Search Results (24)

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: 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: 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

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

Aim: To assess the association between demographic and clinical variables and the outcome of root-end surgery using digital periapical radiographs (PA) and cone-beam computed tomography (CBCT). Methodology: One hundred and fifty teeth that received endodontic microsurgery were clinically and radiographically examined (PA and CBCT scans) after 1 and 2 years. Two calibrated endodontists evaluated the radiographic healing based on a six-point outcome classification. The outcome was classified using both strict (healed) and loose (healing) criteria. The success rates were calculated, and several outcome prognostic factors were assessed. Results: One hundred and fifty teeth were assessed with both radiographic systems. When “loose” success criteria were applied using PA, 90% (n = 135) of teeth were assessed as having had a favourable outcome (90%; 95% CI: 85.2–94.8%), whereas 90.7% (n = 136) of teeth showed a successful outcome when assessed with CBCT (90.7%; 95% CI: 86.0–95.3%). When “strict” success criteria were applied, there was a statistically significant difference (p = 0.018) between the success rates of mineral trioxide aggregate (MTA) (63.7%) and Biodentine (95.5%). Conclusions: Within the limitations of this study, endodontic microsurgery showed a high success rate. Among all the demographic and clinical variables assessed, in the multiregression analysis, only the use of Biodentine was associated with a higher proportion of “complete” healings compared to MTA or Intermediate Restorative Material (IRM) when assessed using CBCT. MTA and Biodentine performed similarly when “incomplete” healings were regarded as successful outcomes. Full article

Narrow-diameter implants (NDI) serve as a solution for treating limited bone volume in the anterior mandible. This study aimed to evaluate the one-year clinical outcomes of various NDIs in the mandibular incisor area after immediate loading in partially edentulous patients. This single-center, prospective, single-blinded, randomized controlled trial study included 21 patients, with 7 patients in each of the following groups: control (BLT NC SLActive^®; Straumann), experimental group 1 (CMI IS-III Active^® S-Narrow; Neobiotech), and experimental group 2 (CMI IS-III Active^® Narrow; Neobiotech). Using full digital flow, two fixtures were placed in each patient and immediately provisionalized on the day of surgery. Evaluations encompassed periapical radiographs, implant stability quotient (ISQ), implant stability test (IST) readings, per-implant soft tissue health, patient satisfaction surveys, and esthetic score assessments. Definitive prostheses were delivered twelve weeks post-surgery (CRiS, number: KCT0007300). Following exclusions due to low stability values (n = 2), fixture failure (n = 5), and voluntary withdrawal (n = 1), the implant success rate for patients completing all clinical protocols stood at 100%. The resulting patient failure rates in the control, experimental group 1, and experimental group 2 were 50.0%, 42.9%, and 14.3%, respectively. There were no significant differences between the groups in terms of marginal bone loss, soft tissue health, patient satisfaction, and esthetic scores. Narrow implants showed superior clinical outcomes, followed by S-Narrow and Straumann implants. Calculated one-year survival rates at the implant level were 66.7% for the control group, 85.7% for experimental group 1, and 100% for experimental group 2. All three types of NDIs showed acceptable clinical and radiographic results during the year-long observation period. Full article

Periodontal disease is a broad term given when the periodontium is affected by inflammation. There are several methods to diagnose periodontitis, but no method to quantify the cancellous bone is presently used. For this purpose, a non-invasive tool that is efficient in analyzing bone quality called fractal analysis can be employed. The objective of the study was to utilize fractal dimension (FD) to evaluate cancellous patterns of interproximal alveolar bone using a digital intraoral periapical radiograph (IOPAR) in different clinical presentations of periodontitis classified according to the latest classification by the World Workshop for Periodontal and Peri-Implant Diseases and Conditions, 2017 (WWDC, 2017). The study aimed to numerically calculate the periodontitis changes in the cancellous bone around the affected tooth on an IOPAR using fractal analysis and to provide an additional criterion for the staging of periodontitis. In this cross-sectional observational study, 75 patients were selected and equally allotted to five groups based on the staging system proposed by the WWDC, 2017. The region of interest was selected on the IOPA radiograph of the tooth with the site having the most significant clinical attachment loss, and FD was calculated using Image J analysis. The association of gender and age with stages of periodontitis was studied using the chi-square test of independence. A comparison of % bone loss and fractal dimension among stages was studied by using the non-parametric Kruskal Wallis test. The relationship between % bone loss and fractal dimension within stages and gender was studied by using the Karl Pearson correlation. A receiver operating characteristic (ROC) curve analysis was performed for FD value as a marker of periodontitis patients. We demonstrated that the FD values decreased significantly with the increase in stages (p < 0.0001). The overall relationship between % bone loss and FD showed a significantly strong negative correlation of −0.739 (p < 0.0001), except for stages III and IV. FD can be utilized as a quantitative method for detecting cancellous bone changes in different stages of periodontitis, aiding in diagnosing periodontitis. Full article

