Left ventricular global myocardial strain assessment: Are CMR feature-tracking algorithms useful in the clinical setting?
Objectives Myocardial strains can be calculated using cardiovascular magnetic resonance (CMR) feature-tracking (FT) algorithms. They show excellent intra- and inter-observer agreement but rather disappointing inter-vendor agreement. Currently, it is unknown how well CMR-FT-based strain values agree...
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| Published in: | Radiologia medica Vol. 125; no. 5; pp. 444 - 450 |
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| Main Authors: | , , , , , , |
| Format: | Journal Article |
| Language: | English |
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Milan
Springer Milan
01.05.2020
Springer Nature B.V |
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| ISSN: | 0033-8362, 1826-6983, 1826-6983 |
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| Abstract | Objectives
Myocardial strains can be calculated using cardiovascular magnetic resonance (CMR) feature-tracking (FT) algorithms. They show excellent intra- and inter-observer agreement but rather disappointing inter-vendor agreement. Currently, it is unknown how well CMR-FT-based strain values agree with manually obtained strain values.
Methods
In 45 subjects (15 controls, 15 acute myocardial infarction, 15 non-ischemic dilated cardiomyopathy), end-systolic manually derived strains were compared to four CMR-FT software packages. Global radial strain (GRS), global circumferential strain (GCS) and global longitudinal strain (GLS) were determined. Intra- and inter-observer agreement and agreement between manual and CMR-FT analysis were calculated. Statistical analysis included Bland–Altman plots, intra-class correlation coefficient (ICC) and coefficient of variation (CV).
Results
Manual contouring yielded excellent intra-observer (ICC 0.903 (GRS) to 0.995 (GCS)) and inter-observer agreement (ICC 0.915 (GRS) to 0.966 (GCS)) with CV ranging 4.7% (GCS) to 20.7% (GRS) and 12.7% (GCS) to 20.0% (GRS), for intra-observer and inter-observer agreement, respectively. Agreement between manual and CMR-FT strain values ranged from poor to excellent, with best agreement for GCS (ICC 0.857–0.935) and intermediate for GLS (ICC 0.591–0.914), while ICC values for GRS ranged widely (ICC 0.271–0.851). In particular, two software packages showed a strong trend toward systematic underestimation of myocardial strain in radial and longitudinal direction, correlating poorly to moderately with manual contouring, i.e., GRS (ICC 0.271, CV 25.2%) and GLS (ICC 0.591, CV 17.6%).
Conclusion
Some CMR-FT values agree poorly with manually derived strains, emphasizing to be cautious to use these software packages in the clinical setting. In particular, radial and longitudinal strain tends to be underestimated when using manually derived strains as reference. |
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| AbstractList | Myocardial strains can be calculated using cardiovascular magnetic resonance (CMR) feature-tracking (FT) algorithms. They show excellent intra- and inter-observer agreement but rather disappointing inter-vendor agreement. Currently, it is unknown how well CMR-FT-based strain values agree with manually obtained strain values.OBJECTIVESMyocardial strains can be calculated using cardiovascular magnetic resonance (CMR) feature-tracking (FT) algorithms. They show excellent intra- and inter-observer agreement but rather disappointing inter-vendor agreement. Currently, it is unknown how well CMR-FT-based strain values agree with manually obtained strain values.In 45 subjects (15 controls, 15 acute myocardial infarction, 15 non-ischemic dilated cardiomyopathy), end-systolic manually derived strains were compared to four CMR-FT software packages. Global radial strain (GRS), global circumferential strain (GCS) and global longitudinal strain (GLS) were