Yin Wu1, Ke Jiang1, Na Zhang1, Yinzhu Gao1, Yucheng Chen2, Hairong Zheng1, Xin Liu1, Yiu-Cho Chung1. 1. Paul C. Lauterbur Research Centre for Biomedical Imaging, Shenzhen Key Laboratory for MRI, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong, China. 2. Cardiology Division, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
Abstract
BACKGROUND: To develop and assess an efficient method to identify end-expiratory end-diastolic (ED) and end-systolic (ES) images for accurate quantification of left ventricular (LV) function in real-time cine imaging. METHODS: ECG-free free-breathing real-time cine imaging was performed on short-axis slices of thirteen healthy volunteers at 3 Tesla. K-means cluster segmentation was applied to delineate the endocardial contour, from which the LV centroid and cavity area were determined in each cine image. LV centroid displacement along the superior-inferior direction was filtered to extract respiratory motion in each slice. End-expiratory ED and ES images were then identified and used for LV function quantification. Accuracy was evaluated with that measured from the slice-matched standard ECG-gated breathhold segmented cines using two-tail paired Student's t-tests, linear regression analyses and Bland-Altman plots. Intra- and interobserver variability was calculated for each imaging technique. RESULTS: Qualitatively, end-expiratory ED and ES images identified with the proposed method agreed with those determined by frame-by-frame visual inspection in 97.5% of cases (P > 0.05). Quantitatively, good agreement of LV function indices between the real-time cine and the standard segmented cine was observed with averaged differences of 0.1 ± 0.9 g for myocardium mass, -0.3 ± 1.0 mL for ED volume, 0.2 ± 1.2 mL for ES volume, -0.2 ± 1.3 mL for stroke volume, and -0.3 ± 0.8% for ejection fraction. Paired LV function values exhibited strong correlation (r ≥ 0.96) and no significant difference (P > 0.05). The real-time cine and the standard segmented cine showed similar intra- (1.2-3.3% and 1.1-2.8%, respectively) and interobserver variability (2.6-6.9% and 1.8-4.8%, respectively) with all P-values > 0.05. All the variability was comparable with published results. CONCLUSION: Compared with the laborious frame-by-frame visual inspection, as conventionally adopted, the proposed method is efficient in analyzing real-time cines for the accurate quantification of LV function without excessively manual interactions.
BACKGROUND: To develop and assess an efficient method to identify end-expiratory end-diastolic (ED) and end-systolic (ES) images for accurate quantification of left ventricular (LV) function in real-time cine imaging. METHODS: ECG-free free-breathing real-time cine imaging was performed on short-axis slices of thirteen healthy volunteers at 3 Tesla. K-means cluster segmentation was applied to delineate the endocardial contour, from which the LV centroid and cavity area were determined in each cine image. LV centroid displacement along the superior-inferior direction was filtered to extract respiratory motion in each slice. End-expiratory ED and ES images were then identified and used for LV function quantification. Accuracy was evaluated with that measured from the slice-matched standard ECG-gated breathhold segmented cines using two-tail paired Student's t-tests, linear regression analyses and Bland-Altman plots. Intra- and interobserver variability was calculated for each imaging technique. RESULTS: Qualitatively, end-expiratory ED and ES images identified with the proposed method agreed with those determined by frame-by-frame visual inspection in 97.5% of cases (P > 0.05). Quantitatively, good agreement of LV function indices between the real-time cine and the standard segmented cine was observed with averaged differences of 0.1 ± 0.9 g for myocardium mass, -0.3 ± 1.0 mL for ED volume, 0.2 ± 1.2 mL for ES volume, -0.2 ± 1.3 mL for stroke volume, and -0.3 ± 0.8% for ejection fraction. Paired LV function values exhibited strong correlation (r ≥ 0.96) and no significant difference (P > 0.05). The real-time cine and the standard segmented cine showed similar intra- (1.2-3.3% and 1.1-2.8%, respectively) and interobserver variability (2.6-6.9% and 1.8-4.8%, respectively) with all P-values > 0.05. All the variability was comparable with published results. CONCLUSION: Compared with the laborious frame-by-frame visual inspection, as conventionally adopted, the proposed method is efficient in analyzing real-time cines for the accurate quantification of LV function without excessively manual interactions.
Authors: Li Kuo Tan; Yih Miin Liew; Einly Lim; Yang Faridah Abdul Aziz; Kok Han Chee; Robert A McLaughlin Journal: Med Biol Eng Comput Date: 2017-11-17 Impact factor: 2.602