Automatic Classification System for Periapical Lesions in Cone-Beam Computed Tomography

Imaging examinations are of remarkable importance for diagnostic support in Dentistry. Imaging techniques allow analysis of dental and maxillofacial tissues (e.g., bone, dentine, and enamel) that are inaccessible through clinical examination, which aids in the diagnosis of diseases as well as treatment planning. The analysis of imaging exams is not trivial; so, it is usually performed by oral and maxillofacial radiologists. The increasing demand for imaging examinations motivates the development of an automatic classification system for diagnostic support, as proposed in this paper, in which we aim to classify teeth as healthy or with endodontic lesion. The classification system was developed based on a Siamese Network combined with the use of convolutional neural networks with transfer learning for VGG-16 and DenseNet-121 networks. For this purpose, a database with 1000 sagittal and coronal sections of cone-beam CT scans was used. The results in terms of accuracy, recall, precision, specificity, and F1-score show that the proposed system has a satisfactory classification performance. The innovative automatic classification system led to an accuracy of about 70%. The work is pioneer since, to the authors knowledge, no other previous work has used a Siamese Network for the purpose of classifying teeth as healthy or with endodontic lesion, based on cone-beam computed tomography images

Cemento-Osseous Dysplasias: Imaging Features Based on Cone Beam Computed Tomography Scans

<div><p>Abstract Imaging exams have important role in diagnosis of cemento-osseous dysplasia (COD). Cone beam computed tomography (CBCT) stands out for allowing three-dimensional image evaluation. This study aimed to assess the prevalence of cases diagnosed as COD on CBCT scans, as well identify the main imaging features related to these lesions. An analysis was performed in a database containing 22,400 radiological reports, in which all cases showing some type of COD were initially selected. These CBCT exams were reevaluated to confirm the radiographic diagnosis and determine the prevalence and distribution of the types of COD with regard to gender, age and preferred location, while describing its most common imaging aspects. Data were presented using descriptive analyses. There were 82 cases diagnosed as COD in the CBCT images (prevalence of 0.4%). The distribution of patients was 11 (13.4%) male and 71 (86.6%) female, with a mean age of 49.8 years (age-range 17-85 years). There were 47 (57.3%) cases of periapical COD, 23 (28%) of focal COD and 12 (14.6%) of florid COD. The mandible was more affected than the maxilla. In most cases, the lesions were mixed or hyperdense. All COD had well-defined limits and there were no cases of tooth displacement. In conclusion, periapical COD was the most common type and the most affected bone was the mandible. Imaging evaluation is critical for diagnosis and dentists should bear in mind all possible radiographic presentations of COD in order to prevent misleading diagnoses and consequently, inadequate treatments.</p></div

Brazilian Oral Research

p. 503-509This study was conducted to investigate how well cone-beam computed tomography (CBCT) can detect simulated cavitary defects in condyles, and to test the influence of the reconstruction protocols. Defects were created with spherical diamond burs (numbers 1013, 1016, 3017) in superior and/or posterior surfaces of twenty condyles. The condyles were scanned, and cross-sectional reconstructions were performed with nine different protocols, based on slice thickness (0.2, 0.6, 1.0 mm) and on the filters (original image, Sharpen Mild, S9) used. Two observers evaluated the defects, determining their presence and location. Statistical analysis was carried out using simple Kappa coefficient and McNemar's test to check inter- and intra-rater reliability. The chi-square test was used to compare the rater accuracy. Analysis of variance (Tukey's test) assessed the effect of the protocols used. Kappa values for inter- and intra-rater reliability demonstrate almost perfect agreement. The proportion of correct answers was significantly higher than that of errors for cavitary defects on both condyle surfaces (p < 0.01). Only in identifying the defects located on the posterior surface was it possible to observe the influence of the 1.0 mm protocol thickness and no filter, which showed a significantly lower value. Based on the results of the current study, the technique used was valid for identifying the existence of cavities in the condyle surface. However, the protocol of a 1.0 mm-thick slice and no filter proved to be the worst method for identifying the defects on the posterior surface