In modern dentistry, radiographic imaging is crucial for examining the connection between the maxillary sinus floor and the root apices of the maxillary posterior teeth, particularly when the periapical region is affected by pathology that could result in infectious, inflammatory, or traumatic changes in the maxillary sinus. This study aimed to investigate the prevalence of periapical pathologies in the maxillary posterior teeth and their relationship with maxillary sinus mucosal thickening by using cone-beam computed tomography scans. This retrospective study was conducted on 420 digitized CBCT images which were scanned in sagittal, axial, and coronal views. Out of 420 total images, 223 (53.1%) were of males and 197 (44.9%) were of females. The data were analyzed using SPSS version 28. A total of 2936 posterior maxillary teeth were tested for periapical pathology (PP), 1477 on the right side and 1459 on the left side. In terms of gender, there was no significant relationship between PP in maxillary posterior teeth on both sides and mucosal thickness of the maxillary sinus (p > 0.05). A significant relationship was found between PP in maxillary posterior teeth on both sides and maxillary sinus mucosal thickening (p < 0.05). This study concluded that the prevalence of periapical pathology in the maxillary posterior teeth was significantly associated with a rise in the incidence of maxillary sinus mucosal thickening. Moreover, the primary causative factor for the pathophysiology of the odontogenic maxillary sinus was the periapical pathology in both maxillary first molars. Full article

Technological advancements in health sciences have led to enormous developments in artificial intelligence (AI) models designed for application in health sectors. This article aimed at reporting on the application and performances of AI models that have been designed for application in endodontics. Renowned online databases, primarily PubMed, Scopus, Web of Science, Embase, and Cochrane and secondarily Google Scholar and the Saudi Digital Library, were accessed for articles relevant to the research question that were published from 1 January 2000 to 30 November 2022. In the last 5 years, there has been a significant increase in the number of articles reporting on AI models applied for endodontics. AI models have been developed for determining working length, vertical root fractures, root canal failures, root morphology, and thrust force and torque in canal preparation; detecting pulpal diseases; detecting and diagnosing periapical lesions; predicting postoperative pain, curative effect after treatment, and case difficulty; and segmenting pulp cavities. Most of the included studies (n = 21) were developed using convolutional neural networks. Among the included studies. datasets that were used were mostly cone-beam computed tomography images, followed by periapical radiographs and panoramic radiographs. Thirty-seven original research articles that fulfilled the eligibility criteria were critically assessed in accordance with QUADAS-2 guidelines, which revealed a low risk of bias in the patient selection domain in most of the studies (risk of bias: 90%; applicability: 70%). The certainty of the evidence was assessed using the GRADE approach. These models can be used as supplementary tools in clinical practice in order to expedite the clinical decision-making process and enhance the treatment modality and clinical operation. Full article

While a large number of archived digital images make it easy for radiology to provide data for Artificial Intelligence (AI) evaluation; AI algorithms are more and more applied in detecting diseases. The aim of the study is to perform a diagnostic evaluation on periapical radiographs with an AI model based on Convoluted Neural Networks (CNNs). The dataset includes 1169 adult periapical radiographs, which were labelled in CranioCatch annotation software. Deep learning was performed using the U-Net model implemented with the PyTorch library. The AI models based on deep learning models improved the success rate of carious lesion, crown, dental pulp, dental filling, periapical lesion, and root canal filling segmentation in periapical images. Sensitivity, precision and F1 scores for carious lesion were 0.82, 0.82, and 0.82, respectively; sensitivity, precision and F1 score for crown were 1, 1, and 1, respectively; sensitivity, precision and F1 score for dental pulp, were 0.97, 0.87 and 0.92, respectively; sensitivity, precision and F1 score for filling were 0.95, 0.95, and 0.95, respectively; sensitivity, precision and F1 score for the periapical lesion were 0.92, 0.85, and 0.88, respectively; sensitivity, precision and F1 score for root canal filling, were found to be 1, 0.96, and 0.98, respectively. The success of AI algorithms in evaluating periapical radiographs is encouraging and promising for their use in routine clinical processes as a clinical decision support system. Full article

