The major application of forensic odontology includes the identification of human remains using antemortem and postmortem dental records where an individual is skeletonized, burnt, decomposed, or diminished and cannot be identified by regular methods. The present study aims to assess the knowledge, attitude, and practice of forensic odontology in dental practitioners. This questionnaire-based cross-sectional descriptive study was done among dental practitioners working in different hospitals, medical colleges and dental clinics in Kathmandu, Nepal. A total of 171 general dental practitioners, specialists and faculty members were included in the study. The questionnaire included eight questions related to knowledge, four questions on attitude and four questions on practice. The data obtained was entered into a Microsoft Excel sheet and analyzed using the Statistical Package for Social Sciences Version 21. For knowledge, attitude and practice scores, frequency, percentage, mean, and standard deviation were calculated. The independent sample t-test was used to compare the knowledge, attitude and practice scores between general dentists and specialists. The mean knowledge score was 6.70±0.73, the mean attitude score was 2.05±0.97and the mean practice score was 2.68±0.89. Of the total study participants, 170 (99.4%) had adequate knowledge,122(71.3%) had adequate attitude, and 153(89.5%) had adequate practice. There was no statistically significant difference in mean knowledge and practice scores between general dentists and specialists. The mean attitude score was found to be higher among general dentists than among specialists, which was statistically significant (p-value less than 0.05). The study highlights a gap between dentists' knowledge and their attitudes and practices regarding forensic odontology. While they are well-informed, there is a need to improve their practical engagement and record-keeping for effective forensic application in medicolegal cases.
The objective of this study was to develop an evidence-based S3-level clinical practice guideline for the management of deep and extremely deep caries in vital permanent teeth. An evidence-based medical guideline based on systematically searched and appraised evidence as well as a structured consensus (S3-level) was jointly developed by the European Federation of Conservative Dentistry (EFCD), the European Society of Endodontology (ESE), the Organization for Caries Research (ORCA), and the German Society of Conservative Dentistry (DGZ), following the methodological framework of the Association of Scientific Medical Societies in Germany (AWMF) and the GRADE approach. Four working groups formulated key clinical questions regarding: (1) caries removal strategies, (2) cavity liners, (3) management of exposed pulps, and (4) materials for direct pulp capping and pulpotomy. Systematic reviews were conducted for each question, and evidence was synthesized and graded for quality. A structured consensus process was used to formulate recommendations. In order to encourage its wide dissemination, this article is freely accessible on Clinical Oral Investigations, International Endodontic Journal, and Caries Research journals' websites. Evidence supports selective (SE) or stepwise caries removal (SW) over non-selective removal (NSE) to reduce the risk of pulp exposure in deep caries. Routine use of cavity liners after caries removal showed no consistent clinical benefit and is not routinely recommended. For vital pulp therapy following pulp exposure, both direct pulp capping and pulpotomy are effective options in teeth without irreversible pulpitis, while pulpotomy is an acceptable alternative to pulpectomy in cases with signs of irreversible pulpitis. Hydraulic calcium silicate cements demonstrated superior clinical outcomes compared to calcium hydroxide and should be preferred for pulp capping and pulpotomy. The certainty of evidence ranged from very low to moderate across questions and outcomes. For deep caries, maintaining pulp vitality by using less invasive management strategies is supported by current evidence. Implementation of this guideline requires clinician training, patient-centred decision-making, and consideration of economic and practical factors. Further research is needed, particularly for extremely deep caries and towards long-term outcomes.
