Root development stage, quality of root canal filling, the presence and severity of periapical radiolucencies, and their relationship with anatomical structures were recorded. This study aimed to assess the quality of root canal fillings and the prevalence of periapical radiolucencies in the permanent teeth of 6–18 year-old Turkish children.MethodsCBCT images of 150 patients’ 235 teeth with a mean age of 16.0 ± 2.06 years were included. The success detection rate of the tooth localization network ranged between 72.6% and 97.3%, whereas the sensitivity and specificity values of lesion detection were 97.1% and 88.0%, respectively.Īlthough PALs showed variations in appearance, size, and shape in the CBCT dataset, and a high imbalance existed between teeth with and without PALs, the proposed fully automated method provided excellent results compared with related literature. The method was evaluated using the four-fold cross-validation technique. A total of 144 CBCT images were used to train and test the networks. Second, binary segmentation of lesions was performed using a modified U-Net architecture. First, tooth localization and identification were performed using the SpatialConfiguration-Net based on heatmap regression. A two-step approach was used for automatic PAL detection. This study was conducted to develop and validate a deep convolutional neuronal network for the automated detection of osteolytic PALs in CBCT datasets.ĬBCT datasets from routine clinical operations (maxilla, mandible, or both) performed from January to October 2020 were retrospectively screened and selected. To improve quality, dentists may use artificial intelligence in the form of deep learning tools. However, the description, interpretation, and documentation of radiological findings, especially incidental findings, are time-consuming and resource-intensive, requiring a high degree of expertise. Radiolucent periapical lesions (PALs) represent the most frequent jaw lesions. Key words:Cone-beam computed tomography, diagnostic accuracy, diagnostic surgery, predictor variables, root canal treatment, vertical root fracture.Ĭone beam computed tomography (CBCT) is an essential diagnostic tool in oral radiology. The parafunctional habits, one-canal roots, excessive root canal enlargement, and the absence of intra-radicular posts may act strongly/independently for the occurrence of VRFs in endodontically treated teeth. VRFs cannot be reliably diagnosed by isolated clinical signs/symptoms instead those teeth possessing more than three diagnostic criteria might be considered practically pathognomonic. After logistic regression analysis, parafunctional habits, one-canal roots, excessive root canal enlargement, and absence of intra-radicular posts remained as robust predictor variables of VRFs.Īlthough the sensitivity of CBCT for VRFs detection is high, the risk of false-positive results related to its low specificity makes that all suspected cases must be confirmed by surgical exploration. Teeth having more than three diagnostic criteria present had significant higher odds for VRF diagnosis. Based on the finding of fracture lines on CBCT scans, sensitivity, specificity, and accuracy were 86.2%, 13.8%, and 50%, respectively. VRFs were detected during EMS in 50% of the teeth. Predictive value of diagnostic criteria and the association between predictor variables with VRFs were analyzed using logistic regression models. ![]() Determination of diagnostic performance of CBCT was based on standard algorithms derived from two-way contingency table analysis. Definite diagnosis of VRF was confirmed by endodontic microsurgical (EMS) exploration. This study aimed: (a) to determine the diagnostic performance of cone-beam computed tomography (CBCT) for detection of vertical root fractures (VRFs) (b) to evaluate the predictive value of diagnostic criteria regarding the definition of VRFs and (c) to examine the robustness of the association of patient-, tooth-, and treatment-related variables with VRFs.ġ30 root-filled teeth with signs/symptoms of VRFs underwent clinical and CBCT assessments.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |