Purpose: Vertical root fractures (VRFs) remain a major diagnostic challenge in endodontics due to image noise and artifacts in cone-beam computed tomography (CBCT), particularly those caused by intracanal posts. This study evaluated the effect of an advanced noise reduction (ANR) algorithm on CBCT performance in detecting VRFs inmaxillary second premolars and examined how different post materials influenced diagnostic outcomes. Materials and Methods: Seventy extracted maxillary second premolars with single canals were divided into 5groups according to post material (cast, fiberglass, titanium, stainless steel, and brass). VRFs were induced in half of the specimens using a universal testing machine under standardized conditions. CBCT scans were obtainedusing a Carestream 9600 device with fixed parameters, both with and without ANR. Two experienced radiologists independently evaluated the images using a 5-point scale. Sensitivity, specificity, predictive values, and interobserveragreement were analyzed using SPSS version 21 (IBM Corp., Armonk, NY, USA). Results: The application of ANR increased overall sensitivity and interobserver agreement compared with conventional images. Specificity varied by post material: fiberglass posts demonstrated the highest diagnostic accuracy, while stainless steel and brass produced stronger artifacts and lower sensitivity. Conclusion Incorporating ANR into CBCT imaging improves VRF detection by improving sensitivity and observerconsistency, especially in cases with minimal metallic interference. These findings highlight the clinical benefits of ANR and support further research integrating noise and metal artifact reduction techniques with artificial intelligenceto optimize diagnostic precision.

Purpose: The aim of this study was to compare the accuracy of AI-based AudaxCeph software, Dolphin software, and the manual technique for identifying orthodontic landmarks and tracing lateral cephalograms. Materials and Methods: In this cross-sectional study, 23 anatomical landmarks were identified on 60 randomlyselected lateral cephalograms, and 5 dental indices, 4 skeletal indices, and 1 soft tissue index were measured. Each cephalogram was traced using 4 different methods: manually, with the Dolphin software, with the AudaxCeph software automatically, and with the AudaxCeph software in semi-automatic mode. The intra-class correlation coefficient (ICC) and Bland-Altman plots were used to evaluate the agreement between methods. Inter-observer and intra-observer agreements, calculated using the ICC, confirmed the accuracy, reliability, and reproducibility of the results: . Results: There was strong agreement among the AudexCeph (semi-automated or automated) AudaxCeph, Dolphin, and manual methods in measuring orthodontic indices, with ICC values consistently above 0.90. Bland-Altman plots confirmed satisfactory agreement between both versions of AudaxCeph (semi-automated and automated) with the manual method, with mean differences close to 0 and about 95% of data points within the limits of agreement.However, the semi-automated AudaxCeph showed greater agreement and precision than the automated version, as indicated by narrower limits of agreement. The ICC values for inter-observer and intra-observer agreements exceeded 0.98 and 0.99, respectively. Conclusion The semi-automated AudaxCeph software offers a robust and cost-effective solution for cephalometric analysis. Its high accuracy and affordability make it a compelling alternative to Dolphin software and the manual method.

Purpose: The aim of this study was to compare the accuracy of AI-based AudaxCeph software, Dolphin software, and the manual technique for identifying orthodontic landmarks and tracing lateral cephalograms. Materials and Methods: In this cross-sectional study, 23 anatomical landmarks were identified on 60 randomlyselected lateral cephalograms, and 5 dental indices, 4 skeletal indices, and 1 soft tissue index were measured. Each cephalogram was traced using 4 different methods: manually, with the Dolphin software, with the AudaxCeph software automatically, and with the AudaxCeph software in semi-automatic mode. The intra-class correlation coefficient (ICC) and Bland-Altman plots were used to evaluate the agreement between methods. Inter-observer and intra-observer agreements, calculated using the ICC, confirmed the accuracy, reliability, and reproducibility of the results: . Results: There was strong agreement among the AudexCeph (semi-automated or automated) AudaxCeph, Dolphin, and manual methods in measuring orthodontic indices, with ICC values consistently above 0.90. Bland-Altman plots confirmed satisfactory agreement between both versions of AudaxCeph (semi-automated and automated) with the manual method, with mean differences close to 0 and about 95% of data points within the limits of agreement.However, the semi-automated AudaxCeph showed greater agreement and precision than the automated version, as indicated by narrower limits of agreement. The ICC values for inter-observer and intra-observer agreements exceeded 0.98 and 0.99, respectively. Conclusion The semi-automated AudaxCeph software offers a robust and cost-effective solution for cephalometric analysis. Its high accuracy and affordability make it a compelling alternative to Dolphin software and the manual method.