Age estimation is vital in forensic odontology, with exfoliative cytology and cytomorphometry emerging as promising non-invasive techniques. This study evaluates the accuracy of cytomorphometric parameters like nuclear perimeter (NP), cell perimeter (CP), and NP:CP ratio, in estimating age and gender across various age groups. This cross-sectional study involved 120 participants (60 males and 60 females) divided into six age groups (10-20, 21-30, 31-40, 41-50, 51-60, ≥61 years). Exfoliative cytology was performed to collect buccal mucosal cells, stained with Papanicolaou stain and analyzed for NP, CP, and NP:CP ratio in 50 cells per smear at 400×magnification. Statistical analysis was conducted. A significant decline in mean NP and CP values was observed with increasing age, while NP:CP ratio showed a slight increase in those aged ≥61 years. On intergroup comparisons, notable differences were seen between juvenile/early adulthood and middle/older adulthood groups. Regression analysis showed CP had the highest age prediction accuracy (31.7%), with a combined model improving accuracy to only 35.8%. Logistic regression using NP and CP achieved 90% predictive accuracy in distinguishing juvenile from older adulthood, with CP as the primary predictor. No significant gender differences were found, except for NCR, which was higher in females. This study demonstrates that the cytomorphometric evaluation (NP, CP, NP:CP ratio) of exfoliated buccal mucosal cells is not a potent tool for age estimation due to its moderate predictive accuracy. While it excels in distinguishing between distinctly separated age groups, its precision falters in closely adjacent groups, rendering it of limited forensic relevance.
Modern forensic odontology is undergoing a digital transformation associated with the introduction of 3D technologies and the creation of specialized digital databases. These innovations radically change traditional approaches to personal identification, providing increased accuracy, speed and objectivity of analysis. The use of 3D scanning, CAD/CAM systems, computed tomography, and 3D printing makes it possible to create highly detailed digital models of the maxillofacial region that can be used to identify individuals in cases of mass disasters, criminal investigations, and when working with severely damaged remains. Despite the obvious advantages, the integration of these technologies faces challenges of standardization, implementation costs, and cybersecurity. A systematic search and analytical review of scientific literature published over the past 10 years (2014-2024) was conducted. Relevant publications were searched in international electronic databases (PubMed, Cochrane Library, Scopus, Web of Science) and in Russian scientific electronic libraries (eLibrary, CyberLeninka). The inclusion criteria were: focus on the application of 3D technologies (3D scanning, CAD/CAM, 3D printing) and/or digital databases in the context of forensic dentistry; description of specific clinical cases or research techniques; the presence of an analysis of advantages, limitations and prospects. Articles that did not contain original data were excluded, as well as publications that were not available in full text. As part of the study, 20 publications were selected from the proposed 254 that meet the specified inclusion criteria. Современная судебная одонтология переживает цифровую трансформацию, связанную с внедрением 3D-технологий и созданием специализированных цифровых баз данных. Эти инновации кардинально меняют традиционные подходы к идентификации личности, обеспечивая повышенную точность, скорость и объективность анализа. Использование 3D-сканирования, CAD/CAM-систем, компьютерной томографии и 3D-печати позволяет создавать высокодетализированные цифровые модели челюстно-лицевой области, которые могут использоваться для установления личности в случаях массовых катастроф, криминальных расследований и при работе с сильно поврежденными останками. Несмотря на очевидные преимущества, интеграция этих технологий сталкивается с проблемами стандартизации, затрат на внедрение и обеспечения кибербезопасности. Проведен аналитический обзор научной литературы, опубликованной за последние 10 лет (2014—2024 гг.). Поиск релевантных публикаций осуществлялся в международных электронных базах данных (PubMed, Cochrane Library, Scopus, Web of Science) и в российских научных электронных библиотеках (eLibrary, CyberLeninka). Критериями включения являлись фокус на применении 3D-технологий (3D-сканирование, CAD/CAM, 3D-печать) и/или цифровых баз данных в контексте судебной стоматологии; описание конкретных клинических случаев или исследовательских методик; наличие анализа преимуществ, ограничений и перспектив. Исключались статьи, не содержащие оригинальных данных, а также публикации, недоступные в полном тексте. В рамках исследования из предложенных 254 отобрано 20 публикаций, отвечающих указанным критериям включения.
