Journal Article
Research Support, Non-U.S. Gov't
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Improved workflow for quantifying left ventricular function via cardiorespiratory-resolved analysis of free-breathing MR real-time cines.

PURPOSE: To evaluate the feasibility of a proposed cardiorespiratory-resolved analysis in left ventricular (LV) function quantification from real-time cines in a cohort of cardiac patients.

MATERIALS AND METHODS: Electrocardiograph (ECG)-free free-breathing real-time cine imaging based on the balanced steady-state free precession technique was performed on short-axis slices of 20 cardiac patients at 3T. K-means cluster segmentation was used to delineate the endocardial contours, from which the LV centroid and cavity area were determined. Respiratory and cardiac signals were respectively resolved from the filtered LV centroid displacement and time-varied LV cavity area to identify end-expiratory end-diastolic (ED) and end-systolic (ES) images. The obtained LV cavity areas and derived volumetric function indices, including ED volume (EDV), ES volume (ESV), stroke volume (SV), and ejection fraction (EF), were compared with those measured from manual analysis using two-tailed paired Student's t-tests, linear regression analyses, and Bland-Altman plots. Interobserver variability was calculated.

RESULTS: The LV cavity area was strongly correlated between the proposed and conventional manual methods (r > 0.87) for three representative slices at the base, middle ventricle, and apex. The average differences between the two methods were 0.66 ± 3.22 mL for EDV, -0.02 ± 2.68 mL for ESV, 0.67 ± 3.73 mL for SV, and 0.17 ± 2.30% for EF. All paired measures exhibited strong correlations (r > 0.96) without significant differences (P = 0.38-0.98). Acceptable interobserver variability (0.19-3.55%) and strong correlations (r > 0.96) were shown for all measures between the two observers.

CONCLUSION: The proposed method is feasible for efficient measurement of LV function from real-time cines.

LEVEL OF EVIDENCE: 2 Technical Efficacy: Stage 1 J. MAGN. RESON. IMAGING 2017;46:905-914.

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