Literature DB >> 28722247

Left ventricular function and regional strain with subtly-tagged steady-state free precession feature tracking.

Eric M Schrauben1, Brett R Cowan2, Andreas Greiser3, Alistair A Young2.   

Abstract

PURPOSE: To provide regional strain and ventricular volume from a single acquisition, using subtly tagged steady-state free precession (SubTag SSFP) feature tracking.
MATERIALS AND METHODS: The effects on regional strain of tag strength in gradient recalled echo (GRE) tagging, flip angle in untagged balanced SSFP, and both in SubTag SSFP were examined in the mid left ventricle of 15 healthy volunteers at 3T. Optimal parameters were determined from varying both tag strength and SSFP flip angle using full tag saturation GRE as the reference standard. SubTag SSFP was acquired in 15 additional healthy volunteers for whole-heart volume and strain assessment using the optimized parameters. Values measured by two image analysts were compared to clinical reference standards from untagged SSFP (volumes) and GRE tagging (strains).
RESULTS: Regional strain accuracy was maintained with decreasing total tagging flip angle (β); less than 3% differences for β ≥ 26°. For untagged SSFP flip angle (α), whole-wall strain differences became statistically significant when α < 40°. A SubTag SSFP acquisition with α = 40° and β = 46° showed the best combination of tagging strength, blood-myocardial contrast, and tag persistence at end-systole for regional strain estimation. SubTag SSFP also showed excellent agreement with untagged SSFP for volumetrics (percent difference: end-diastolic volume = 0.6%, end-systolic volume = 0.4%, stroke volume = 1.2%, ejection fraction = 0.6%, mass = 1.1%).
CONCLUSION: Feature tracking for regional myocardial strain assessment is dependent on image features, mainly the tag strength, persistence, and image contrast. SubTag SSFP balances these criteria to provide accurate regional strain and volumetric assessment in a single acquisition. LEVEL OF EVIDENCE: 1 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2018;47:787-797.
© 2017 International Society for Magnetic Resonance in Medicine.

Entities:  

Keywords:  cardiovascular magnetic resonance; circumferential strain; feature tracking; tagging; volumetrics

Mesh:

Year:  2017        PMID: 28722247     DOI: 10.1002/jmri.25819

Source DB:  PubMed          Journal:  J Magn Reson Imaging        ISSN: 1053-1807            Impact factor:   4.813


  2 in total

1.  Using synthetic data generation to train a cardiac motion tag tracking neural network.

Authors:  Michael Loecher; Luigi E Perotti; Daniel B Ennis
Journal:  Med Image Anal       Date:  2021-09-10       Impact factor: 8.545

2.  In-silico study of accuracy and precision of left-ventricular strain quantification from 3D tagged MRI.

Authors:  Ezgi Berberoğlu; Christian T Stoeck; Philippe Moireau; Sebastian Kozerke; Martin Genet
Journal:  PLoS One       Date:  2021-11-05       Impact factor: 3.240

  2 in total

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