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INTRODUCTION: 3D printing is experiencing significant growth in the teaching and learning process. This study aims to present a 3D printed skull model for preclinical intraoral radiographic practice. MATERIALS AND METHODS: Two 3D printed mannequins were created. One mannequin used an STL file of a skull that was edited using two 3D modelling software (Meshmixer and Netfabb). The second mannequin was designed directly from a patient's segmented CBCT data and then converted into an STL file. Both mannequins were printed using fused deposition modelling (FDM) technology and polylactic acid (PLA) filament; teeth for the second mannequin were also printed using digital light processing (DLP). The printed skull bones were attached, the mandible was articulated to the articular fossa of the temporal bone, and the teeth were inserted into the alveoli. Intraoral radiographs of both mannequins were taken using a digital sensor (RVG 5100, Carestream). RESULTS: Both 3D printed mannequins showed satisfactory radiographic appearance, allowing geometric representation of each intraoral radiographic projection, regardless of STL file origin. Anatomical structures, such as the periodontal ligament space, zygomatic process of the maxilla and intermaxillary suture, were represented. The material cost of the first and second printed prototype was $34.00 and $39.00, respectively. CONCLUSIONS: The use of 3D printed models is presented as an alternative to artificial commercial phantoms for the preclinical training of intraoral radiographic techniques through the combined benefits of superior radiographic projection quality, the possibility of model manipulation and an affordable price.
Assuntos
Educação em Odontologia , Radiologia , Humanos , Impressão Tridimensional , Manequins , MaxilaRESUMO
OBJECTIVE: To compare the accuracy of computer monitor and smartphone screen for radiographic diagnosis of marginal gap. MATERIALS AND METHODS: Forty teeth with mesial-occlusal-distal inlays (each tooth with a perfect fit and a 0.4-mm marginal gap restoration) were imaged with a phosphor plate system. Original digital radiographs were exported and analyzed with two different methods: computer monitor and smartphone screen; for the last method, images were shared with WhatsApp. Three examiners assessed all radiographs (n = 160) for the presence of marginal gap by using a dichotomous scale (yes/no). Diagnostic performance of each examiner and viewing method was evaluated by means of sensitivity (Se), specificity (Sp), and overall accuracy (Ac). Difference between the frequencies of gap detection of each method was analyzed using the McNemar test. Intra- and inter-examiner agreements were calculated using kappa statistics. RESULTS: Intra- and inter-examiner agreements were ≥ 0.80 for both methods. Similar diagnostic performance was found for computer monitor (Se = 0.87-1; Sp = 0.8-0.97; Ac = 0.84-0.99) and smartphone (Se = 0.77-1; Sp = 0.87-1; Ac = 0.88-0.95) viewing methods. No statistically significant differences in the frequency of gap detection were observed between the methods (P > 0.05). CONCLUSION: Diagnostic accuracy of smartphone screens was similar to that of computer monitor for marginal gap detection. CLINICAL RELEVANCE: Smartphones are becoming a common daily tool. In this sense, it might be an important new aid in Dentistry, including radiographic evaluation, which could benefit patients and dentists.