Age and gender estimation are crucial in forensic odontology for identification and legal purposes. Conventional methods utilizing manual interpretation like Demirjian's and Gustafson's techniques are labor-intensive and prone to observer bias. Deep learning models, therefore, offer a promising alternative, enabling automated, accurate, and efficient assessments using dental radiographs. Therefore, the present study aims to predict age and gender using deep learning models and to compare their efficiency. Multiple convolutional neural network (CNN) architectures including ResNet18/50, DenseNet variants, EfficientNetB0, VGG16, MobileNetV3, and AlexNet were used; a total of 2341 panoramic radiographs were utilized. Images underwent preprocessing including normalization, resizing (to 224 × 224 pixels), and data augmentation (AutoAugment and RandAugment) to enhance model performance. Transfer learning with pretrained models-ResNet variants and DenseNet-was implemented with an ensemble strategy to optimize accuracy. Performance was assessed using metrics including accuracy, precision, recall, F1-score, and prediction time. DenseNet161 achieved the highest accuracy among individual models, with 90.4% accuracy for gender classification and 94% accuracy for age categorization. Ensemble models achieved accuracies of 94% for gender and 90.4% for age classification. While ensemble learning improved gender prediction, it did not outperform DenseNet161 in age estimation. Deep learning models provide a promising and objective approach for demographic estimation using panoramic radiographs. However, their clinical applicability requires further validation using larger, multi-center datasets and standardized evaluation protocols.
Developmental stages of the dentition and age-group classification are crucial in forensic odontology, oral radiology, pediatric dentistry, and orthodontic dentistry. However, the manual interpretation of dental panoramic (OPG) radiographs for assessing the developmental stages and further age-group classification is time-consuming and prone to variability. This current model aims to evaluate the performance of a computational neural network (CNN) based model for automated detection of Nolla's developmental stages of permanent teeth and subsequent dental age group classification using digital OPGs from individuals aged 3 - 30 years. Nolla's method was selected for its broad applicability to all the permanent teeth, including the developing third molar, and its comprehensive staging system. A total of 4073 radiographic images for Nolla's developmental stages (0 to 10) and age-group classification were utilized for training and validation of an annotated dataset, with an independent dataset of 1450 anonymized radiographs with varying quality and 644 repository images for testing of the YOLOv8-based models. For the developmental stage classification, the model achieved a precision of 0.912, recall rate of 0.927, F1 score of 0.919, and a mean average precision (mAP) of 0.963. For age-group classification, the model demonstrated a precision of 0.83, recall of 0.79, F1 score of 0.81, and mAP of 0.88. The overall performance was highest in the mid-age range, and the lower metrics were observed in younger age groups less than 6 years of age. The current model effectively identifies and classifies the developmental stages of permanent teeth and estimates age from panoramic radiographs with high accuracy, especially in well-represented age groups. It emphasizes the feasibility of applying real-time object detection frameworks for age assessment. While not intended as a validated forensic age-group classification tool, the model provides a proof-of-concept for integrating real-time object detection approaches into dental developmental assessment workflows and establishes a foundation for future population-specific, sex stratified, and forensically validated models.
To evaluate the quality and readability of large language models (LLMs) when responding to Frequently Asked Questions (FAQs) about oral lichen planus (OLP). We evaluated the responses of three LLMs (ChatGPT-4o, Gemini 2.0 Flash Experimental, and Copilot) to 13 patient-centered FAQs about OLP. Questions were identified using query tools, and answers were assessed by 14 oral medicine experts using the Quality Assessment of Medical Artificial Intelligence (QAMAI) tool. Readability was analyzed with the Flesch Reading Ease (FRE) and Flesch-Kincaid Grade Level (FKG) tools. All LLMs provided generally accurate and relevant responses, with median QAMAI scores indicating "good" to "very good" quality. ChatGPT achieved slightly higher completeness, particularly for questions on OLP definition and treatment. The reference provision was inconsistent across all chatbots. Readability analysis revealed that most responses required college-level literacy, with ChatGPT producing the most complex texts, Gemini occasionally achieving more accessible outputs, and Copilot situated in an intermediate position. LLMs may have potential as adjunctive tools for patient education in OLP, although they remain limited by incomplete information, inconsistent references, and suboptimal readability. Future research should incorporate longitudinal LLMs evaluations and training to develop models delivering accurate, accessible information, tailored to users' literacy levels.
