As the panoramic x-ray is the most common extraoral radiography in dentistry, segmentation of its anatomical structures facilitates diagnosis and registration of dental records. This study presents a fast and accurate method for automatic segmentation of mandible in panoramic x-rays. In the proposed four-step algorithm, a superior border is extracted through horizontal integral projections. A modified Canny edge detector accompanied by morphological operators extracts the inferior border of the mandible body. The exterior borders of ramuses are extracted through a contour tracing method based on the average model of mandible. The best-matched template is fetched from the atlas of mandibles to complete the contour of left and right processes. The algorithm was tested on a set of 95 panoramic x-rays. Evaluating the results against manual segmentations of three expert dentists showed that the method is robust. It achieved an average performance of $>93%$ in Dice similarity, specificity, and sensitivity.

The aim of this investigation was to evaluate root canal morphology of maxillary first and second molars and also to assess the prevalence and morphology of the second mesiobuccal canal (MB2) in these teeth, using cone-beam computed tomography (CBCT). In this cross-sectional study, the total of 470 CBCT images from the archive of Radiology Department of Isfahan University of Medical Sciences (IUMS), Iran, was evaluated and 295 images were selected. The number of roots, and canal configuration were determined based on Vertucci’s classification system. The data was analyzed using SPSS 20, and P-values less than 0.05 were considered significant. A total of 295 images from 295 patients (165 females and 130 males), including 389 maxillary first (197 right and 192 left) and 460 maxillary second (235 right and 225 left) molars were evaluated. The prevalence of MB2 canals were 70.2% and 43.4% in the maxillary first and second molars, respectively. The most common type of Vertucci’s classification was type II (53.1%), followed by type I. The second mesiobuccal canal was present in almost two thirds of first and less than half of second molars. The morphology and canal configuration of a maxillary molar can almost predict the morphology of contralateral molar. However, it does not relate to the ipsilateral molar.

This study aimed to investigate the accuracy of gingival thickness measurement by two methods of clinical evaluation and intraoral ultrasonography. The gingival thickness was measured in the midbuccal area of the right maxillary lateral incisor and first molar teeth in 30 individuals. For clinical measurement, a #15 K-file with rubber stops was vertically inserted 2 mm apical to the gingival margin and the length of the file in the tissue was measured using a digital caliper. Ultrasonographic measurement was performed using an intraoral probe on the gingival surface in the midbuccal area, at the entry point of the file. Statistical analysis was performed by paired t-test, correlation coefficient, and receiver operating characteristic (ROC) curve (α = 0.05). In the anterior region, the mean gingival thicknesses using ultrasonography (1.517 ± 0.293 mm) and clinical evaluation (1.610 ± 0.272 mm) were not significantly different (p = 0.434). In the posterior region, the mean gingival thicknesses were significantly different between ultrasonography (1.372 ± 0.442 mm) and clinical evaluation (1.626 ± 0.310 mm) (p = 0.006). The area under ROC curve values for ultrasonographic measurements in the anterior and posterior regions were 0.681 and 0.597, respectively. The use of ultrasonography with an intraoral probe has acceptable accuracy for the determination of gingival thickness, especially for the anterior regions.

Background: Different techniques are used to evaluate the anatomy of root canal system. The present study was aimed to evaluate the root canal morphology of mandibular premolars using clearing and cone beam computed tomography (CBCT) techniques. Materials and Methods: A total of 182 mandibular first and second premolars were evaluated in vitro using 100 μm CBCT cross sections. The root canal morphology of the teeth was determined based on Vertucci classification in relation to the prevalence of C-shaped canals, lateral canals, and furcation location. Having removed the pulp tissue with NaOCl solution and staining the root canals with India ink, the samples were decalcified with 5% nitric acid and dehydrated with isopropyl alcohol. Finally, the samples were cleared with methyl salicylate. Data were analyzed by SPSS 16 software using McNamara, t-test, and Kappa coefficient. Results: After Type I, the most frequent morphologies in both first and second premolars were Type V followed by Type IV. The prevalence rates of C-shaped morphology in first premolars using clearing and CBCT were 4.4% and 6.6%, respectively. However, no C-shaped morphology was found in second premolars. The maximum and minimum levels of agreement between the two techniques were observed in Type IV and Type V root canal morphologies, respectively. Extra root canals were identified in 25% and 13% of the first and second premolars, respectively. Conclusion: CBCT showed a higher accuracy in determining C-shaped root canal morphology than the clearing technique. It also showed the least accuracy in diagnosing lateral root canals.

Bijan Movahedian Attar, Parisa Soltani, Davood Davari, Mojdeh Mehdizadeh. JKAOMS 2022;48:85-93. https://doi.org/10.5125/jkaoms.2022.48.2.85