Search Results (169)

Objective: The accurate visualization of root canal systems on periapical radiographs is critical for successful endodontic treatment. This study aimed to evaluate and compare the effectiveness of several image enhancement algorithms—including a novel Total Variation–Contrast-Limited Adaptive Histogram Equalization (TV-CLAHE) technique—in improving the detectability of root canal configurations in mandibular incisors, using cone-beam computed tomography (CBCT) as the gold standard. A null hypothesis was tested, assuming that enhancement methods would not significantly improve root canal detection compared to original radiographs. Method: A retrospective analysis was conducted on 60 periapical radiographs of mandibular incisors, resulting in 420 images after applying seven enhancement techniques: Histogram Equalization (HE), Contrast-Limited Adaptive Histogram Equalization (CLAHE), CLAHE optimized with Pelican Optimization Algorithm (CLAHE-POA), Global CLAHE (G-CLAHE), k-Caputo Fractional Differential Operator (KCFDO), and the proposed TV-CLAHE. Four experienced observers (two radiologists and two dentists) independently assessed root canal visibility. Subjective evaluation was performed using an own scale inspired by a 5-point Likert scale, and the detection accuracy was compared to the CBCT findings. Quantitative metrics including Peak Signal-to-Noise Ratio (PSNR), Signal-to-Noise Ratio (SNR), image entropy, and Structural Similarity Index Measure (SSIM) were calculated to objectively assess image quality. Results: Root canal detection accuracy improved across all enhancement methods, with the proposed TV-CLAHE algorithm achieving the highest performance (93–98% accuracy), closely approaching CBCT-level visualization. G-CLAHE also showed substantial improvement (up to 92%). Statistical analysis confirmed significant inter-method differences (p < 0.001). TV-CLAHE outperformed all other techniques in subjective quality ratings and yielded superior SNR and entropy values. Conclusions: Advanced image enhancement methods, particularly TV-CLAHE, significantly improve root canal visibility in 2D radiographs and offer a practical, low-cost alternative to CBCT in routine dental diagnostics. These findings support the integration of optimized contrast enhancement techniques into endodontic imaging workflows to reduce the risk of missed canals and improve treatment outcomes. Full article

Background: Two-dimensional periapical radiographs (PAs) only offer limited information regarding three-dimensional periodontal infrabony defects. In contrast, cone beam computed tomography (CBCT) enables visualization of the entire defect morphology. This study aimed to evaluate the agreement between CBCT and direct intrasurgical measurements (ISs) regarding the characteristics of infrabony defects, including measurements of defect depth, width, the type of defect (one-wall, two-wall, three-wall), and defect extension. Methods: Intrasurgical and radiographic assessments were performed by two calibrated examiners on 26 infrabony defects in 17 patients who underwent periodontal surgery. The defect depth, width, type, and extension were compared between intrasurgical observations and PA or CBCT findings. The CBCT assessment was performed mainly using axial reconstructions. Angle measurements were compared between CBCT and PAs. Results: The mean differences between CBCT and intrasurgical measurements were −0.11 ± 0.49 mm for depth and −0.07 ± 0.41 mm for width, with no significant differences. The ICC values were 0.938 and 0.923 for depth and width, respectively. The mean difference in width between PAs and ISs was significantly different (−0.36 ± 0.73 mm; p = 0.002). CBCT demonstrated high agreement with intrasurgical observations for defect type (κ = 0.819) and defect extension (κ = 0.855), while lower agreements were found for PAs. Conclusions: CBCT is a valid assessment modality for infrabony defects. It demonstrated strong agreement with ISs—as the gold standard—for depth and width measurements, and its agreement with ISs regarding defect type and extension appeared to surpass that of PAs. Full article

