J Endod. 2021 Mar 7:S0099-2399(21)00150-3. doi: 10.1016/j.joen.2021.02.013. Online ahead of print.
ABSTRACT
AIM: To classify ten CBCT devices, by using a ranking model, according to the detection of fine endodontic structures.
METHODS: A dedicated dentate anthropomorphic phantom was scanned two times using ten CBCT devices: without any metal (metal-free condition) and with an endodontically treated tooth containing a metallic post (metal condition). A reference image acquired on an industrial micro-CT scanner was used to register all CBCT images, yielding corresponding anatomic slices. Afterwards, three experienced observers assessed all acquired CBCT images for their ability to assess narrow canal, isthmus and apical delta ramification following a categorical rank from 1 (best) to 10 (worst). Fleiss Kappa statistics were used to calculate intra- and interobserver agreements for each CBCT device separately. Based on the observers` scores, general linear mixed models were applied to compare image quality among different CBCTs for performing endodontic diagnostic tasks (α = .05).
RESULTS: The ten CBCT devices performed differently for the evaluated endodontic tasks (P < .05), with three devices performing better for endodontic feature detection. Yet, in the presence of metal, only two devices were able to keep a high level of endodontic feature detection.
CONCLUSIONS: The evaluated endodontic tasks were CBCT device-dependent, and its detection was influenced by the presence of metal.
PMID:33691170 | DOI:10.1016/j.joen.2021.02.013