determined. Intra- and inter-observer agreement and agreement between manual and CMR-FT analysis were calculated. Statistical analysis included Bland-Altman plots, intra-class correlation coefficient (ICC) and coefficient of variation (CV).METHODSIn 45 subjects (15 controls, 15 acute myocardial infarction, 15 non-ischemic dilated cardiomyopathy), end-systolic manually derived strains were compared to four CMR-FT software packages. Global radial strain (GRS), global circumferential strain (GCS) and global longitudinal strain (GLS) were determined. Intra- and inter-observer agreement and agreement between manual and CMR-FT analysis were calculated. Statistical analysis included Bland-Altman plots, intra-class correlation coefficient (ICC) and coefficient of variation (CV).Manual contouring yielded excellent intra-observer (ICC 0.903 (GRS) to 0.995 (GCS)) and inter-observer agreement (ICC 0.915 (GRS) to 0.966 (GCS)) with CV ranging 4.7% (GCS) to 20.7% (GRS) and 12.7% (GCS) to 20.0% (GRS), for intra-observer and inter-observer agreement, respectively. Agreement between manual and CMR-FT strain values ranged from poor to excellent, with best agreement for GCS (ICC 0.857-0.935) and intermediate for GLS (ICC 0.591-0.914), while ICC values for GRS ranged widely (ICC 0.271-0.851). In particular, two software packages showed a strong trend toward systematic underestimation of myocardial strain in radial and longitudinal direction, correlating poorly to moderately with manual contouring, i.e., GRS (ICC 0.271, CV 25.2%) and GLS (ICC 0.591, CV 17.6%).RESULTSManual contouring yielded excellent intra-observer (ICC 0.903 (GRS) to 0.995 (GCS)) and inter-observer agreement (ICC 0.915 (GRS) to 0.966 (GCS)) with CV ranging 4.7% (GCS) to 20.7% (GRS) and 12.7% (GCS) to 20.0% (GRS), for intra-observer and inter-observer agreement, respectively. Agreement between manual and CMR-FT strain values ranged from poor to excellent, with best agreement for GCS (ICC 0.857-0.935) and intermediate for GLS (ICC 0.591-0.914), while ICC values for GRS ranged widely (ICC 0.271-0.851). In particular, two software packages showed a strong trend toward systematic underestimation of myocardial strain in radial and longitudinal direction, correlating poorly to moderately with manual contouring, i.e., GRS (ICC 0.271, CV 25.2%) and GLS (ICC 0.591, CV 17.6%).Some CMR-FT values agree poorly with manually derived strains, emphasizing to be cautious to use these software packages in the clinical setting. In particular, radial and longitudinal strain tends to be underestimated when using manually derived strains as reference.CONCLUSIONSome CMR-FT values agree poorly with manually derived strains, emphasizing to be cautious to use these software packages in the clinical setting. In particular, radial and longitudinal strain tends to be underestimated when using manually derived strains as reference. Myocardial strains can be calculated using cardiovascular magnetic resonance (CMR) feature-tracking (FT) algorithms. They show excellent intra- and inter-observer agreement but rather disappointing inter-vendor agreement. Currently, it is unknown how well CMR-FT-based strain values agree with manually obtained strain values. In 45 subjects (15 controls, 15 acute myocardial infarction, 15 non-ischemic dilated cardiomyopathy), end-systolic manually derived strains were compared to four CMR-FT software packages. Global radial strain (GRS), global circumferential strain (GCS) and global longitudinal strain (GLS) were determined. Intra- and inter-observer agreement and agreement between manual and CMR-FT analysis were calculated. Statistical analysis included Bland-Altman plots, intra-class correlation coefficient (ICC) and coefficient of variation (CV). Manual contouring yielded excellent intra-observer (ICC 0.903 (GRS) to 0.995 (GCS)) and inter-observer agreement (ICC 0.915 (GRS) to 0.966 (GCS)) with CV ranging 4.7% (GCS) to 20.7% (GRS) and 