evaluation of bone regeneration following maxillary sinus floor elevation commonly emphasizes volumetric gains. However, the qualitative microarchitecture of the regenerated bone, particularly when assessed via two-dimensional imaging modalities, such as panoramic radiographs, remains insufficiently explored. This study aimed to evaluate early trabecular changes in grafted maxillary sinus regions using fractal dimension, first-order statistics, and gray-level co-occurrence matrix analysis. Methods: This retrospective study included 150 patients who underwent maxillary sinus floor augmentation with bovine-derived xenohybrid grafts. Postoperative panoramic radiographs were analyzed at 6 months to assess early healing. Four standardized regions of interest representing grafted sinus floors and adjacent tuberosity regions were analyzed. Image processing and quantitative analyses were performed to extract fractal dimension (FD), first-order statistics (FOS), and gray-level co-occurrence matrix (GLCM) features (contrast, homogeneity, energy, correlation). Results: A total of 150 grafted sites and 150 control tuberosity sites were analyzed. Fractal dimension (FD) and contrast values were significantly lower in grafted areas than in native tuberosity bone (p < 0.001 for both), suggesting reduced trabecular complexity and less distinct transitions. In contrast, higher homogeneity (p < 0.001) and mean gray-level intensity values (p < 0.001) were observed in the grafted regions, reflecting a more uniform but immature trabecular pattern during the early healing phase. Energy and correlation values also differed significantly between groups (p < 0.001). No postoperative complications were reported, and resorbable collagen membranes appeared to support graft stability. Conclusions: Although the grafted sites demonstrated radiographic volume stability, their trabecular architecture remained immature at 6 months, implying that volumetric measurements alone may be insufficient to assess biological bone maturation. These results support the utility of advanced textural and fractal analysis in routine imaging to optimize clinical decision-making regarding implant placement timing in grafted sinuses. Full article

Background/Objectives: Craniofacial microsomia (CFM), previously known as hemifacial microsomia, is a congenital condition involving structures derived from the first and second pharyngeal arches. CFM is characterized by asymmetrical craniofacial growth, affecting the mandible, ear, orbit, soft tissues, and facial nerve. Functional therapy is among the treatment options for mild to moderate cases. This study aimed to assess the effect of functional therapy on mandibular growth in patients with CFM by comparing mandibular and condylar height on the affected and unaffected sides, using pre- and post-treatment panoramic radiographs. Methods: A retrospective longitudinal study was conducted on 14 patients treated with functional therapy with the Asymmetrical Functional Activator (AFA) appliance. Mandibular ramus height (Co-Go) and condylar height (Co-Is) were measured bilaterally on pre- (T0) and post-treatment (T1) panoramic radiographs. Growth differences and rates were analyzed using descriptive and inferential statistics. Results: A significant increase in the mandibular ramus height (Co-Go) and in condylar height (Co-Is) was observed on the affected side from T0 to T1. The increase in mandibular ramus height was significantly greater on the affected side compared to the unaffected side (p = 0.0016). Although condylar height increased significantly on both sides over time, the difference in growth rate between sides was not statistically significant (p = 0.7148). Conclusions: Functional therapy may contribute to reducing mandibular asymmetry in CFM patients by enhancing the growth of the affected mandibular ramus, but the asymmetry may still be present at the end of treatment. These findings support its use in the early management of mild to moderate CFM. Full article

Background/Objectives: Different sized calcified masses called pulp stones are often detected in dental pulp and can impact dental procedures. The current research was conducted with the aim of measuring the ability of artificial intelligence algorithms to accurately diagnose pulp and pulp stone calcifications on panoramic radiographs. Methods: We used 713 panoramic radiographs, on which a minimum of one pulp stone was detected, identified retrospectively, and included in the study—4675 pulp stones and 5085 pulps were marked on these radiographs using CVAT v1.7.0 labeling software. Results: In the test dataset, the AI model segmented 462 panoramic radiographs for pulp stone and 220 panoramic radiographs for pulp. The dice coefficient and Intersection over Union (IoU) recorded for the Pulp Segmentation model were 0.84 and 0.758, respectively. Precision and recall were computed to be 0.858 and 0.827, respectively. The Pulp Stone Segmentation model achieved a dice coefficient of 0.759 and an IoU of 0.686, with precision and recall of 0.792 and 0.773, respectively. Conclusions: Pulp and pulp stones can successfully be identified using artificial intelligence algorithms. This study provides evidence that artificial intelligence software using deep learning algorithms can be valuable adjunct tools in aiding clinicians in radiographic diagnosis. Further research in which larger datasets are examined are needed to enhance the capability of artificial intelligence models to make accurate diagnoses. Full article