To evaluate the effects of endodontic irrigants on the surface roughness of flowable and conventional composite resins using contact profilometry and atomic force microscopy (AFM). Seventy-two discs were prepared from a flowable and a conventional resin composite (n = 36 each). Specimens were immersed in 5.25% NaOCl, 17% EDTA, or sequential NaOCl + EDTA. Surface roughness (Ra) was measured before and after irrigation with a contact profilometer; nano-topography was quantified on 45 µm × 45 µm areas using AFM. Data were analyzed with mixed-model repeated measures ANOVA and paired t-tests (α = 0.05). Profilometry revealed a significant Ra increase only in the flowable resin composite after NaOCl + EDTA (p = 0.009); no significant changes were detected in the conventional resin composite for any irrigant. AFM showed consistently higher nano-roughness in the conventional resin composite than in the flowable resin composite for all solutions (p < 0.001). NaOCl and NaOCl + EDTA significantly reduced AFM Ra in the flowable resin composite, whereas EDTA significantly decreased Ra in the conventional resin composite. Irrigation-induced surface changes are material- and method-dependent. Flowable resin composites are more susceptible to macro-scale roughening under sequential NaOCl + EDTA, while conventional resin composites exhibit greater chemical stability. Combined use of profilometry and AFM provides a more comprehensive assessment of irrigant-related surface alterations.
Background: Magnetic resonance imaging (MRI) is the reference standard for evaluating temporomandibular joint (TMJ) disorders, particularly for assessing disc position, joint effusion, and degenerative changes. With increasing imaging demands and advances in deep learning, artificial intelligence (AI) has emerged as a potential adjunct to expert interpretation. This systematic review aimed to compare the diagnostic performance of AI-based models with that of human experts in TMJ MRI analysis. Methods: This review was conducted in accordance with the PRISMA 2020 guidelines and prospectively registered in PROSPERO (CRD420251174127). A systematic search of PubMed/MEDLINE, ScienceDirect, Wiley Online Library, and Springer Nature Link was performed for studies published between 2020 and 2026. Eligible studies included human participants undergoing TMJ MRI and evaluated AI, machine learning, or deep learning models against human expert interpretation. Extracted outcomes included sensitivity, specificity, accuracy, area under the receiver operating characteristic curve (AUC), and agreement metrics. Risk of bias was assessed using QUADAS-2. Due to substantial heterogeneity, a narrative synthesis was conducted. Results: Five retrospective diagnostic accuracy studies were included, comprising sample sizes ranging from 118 to 1474 patients. Target conditions included anterior disc displacement, joint effusion, osteoarthritis, and disc perforation. AI models demonstrated strong discriminative performance, with reported AUC values ranging from 0.79 to 0.98. In direct comparisons, AI achieved diagnostic accuracy comparable to experienced radiologists. AI systems frequently demonstrated higher specificity and similar overall accuracy, whereas human experts often showed higher sensitivity. In osteoarthritis assessment, AI performance approached expert level and exceeded that of less experienced readers. All studies were retrospective and predominantly single-center, with heterogeneous reference standards and limited external validation. Conclusions: AI achieves diagnostic performance comparable to experienced clinicians in TMJ MRI interpretation and shows promise as a decision-support tool. Nevertheless, it should be regarded as complementary to, rather than a replacement for, expert radiological assessment pending further rigorous validation.
To histologically evaluate the healing of intrabony periodontal defects treated with guided tissue regeneration (GTR), if it is combined with orthodontic tooth movement (OTM) or used as a sole treatment. Twenty subjects requiring regenerative periodontal therapy and OTM were treated with the use of extended, coronally advanced flaps according to the GTR techniques with the utilization of deproteinized bovine bone mineral (DBBM) particles. Patients either received early initiation of OTM (test) or had their teeth splinted (control) after the surgical intervention. Re-entry procedures were scheduled 9 months postoperatively to obtain a biopsy from the previous defect sites. The primary outcome variable comprised histological and histomorphometric analysis. Control group cases (n = 9) revealed nice embedding of graft particles into newly formed bone, which were predominantly present in the central and apical third of the biopsy samples. The coronally located DBBM was more often encapsulated in the connective tissue. Test samples (n = 10), both at the tension and pressure sites, demonstrated incorporation of a reduced graft ratio into newly formed bone. Ongoing bone formation and the presumably orthodontic-induced remodeling also interfered with the bone substitute material. Histomorphometry showed a distribution of 17.4% versus 33.9% new bone (p = 0.011), 33.2% versus 16.3% graft ratio (p = 0.001) and 49.4% versus 49.7% soft tissue components (p = 0.74) in the control versus test groups, respectively. Early initiation of tooth movement does not appear to adversely affect periodontal bone healing. A pronounced graft reduction and new bone formation in test patients, compared to those in controls, occurred presumably due to the effects of orthodontic-induced bone remodeling.