12.7% (GCS) to 20.0% (GRS), for intra-observer and inter-observer agreement, respectively. Agreement between manual and CMR-FT strain values ranged from poor to excellent, with best agreement for GCS (ICC 0.857-0.935) and intermediate for GLS (ICC 0.591-0.914), while ICC values for GRS ranged widely (ICC 0.271-0.851). In particular, two software packages showed a strong trend toward systematic underestimation of myocardial strain in radial and longitudinal direction, correlating poorly to moderately with manual contouring, i.e., GRS (ICC 0.271, CV 25.2%) and GLS (ICC 0.591, CV 17.6%). Some CMR-FT values agree poorly with manually derived strains, emphasizing to be cautious to use these software packages in the clinical setting. In particular, radial and longitudinal strain tends to be underestimated when using manually derived strains as reference. Objectives Myocardial strains can be calculated using cardiovascular magnetic resonance (CMR) feature-tracking (FT) algorithms. They show excellent intra- and inter-observer agreement but rather disappointing inter-vendor agreement. Currently, it is unknown how well CMR-FT-based strain values agree with manually obtained strain values. Methods In 45 subjects (15 controls, 15 acute myocardial infarction, 15 non-ischemic dilated cardiomyopathy), end-systolic manually derived strains were compared to four CMR-FT software packages. Global radial strain (GRS), global circumferential strain (GCS) and global longitudinal strain (GLS) were determined. Intra- and inter-observer agreement and agreement between manual and CMR-FT analysis were calculated. Statistical analysis included Bland–Altman plots, intra-class correlation coefficient (ICC) and coefficient of variation (CV). Results Manual contouring yielded excellent intra-observer (ICC 0.903 (GRS) to 0.995 (GCS)) and inter-observer agreement (ICC 0.915 (GRS) to 0.966 (GCS)) with CV ranging 4.7% (GCS) to 20.7% (GRS) and 12.7% (GCS) to 20.0% (GRS), for intra-observer and inter-observer agreement, respectively. Agreement between manual and CMR-FT strain values ranged from poor to excellent, with best agreement for GCS (ICC 0.857–0.935) and intermediate for GLS (ICC 0.591–0.914), while ICC values for GRS ranged widely (ICC 0.271–0.851). In particular, two software packages showed a strong trend toward systematic underestimation of myocardial strain in radial and longitudinal direction, correlating poorly to moderately with manual contouring, i.e., GRS (ICC 0.271, CV 25.2%) and GLS (ICC 0.591, CV 17.6%). Conclusion Some CMR-FT values agree poorly with manually derived strains, emphasizing to be cautious to use these software packages in the clinical setting. In particular, radial and longitudinal strain tends to be underestimated when using manually derived strains as reference. ObjectivesMyocardial strains can be calculated using cardiovascular magnetic resonance (CMR) feature-tracking (FT) algorithms. They show excellent intra- and inter-observer agreement but rather disappointing inter-vendor agreement. Currently, it is unknown how well CMR-FT-based strain values agree with manually obtained strain values.MethodsIn 45 subjects (15 controls, 15 acute myocardial infarction, 15 non-ischemic dilated cardiomyopathy), end-systolic manually derived strains were compared to four CMR-FT software packages. Global radial strain (GRS), global circumferential strain (GCS) and global longitudinal strain (GLS) were determined. Intra- and inter-observer agreement and agreement between manual and CMR-FT analysis were calculated. Statistical analysis included Bland–Altman plots, intra-class correlation coefficient (ICC) and coefficient of variation (CV).ResultsManual contouring yielded excellent intra-observer (ICC 0.903 (GRS) to 0.995 (GCS)) and inter-observer agreement (ICC 0.915 (GRS) to 0.966 (GCS)) with CV ranging 4.7% (GCS) to 20.7% (GRS) and 12.7% (GCS) to 20.0% (GRS), for intra-observer and