Purpose: This pilot study aimed to evaluate how deviations in X-ray tube head angulation and digital sensor alignment affect the radiographic measurement of the profile angle in CAD-CAM abutments. Materials and Methods: A mandibular model was used with five implant positions (central, buccal, and lingual offsets). Custom CAD-CAM abutments were designed with identical bucco-lingual direction contours and varying mesio-distal asymmetry for the corresponding implant positions. Periapical radiographs were acquired under controlled conditions by systematically varying vertical tube angulation, horizontal tube angulation, and horizontal sensor rotation from 0° to 20° in 5° increments for each parameter. Profile angles, interthread distances, and proximal overlaps were measured and compared with baseline STL data. Results: Profile angle measurements were significantly affected by both X-ray tube and sensor deviations. Horizontal tube angulation produced the greatest profile angle distortion, particularly in buccally positioned implants. Vertical x-ray tube angulations beyond 15° led to progressive underestimation of profile angles, while horizontal tube head rotation introduced asymmetric mesial–distal variation. Sensor rotation also caused marked interthread elongation, in some cases exceeding 100%, despite vertical projection being maintained. Profile angle deviations greater than 5° occurred in multiple conditions. Conclusions: X-ray tube angulation and sensor alignment influence the reliability of profile angle measurements. Radiographs with > 10% interthread elongation or crown overlap may be inaccurate and warrant re-acquisition. Special attention is needed when imaging buccally positioned implants. Full article

Objectives: This study aimed to evaluate the success rates of NSRCT performed by AEGD residents and to identify predictive factors associated with clinical outcomes and patient satisfaction. Methods: A retrospective chart review was conducted on cases treated between 2012 and 2021. Eligible cases included fully developed permanent teeth that underwent NSRCT and received a final restoration by general dentistry residents, with a minimum of 12 months of follow-up. Data collected included demographic information, medical history, clinical symptoms, radiographic findings, instrumentation, type and timing of final restorations, and patient satisfaction scores. Treatment success was defined as the absence of symptoms and either the resolution or stability of periapical radiolucency. Patient satisfaction and pain levels were also analyzed. Results: AEGD residents achieved radiographic and clinical RCT success rates of 93.3% and 91.5%, respectively. Multivariate logistic regression showed that the presence of an intact restoration was significantly associated with increased odds of tooth retention (odds ratio [OR] = 3.4, p < 0.001), while post placement in a straight root was also a significant predictor of survival (OR = 4.2, p = 0.02). Conversely, pre-existing radiolucency (OR = 0.37, p = 0.018) and the use of a metal post (OR = 0.23, p = 0.012) were significantly associated with lower odds of tooth retention. Worse periodontal health was significantly associated with increased odds of pain on percussion, with a 74.19% increase in odds per worsening category (OR = 1.74, p = 0.002). Patient satisfaction was significantly higher when restorations remained intact, with esthetic satisfaction increasing by a factor of 3.08 (OR = 3.08, p < 0.001) and functional satisfaction increasing by a factor of 3.9 (OR = 3.9, p < 0.001). Conclusions: Endodontic treatments performed by AEGD residents demonstrated high success rates and favorable patient-reported outcomes. Restoration integrity, periodontal health, and post and final restoration selection play critical roles in treatment success and patient satisfaction. Full article

Background/Objectives: In dental medicine, the integration of various types of X-ray images, such as periapical (PA), bitewing (BW), and panoramic (PANO) radiographs, is crucial for comprehensive oral health assessment. These complementary imaging modalities provide diverse diagnostic perspectives and support the early detection of oral diseases, thereby enhancing treatment outcomes. However, there is currently no existing system that integrates multiple types of dental X-rays for both adults and children to perform tooth localization and numbering. Methods: Therefore, this study aimed to propose a system based on YOLOv8 that integrates multiple dental X-ray images and automatically detects and numbers both permanent and deciduous teeth. Through image preprocessing, various types of dental X-ray images were standardized and enhanced to improve the recognition accuracy of individual teeth. Results: With the implementation of a novel image preprocessing method, the system achieved a detection precision of 98.16% for permanent and deciduous teeth, representing a 3% improvement over models without image enhancement. In addition, the system attained an average tooth numbering accuracy of 98.5% for permanent teeth and 96.3% for deciduous teeth, surpassing existing methods by 5.6%. Conclusions: These results might highlight the innovation of the proposed image processing method and show its practical value in assisting clinicians with accurate diagnosis of tooth loss and the identification of missing teeth, ultimately contributing to improved diagnosis and treatment in dental care. Full article

Objective: To assess radiographic changes in the alveolar bone on the distal aspect of the second molars (2Ms) over time, while impacted third molars (ITMs) remain present across two timepoints. Methods: This retrospective observational study aimed to assess radiographic changes between two timepoints (T0 and T1). Both Orthopantomogram (OPG) and Periapical (PA) X-rays were utilized, with three measurements taken on the distal surface of 2Ms using EMAGO 6.1 software. Statistical significance was defined as a p-value < 0.05. Results: A total of 51 patients met the inclusion criteria, with a mean age of 45 years (SD ± 13). Sixty-eight second molars were assessed at baseline (T0) and follow-up (T1), with a mean interval of 20 months (SEM ± 62 days). No significant changes were found in vertical, oblique, or angular bone levels between T0 and T1. Gender significantly affected the cementoenamel junction (CEJ)–base of defect (BD) measurements (p = 0.022) and defect angles at T0 (p = 0.048), but not at the adjusted T1 (p = 0.292). Other variables, including medical history, smoking, and ITM angulation, showed no influence. Patient age was borderline significant in relation to intrabony defect angle (p = 0.047). Conclusions: Considering its limitations, this analysis does not provide evidence to support the hypothesis that prophylactic extraction of ITMs yields significant bone-sparing benefits. Furthermore, it does not establish that prolonged retention of ITMs consistently results in short-term bone alterations in adjacent 2Ms. Consequently, further research is warranted to more accurately assess the medium- to long-term implications of ITM retention on the bone levels of 2Ms. Full article

Background and Objectives: Periapical healing and bone regeneration are key indicators of endodontic success. This study evaluated the effectiveness of laser-assisted disinfection compared to conventional chemical irrigation in promoting periapical healing across various bone densities (D1–D5), using cone-beam computed tomography (CBCT) over multiple follow-up intervals. Materials and Methods: A total of 120 patients with radiographically confirmed periapical lesions were enrolled and allocated into two groups: an experimental group (n = 60, chemical irrigation + Er,Cr:YSGG laser disinfection) and a control group (n = 60, chemical irrigation only). CBCT scans were obtained at 6 months, 1 year, 2 years, and 2.5 years post-treatment to assess lesion size and CBCT-PAI scores. Lesions were classified radiographically as either well-defined radiolucent lesions or undefined periapical radiolucencies. Paired t-tests and ANOVA were used for statistical comparisons. Results: The experimental group demonstrated significantly greater reductions in lesion size and improvements in CBCT-PAI scores at all time points. Healing was especially enhanced in low-density bone (D4–D5). Complete healing rates were higher in the laser group for well-defined radiolucent (89.5% vs. 68.4%) and undefined lesions (81.8% vs. 59.1%). Post hoc power analysis confirmed statistical reliability (Cohen’s d = 3.48; power > 0.99). Conclusions: Laser-assisted endodontic disinfection significantly accelerates periapical healing and promotes bone regeneration, particularly in low-density bone. CBCT imaging supports its clinical superiority over conventional irrigation methods. Full article

