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  • Title: Semiautomated detection and quantification of aortic plaques from three-dimensional transesophageal echocardiography.
    Author: Piazzese C, Tsang W, Sotaquira M, Kronzon I, Lang RM, Caiani EG.
    Journal: J Am Soc Echocardiogr; 2014 Jul; 27(7):758-66. PubMed ID: 24767971.
    Abstract:
    BACKGROUND: Aortic atherosclerosis is a risk factor for cerebrovascular events. Two-dimensional transesophageal echocardiographic quantification of descending aortic plaques is time-consuming and underestimates plaque burden. The aim of this study was to assess the feasibility and accuracy of a novel semiautomated program that uses three-dimensional (3D) transesophageal echocardiography to identify and quantify aortic plaque severity as determined by plaque thickness, volume, and number. The relationship between maximum plaque thickness and volume was also examined. METHODS: Descending aortic 3D transesophageal echocardiographic images from 58 patients were analyzed for plaque thickness, volume, and number using semiautomated custom software. The reference standard was manual assessment by an expert reader using 3D multiplanar reconstructions. Agreement and κ values were calculated to determine the program's accuracy against the reference standard. Correlation and bias were examined using linear regression and Bland-Altman statistics. Pearson's correlation was used to examine the relationship between maximum plaque thickness and volume. RESULTS: Analysis was possible in all patients. Overall agreement for the absolute presence or absence of plaque per patient was 95%. Agreement regarding the number of plaques per patient and plaque severity was high at 95% and 85%, respectively. Plaque volume was slightly underestimated by the program compared with manual measurements. The correlation between plaque thickness and volume was 0.56. CONCLUSIONS: The results of this study demonstrate that semiautomated plaque analysis of 3D transesophageal echocardiographic descending aortic data sets is feasible and accurate in determining plaque severity as measured by plaque thickness, volume, and number. This methodology allows the standardization of plaque quantification, which will improve its utility in clinical trials. A greater understanding of the importance of plaque thickness versus volume is needed.
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