This study aimed to demonstrate the Convolutional Neural Network (CNN) algorithm’s efficiency in detecting alveolar bone loss using panoramic radiographs. The comparison was evaluated among 1874 pictures retrieved from an institution, from which the training set included 953 showing bone loss and 921 normal cases. A confusion matrix was performed for statistical analysis. The CNN method correctly identified 92 out of 100 bone loss cases and 89 out of 100 healthy cases. The model showed a sensitivity of 0.8327, a specificity of 0.8683, a precision of 0.8918, an accuracy of 0.8927, and an F1 score of 0.8615 in detecting bone loss. This study concluded that a faster CNN model may be used as an adjuvant technique to diagnose periodontal disease and alveolar bone loss using dental panoramic radiography images, thereby minimizing diagnostic effort, and saving assessment time. However, the execution of precisely detecting periodontal cases by fully automated AI models using panoramic radiographs appears imminent and needs clinical periodontal evaluation for definitive diagnosis. The suitability of this approach is supported by the sensitivity, specificity, accuracy, and F-measure, which showed satisfactory performance for classifying cases. Based on population and periodontal disease burden standpoint, the use of AI in diagnosing periodontal diseases may serve as an excellent surveillance method to classify alveolar bone loss. Monitoring a periodontal patient after treatment needs a wide area to cover by AI-based diagnostic modality. With AI as the future of dentistry, performance-based clinical usage of CNN models demands confirmed practical application by dentists. Full article

This study investigates shear cutting of high-strength steel sheets, a process known to negatively impact the forming and fatigue properties of the material. The localized deformation near the cut edges imposes sheared-edge damage, especially in advanced high-strength steels where severe shear deformation occurs in the very vicinity of the cut edge. In this work, an extensive experimental investigation was carried out on punched holes of thin sheets, using light optical microscopy and metallographic techniques for sheared-edge damage assessment. These methods provided detailed insights into the sheared-edge damage and offer a thorough understanding of the deformation behavior in the shear-affected zone. Advanced engineering cut-edge investigation methods have been developed based on 2D and 3D stereo light microscopy for non-destructive panoramic cut-edge parameters and cut-edge profile determination along cut-hole circumference. Such methods provide an efficient evaluation instrument for challenging close-cut holes, with the possibility of industrial in-line monitoring and machine learning applications for Industry 4.0 implementation. Additionally, the study compares grain shear angle measurement and Vickers indentation for deformation assessment of the cut edge. It concludes that grain shear angle offers higher resolution. This parameter is therefore postulated as relevant for assessing the sheared-edge zone. The findings contribute to a deeper understanding of sheared-edge damage and improve evaluation methods, potentially enhancing the use of high-strength steels in automotive and safety-critical applications. Full article

