Feasibility of automatic assessment of four-chamber cardiac function with MDCT: Initial clinical application and validation

Abstract

Background: The ability to perform a simultaneous analysis of ventricular and atrial volumes may provide clinically useful information for diagnosis and prognosis. We aimed to evaluate the feasibility and clinical value of a novel algorithm that performs fully automatic evaluation of the four cardiac chambers and myocardium from gated CT datasets.

Methods: 50 patients were studied-Group 1: 30 consecutive unselected patients, Group 2A: 10 patients after myocardial infarction and Group 2B: 10 normal controls. Fully automatic, segmentation of the heart was performed with a model-based segmentation algorithm requiring no user input other than loading the datasets. Qualitative and quantitative evaluation of segmentation quality was performed. Left ventricular (LV) and right ventricular (RV) stroke volumes (SV) were compared.

Results: Overall, segmentation succeeded in all patients although 11/500 (2.2%) cardiac chambers achieved poor segmentation grading. Correlation coefficients between automatic and manually derived volumes were excellent (r>0.98) for all chambers. Bland-Altman analysis showed minimal bias (-1.0ml, 0.4ml, -1.8ml) for the LV and RV, and right atria, respectively, with mild overestimation of LV myocardial volume (5.2ml). Significant, yet consistent, overestimation of left atrial volume (23.6ml) due to inclusion of proximal pulmonary veins was observed. LV and RV ejection fraction (r=0.91 and 0.98) and SV (r=0.98 and 0.99) also correlated closely with minimal bias (<2%). Most significantly, LV SV (91.0+/-21.6ml) correlated highly with RV SV (81.7+/-18.2ml, r=0.86). Outliers could usually be explained by valvular regurgitation.

Conclusions: Fully automatic segmentation of all cardiac chambers can be achieved with high accuracy over multiple cardiac phases, enabling reliable comprehensive evaluation of four-chamber cardiac function.