Quantification of myocardial deformation by deformable registration–based analysis of cine MRI: validation with tagged CMR View Full Text


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Article Info

DATE

2019-02-15

AUTHORS

Mariana M. Lamacie, Christian P. Houbois, Andreas Greiser, Marie-Pierre Jolly, Paaladinesh Thavendiranathan, Bernd J. Wintersperger

ABSTRACT

ObjectivesTo validate deformable registration algorithms (DRAs) for cine balanced steady-state free precession (bSSFP) assessment of global longitudinal strain (GLS) and global circumferential strain (GCS) using harmonic phase (HARP) cardiovascular magnetic resonance as standard of reference (SoR).MethodsSeventeen patients and 17 volunteers underwent short axis stack and 2-/4-chamber cine bSSFP imaging with matching slice long-axis and mid-ventricular spatial modulation of magnetization (SPAMM) myocardial tagging. Inverse DRA was applied on bSSFP data for assessment of GLS and GCS while myocardial tagging was processed using HARP. Intra- and inter-observer variability assessment was based on repeated analysis by a single observer and analysis by a second observer, respectively. Standard semi-automated short axis stack segmentation was performed for analysis of left ventricular (LV) volumes and ejection fraction (EF).ResultsDRA demonstrated strong relationships to HARP for myocardial GLS (R2 = 0.75; p < 0.0001) and endocardial GLS (R2 = 0.61; p < 0.0001). GCS result comparison also demonstrated significant relationships between DRA and HARP for myocardial strain (R2 = 0.61; p < 0.0001) and endocardial strain (R2 = 0.51; p < 0.0001). Both methods demonstrated small systematic errors for intra- and inter-observer variability but DRA demonstrated consistently lower CV. Global LVEF was significantly lower (p = 0.0099) in patients (53.7%; IQR 43.9/64.0%) than in healthy volunteers (62.6%; IQR 61.1/66.2%). DRA and HARP strain data demonstrated significant relationships to LVEF.ConclusionsNon-rigid deformation method–based DRA provides a reliable measure of peak systolic GCS and GLS based on cine bSSFP with superior intra- and inter-observer reproducibility compared to HARP.Key Point• Myocardial strain can be reliably analyzed using inverse deformable registration algorithms (DRAs) on cine CMR.• Inverse DRA-derived strain shows higher reproducibility than tagged CMR.• DRA and tagged CMR-based myocardial strain demonstrate strong relationships to global left ventricular function. More... »

PAGES

3658-3668

References to SciGraph publications

  • 2017-02-26. The consistency of myocardial strain derived from heart deformation analysis in THE INTERNATIONAL JOURNAL OF CARDIOVASCULAR IMAGING
  • 2016-08-04. Quantification of global myocardial function by cine MRI deformable registration-based analysis: Comparison with MR feature tracking and speckle-tracking echocardiography in EUROPEAN RADIOLOGY
  • 2009-12-21. Myocardial tissue tagging with cardiovascular magnetic resonance in JOURNAL OF CARDIOVASCULAR MAGNETIC RESONANCE
  • 2017-08-02. Automated assessments of circumferential strain from cine CMR correlate with LVEF declines in cancer patients early after receipt of cardio-toxic chemotherapy in JOURNAL OF CARDIOVASCULAR MAGNETIC RESONANCE
  • 2012-05-31. Quantification of biventricular myocardial function using cardiac magnetic resonance feature tracking, endocardial border delineation and echocardiographic speckle tracking in patients with repaired tetralogy of fallot and healthy controls in JOURNAL OF CARDIOVASCULAR MAGNETIC RESONANCE
  • 2018-06-05. Left ventricular global myocardial strain assessment comparing the reproducibility of four commercially available CMR-feature tracking algorithms in EUROPEAN RADIOLOGY
  • 2013-10-17. Feature tracking measurement of dyssynchrony from cardiovascular magnetic resonance cine acquisitions: comparison with echocardiographic speckle tracking in JOURNAL OF CARDIOVASCULAR MAGNETIC RESONANCE
  • 2011-10-12. Cardiovascular magnetic resonance myocardial feature tracking detects quantitative wall motion during dobutamine stress in JOURNAL OF CARDIOVASCULAR MAGNETIC RESONANCE
  • 2013-01-18. Global and regional left ventricular myocardial deformation measures by magnetic resonance feature tracking in healthy volunteers: comparison with tagging and relevance of gender in JOURNAL OF CARDIOVASCULAR MAGNETIC RESONANCE
  • 2013-04-21. Normal values of regional and global myocardial wall motion in young and elderly individuals using navigator gated tissue phase mapping in GEROSCIENCE
  • 2014-04-24. Strain measurement by cardiovascular magnetic resonance in pediatric cancer survivors: validation of feature tracking against harmonic phase imaging in PEDIATRIC RADIOLOGY
  • Identifiers

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    http://scigraph.springernature.com/pub.10.1007/s00330-019-06019-9

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    http://dx.doi.org/10.1007/s00330-019-06019-9