The electrically evoked compound action potential (ECAP) is a crucial physiological signal used by clinicians to evaluate auditory nerve functionality. Clean ECAP recordings help to accurately estimate auditory neural activity patterns and ECAP magnitudes, particularly through the panoramic ECAP (PECAP) framework. However, noise—especially in low-signal-to-noise ratio (SNR) conditions—can lead to significant errors in parameter estimation. This study proposes a two-stage preprocessing denoising (TSPD) algorithm to address this issue and enhance ECAP signals. First, an ECAP matrix is constructed using the forward-masking technique, representing the signal as a two-dimensional image. This matrix undergoes spatial noise reduction via an improved spatial median (I-Median) filter. In the second stage, the denoised matrix is vectorized and further processed using a log-spectral amplitude (LSA) Wiener filter for spectral domain denoising. The enhanced vector is then reconstructed into the ECAP matrix for parameter estimation using PECAP. The above integrated spatial-spectral denoising framework is denoted as PECAP-TSPD in this work. Evaluations are conducted using a simulation-based ECAP model mixed with simulated and experimental noise, designed to emulate the spatial characteristics of real ECAPs. Three objective quality measures—namely, normalized root mean square error (RMSE), two-dimensional correlation coefficient (TDCC), and structural similarity index (SSIM)—are used. Simulated and experimental results show that the proposed PECAP-TSPD method has the lowest average RMSE of PECAP magnitudes (1.952%) and auditory neural patterns (1.407%), highest average TDCC (0.9988), and average SSIM (0.9931) compared to PECAP (6.446%, 5.703%, 0.9859, 0.8997), PECAP with convolutional neural network (CNN)-based denoising mask (PECAP-CNN) (9.700%, 7.111%, 0.9766, 0.8832), and PECAP with improved median filtering (PECAP-I-Median) (4.515%, 3.321%, 0.9949, 0.9470) under impulse noise conditions. Full article

Background/Objectives: Dental anomalies can manifest as a consequence of developmental defects and/or genetic influences, which disrupt the normal functioning of the oral cavity and present in various forms. Cases of fusion, gemination and concrescence are rare dental anomalies which are seen in the area of the mandibular molars. Case report: This case report concerns a 69-year-old Greek male patient who presented in the dental office asking for comprehensive oral treatment. During the clinical examination, a morphologically atypical molar was identified in the area of #37–38 presented with a large crown in the mesio-distal dimension (‘double’ crown). Panoramic and periapical radiographs offered valuable insights on the morphology of the irregular tooth, as they revealed the crown and root morphology, including the two pulp chambers and the three parallel roots of the tooth. Discussion: A plausible hypothesis identifies the atypical tooth as a third molar exhibiting morphological variation, a common characteristic of third molars. Additional diagnostic considerations—while supposing the existence of a supernumerary fourth molar—include the developmental anomalies of gemination, concrescence and fusion, as the clinical and radiographic features of the tooth display elements associated with all three. Conclusions: Considering the patient’s history, clinical and radiographic findings and the relevant literature, fusion is determined to be the most probable diagnosis. Early identification of the atypical tooth is essential to facilitate the implementation of appropriate preventive measures and to support informed treatment planning, should invasive procedures such as endodontic or surgical intervention be required in the future. Full article

Panoramic images in indoor construction sites are gaining attention as valuable tools for process monitoring and quality assessment. However, despite the environmental complexity and the demand for high segmentation performance in indoor construction environments, the scarcity of specialized segmentation models and datasets has created a gap between technological advancements and practical application, thus hindering the effective utilization of panoramic images. To address these challenges, this study proposes a novel approach leveraging the Segment Anything Model (SAM), a perspective image segmentation foundation model, to enhance the performance of existing segmentation models. The proposed method iteratively executes SAM with adjusted input parameters to extract objects of varying sizes and subsequently applies filtering algorithms to retain valid objects. Then, label assignment and merging processes are performed based on the predictions from the target model to improve segmentation accuracy. The experimental study was conducted using Panoplane360, a model specifically designed for plane segmentation, as the target model. A quantitative evaluation was conducted to measure the exactness of label assignment, and two qualitative evaluations were performed to assess whether the assigned labels accurately represent the actual planar information. The evaluation results confirmed that the proposed method significantly improves segmentation performance compared to conventional approaches. The findings of this study highlight the potential of SAM-based methods to enhance segmentation accuracy in dynamic indoor construction environments. Furthermore, the proposed approach provides practical advantages, as it improves segmentation performance without requiring the construction of additional datasets. Future research will focus on resolving computational efficiency issues resulting from iterative SAM execution and will extend the applicability of the proposed approach to diverse segmentation tasks and models. Full article