Purpose: The aim of this study was to compare the accuracy of AI-based AudaxCeph software, Dolphin software, and the manual technique for identifying orthodontic landmarks and tracing lateral cephalograms. Materials and Methods: In this cross-sectional study, 23 anatomical landmarks were identified on 60 randomlyselected lateral cephalograms, and 5 dental indices, 4 skeletal indices, and 1 soft tissue index were measured. Each cephalogram was traced using 4 different methods: manually, with the Dolphin software, with the AudaxCeph software automatically, and with the AudaxCeph software in semi-automatic mode. The intra-class correlation coefficient (ICC) and Bland-Altman plots were used to evaluate the agreement between methods. Inter-observer and intra-observer agreements, calculated using the ICC, confirmed the accuracy, reliability, and reproducibility of the results: . Results: There was strong agreement among the AudexCeph (semi-automated or automated) AudaxCeph, Dolphin, and manual methods in measuring orthodontic indices, with ICC values consistently above 0.90. Bland-Altman plots confirmed satisfactory agreement between both versions of AudaxCeph (semi-automated and automated) with the manual method, with mean differences close to 0 and about 95% of data points within the limits of agreement.However, the semi-automated AudaxCeph showed greater agreement and precision than the automated version, as indicated by narrower limits of agreement. The ICC values for inter-observer and intra-observer agreements exceeded 0.98 and 0.99, respectively. Conclusion The semi-automated AudaxCeph software offers a robust and cost-effective solution for cephalometric analysis. Its high accuracy and affordability make it a compelling alternative to Dolphin software and the manual method.

SITUATIONAL ANALYSIS OF GENERAL PRACTITIONERS USING A FORECASTING APPROACH UNTIL 2025 AND A MULTI-STATE MARKOV MODEL: A RETROSPECTIVE LONGITUDINAL STUDY ntroduction: Undesirable working conditions, insufficient professional development and other labour market pressures have significantly impacted the status of general practitioners (GPs). This study aimed to conduct a situational analysis of GPs in Iran using a forecasting approach until 2025. Methods: Data were collected concurrently through direct contact, data matching among databases and tracking among graduates from four clusters of medical science universities over the past decade. This retrospective longitudinal study determined the status of GPs over consecutive years. Multi-state Markov and binary logistic regression analyses were performed using R and Stata 14. Results: Of 430 graduates over the past decade, 94% were successfully identified. Only 20% of the graduates remained active as GPs. The greatest fluctuations in transfer occurred in the third year after graduation, with the remaining proportion of GPs dropping to less than 50%. The probability of remaining as GPs was 0.76 per year, while the highest transition was observed towards specialisation (0.12). Additionally, 2% of the GPs chose not to work, and less than 1% transitioned to a different specialty. Based on the transfer matrix for 2025, only 19% of the GPs were projected to remain, with the majority (59%) transitioning to specialisation. Conclusion: The transfer probability varies across different years, indicating higher flow rates among GPs. However, only a limited number of GPs are projected to remain until 2025. A comprehensive set of interventions should be considered, spanning the pre-medical stage, during education and after graduation, to mitigate the factors contributing to GPs leaving their profession.

Purpose: This study aimed to assess incidental abnormal findings in the paranasal sinuses and anatomical variations of the ostiomeatal complex (OMC) on magnetic resonance imaging (MRI) scans. Materials and Methods: MRI scans of 616 patients (mean age, 44.0±19.4 years) were evaluated. Prior to obtaining the MRI scans, a checklist of patients’ clinical symptoms was filled out after obtaining their consent. The Lund-Mackay classification was used to assess the paranasal sinuses and OMC. The prevalence of abnormal findings and their associations with patients’ age, sex, and subjective symptoms were analyzed by the chi-square test, independent-sample t-test, and analysis of variance. The level of significance was set at 0.05. Results: Abnormal findings in the paranasal sinuses were detected in 32.0% of patients, with a significantly higher prevalence in males (P<0.05), but no significant association with age (P>0.05). Epithelial thickening and retention cyst were the most common abnormal findings in the paranasal sinuses. According to the Lund-Mackay classification, 93% of the study population had normal sinuses (score<4). Concha bullosa and paradoxical concha were detected in 15.3% and 3.4%, respectively, with no significant association with the presence of septal deviation or Lund-Mackay classification (P>0.05). Conclusion Considering the relatively high prevalence of abnormal findings in the paranasal sinuses, it appears that clinical symptoms alone are not sufficient to diagnose sinusitis. A more accurate strategy would be to assess radiographic images of the paranasal sinuses and use a classification system. Sinusitis should be suspected in patients receiving a high score in this classification.

Purpose: This study investigated the accuracy of laser-scanned models and 3-dimensional (3D) rendered cone-beam computed tomography (CBCT) compared to the gold standard (plaster casts) for linear measurements on dental arches. Materials and Methods: CBCT scans and plaster models from 30 patients were retrieved. Plaster models were scanned by an Emerald laser scanner (Planmeca, Helsinki, Finland). Sixteen different measurements, encompassing the mesiodistal width of teeth and both arches’ length and width, were calculated using various landmarks. Linear measurements were made on laser-scanned models using Autodesk Meshmixer software v. 3.0 (Autodesk, Mill Valley, CA, USA), on 3D-rendered CBCT models using OnDemand 3D v. 1.0 (Cybermed, Seoul, Korea) and on plaster casts by a digital caliper. Descriptive statistics, the paired t-test, and intra- and inter-class correlation coefficients were used to analyze the data. Results: There were statistically significant differences between some measurements on plaster casts and laser-scanned or 3D-rendered CBCT models (P<0.05). Molar mesiodistal width and mandibular anterior arch width deviated significantly different from the gold standard in both methods. The largest mean differences of laser-scanned and 3D-rendered CBCT models compared to the gold standard were 0.12±0.23 mm and 0.42±0.53 mm, respectively. Most of the mean differences were not clinically significant. The intra- and inter-class correlation results were acceptable for all measurements (>0.830) and between observers (>0.801). Conclusion The 3D-rendered CBCT images and laser-scanned models were useful and accurate alternatives to conventional plaster models. They could be used for clinical purposes in orthodontics and prostheses.

