Literature DB >> 33618722

Comparison between conventional and compressed sensing cine cardiovascular magnetic resonance for feature tracking global circumferential strain assessment.

Tomoyuki Kido1, Kuniaki Hirai2, Ryo Ogawa3, Yuki Tanabe3, Masashi Nakamura3, Naoto Kawaguchi3, Akira Kurata3, Kouki Watanabe4, Michaela Schmidt5, Christoph Forman5, Teruhito Mochizuki6,7, Teruhito Kido3.   

Abstract

BACKGROUND: Feature tracking (FT) has become an established tool for cardiovascular magnetic resonance (CMR)-based strain analysis. Recently, the compressed sensing (CS) technique has been applied to cine CMR, which has drastically reduced its acquisition time. However, the effects of CS imaging on FT strain analysis need to be carefully studied. This study aimed to investigate the use of CS cine CMR for FT strain analysis compared to conventional cine CMR.
METHODS: Sixty-five patients with different left ventricular (LV) pathologies underwent both retrospective conventional cine CMR and prospective CS cine CMR using a prototype sequence with the comparable temporal and spatial resolution at 3 T. Eight short-axis cine images covering the entire LV were obtained and used for LV volume assessment and FT strain analysis. Prospective CS cine CMR data over 1.5 heartbeats were acquired to capture the complete end-diastolic data between the first and second heartbeats. LV volume assessment and FT strain analysis were performed using a dedicated software (ci42; Circle Cardiovasacular Imaging, Calgary, Canada), and the global circumferential strain (GCS) and GCS rate were calculated from both cine CMR sequences.
RESULTS: There were no significant differences in the GCS (- 17.1% [- 11.7, - 19.5] vs. - 16.1% [- 11.9, - 19.3; p = 0.508) and GCS rate (- 0.8 [- 0.6, - 1.0] vs. - 0.8 [- 0.7, - 1.0]; p = 0.587) obtained using conventional and CS cine CMR. The GCS obtained using both methods showed excellent agreement (y = 0.99x - 0.24; r = 0.95; p < 0.001). The Bland-Altman analysis revealed that the mean difference in the GCS between the conventional and CS cine CMR was 0.1% with limits of agreement between -2.8% and 3.0%. No significant differences were found in all LV volume assessment between both types of cine CMR.
CONCLUSION: CS cine CMR could be used for GCS assessment by CMR-FT as well as conventional cine CMR. This finding further enhances the clinical utility of high-speed CS cine CMR imaging.

Entities:  

Keywords:  Cardiovascular magnetic resonance; Compressed sensing; Feature tracking; Myocardial strain

Year:  2021        PMID: 33618722      PMCID: PMC7898736          DOI: 10.1186/s12968-021-00708-5

Source DB:  PubMed          Journal:  J Cardiovasc Magn Reson        ISSN: 1097-6647            Impact factor:   5.364


  33 in total

1.  Normal human left and right ventricular dimensions for MRI as assessed by turbo gradient echo and steady-state free precession imaging sequences.

Authors:  Khaled Alfakih; Sven Plein; Holger Thiele; Tim Jones; John P Ridgway; Mohan U Sivananthan
Journal:  J Magn Reson Imaging       Date:  2003-03       Impact factor: 4.813

Review 2.  Imaging of ventricular function by cardiovascular magnetic resonance.

Authors:  Vikas K Rathi; Robert W W Biederman
Journal:  Curr Cardiol Rep       Date:  2004-01       Impact factor: 2.931

3.  Sparse MRI: The application of compressed sensing for rapid MR imaging.

Authors:  Michael Lustig; David Donoho; John M Pauly
Journal:  Magn Reson Med       Date:  2007-12       Impact factor: 4.668

4.  Compressed sensing in dynamic MRI.

Authors:  Urs Gamper; Peter Boesiger; Sebastian Kozerke
Journal:  Magn Reson Med       Date:  2008-02       Impact factor: 4.668

5.  Prediction of all-cause mortality from global longitudinal speckle strain: comparison with ejection fraction and wall motion scoring.

Authors:  Tony Stanton; Rodel Leano; Thomas H Marwick
Journal:  Circ Cardiovasc Imaging       Date:  2009-07-21       Impact factor: 7.792

Review 6.  Cardiovascular Magnetic Resonance Myocardial Feature Tracking: Concepts and Clinical Applications.

Authors:  Andreas Schuster; Kan N Hor; Johannes T Kowallick; Philipp Beerbaum; Shelby Kutty
Journal:  Circ Cardiovasc Imaging       Date:  2016-04       Impact factor: 7.792

7.  Estimation of myocardial strain from non-rigid registration and highly accelerated cine CMR.

Authors:  Jonathan E N Langton; Hoi-Ieng Lam; Brett R Cowan; Christopher J Occleshaw; Ruvin Gabriel; Boris Lowe; Suzanne Lydiard; Andreas Greiser; Michaela Schmidt; Alistair A Young
Journal:  Int J Cardiovasc Imaging       Date:  2016-09-13       Impact factor: 2.357

8.  Statistical methods for assessing agreement between two methods of clinical measurement.

Authors:  J M Bland; D G Altman
Journal:  Lancet       Date:  1986-02-08       Impact factor: 79.321

9.  Comparison of magnetic resonance feature tracking for strain calculation with harmonic phase imaging analysis.

Authors:  Kan N Hor; William M Gottliebson; Christopher Carson; Erin Wash; James Cnota; Robert Fleck; Janaka Wansapura; Piotr Klimeczek; Hussein R Al-Khalidi; Eugene S Chung; D Woodrow Benson; Wojciech Mazur
Journal:  JACC Cardiovasc Imaging       Date:  2010-02

10.  Efficient and reproducible high resolution spiral myocardial phase velocity mapping of the entire cardiac cycle.

Authors:  Robin Simpson; Jennifer Keegan; David Firmin
Journal:  J Cardiovasc Magn Reson       Date:  2013-04-15       Impact factor: 5.364

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  1 in total

1.  Feasibility of one breath-hold cardiovascular magnetic resonance compressed sensing cine for left ventricular strain analysis.

Authors:  Xiaorong Chen; Jiangfeng Pan; Yi Hu; Hongjie Hu; Yonghao Pan
Journal:  Front Cardiovasc Med       Date:  2022-08-12
  1 in total

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