Background: Template-guided implant placement is a method for optimal implant positioning from a prosthetic and surgical viewpoint. The treatment planning is based on three-dimensional X-ray data and model scan data, as well as on prosthetic planning (set-up). These data are matched (superimposed) with the aid of an X-ray template or by manual matching without special referencing.
Purpose: The objective of this prospective controlled clinical study was to determine and compare the accuracy of the match with and without an additional X-ray template.
Materials And Methods: The DICOM data of the cone beam computed tomography (CBCT) were converted into surface data sets and then superimposed on model scan data using three different methods (manually, based on an X-ray template, or semi-automatically with computer assistance). The mean deviations between these results of these matching methods were investigated.
Results: The procedures achieved a matching accuracy of 0.2 mm on average. This corresponds to the resolution of the CBCT (0.2 voxels). Further studies are necessary to verify the procedure even for patients with few (0-4) residual teeth.
Conclusion: In the presence of a sufficient number of residual teeth, the manual matching of model scan data with CBCT data is sufficiently accurate for implant planning and template-guided implementation. The results of the present study suggest that X-ray templates can be dispensed with saving the patient a substantial amount of time and money.
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http://dx.doi.org/10.1111/cid.12614 | DOI Listing |
BMC Pulm Med
December 2024
Centre d'Atenció Primària Onze de Setembre. Gerència Territorial de Lleida, Institut Català de La Salut, Passeig 11 de Setembre,10 , 25005, Lleida, Spain.
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December 2024
Gyula Petrányi Doctoral School of Clinical Immunology and Allergology, Faculty of Medicine, University of Debrecen, Debrecen, Hungary.
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Comput Med Imaging Graph
November 2024
Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, Clinical Center, National Institutes of Health, United States of America. Electronic address:
Multiple intravenous contrast phases of CT scans are commonly used in clinical practice to facilitate disease diagnosis. However, contrast phase information is commonly missing or incorrect due to discrepancies in CT series descriptions and imaging practices. This work aims to develop a classification algorithm to automatically determine the contrast phase of a CT scan.
View Article and Find Full Text PDFBiochem Biophys Res Commun
December 2024
Korea Radioisotope Center for Pharmaceuticals, Korea Institute of Radiological & Medical Sciences, Seoul, South Korea. Electronic address:
Radiation therapy is crucial for cancer treatment, but it often causes tissue damage. The kidney, which is sensitive to radiation, is under-researched in this context. This study aimed to develop a mouse model for radiation-induced acute kidney injury (AKI) using a small animal radiation research platform (SARRP) to mimic clinical radiation conditions.
View Article and Find Full Text PDFPLoS One
December 2024
Department of Biochemistry, S S Hospital, S S Institute of Medical Sciences & Research Centre, Rajiv Gandhi University of Health Sciences, Davangere, Karnataka, India.
Early Lung Cancer (LC) detection is essential for reducing the global mortality rate. The limitations of traditional diagnostic techniques cause challenges in identifying LC using medical imaging data. In this study, we aim to develop a robust LC detection model.
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