Objectives: To evaluate any changes in condylar and mandibular ramus height and dental malocclusion in adult patients with temporomandibular disorders (TMDs) diagnosed with DC/TMD criteria after treatment with an upper occlusal splint. Methods: This retrospective observational study included 48 adult patients with TMDs treated with an occlusal splint in the upper arch for about 12 months. For each patient, panoramic dental X-rays were analyzed using the Habets method to calculate the asymmetry index between the condyles and mandibular branches before and after treatment. The digital dental models were also studied at T0 and T1 to define the occlusal sagittal molar relationship and the posterior dental crossbite. The statistical analysis was performed using the Shapiro–Wilk normality tests, Student t-tests, or Wilcoxon tests using the R studio software (released version 4.3.3). Results: Condylar height showed a statistically significant difference (p = 0.022) and reduced condylar asymmetry between T0 and T1. The measurement of the condylar branch showed a statistical significance (p = 0.037), revealing an improvement of the mandibular symmetry in the vertical direction after treatment. Moreover, at T0, posterior dental crossbite was found in 37.5% of patients, specifically, bilateral in 12.5%, while unilateral crossbite in 22.9% on the right and 2.1% on the left side, and Class I malocclusion was found in the main part of the sample (72.9%). Conclusions: Patients with TMDs diagnosed according to DC/TMD and treated with an upper stabilization occlusal splint in the case of symptoms of masticatory muscle dysfunction showed a symmetrization in the mandibular ramus and condyle pre- and post-treatment (T0-T1). At the same time, no clinical differences were found in the occlusal characteristics. Full article

Background: Evidence supporting the validity of photogrammetry for assessing body segment alignment remains limited, with most studies focusing on spinal evaluation. Thus, there is a lack of robust research examining its use for other body segments such as the lower limbs. Objective: This study aimed to evaluate the concurrent validity of three photogrammetric methods for measuring knee alignment in the sagittal plane with and without corrections for potential rotational deviations in the participant’s thigh and leg. Methods: A total of 21 adults underwent sequential evaluations involving panoramic radiography of the lower limbs and photogrammetry at a private radiology clinic. Photogrammetric analysis involved identifying the following anatomical landmarks: the greater trochanter of the femur (GTF), the lateral condyle of the femur (LCF), the head of the fibula (HF), and lateral malleolus (LM). Three photogrammetric methods were employed: (1) the condylar angle (CA) defined by the GTF, LCF, and LM points; (2) the fibula head angle (FHA) defined by the GTF, HF, and LM points; and (3) the four-point angle (4PA) incorporating the GTF, LCF, HF, and LM. Concurrent validity was assessed using correlation analysis, agreement with radiographic measurements, and the root mean square error (RMSE). Each photogrammetric method was tested using raw (CA, FHA, and 4PA) and corrected (CAcorr, FHAcorr, and 4PAcorr) values, accounting for thigh and/or leg rotational deviations. Results: Correcting for thigh and leg rotations significantly improved the validity metrics for all methods. The best performance was observed with the corrected condylar angle (CAcorr: r = 0.746; adjusted r² = 0.533; RMSE = 2.9°) and the corrected four-point angle (4PAcorr: r = 0.733; adjusted r² = 0.513; RMSE = 3.0°); however, the measurements presented proportional errors, possible due the method of assessment of rotations. Conclusions: The findings validate the evaluated photogrammetric methods for assessing sagittal knee alignment. Accounting for thigh and leg rotational deviations is critical for achieving accurate measurements, raising the need of accurate tools for measuring rotational changes in the lower limbs to avoid errors. Full article

Objectives: The aim was to establish whether there is a relationship between the presence of unilateral posterior crossbite (u-PCB) and the mesio-distal inclination of permanent upper canines, the angulation of the occlusal plane, or the labial commissure inclination in children. Methods: A cross-sectional association study was conducted. Panoramic radiography was used to measure the inclination of the canines and the occlusal plane, and frontal rest photography was used to measure the inclination of the labial commissure. The measurements were performed with tpsDig264 software version 2.25, 2016, Ecology & Evolution, SUNY), and the data obtained were analyzed with SPSS 22.0 software, using ANOVA and Kruskal–Wallis tests for the statistical analysis. Results: A total of 106 patients with u-PCB and 41 patients in the control group were studied. No statistically significant differences were observed in the inclination of the right and left canines in patients with u-PCB compared to patients in the control group. There is a relationship between the presence of u-PCB and the inclination of the occlusal plane. No statistically significant differences were observed in the inclination of the labial commissure in patients with u-PCB compared to patients in the control group. Conclusions: There is no relationship between the presence of u-PCB and the alteration in the eruptive trajectory of the permanent upper canines or in the inclination of the labial commissure. However, a relationship between the presence of u-PCB and altered occlusal plane inclination was found. Full article

