%0 Journal Article
%T Model-based automatic segmentation algorithm accurately assesses the whole cardiac volumetric parameters in patients with cardiac CT angiography: a validation study for evaluating the accuracy of the workstation software and establishing the reference values.
%A Mao SS
%A Li D
%A Vembar M
%A Gao Y
%A Luo Y
%A Lam F
%A Syed YS
%A Liu C
%A Woo K
%A Flores F
%A Budoff MJ
%J Acad Radiol
%V 21
%N 5
%D May 2014
%M 24703477
%F 5.482
%R 10.1016/j.acra.2014.01.010
%X <B>OBJECTIVE: </B>The cardiac chamber volumes and functions can be assessed manually and automatically using the current computed tomography (CT) workstation system. We aimed to evaluate the accuracy and precision and to establish the reference values for both segmentation methods using cardiac CT angiography (CTA).<BR><B>METHODS: </B>A total of 134 subjects (mean age 55.3 years, 72 women) without heart disease were enrolled in the study. The cardiac four-chamber volumes, left ventricular (LV) mass, and biventricular functions were measured with manual, semiautomatic, and model-based fully automatic approaches. The accuracies of the semiautomated and fully automated approaches were validated by comparing them with manual segmentation as a reference. The precision error was determined and compared for both manual and automatic measurements.<BR><B>RESULTS: </B>No significant difference was found between the manual and semiautomatic assessments for the assessment of all functional parameters (P > .05). Using the manual method as a reference, the automatic approach provided a similar value in LV ejection fraction and left atrial volumes in both genders and right ventricular (RV) stroke volume in women (P > .05), with some underestimation of RV volume (P < .001) and overestimation of all remaining parameters (P < .05) in both genders. In addition, a significantly higher precision with a considerable association in intermeasurement (reproducibility) was observed using the automated approach.<BR><B>CONCLUSIONS: </B>The model-based fully automatic segmentation algorithm can help with the assessment of the cardiac four-chamber volume and function. This may help in establishing reference values of functional parameters in patients who undergo cardiac CTA.