Objectives: The purpose of the study is to evaluate the diagnostic accuracy of artificial intelligence (AI) software in detecting a common set of periodontal and restorative conditions, including marginal bone loss, dental caries, periapical lesions, calculus, endodontic treatment, crowns, restorations, and open crown margins, using intraoral periapical radiographs. Additionally, the study will assess how this AI software influences the diagnostic accuracy of dentists with varying levels of experience in identifying these conditions. Methods: A total of three hundred digital IOPARs representing 1030 teeth were selected based on predetermined selection criteria. The parameters assessed included (a) calculus, (b) periapical radiolucency, (c) caries, (d) marginal bone loss, (e) type of restorative (filling) material, (f) type of crown retainer material, and (g) detection of open crown margins. Two oral radiologists performed the initial diagnosis of the selected radiographs and independently labeled all the predefined parameters for the provided IOPARs under standardized conditions. This data served as reference data. A pre-trained AI-based computer-aided detection (“CADe”) software (Second Opinion^®, version 1.1) was used for the detection of the predefined features. The reports generated by the AI software were compared with the reference data to evaluate the diagnostic accuracy of the AI software. In the second phase of the study, thirty dental interns and thirty dental specialists were randomly selected. Each participant was randomly assigned five IOPARs and was asked to detect and diagnose the predefined conditions. Subsequently, all the participants were requested to reassess the IOPARs, this time with the assistance of the AI software. All the data was recorded using a self-designed Performa. Results: The sensitivity of the AI software in detecting caries, periapical lesions, crowns, open crown margins, restoration, endodontic treatment, calculus, and marginal bone loss was 91.0%, 86.6%, 97.1%, 82.6%, 89.3%, 93.4%, 80.2%, and 91.1%, respectively. The specificity of the AI software in detected caries, periapical lesions, crowns, open crown margins, restoration, endodontic treatment, calculus, and marginal bone loss was 87%, 98.3%, 99.6%, 91.9%, 96.4%, 99.3%, 97.8%, and 93.1%, respectively. The differences between the AI software and radiologist diagnoses of caries, periapical lesions, crowns, open crown margins, restoration, endodontic treatment, calculus, and marginal bone loss were statistically significant (all p values < 0.0001). The results showed that the diagnostic accuracy of operators (interns and specialists) with AI software revealed higher accuracy, sensitivity, and specificity in detecting caries, PA lesions, restoration, endodontic treatment, calculus, and marginal bone loss compared to that without using AI software. There were variations in the improvements in the diagnostic accuracy of interns and dental specialists. Conclusions: Within the limitations of the study, it can be concluded that the tested AI software has high accuracy in detecting the tested dental conditions in IOPARs. The use of AI software enhanced the diagnostic capabilities of dental operators. The present study used AI software to detect a clinically useful set of periodontal and restorative conditions, which can help dental operators in fast and accurate diagnosis and provide high-quality treatment to their patients. 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

Background/Objectives: Accurate scientific methods are essential for monitoring the osseointegration of dental implants postoperatively. This study aims to evaluate peri-implant bone changes using the fractal analysis (FA) method during follow-up. Methods: Periapical radiographs were obtained from 77 patients with dental implants, and 33 permanent teeth serving as a control group, retrieved from the radiology archive. Radiographs were taken using the parallel technique at 3, 6, and 12 months post-surgery. All images were digitized and saved in TIFF. Each image was aligned using the TurboReg plugin in ImageJ software. Regions of interest (ROIs) were selected from the mesial and distal aspects of the implants, then prepared for fractal analysis. FA was performed to assess changes in bone structure over time. Results: In the study group, radiographs of 24 patients for 0, 3 and 6 month, radiographs of 34 patients for 0, 6 and 12 month, radiographs of 8 patients for 0 and 12 month, radiographs of 5 patients for 0 and 3 month, radiographs of 5 patients for 0 and 6 month, and 1 patient of 0, 3, 6 and 12 month of radiographs were used in the study. There were no statistically significant differences in FA values over time when analyzed by gender and age in both the study and control groups. However, a statistically significant difference was observed in FA value changes over time and jaws. Conclusions: The study indicates a positive correlation between bone remodeling over time and FA results, likely due to the restoration of masticatory forces in the implant area. Image analysis on two-dimensional dental radiographs can be a useful tool for detecting changes in bone density. Fractal analysis is a cost-effective and practical diagnostic method for monitoring bone changes over time. Full article