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    31 schema:description ObjectivesTo validate deformable registration algorithms (DRAs) for cine balanced steady-state free precession (bSSFP) assessment of global longitudinal strain (GLS) and global circumferential strain (GCS) using harmonic phase (HARP) cardiovascular magnetic resonance as standard of reference (SoR).MethodsSeventeen patients and 17 volunteers underwent short axis stack and 2-/4-chamber cine bSSFP imaging with matching slice long-axis and mid-ventricular spatial modulation of magnetization (SPAMM) myocardial tagging. Inverse DRA was applied on bSSFP data for assessment of GLS and GCS while myocardial tagging was processed using HARP. Intra- and inter-observer variability assessment was based on repeated analysis by a single observer and analysis by a second observer, respectively. Standard semi-automated short axis stack segmentation was performed for analysis of left ventricular (LV) volumes and ejection fraction (EF).ResultsDRA demonstrated strong relationships to HARP for myocardial GLS (R2 = 0.75; p < 0.0001) and endocardial GLS (R2 = 0.61; p < 0.0001). GCS result comparison also demonstrated significant relationships between DRA and HARP for myocardial strain (R2 = 0.61; p < 0.0001) and endocardial strain (R2 = 0.51; p < 0.0001). Both methods demonstrated small systematic errors for intra- and inter-observer variability but DRA demonstrated consistently lower CV. Global LVEF was significantly lower (p = 0.0099) in patients (53.7%; IQR 43.9/64.0%) than in healthy volunteers (62.6%; IQR 61.1/66.2%). DRA and HARP strain data demonstrated significant relationships to LVEF.ConclusionsNon-rigid deformation method–based DRA provides a reliable measure of peak systolic GCS and GLS based on cine bSSFP with superior intra- and inter-observer reproducibility compared to HARP.Key Point• Myocardial strain can be reliably analyzed using inverse deformable registration algorithms (DRAs) on cine CMR.• Inverse DRA-derived strain shows higher reproducibility than tagged CMR.• DRA and tagged CMR-based myocardial strain demonstrate strong relationships to global left ventricular function.
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    38 schema:keywords CINE-bSSFP
    39 CMR
    40 CMR-based myocardial strain
    41 ConclusionsNon-rigid deformation method–based DRA
    42 GCS result comparison
    43 HARP
    44 Inverse DRA
    45 LVEF
    46 MRI
    47 MethodsSeventeen patients
    48 ObjectivesTo
    49 ResultsDRA
    50 algorithm
    51 analysis
    52 assessment
    53 assessment of GLS
    54 axis stack
    55 axis stack segmentation
    56 bSSFP
    57 balanced steady-state free precession (bSSFP) assessment
    58 cardiovascular magnetic resonance
    59 cine
    60 cine CMR
    61 cine MRI
    62 cine balanced steady-state free precession (bSSFP) assessment
    63 circumferential strain
    64 comparison
    65 cv
    66 data
    67 deformable registration algorithm
    68 deformable registration–based analysis
    69 deformation
    70 deformation method–based DRA
    71 ejection fraction
    72 endocardial global longitudinal strain
    73 endocardial strain
    74 error
    75 fraction
    76 free precession (bSSFP) assessment
    77 function
    78 global LVEF
    79 global circumferential strain
    80 global left ventricular function
    81 global longitudinal strain
    82 harmonic phase (HARP) cardiovascular magnetic resonance
    83 healthy volunteers
    84 high reproducibility
    85 inter-observer reproducibility
    86 inter-observer variability
    87 inter-observer variability assessment
    88 intra
    89 left ventricular function
    90 left ventricular volume
    91 longitudinal strain
    92 lower CV
    93 magnetic resonance
    94 magnetization (SPAMM) myocardial tagging
    95 measures
    96 method
    97 method–based DRA
    98 mid-ventricular spatial modulation
    99 modulation
    100 myocardial deformation
    101 myocardial global longitudinal strain
    102 myocardial strain
    103 myocardial tagging
    104 observer
    105 patients
    106 peak systolic GCS
    107 phase (HARP) cardiovascular magnetic resonance
    108 precession (bSSFP) assessment
    109 quantification
    110 reference
    111 registration algorithm
    112 registration–based analysis
    113 relationship
    114 reliable measure
    115 reproducibility
    116 resonance
    117 results comparison
    118 second observer
    119 segmentation
    120 short axis stack segmentation
    121 short-axis stack
    122 significant relationship
    123 single observer
    124 slices
    125 small systematic errors
    126 spatial modulation
    127 stack
    128 stack segmentation
    129 standard of reference
    130 standards
    131 steady-state free precession (bSSFP) assessment
    132 strains
    133 strong relationship
    134 superior intra
    135 systematic errors
    136 systolic GCS
    137 tagged CMR
    138 tagged CMR-based myocardial strain
    139 tagging
    140 validation
    141 variability
    142 variability assessment
    143 ventricular function
    144 ventricular volume
    145 volume
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    147 schema:name Quantification of myocardial deformation by deformable registration–based analysis of cine MRI: validation with tagged CMR
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