inter-observer agreement, respectively. Agreement between manual and CMR-FT strain values ranged from poor to excellent, with best agreement for GCS (ICC 0.857–0.935) and intermediate for GLS (ICC 0.591–0.914), while ICC values for GRS ranged widely (ICC 0.271–0.851). In particular, two software packages showed a strong trend toward systematic underestimation of myocardial strain in radial and longitudinal direction, correlating poorly to moderately with manual contouring, i.e., GRS (ICC 0.271, CV 25.2%) and GLS (ICC 0.591, CV 17.6%).ConclusionSome CMR-FT values agree poorly with manually derived strains, emphasizing to be cautious to use these software packages in the clinical setting. In particular, radial and longitudinal strain tends to be underestimated when using manually derived strains as reference. |
| Author | Manuel, Barreiro-Pérez Rolf, Symons Davide, Curione Dresselaers, Tom Pierpaolo, Palumbo Bogaert, Jan Claus, Piet |
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| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/32125636$$D View this record in MEDLINE/PubMed |
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| Cites_doi | 10.1186/s12968-016-0249-y 10.1186/s12968-017-0333-y 10.1016/j.ultrasmedbio.2013.02.463 10.1148/radiol.2018180513 10.1093/ehjci/jev006 10.1186/s12968-016-0269-7 10.1136/heartjnl-2014-305538 10.1016/j.crad.2015.05.006 10.1186/s12968-019-0575-y 10.1002/0471445428 10.1093/ehjci/jew042 10.1016/j.jacc.2014.01.073 10.1002/jmri.24979 10.1002/jmri.24623 10.1186/1532-429X-14-43 10.1093/eurheartj/ehv529 10.1002/jmri.24625 10.1186/s12968-017-0380-4 10.1007/978-3-642-38899-6_38 10.1038/s41591-018-0300-7 10.1161/CIRCIMAGING.115.004077 10.1007/s00330-018-5538-4 10.1007/s00330-019-06019-9 |
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| References | Topol (CR22) 2019; 25 Singh, Steadman, Khan (CR10) 2015; 41 Moody, Taylor, Edwards, Chue, Umar, Taylor, Ferro, Young, Townend, Leyva, Steeds (CR7) 2015; 41 Heyde, Bouchez, Thieren (CR8) 2013; 39 Smiseth, Torp, Opdahl, Haugaa, Urheim (CR3) 2016; 37 Thavendiranathan, Poulin, Lim, Plana, Woo, Marwick (CR1) 2014; 63 Schuster, Hor, Kowallick, Beerbaum, Kutty (CR11) 2016; 9 Taylor, Moody, Umar (CR17) 2015; 16 Schuster, Stahnke, Unterberg-Buchwald (CR12) 2015; 70 Fleiss, Levin, Paik (CR20) 2003 Bourfiss, Vigneault, Aliyari Ghasebeh (CR18) 2017; 19 Kuetting, Dabir, Homsi (CR14) 2016; 18 Morais, Heyde, Barbosa, Queirós, Claus, D’hooge (CR9) 2013 Morais, Marchi, Bogaert (CR6) 2017; 19 Leiner, Rueckert, Suinesiaputra (CR23) 2019; 21 Kowallick, Morton, Lamata (CR15) 2016; 43 Pedrizzetti, Claus, Kilner, Nagel (CR2) 2016; 18 Tao, Wenjun, Wang (CR21) 2019; 290 Kuetting, Dabir, Homsi (CR25) 2016; 18 Morton, Schuster, Jogiya, Kutty, Beerbaum, Nagel (CR13) 2012; 14 Kalam, Otahal, Marwick (CR4) 2014; 100 Hor, Baumann, Pedrizzetti (CR5) 2011; 48 Lamacie, Houbois, Greiser, Jolly, Thavendiranathan, Wintersperger (CR24) 2019; 29 Barreiro-Pérez, Curione, Symons, Claus, Voigt, Bogaert (CR19) 2018; 28 Aurich, Keller, Greiner (CR16) 2016; 17 P Morais (1159_CR9) 2013 RJ Taylor (1159_CR17) 2015; 16 DL Kuetting (1159_CR25) 2016; 18 P Thavendiranathan (1159_CR1) 2014; 63 A Schuster (1159_CR11) 2016; 9 M Barreiro-Pérez (1159_CR19) 2018; 28 B Heyde (1159_CR8) 2013; 39 JL Fleiss (1159_CR20) 2003 A Singh (1159_CR10) 2015; 41 MM Lamacie (1159_CR24) 2019; 29 OA Smiseth (1159_CR3) 2016; 37 M Bourfiss (1159_CR18) 2017; 19 P Morais (1159_CR6) 2017; 19 DL Kuetting (1159_CR14) 2016; 18 JT Kowallick (1159_CR15) 2016; 43 KN Hor (1159_CR5) 2011; 48 K Kalam (1159_CR4) 2014; 100 Q Tao (1159_CR21) 2019; 290 M Aurich (1159_CR16) 2016; 17 A Schuster (1159_CR12) 2015; 70 G Pedrizzetti (1159_CR2) 2016; 18 T Leiner (1159_CR23) 2019; 21 EJ Topol (1159_CR22) 2019; 25 G Morton (1159_CR13) 2012; 14 WE Moody (1159_CR7) 2015; 41 |