Interdisciplinary decision-making significantly influences both the therapeutic potential and clinical outcomes, shaping clinical attitudes and management strategies. As the integration between endodontic and restorative-prosthetic considerations becomes increasingly prevalent, it is essential to understand how different dental specialists, particularly general dental practitioners, prosthodontists and endodontists, approach clinical decision-making and collaborate to optimize patient care. Objectives: This study aims to identify practice disparities in post-endodontic crown placement to inform national policy reforms, including standardised timing protocols and interdisciplinary referral criteria. Methods: A structured questionnaire was distributed to dentists practicing in Romania, yielding 238 collected responses. Results: Substantial variability was found in clinical approaches: diagnostic imaging preferences indicated frequent use of periapical radiography (83.49%) and CBCT (53.67%). Over 70% expressed high confidence in CBCT’s diagnostic precision, significantly higher than periapical radiography (Wilcoxon Signed-Rank test, p < 0.00001). A statistically significant majority (69.3%, binomial test, p < 0.001) preferred delaying definitive crown placement until radiographic healing of periapical lesions. Logistic regression analysis showed endodontists were significantly less likely to choose invasive treatments compared to other specialists (p = 0.027). Although clinicians widely recognize the significance of prosthetic planning, its early integration into the overall treatment strategy has been inconsistent. Conclusions: This study points out the necessity for standardised guidelines that clearly integrate prosthetic planning into endodontic decision-making, enhancing predictability and tooth preservation. Full article

Background and Objectives: Implant brand identification is critical in modern dental clinical diagnostics. With the increasing variety of implant brands and the difficulty of accurate identification in periapical radiographs, there is a growing demand for automated solutions. This study aims to leverage deep learning techniques to assist in dental implant classification, providing dentists with an efficient and reliable tool for implant brand detection. Methods: We proposed an innovative implant brand feature extraction method with multiple image enhancement techniques to improve implant visibility and classification accuracy. Additionally, we introduced a PA resolution enhancement technique that utilizes Dark Channel Prior and Lanczos interpolation for image resolution upscaling. Results: We evaluated the performance differences among various YOLO models for implant brand detection. Additionally, we analyzed the impact of implant brand feature extraction and PA resolution enhancement techniques on YOLO’s detection accuracy. Our results show that IB-YOLOv10 achieves a 17.8% accuracy improvement when incorporating these enhancement techniques compared to IB-YOLOv10 without enhancements. In real-world clinical applications, IB-YOLOv10 can classify implant brands in just 6.47 ms per PA, significantly reducing diagnostic time. Compared to existing studies, our model improves implant detection accuracy by 2.3%, achieving an overall classification accuracy of 94.5%. Conclusions: The findings of this study demonstrate that IB-YOLOv10 effectively reduces the diagnostic burden on dentists while providing a fast and reliable implant brand detection solution, improves clinical efficiency, and establishes a robust deep learning approach for automated implant detection in PA. Full article

Background: Artificial intelligence (AI) is playing an increasingly important role in everyday dental practice and diagnosis, especially in the area of analysing digital pantomographic images. Through the use of innovative and modern algorithms, clinicians can more quickly and accurately identify pathological changes contained in digital pantomographic images, such as caries, periapical lesions, cysts, and tumours. It should be noted that pantomographic images are one of the most commonly used imaging modalities in dentistry, and their digital analysis enables the construction of AI models to support diagnosis. Objectives: This paper presents a systematic narrative review of studies included in scientific articles from 2020 to 2025, focusing on three main diagnostic areas: detection of caries, periapical lesions, and cysts and tumours. The results show that neural network models, such as U-Net, Swin Transformer, and CNN, are most commonly used in caries diagnosis and have achieved high performance in lesion identification. In the case of periapical lesions, AI models such as U-Net and Decision Tree also showed high performance, surpassing the performance of young dentists in assessing radiographs in some cases. Results: The studies cited in this review show that the diagnosis of cysts and tumours, on the other hand, relies on more advanced models such as YOLO v8, DCNN, and EfficientDet, which in many cases achieved more than 95% accuracy in the detection of this pathology. The cited studies were conducted at various universities and institutions around the world, and the databases (case databases) analysed in this work ranged from tens to thousands of images. Conclusions: The main conclusion of the literature analysis is that, thanks to its accessibility, speed, and accuracy, AI can significantly assist the work of physicians by reducing the time needed to analyse images. However, despite the promising results, AI should only be considered as an enabling tool and not as a replacement for the knowledge of doctors and their long experience. There is still a need for further improvement of algorithms and further training of the network, especially in identifying more complex clinical cases. Full article

