Left Ventricular Ejection Fraction Calculation from Automatically Selected and Processed Diastolic and Systolic Frames in Short?Axis Cine?MRI

Abstract

The calculation of the left ventricular ejection fraction (LVEF) is dependent upon the accurate measurement of diastolic and systolic left ventricular volumes. Although breath-hold cine magnetic resonance imaging (MRI) allows coverage of the whole cardiac cycle with an excellent time resolution, many authors rely on the visual selection of diastolic and the systolic short-axis slices in order to reduce the postprocessing time. An automatic method was developed to detect the endocardial contour on each image, allowing an automatic selection of the systolic frame. The calculated ejection fraction was compared with radionuclide ventriculography (RNV). Sixty-five patients were examined using an electrocardiogram (ECG)-gated gradient echo sequence. Among these examinations, manual and automatic processing with MRI were compared when the time of the systolic frame concorded. Good correlations have been found between the automatic MRI approach and RNV, and between manual and automatic processing on MRI alone. The results show that the automatic determination of the ejection fraction is feasible, and should constitute an important step toward a larger acceptance of MRI as a routine tool in heart disease imaging. One major benefit of using automatic postprocessing is that it may eliminate the visual choice of the systolic frame, inaccurate in more than 50% of the studied patients.

Nonsupervised Ranking of Different Segmentation Approaches: Application to the Estimation of the Left Ventricular Ejection Fraction From Cardiac Cine MRI Sequences

“…during the segmentation process. Method M7, described in [17], was mostly automated. Method M8 was fully automated and its main principle was described in [18].…”

An SPCNN-GVF-based approach for the automatic segmentation of left ventricle in cardiac cine MR images

“…Since the APD and ODM are only computed for the "good contours," more segmented contours are calculated in our results. Even so, our method still obtains better performance on APD than the algorithms in [13,33,35,36]. As a combination method, the STAPLE segmentation performs better than the independent automatic algorithms in [13,35,36].…”

“…And, it is applied in 2-D with the default parameters). As shown in Table 2, compared with the approaches in [4,13,[33][34][35][36], the SPCNN-GVF-based method obtains the obviously higher PGC for both the endocardium and the epicardium. Since the APD and ODM are only computed for the "good contours," more segmented contours are calculated in our results.…”

“…The methods described, respectively, in [3][4][5]13,15] are fully automated, and the approaches introduced, respectively, in [33][34][35][36] need some user interventions. The STAPLE segmentation is created by combining the segmentation results of [13,[34][35][36] (the STAPLE algorithm [19] is implemented using the software CRKIT which is freely available on: http:// crl.med.harvard.edu/software/CRKIT/index.php.…”

Aging Does Not Affect Radial Viscoelastic Behavior of the Left Ventricle

“…Since the extreme basal slice cannot be used for contour determination, the small but significant distance separating the last usable slice and the level of the valves was considered instead. The missing volume at the base of the ventricle was computed based on the method described by Lalande et al [19]. …”