To determine intrafollicular concentrations of letrozole (LTZ) and key steroids in women undergoing ovarian stimulation (OS) with or without LTZ co-treatment, and to explore associated clinical outcomes. Follicular fluid (FF) collected at oocyte pickup from 30 women participating in the RIOT-B study, a randomized controlled trial comparing OS with recombinant FSH (150 IU/day) combined with either LTZ (5 mg/day; n = 15) or placebo (n = 15). Concentrations of LTZ and steroid were quantified by LC-MS/MS. Associations between FF composition and clinical outcomes were evaluated. At oocyte pickup, mean FF LTZ concentration was 144 ± 12 nmol/L (nM) (range 51-270). FF 17β-estradiol (E2) concentrations were similar between groups (≈900 nM), whereas testosterone, androstenedione, DHEA, and 17OH-progesterone (17OH-P4) were markedly elevated in the LTZ group (p < 0.001-0.0001). In contrast, P4 levels remained unchanged. Among LTZ-treated women, higher FF concentrations of LTZ and testosterone were significantly associated with failure to conceive. No relationship was observed between FF LTZ levels and BMI or gonadotropin dose. Intrafollicular estrogen levels remain preserved during LTZ administration, accompanied by pronounced androgen accumulation and elevated 17OH-P4. These findings suggest complex, cell-specific effects of aromatase inhibition on follicular steroidogenesis and raise questions regarding the optimal dosing and mechanistic rationale for LTZ co-treatment in assisted reproduction.
To evaluate the survival and success rates, as well as mechanical and biological outcomes of posterior 3D-printed resin-matrix ceramic crowns in a fully digital workflow over a 2-year follow-up. A prospective clinical trial was conducting involving 30 posterior crowns fabricated from a resin-matrix ceramic using DLP 3D-printing technology. Dental preparations were performed and scanned with an intraoral scanner by a single operator. All crowns were cemented using the same dual-curing resin cement. Clinical performance was assessed using California Dental Association (CDA) criteria. Periodontal parameters (plaque index, gingival index and probing depth) were evaluated with a periodontal probe at cementation and at 6-month, 1-year, and 2-year recall appointments on abutment teeth and contralateral or antagonistic uncrowned natural teeth used as controls. Data were analyzed using Wilcoxon signed rank test and Kaplan–Meier survival analysis. The 2-year survival rate was 93%, and the success rate was 87%. Two crowns debonded, and no biological complications were observed. All crowns remained within the satisfactory range after 2 years. A slight yellow shift was detected in 4 crowns, resulting in a significant color change at 2 years (p = 0.046), while all other CDA parameters remained unchanged. The margin remained stable throughout the observation period. Plaque index increased after one year in the abutment and control teeth. Within the limitations of this study, including the absence of a control group, 3D-printed resin-matrix ceramic crowns may represent a viable alternative for posterior teeth. Long-term studies are required to confirm these results. Posterior 3D-printed resin–matrix ceramic crowns within a fully digital workflow demonstrated satisfactory performance after two years, supporting their potential as a viable option for posterior restorations.
The identification of human remains often relies on dental data, which remain stable under extreme postmortem conditions. Dental resin composites, in particular, can retain their microstructural and elemental characteristics after thermal exposure or degradation, providing valuable adjunct information in forensic identification. This descriptive cross-sectional study presents the development of an ongoing multinational reference database of 50 dental resin composites collected from nine countries: Australia, Brazil, China, Germany, Italy, Japan, Korea, Luxembourg, and Switzerland. Each sample underwent morphological and elemental characterization using scanning electron microscopy with energy-dispersive X-ray spectroscopy (SEM/EDS). Microstructural and compositional variability was observed across brands and countries; the database documents these differences through magnified imagery (2000 ×, 5000 ×, and 10,000 ×) and corresponding elemental spectra. Although geographical inference has inherent limitations due to global migration, displacement, dental tourism, and the international distribution of dental materials, resin composite analysis can contribute meaningfully to postmortem dental profiling, particularly where certain materials remain market- or region-specific. The database is designed as a practical comparison atlas for forensic odontologists, promoting systematic sampling and analysis of composite restorations during dental autopsies of unidentified human remains to support identification and assist in the preliminary reconstruction of geographic treatment history. The database is continuously updated and is available to forensic odontologists upon request. This research underscores the need for continued expansion, validation, and integration of resin-composite comparison databases into forensic odontology workflows.