The aim of this retrospective study was to investigate the relationship between the amount of early bone remodeling, the marginal bone loss (MBL) progression, and the peri-implant sulcular fluid concentration of active metalloproteinase-8 (a-MMP-8) and the incidence of peri-implantitis (P) over 5 years of implant function. It has been documented that dental implants with a high degree of early marginal bone loss (MBL) are likely to achieve additional increased MBL during function. Moreover, it has been speculated that early increased MBL might be a predictive factor for the subsequent onset of peri-implant inflammatory diseases. Clinical and radiographic data at implant placement (T0) and restoration delivery (TR) at 6 months (T1), 2 years (T2), and 5 years (T5) post-loading were retrospectively collected. MBL levels/rates (MBLr) and peri-implant sulcular fluid levels/rates of a-MMP-8 were assessed at TR, T1, T2, and T5. Implants were divided into two groups: group 1 with peri-implantitis (P+) and group 2 without peri-implantitis (P−). A multi-level simple binary logistic regression, using generalized estimation equations (GEEs), was implemented to assess the association between each independent variable and P+. A receiver operating characteristics (ROC) curve was used to evaluate an optimal cutoff point for T1 MBL degree and a-MMP-8 level to discriminate between P+ and P− implants. A total of 80 patients who had received 80 implants between them (39 implants with a laser-microtextured collar surface (LMS) and 41 implants with a machined collar surface (MS)) were included. Periapical radiographs and a software package were used to measure MBL rates. Peri-implant sulcular implant fluid samples were analyzed by a chairside mouth-rinse test (ImplantSafe^®) in combination with a digital reader (ORALyzer^®). Twenty-four implants (six with an LMS and eighteen with an MS) were classified as P+. No statistically significant association was found between the amount of early bone remodeling, MBL progression, and MBLr and the incidence of peri-implantitis. Implants with a-MMP-8 levels >15.3 ng/mL at T1 presented a significantly higher probability of P+. The amount of early marginal bone remodeling cannot be considered as an indicator of the subsequent onset of P, whereas high a-MMP-8 levels 6 months after loading could have a distinct ability to predict P. Full article

Background: The aim of the present study was to highlight clinical and radiographical differences among implants sharing the same macro-geometry but with two different prosthodontic connections. Methods: Patients requiring at least 2 implants in the posterior area of the jaw were randomly divided into two groups (Conical (CS) and Internal Hexagonal (IH) connection). At implant surgery (T0), insertion torque, implant stability quotient (ISQ values recorded by resonance frequency analysis, RFA), and soft tissue thickness (STH) were assessed. A 1-abutment/1-time protocol was applied, and the prosthesis was realized following a fully digital workflow. At the 36-month follow-up periapical x-rays were taken. In order to statistically analyse differences among the two groups and the different variables, paired T-test was used. Linear regression analysis was conducted to analyze how marginal bone loss (MBL) was affected by other independent variables. A neural network created to predict the success (good or not good) of the implant itself was implemented. Results: 30 out of 33 patients (14 males, 16 females, mean age: 68.94 ± 13.01 years) (32 CS and 32 IH) were analyzed. No implants failed. Marginal bone loss at the 3-year time-point was 0.33 ± 0.34 mm and 0.43 ± 0.37 mm respectively for CS and IH with a significant difference between the two groups (p = 0.004). The presence of keratinized gingiva (p = 0.034) significantly influenced MBL. Conclusions: Both the implant connections investigated presented optimal clinical outcomes with minimal marginal bone loss; however, CS implants and implants with the presence of a greater width of keratinized tissue presented significantly lower MBL. Full article