Background/Objectives: Osteogenesis Imperfecta (OI) is a congenital disorder, in which the production of collagen, mainly type I, is altered, leading to a decrease in bone mineral density, increasing the risk of fracture with minimal trauma. Several studies have analyzed bone mineral density in osteoporotic patients based on linear measurements such as radiomorphometric indices measured with panoramic radiographs, although few studies have investigated bone trabeculation in children diagnosed with OI. Therefore, the aim of the present investigation was to analyze the dental panoramic indices in panoramic radiographs in the cortical and trabeculated bone of children with OI. Methods: Thus, 66 pediatric patients diagnosed with OI under antiresorptive treatment were compared with a sample of controls matched for sex and age. Using Image J software (version: 1.54d), three radiomorphometric indices were analyzed in orthopantomographies of the study and control groups, evaluating the influence of disease severity as well as the type of antiresorptive treatment administered. Results: Patients with OI had a higher presence of type C2 and C3 MCI (mandibular cortical index) than their matched controls (p < 0.05), although no differences were found for the visual estimation of cortical width (SVE) and mandibular cortical width (MCW). Treatment with zoledronic acid was associated with a higher number of cases of type C1 MCI, in terms of sample description, while patients treated with a combination of pamidronate and zoledronic acid had a higher rate of type C1 and C2 MCI, with no statistical differences. Conclusions: In the overall sample, most patients showed a thin SVE index (59.1%), a C2 or C1 type MCI (46.2% and 42.4%) and an MCW of 2.9 mm. Differences in bone mineral density were also observed throughout growth and the different antiresorptive treatments. Zoledronic acid has been associated with a higher percentage of C1 and C3 ICM, and pamidronate alone or in combination is associated with a C1 and C2 MCI index. Full article

Background and Objectives: Analysing the characteristics of the mandibular bone through panoramic radiographs could be useful as a prescreening tool for detecting individuals with osteoporosis. The aims of this study were to evaluate the possible associations between the mandibular cortical index (MCI) and bone mineral density (BMD) in various bone regions, to investigate whether BMD better identifies moderate–severe mandibular erosion or severe mandibular erosion, and to establish BMD cut-off points to identify individuals with moderate or severe mandibular cortical erosion. Methods: This study analysed 179 Spanish Caucasian women between September 2021 and June 2024. Bone measurements, including amplitude-dependent speed of sound (Ad-SOS), the ultrasound bone profiler index (UBPI), and the bone transmission time (BTT), were obtained via dual energy X-ray absorptiometry (DXA) for the femoral neck, lumbar spine, and trochanter and quantitative bone ultrasound (QUS) for the phalanx. The MCI was calculated via the Klemetti index from panoramic radiographs. Results: According to the Klemetti index classification, lower QUS measurements in the phalanx and DXA measurements in the femoral neck, trochanter, and lumbar spine were found in women with poorer mandibular cortical bone quality. Our results revealed that, compared with moderate cortical erosion, all the BMD measures had better AUCs when identifying severe cortical erosion. Moreover, femoral neck BMD had the largest area under the curve (AUC = 0.719) for detecting severe mandibular cortical erosion, suggesting a cut-off of <0.703 gr/cm². Finally, predictor analysis of osteoporosis revealed that moderate and severe mandibular cortical erosion, compared with an uninjured mandibular cortical area, was independently associated with a diagnosis of osteoporosis. Conclusions: In conclusion, MCI was associated with BMD measurements assessed by QUS and DXA in various bone regions. Our results suggest that the Klemetti index could be used as a predictor of osteoporosis and fracture risk. Full article