The aim of this study was to investigate tooth extractions in a Swedish public general dental practice setting, including the proportion of endodontically treated teeth, reasons for extraction, and subsequent prosthetic replacement. A prospective cohort study was conducted in 20 clinics within the Public Dental Service of Västra Götaland, Sweden. During an 8-week period, general dental practitioners consecutively registered reasons for tooth extraction. Patients' pain levels were assessed. Pre-extraction radiographs were assessed for tooth status. Five-year follow-up data from electronic dental records were used to determine whether the extracted teeth had been prosthetically replaced and to classify the type of replacement. Descriptive and inferential statistics were used. A total of 133 patients (61 men and 72 women; mean age 54.0 years, SD = ± 15.8) underwent extractions. Endodontic pathology (36.8%) and fractures (24.8%) were the most common reasons. Sixty-one patients had previous endodontic treatment, and one-third of extracted teeth were root-filled. Thirty-five teeth were prosthetically replaced, most often with removable prostheses (45.7%). Endodontically treated teeth, including those with initiated or completed root canal treatment, were markedly overrepresented among extractions, yet prosthetic replacement was infrequent. Younger patients less often opted for replacement, warranting further investigation of factors influencing replacement decisions.
This retrospective cohort study was performed to evaluate the original Brånemark scheme vs the quad zygoma scheme for treating severe maxillary atrophy. Zygomatic implant surgeries performed between 1998 and 2021 at Ziekenhuis Oost Limburg, Belgium were analysed. Patients with ≥2 years of follow-up were included. Data on implant survival, prosthesis survival, and surgical techniques were assessed using Kaplan-Meier survival curves and multivariable Cox proportional hazards models adjusted for age, sex, and smoking; statistical significance was set at P ≤ 0.05. Overall, 203 patients with 675 zygomatic and 223 standard implants were evaluated. The quad zygoma scheme demonstrated a significantly higher implant survival rate than the classic Brånemark scheme (P = 0.009), particularly in the anterior maxilla, although no significant difference in prosthesis survival was observed between the two. The sinus slot technique showed superior implant and prosthesis survival compared to the intrasinus approach (P = 0.002, P = 0.015). These findings suggest that the quad scheme offers advantages in implant survival, especially in the anterior maxilla, while prosthetic outcomes remain comparable between the two schemes. Additionally, the sinus slot technique may help reduce sinus-related complications. Five-year implant survival was 91.5% for the classic scheme and 94.9% for the quad scheme; 10-year survival was 83.7% and 92.6%, respectively. Personalized surgical strategies are crucial for optimizing outcomes in zygomatic implant treatments, and further long-term research is necessary to confirm these results.
The accurate assessment of infraosseous periodontal defects is crucial for effective diagnosis and treatment planning. Cone-beam computed tomography (CBCT) enables detailed imaging of these defects; however, to leverage their full potential, CBCT images must be reconstructed in 3 dimensions (3D). Manual and semi-automatic (SA) segmentation methods are time-consuming and prone to human error. This study aimed to evaluate the performance of a deep learning (DL) model in segmenting mandibular infraosseous periodontal defects on CBCT scans. A multi-stage Segmentation Residual Network (SegResNet)-based DL model was used to segment CBCT scans from patients with stages III to IV periodontitis. Linear and volumetric measurements of infraosseous defects from DL-generated 3D models were compared to those obtained using SA segmentation. The depth (INFRA), width (WIDTH), angle (ANGLE), and volume of 48 infraosseous defects were assessed on both DL and SA segmentations. Measurements made on the DL and SA segmentations correlated strongly. The intraclass correlation coefficient (ICC) was 0.941 (p < 0.0001) for INFRA, 0.943 (p < 0.0001) for WIDTH, 0.889 (p < 0.0001) for ANGLE, and 0.948 (p < 0.0001) for defect volume. These results indicate high reliability of the DL model in capturing key characteristics of infraosseous periodontal defects. These findings support the use of DL-based CBCT segmentation as a valuable tool for enhancing periodontal diagnosis. However, as this study was limited to mandibular defects, applicability to maxillary cases remains to be validated. Periodontitis can cause severe bone loss around teeth, leading to the formation of complex defects that are challenging to diagnose and to treat. Cone‐beam computed tomography (CBCT) provides detailed 3D imaging of these defects, but current methods for segmenting CBCT scans and acquiring 3D models are time‐consuming and prone to human error. This study evaluated the ability of artificial intelligence (AI) to automatically segment infraosseous periodontal defects on CBCT images. Using a SegResNet‐based deep learning model, the manuscript compared AI‐generated 3D models to the results of traditional semi‐automatic segmentation methods. The depth, width, angle, and volume of 48 infraosseous defects were measured, assessing whether AI could match human accuracy. The AI model performed exceptionally well, with strong statistical agreement between AI and human‐generated measurements. By improving the way periodontal defects are visualized and measured, AI‐powered CBCT analysis could help dentists make better treatment decisions, reduce variability in diagnosis, and reduce the complication rates.