| References_xml | – volume: 18 start-page: 30 year: 2016 ident: CR25 article-title: The effects of extra-cellular contrast agent (Gadobutrol) on the precision and reproducibility of cardiovascular magnetic resonance feature tracking publication-title: J Cardiovasc Magn Reson doi: 10.1186/s12968-016-0249-y – volume: 19 start-page: 24 year: 2017 ident: CR6 article-title: Cardiovascular magnetic resonance myocardial feature tracking using a non-rigid, elastic image registration algorithm. Assessment of variability in a real-life clinical setting publication-title: J Cardiovasc Magn Reson doi: 10.1186/s12968-017-0333-y – volume: 39 start-page: 1688 year: 2013 end-page: 1697 ident: CR8 article-title: Elastic image registration to quantify 3-D regional myocardial deformation from volumetric ultrasound: experimental validation in an animal model publication-title: Ultrasound Med Biol doi: 10.1016/j.ultrasmedbio.2013.02.463 – volume: 290 start-page: 81 year: 2019 end-page: 88 ident: CR21 article-title: Deep-learning-based method for fully automatic quantification of left ventricle function from cine MR images: a multivendor, multicenter study publication-title: Radiology doi: 10.1148/radiol.2018180513 – volume: 16 start-page: 871 year: 2015 end-page: 881 ident: CR17 article-title: Myocardial strain measurement with feature-tracking cardiovascular magnetic resonance: normal values publication-title: Eur Heart J Cardiovasc Imaging doi: 10.1093/ehjci/jev006 – volume: 18 start-page: 51 issue: 1 year: 2016 ident: CR2 article-title: Principles of cardiovascular magnetic resonance feature tracking and echocardiographic speckle tracking for informed clinical use publication-title: J Cardiovasc Magn Reson doi: 10.1186/s12968-016-0269-7 – volume: 100 start-page: 1673 year: 2014 end-page: 1680 ident: CR4 article-title: Prognostic implications of global LV dysfunction: a systematic review and meta-analysis of global longitudinal strain and ejection fraction publication-title: Heart doi: 10.1136/heartjnl-2014-305538 – volume: 70 start-page: 989 year: 2015 end-page: 998 ident: CR12 article-title: Cardiovascular magnetic resonance feature-tracking assessment of myocardial mechanics: intervendor agreement and considerations regarding reproducibility publication-title: Clin Radiol doi: 10.1016/j.crad.2015.05.006 – volume: 21 start-page: 61 year: 2019 ident: CR23 article-title: Machine learning in cardiovascular magnetic resonance: basic concepts and applications publication-title: J Cardiovasc Magn Reson doi: 10.1186/s12968-019-0575-y – year: 2003 ident: CR20 publication-title: Statistical methods for rates and proportions doi: 10.1002/0471445428 – volume: 17 start-page: 1370 year: 2016 end-page: 1378 ident: CR16 article-title: Left ventricular mechanics assessed by two-dimensional echocardiography and cardiac magnetic resonance imaging: comparison of high-resolution speckle tracking and feature tracking publication-title: Eur Heart J Cardiovasc Imaging doi: 10.1093/ehjci/jew042 – volume: 63 start-page: 2751 year: 2014 end-page: 2768 ident: CR1 article-title: Use of myocardial strain imaging by echocardiography for the early detection of cardiotoxicity in patients during and after cancer chemotherapy: a systematic review publication-title: J Am Coll Cardiol doi: 10.1016/j.jacc.2014.01.073 – volume: 43 start-page: 128 year: 2016 end-page: 137 ident: CR15 article-title: Inter-study variability of left ventricular torsion and torsion rate quantification using MR myocardial feature tracking publication-title: J Magn Reson Imaging doi: 10.1002/jmri.24979 – volume: 41 start-page: 1000 year: 2015 end-page: 1012 ident: CR7 article-title: Comparison of magnetic resonance feature tracking for systolic and diastolic strain and strain rate calculation with spatial modulation of magnetization imaging analysis publication-title: J Magn Reson Imaging doi: 10.1002/jmri.24623 – volume: 14 start-page: 43 year: 2012 ident: CR13 article-title: Inter-study reproducibility of cardiovascular magnetic resonance myocardial feature tracking