Literature DB >> 25791016

Feasibility of free-breathing, GRAPPA-based, real-time cardiac cine assessment of left-ventricular function in cardiovascular patients at 3T.

Xiaomei Zhu1, Felix Schwab2, Roy Marcus3, Holger Hetterich4, Daniel Theisen5, Harald Kramer6, Mike Notohamiprodjo7, Christopher L Schlett8, Konstantin Nikolaou9, Maximilian F Reiser10, Fabian Bamberg11.   

Abstract

OBJECTIVES: To determine the feasibility of free-breathing, GRAPPA-based, real-time (RT) cine 3T cardiac magnetic resonance imaging (MRI) with high acceleration factors for the assessment of left-ventricular function in a cohort of patients as compared to conventional segmented cine imaging.
MATERIALS AND METHODS: In this prospective cohort study, subjects with various cardiac conditions underwent MRI involving two RT cine sequences (high resolution and low resolution) and standard segmented cine imaging. Standard qualitative and quantitative parameters of left-ventricular function were quantified.
RESULTS: Among 25 subjects, 24 were included in the analysis (mean age: 50.5±21 years, 67% male, 25% with cardiomyopathy). RT cine derived quantitative parameters of volumes and left ventricular mass were strongly correlated with segmented cine imaging (intraclass correlation coefficient [ICC]: >0.72 for both RT cines) but correlation for peak ejection and filling rates were moderate to poor for both RT cines (ICC<0.40). Similarly, RT cines significantly underestimated peak ejection and filling rates (>103.2±178 ml/s). Among patient-related factors, heart rate was strongly predictive for deviation of measurements (p<0.05).
CONCLUSIONS: RT cine MRI at 3T is feasible for qualitative and quantitative assessment of left ventricular function for low and high-resolution sequences but results in significant underestimation of systolic function, peak ejection and filling rates.
Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Entities:  

Keywords:  Cardiac MRI; Heart rate; Left ventricular function; Parallel imaging; Real time imaging

Mesh:

Year:  2015        PMID: 25791016     DOI: 10.1016/j.ejrad.2015.02.016

Source DB:  PubMed          Journal:  Eur J Radiol        ISSN: 0720-048X            Impact factor:   3.528


  1 in total

1.  Convolutional Neural Network for the Detection of End-Diastole and End-Systole Frames in Free-Breathing Cardiac Magnetic Resonance Imaging.

Authors:  Fan Yang; Yan He; Mubashir Hussain; Hong Xie; Pinggui Lei
Journal:  Comput Math Methods Med       Date:  2017-07-26       Impact factor: 2.238

  1 in total

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