The Effect of Metal Artifacts Reduction Algorithm on Diagnostic Accuracy of Vertical Root Fracture by Cone Beam Computed Tomography, an in Vitro Study
Journal Title: Scholars Journal of Dental Sciences - Year 2017, Vol 4, Issue 3
Abstract
Vertical root fracture is one of the most severe complications of root canal treatment. Cone beam computed tomography (CBCT) is the best diagnostic tool for this type of fracture. Presence of canal filling material especially metal material causes an artifact in CBCT images which can affect the diagnostic efficiency. This study was aimed to evaluate the effect of metal artifact reduction algorithm in the diagnosis of VRF in teeth with stainless steel metal post. Eighty anterior teeth were selected and sectioned 2 mm below the CEJ. After preparation of root canals, each root was mounted in acrylic resin. Vertical fracture was induced in forty teeth by Instron machine. A stainless steel post was inserted into each canal to simulate metal artifact. Two CBCT images with or without artifact reduction algorithm were taken for each tooth. Two observers which were blinded for the presence of fracture analyzed all CBCT images twice in a 2-week interval. Then, intra-examiner agreement with kappa value and diagnostic accuracy of CBCT after use of metal artifact reduction algorithm was determined.Sensitivity, specificity, and accuracy of CBCT images with artifact reduction algorithm was 57%, 69%, and 63% and without algorithm was 54%, 61%, 57%, respectively. Intra-examiner agreement with artifact reduction algorithm was 0.59-0.7 and without artifact reduction algorithm was 0.49-0.63.Application of metal artifact reduction algorithm improved sensitivity, specificity, and accuracy of VRF detection through CBCT images; however, the difference between sensitivity, specificity, and accuracy of CBCT with and without using the metal artifact reduction algorithms were not significant. Keywords:cone beam computed tomography, diagnostic imaging, and algorithms
Authors and Affiliations
Maryam Tofangchiha, Mamak Adel, Elham Tavakolian, Parisa Ghaffari, Razieh Jabbarian
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