Background and Objectives: This study aimed to evaluate associations between dental caries, periodontal pockets, and radiologically detected periapical lesions in relation to serum levels of Dickkopf-1 (Dkk-1) and tartrate-resistant acid phosphatase 5B (TRAP-5B) in oncologic patients with ear, nose, and throat (ENT) cancer compared with healthy controls. Materials and Methods: The study included 63 subjects divided into a study group of 33 patients diagnosed with ENT cancer and a control group of 30 healthy individuals. Blood samples were collected to assess serum Dkk-1 levels using a sandwich enzyme immunoassay and TRAP-5B levels. Radiological dental evaluation included orthopantomography (OPT) and cone beam computed tomography (CBCT) to assess the number and depth of dental caries and the presence of periapical lesions. Periodontal pockets were recorded through clinical examination. Results: Serum biomarker analysis demonstrated significant differences between groups: TRAP-5B levels were significantly higher in patients with ENT cancer, whereas Dkk-1 concentrations were significantly lower compared with healthy controls (p < 0.001). OPT revealed up to eight carious lesions in both groups. The mean number of carious lesions was higher in healthy subjects (2.97 ± 2.48) than in patients with ENT cancer (2.06 ± 2.29). CBCT evaluation revealed 0-8 carious lesions in healthy individuals and 0-6 lesions in patients with ENT cancer, with a significantly higher mean number of lesions in the control group (2.97 ± 2.48 vs. 1.85 ± 1.89). Periodontal pockets were more frequent in patients with ENT cancer (0.67 ± 1.32) than in controls (0.37 ± 0.81). OPT evaluation also showed a higher mean number of periapical lesions in patients with ENT cancer (0.82 ± 1.29) compared with controls (0.37 ± 0.67). CBCT examination demonstrated that the mean number of periapical lesions in patients with ENT cancer was more than twice that of the control group, although this difference did not reach statistical significance. Conclusions: Patients with ENT cancer exhibited significantly altered systemic bone turnover biomarker profiles, characterized by increased TRAP-5B and decreased Dkk-1 levels. Clinically, these patients also presented a higher prevalence of periodontal pockets and periapical lesions, whereas carious lesions were more frequently detected in healthy individuals. The combined radiological and biochemical findings contribute to a better understanding of oral-systemic interactions in oncologic patients and highlight the importance of comprehensive dental evaluation prior to oncologic therapy.