Background and Objectives: There is limited information regarding comparison of long-term dynamics of periapical bone destruction estimated by digital periapical radiography (DPR) and by cone-beam computed tomography (CBCT). This study aimed to compare the radiographically assessed periapical changes of endodontically treated teeth over 2 years of follow-up and to analyse disagreements in periapical lesion size estimates around the same roots using DPR and CBCT. Materials and Methods: A total of 176 endodontically treated teeth, of 128 patients with apical periodontitis, were assessed by DPR and CBCT, at baseline and after 2 years. All periapical radiolucencies were categorised by severity (S0, S1, S2, S3) concerning their size. Descriptive statistics were used to report distribution of the radiolucencies at baseline and at follow-up, and their size transitions over 2 years. Site-specific comparison of the radiolucencies identified by two methods was performed using Z test and Pearson’s chi-square test. Results: majority of the detected radiolucencies were scored as S0: 65% and 68% at baseline; 89% and 83% at follow-up, by DPR and CBCT, respectively. Site-specific score comparison showed that disagreements comprised 18% and 20% of the total number of radiolucencies detected by DPR and CBCT, respectively. There were more disagreements between DPR and CBCT within categories S1 and S2 + S3 compared to S0: at baseline, they comprised 17–33% and after two years 62–95% of all detected radiolucencies within the category. 65% of non-matching score transitions over two years occurred between S0 and S1. The CBCT-based evaluation resulted in negative treatment outcomes for 10 more root canals than the DPR-based result. Conclusions: Most remarkable disagreement between DPR and CBCT recordings was observed within the radiolucency categories S2 and S3. However, the diagnostic accuracy of both radiographic methods was questionable as it resulted in a high proportion of non-matching S0-S1 lesion transitions over 2 years. Full article

No prior study has evaluated the content of YouTube videos that demonstrated how to take periapical radiographs, one of the commonest radiographic examinations in dentistry. This study provided a content analysis on these YouTube videos. Three separate searches were performed with the following search strings: (1) posterior periapical, (2) molar periapical, and (3) anterior periapical. The videos resulting from the searches were sorted by view count, and their related videos (as listed by YouTube on the right of the screen) were also screened. Exclusion criteria included irrelevance to periapical radiography, no real patient involved, no demonstration of periapical radiography procedures), non-English video, and duplicate videos. Finally, 21 videos were included and analyzed. For each included video, the following aspects were evaluated: general settings (types of image receptor, patient age, and radiographic technique), patient preparation, machine preparation, receptor placement, and operator safety. All but one were demonstrated with an adult patient. The videos were largely based on digital imaging with the use of either intraoral sensors or phosphor plates, and mostly used paralleling technique. Several common issues were identified, such as not removing the metallic objects from the patient’s head and neck region, not showing the selection of radiation dose, not placing the orientation dot on the film or phosphor plate on the occlusal side, and not wearing proper personal protective equipment. More instructional videos are definitely required. Future videos should eliminate these issues, and also demonstrate with pediatric patients. Perhaps the dental radiology department of a well-established university should be enticed to produce an instructional video that presents the technique in a flawless presentation, to facilitate the learning of dental students, dental hygienists and dental assistants who have yet to master their skills. Full article

This study aimed to assess the errors that happened during root canal treatment (RCT) and compare the quality of root canal fillings (RCFs) performed by different academic grades of dental students at Jouf University. Materials and Methods: a retrospective audit study was conducted to check the errors that occurred during RCT performed by seniors and undergraduates. The quality of the RCFs were evaluated, using digital periapical radiographs depending on previously validated criteria. Data analyses were performed using Statistical Package for the Social Sciences. Descriptive statistics were used for expressing the frequencies of variables and the Chi-square test was used for comparing different variables with a 0.05 level of significance. Results: overall, 332 endodontically treated teeth (566 root canals) were finally chosen for the study. Out of these treated cases, 156 teeth (47%) had a total of 287 recorded errors, mainly in posterior teeth. From the total number of errors, short obturation was the highest error occurred (29%), followed by lack of apical seal (25.1%). Root perforation was the least reported error (2.8%), proceeded by broken instruments (5.6%). A total of 13.2% of the errors were teeth left with unfilled canals, while 7.7% were for an overextended filling. There were no significant differences between the quality of RCF performed by different academic grades. Conclusion: depending on the current study, the quality of RCTs performed by seniors and undergraduate students was 53% acceptable. A clear plan should be applied to improve the quality of treatment outcomes of undergraduate students by implementing more effective preclinical training courses, increasing the ration of supervisor-to-students, and using more advanced modalities during treatment. Full article