Key result
A semiautomatic segmentation method for cardiac MR imaging showed no significant differences compared to manual segmentation (p>0.05), with excellent correlation for the left ventricle (r>0.9).
Why the study?
Does a semiautomatic segmentation method accurately quantify ventricular function compared to manual segmentation in patients with cardiovascular diseases?
Observational (n=52)
Does a semiautomatic segmentation method accurately quantify ventricular function compared to manual segmentation in patients with cardiovascular diseases?
p-value: p=> 0.05
A novel semiautomatic segmentation method provides fast and accurate assessment of left and right ventricular function from cardiac MRI, with results comparable to manual segmentation.
May streamline routine cardiac MRI workflows; leaves open prospective validation across populations.
The purpose of this study was to evaluate the performance of a semiautomatic segmentation method for the anatomical and functional assessment of both ventricles from cardiac cine magnetic resonance (MR) examinations, reducing user interaction to a "mouse-click". Fifty-two patients with cardiovascular diseases were examined using a 1.5-T MR imaging unit. Several parameters of both ventricles, such as end-diastolic volume (EDV), end-systolic volume (ESV) and ejection fraction (EF), were quantified by an experienced operator using the conventional method based on manually-defined contours, as the standard of reference; and a novel semiautomatic segmentation method based on edge detection, iterative thresholding and region growing techniques, for evaluation purposes. No statistically significant differences were found between the two measurement values obtained for each parameter (p > 0.05). Correlation to estimate right ventricular function was good (r > 0.8) and turned out to be excellent (r > 0.9) for the left ventricle (LV). Bland-Altman plots revealed acceptable limits of agreement between the two methods (95%). Our study findings indicate that the proposed technique allows a fast and accurate assessment of both ventricles. However, further improvements are needed to equal results achieved for the right ventricle (RV) using the conventional methodology.
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Souto et al. (2013) conducted an observational in Cardiovascular diseases (n=52). Semiautomatic segmentation method vs. Conventional manual segmentation method was evaluated on Ventricular parameters including end-diastolic volume, end-systolic volume, and ejection fraction (p=> 0.05). A semiautomatic segmentation method for cardiac MR imaging showed no significant differences compared to manual segmentation (p>0.05), with excellent correlation for the left ventricle (r>0.9).
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