The aim of the study was to compare the clinical efficacy of Platelet Lysate (PL) versus Hyaluronic Acid (HA) after arthrocentesis in the management of patients with anterior disc displacement with reduction. This randomized clinical trial was conducted on 60 patients (17 males and 43 females) with anterior disc displacement with reduction confirmed with magnetic resonance imaging (MRI). The patients were split into two equal groups at random based on the type of treatment that was used. Group 1: arthrocentesis plus PL, Group 2 arthrocentesis plus HA. The pain intensity, clicking sound, maximum inter-incisal opening (MIO) and range of lateral mandibular excursions were measured. All the measured parameters were statistically analyzed. After 6 months, both groups demonstrated a significant improvement in all the parameters that were measured. The PL Group showed a statistically better resolution of clicking compared to HA Group with an Absolute Risk Difference of 33.3% (P < 0.05). The MIO between-group difference was 4.867 mm (P < 0.001), so exceeding the Minimum Clinically Important Difference (MCID). On the other hand, although the PL Group demonstrated statistical superiority in pain scores and range of lateral mandibular excursions (P < 0.05), the clinical magnitude of the between-group difference was modest. PL appears to be a safe and effective adjunctive intra-articular therapy after arthrocentesis for the management of patients with anterior disc displacement with reduction. It provides a clinical advantage over HA in resolving joint clicking and improving MIO. For pain reduction and range of lateral mandibular excursions, the therapeutic benefits of PL and HA are clinically comparable. Trial registration: On 4/12/2024, it was registered in Clinical-Trials.gov PRS ( https://register.clinicaltrials.gov ) with identification number NCT06441279.
Malocclusions occur at high frequencies in children and adolescents. While early orthodontic (interceptive) interventions may reduce the need for later comprehensive treatment, their cost-effectiveness in publicly funded health systems is unclear. This study compares the cost-effectiveness of interceptive orthodontic care and fixed-appliance therapy, focusing on total costs, treatment outcomes, and resource use. A decision tree model was developed using observational data on treatment success rates, duration, and appointments to estimate resource use and costs for interceptive orthodontic care; Fixed Appliance therapy was modeled as an optimal 2-year treatment pathway. A health-care payer perspective was applied. Incremental costs and effects were calculated for four interceptive modalities: Quad Helix, Extraoral Traction (EOT), Removable Plates, and Activator appliances, as compared to fixed appliance therapy. Minimum required success rates were estimated for achieving cost-neutrality. Probabilistic sensitivity analyses (10 000 Monte Carlo simulations) and scenario analyses assessed the robustness of the results. All the interceptive treatments demonstrated lower expected costs than the fixed appliance therapy, albeit with lower clinical effectiveness. Quad Helix exceeded the minimum required success rate 20% points, representing a clear margin of cost-effectiveness. Removable Plates also exceeded the minimum required success rate, but with a smaller margin of 6% points. The Activator and EOT appliances were more dependent on patient compliance and failed to meet the minimum required success rate, requiring increases of 13% and 10% points, respectively, to achieve cost-neutrality. Sensitivity analyses confirmed these patterns and underscored the importance of long-term treatment stability. The model assumed a 100% success rate for fixed appliances and relied on expert opinion for long-term stability parameters, given the limited availability of relapse data. In the publicly funded dental care context studied, the use of Quad Helix and removable plates in publicly funded health-care systems appears to be cost-effective. Activator and EOT appliances should be used selectively. The study also contributes a transparent, adaptable modeling framework that can incorporate locally relevant costs and future long-term outcome data, supporting use in other publicly funded settings.
Effective professional plaque removal is of major importance in the prevention of white spot lesions and gingivitis in patients with fixed orthodontic appliances. However, visual identification of plaque can be difficult, especially around brackets, ligatures and wires. The purpose of the present randomized clinical trial was to evaluate the effectiveness of a plaque disclosing agent (PDA) as a visual guide for biofilm removal. Thirty-two systematically and periodontally healthy adults with fixed orthodontic appliances and Plaque Index (PI) >  = 25% were enrolled from October 2020 to May 2022, the subjects were equally randomized into test and control group. Primary outcome was the change in the difference in percentage of residual plaque area (RPA) between the two study groups. In the test group, a PDA was applied before professional oral hygiene, whilst the control group received a hygiene session without disclosing. The PDA was then re-applied at the end of the treatment in both groups, and the RPA was assessed via Image-J software analysis of standardized frontal photos and compared between groups. The average RPA in the test group was 3.9% (CI 95% 2.6%; 5.1%), which resulted significantly lower than in the control group, where it reached 12.0% (CI 95% 8.0%-16.0%) (p-value < 0.001). The percentage of area with residual plaque was modelled using a beta-regression model. The use of plaque disclosing agents as guidance for professional oral hygiene treatment leads to improved plaque removal in patients with fixed orthodontic appliances. NCT05428189, 2022-06-08, retrospectively registered.