Diagnostic imaging is fundamental in dentistry for disease detection, treatment planning, and outcome assessment. Traditional radiographic methods, such as periapical and panoramic radiographs, along with cone beam computed tomography (CBCT), utilize ionizing radiation and primarily focus on visualizing bony structures. Magnetic resonance imaging (MRI) is emerging as a non-ionizing alternative that offers superior soft tissue contrast. However, standard MRI sequences face challenges visualizing mineralized tissues due to their short transverse relaxation times (T2), which results in rapid signal decay. Recent advancements exploring short T2 sequences, including Ultrashort Echo Time (UTE), Zero Echo Time (ZTE), and Sweep Imaging with Fourier Transformation (SWIFT), allow direct visualization of dental hard tissues. UTE captures signals from short T2 tissues using rapid pulse sequences, while ZTE employs encoding gradients before radiofrequency pulses to reduce signal loss. SWIFT enables near-simultaneous excitation and acquisition, improving ultrashort T2 detection. Additionally, customized intraoral and extraoral surface coils enhance the image resolution and signal-to-noise ratio (SNR), increasing MRI’s relevance in dentistry. Research highlights the potential of these short T2 sequences for early caries detection, pulp vitality assessment, and diagnosing jaw osseous pathology. While high-field MRI (3 T–7 T) improves resolution and increases susceptibility artifacts, low-field systems with specialized coils and short sequences offer promising alternatives. Despite obstacles such as cost and hardware constraints, ongoing studies refine protocols to enhance clinical applicability. Incorporating MRI in dentistry promises a safer, more comprehensive imaging methodology, potentially transforming diagnostics. This review emphasizes three types of short T2 sequences that have potential applications in the maxillofacial region. Full article

Objectives: Endodontic microsurgery has become an integral part of daily endodontic practice. However, research on the correlation between the lesion characteristics observed via cone beam computed tomography (CBCT) and pain and swelling after endodontic microsurgery (EMS) is still lacking in the literature. The present study aims to examine the relationship between the radiographic characteristics of preoperative periapical lesions obtained from CBCT images and post-surgical symptoms such as pain and swelling. Materials and Methods: A total of 61 patients undergoing EMS utilizing modern techniques were asked to report their level of pain and swelling at 8, 24, 48, and 72 h after EMS using VAS. Independent variables such as age, gender, tooth location, CBCT periapical index, endodontic diagnosis, cortical bone perforation by the lesion, duration of the EMS, preoperative analgesic consumption, antibiotic prescription, and pre-/postoperative mouthwash were analyzed using the Fisher Exact test. Multivariate regression analysis was also conducted to determine the independent significant factors associated with pain and swelling. A p-value of ≤0.05 was considered statistically significant. Results: The maximum pain score was recorded at 8 h (4.26 ± 3.13), while peak swelling was measured after 24 h (6.46 ± 2.87). The risk of swelling was more likely to decrease by 75.7% for patients with a CBCT index score of >3 than those with a CBCT index score of ≤3 (AOR = 0.243; CI = 0.071–0.831; p = 0.024). The effects of all other factors on pain, including cortical bone perforation by the lesion (p = 0.290), swelling (p = 0.071), postoperative mouthwash use (p = 0.062), and swelling (p = 0.934), did not reach statistical significance. Conclusions: Patients with periapical lesions larger than 4 mm will likely experience less swelling after EMS, while pain is not affected by lesion size, cortical bone perforation, or mouthwash use. Clinical Relevance: This study identified a new predictor of swelling after EMS based on the size of the periapical lesion. These results will improve the management of post-surgical sequelae after EMS and support shared decision making. Full article