Purpose: This study aimed to compare the accuracy of 3-dimensional (3D) printed models derived from multidetector computed tomography (MDCT) and cone-beam computed tomography (CBCT) systems with different fields of view (FOVs). Materials and Methods: Five human dry mandibles were used to assess the accuracy of reconstructions of anatomical landmarks, bone defects, and intra-socket dimensions by 3D printers. The measurements were made on dry mandibles using a digital caliper (gold standard). The mandibles then underwent MDCT imaging. In addition, CBCT images were obtained using Cranex 3D and NewTom 3G scanners with 2 different FOVs. The images were transferred to two 3D printers, and the digital light processing (DLP) and fused deposition modeling (FDM) techniques were used to fabricate the 3D models, respectively. The same measurements were also made on the fabricated prototypes. The values measured on the 3D models were compared with the actual values, and the differences were analyzed using the paired t-test. Results: The landmarks measured on prototypes fabricated using the FDM and DLP techniques based on all 4 imaging systems showed differences from the gold standard. No significant differences were noted between the FDM and DLP techniques. Conclusion The 3D printers were reliable systems for maxillofacial reconstruction. In this study, scanners with smaller voxels had the highest precision, and the DLP printer showed higher accuracy in reconstructing the maxillofacial landmarks. It seemed that 3D reconstructions of the anterior region were overestimated, while the reconstructions of intra-socket dimensions and implant holes were slightly underestimated.

Objective: In humans, polycystic ovary syndrome (PCOS) is an androgen-dependent ovarian disorder. Aberrant gene expression in folliculogenesis can arrest the transition of preantral to antral follicles, leading to PCOS. We explored the possible role of altered gene expression in preantral follicles of estradiol valerate (EV) induced polycystic ovaries (PCO) in a mouse model. Methods: Twenty female balb/c mice (8 weeks, 20.0±1.5 g) were grouped into control and PCO groups. PCO was induced by intramuscular EV injection. After 8 weeks, the animals were killed by cervical dislocation. Blood serum (for hormonal assessments using the enzyme-linked immunosorbent assay technique) was aspirated, and ovaries (the right ovary for histological examinations and the left for quantitative real-time polymerase) were dissected. Results: Compared to the control group, the PCO group showed significantly lower values for the mean body weight, number of preantral and antral follicles, serum levels of estradiol, luteinizing hormone, testosterone, and follicle-stimulating hormone, and gene expression of TGFB1, GDF-9 and BMPR2 (p<0.05). Serum progesterone levels were significantly higher in the PCO animals than in the control group (p<0.05). No significant between-group differences (p>0.05) were found in BMP6 or BMP15 expression. Conclusions In animals with EV-induced PCO, the preantral follicles did not develop into antral follicles. In this mouse model, the gene expression of TGFB1, GDF9, and BMPR2 was lower in preantral follicles, which is probably related to the pathologic conditions of PCO. Hypoandrogenism was also detected in this EV-induced murine PCO model.

Objective: In humans, polycystic ovary syndrome (PCOS) is an androgen-dependent ovarian disorder. Aberrant gene expression in folliculogenesis can arrest the transition of preantral to antral follicles, leading to PCOS. We explored the possible role of altered gene expression in preantral follicles of estradiol valerate (EV) induced polycystic ovaries (PCO) in a mouse model. Methods: Twenty female balb/c mice (8 weeks, 20.0±1.5 g) were grouped into control and PCO groups. PCO was induced by intramuscular EV injection. After 8 weeks, the animals were killed by cervical dislocation. Blood serum (for hormonal assessments using the enzyme-linked immunosorbent assay technique) was aspirated, and ovaries (the right ovary for histological examinations and the left for quantitative real-time polymerase) were dissected. Results: Compared to the control group, the PCO group showed significantly lower values for the mean body weight, number of preantral and antral follicles, serum levels of estradiol, luteinizing hormone, testosterone, and follicle-stimulating hormone, and gene expression of TGFB1, GDF-9 and BMPR2 (p<0.05). Serum progesterone levels were significantly higher in the PCO animals than in the control group (p<0.05). No significant between-group differences (p>0.05) were found in BMP6 or BMP15 expression. Conclusions In animals with EV-induced PCO, the preantral follicles did not develop into antral follicles. In this mouse model, the gene expression of TGFB1, GDF9, and BMPR2 was lower in preantral follicles, which is probably related to the pathologic conditions of PCO. Hypoandrogenism was also detected in this EV-induced murine PCO model.