publication-title: J Cardiovasc Magn Reson doi: 10.1186/1532-429X-14-43 – volume: 37 start-page: 1196 year: 2016 end-page: 1207 ident: CR3 article-title: Myocardial strain imaging: how useful is it in clinical decision making? publication-title: Eur Heart J doi: 10.1093/eurheartj/ehv529 – volume: 41 start-page: 1129 year: 2015 end-page: 1137 ident: CR10 article-title: Intertechnique agreement and interstudy reproducibility of strain and diastolic strain rate at 1.5 and 3 Tesla: a comparison of feature-tracking and tagging in patients with aortic stenosis publication-title: J Magn Reson Imaging doi: 10.1002/jmri.24625 – volume: 19 start-page: 66 year: 2017 ident: CR18 article-title: Feature tracking CMR reveals abnormal strain in preclinical arrhythmogenic right ventricular dysplasia/cardiomyopathy: a multisoftware feasibility and clinical implementation study publication-title: J Cardiovasc Magn Reson doi: 10.1186/s12968-017-0380-4 – year: 2013 ident: CR9 publication-title: Cardiac motion and deformation estimation from tagged MRI sequences using a temporal coherent image registration framework doi: 10.1007/978-3-642-38899-6_38 – volume: 48 start-page: e2356 year: 2011 ident: CR5 article-title: Magnetic resonance derived myocardial strain assessment using feature tracking publication-title: J Vis Exp – volume: 25 start-page: 44 year: 2019 end-page: 56 ident: CR22 article-title: High-performance medicine: the convergence of human and artificial intelligence publication-title: Nat Med doi: 10.1038/s41591-018-0300-7 – volume: 18 start-page: 30 issue: 1 year: 2016 ident: CR14 article-title: The effects of extracellular contrast agent (Gadobutrol) on the precision and reproducibility of cardiovascular magnetic resonance feature tracking publication-title: J Cardiovasc Magn Reson doi: 10.1186/s12968-016-0249-y – volume: 9 start-page: e0004077 issue: 4 year: 2016 ident: CR11 article-title: Cardiovascular magnetic resonance myocardial feature tracking. Concepts and clinical applications publication-title: Circ Cardiovasc Imaging doi: 10.1161/CIRCIMAGING.115.004077 – volume: 28 start-page: 5137 year: 2018 end-page: 5147 ident: CR19 article-title: Left ventricular global myocardial strain assessment comparing the reproducibility of four commercially available CMR-feature tracking software publication-title: Eur Radiol doi: 10.1007/s00330-018-5538-4 – volume: 29 start-page: 3658 year: 2019 end-page: 3668 ident: CR24 article-title: Quantification of myocardial deformation by deformable registration-based analysis of cine MRI: validation with tagged CMR publication-title: Eur Radiol doi: 10.1007/s00330-019-06019-9 – volume: 19 start-page: 66 year: 2017 ident: 1159_CR18 publication-title: J Cardiovasc Magn Reson doi: 10.1186/s12968-017-0380-4 – volume: 41 start-page: 1000 year: 2015 ident: 1159_CR7 publication-title: J Magn Reson Imaging doi: 10.1002/jmri.24623 – volume-title: Statistical methods for rates and proportions year: 2003 ident: 1159_CR20 doi: 10.1002/0471445428 – volume: 9 start-page: e0004077 issue: 4 year: 2016 ident: 1159_CR11 publication-title: Circ Cardiovasc Imaging doi: 10.1161/CIRCIMAGING.115.004077 – volume: 48 start-page: e2356 year: 2011 ident: 1159_CR5 publication-title: J Vis Exp – volume: 63 start-page: 2751 year: 2014 ident: 1159_CR1 publication-title: J Am Coll Cardiol doi: 10.1016/j.jacc.2014.01.073 – volume: 21 start-page: 61 year: 2019 ident: 1159_CR23 publication-title: J Cardiovasc Magn Reson doi: 10.1186/s12968-019-0575-y – volume: 37 start-page: 1196 year: 2016 ident: 1159_CR3 publication-title: Eur Heart J doi: 10.1093/eurheartj/ehv529 – volume: 14 start-page: 43 year: 2012 ident: 1159_CR13 publication-title: J Cardiovasc Magn Reson doi: 10.1186/1532-429X-14-43 – volume-title: Cardiac motion and deformation estimation from tagged MRI sequences using a temporal coherent image registration framework year: 2013 ident: 1159_CR9 doi: 10.1007/978-3-642-38899-6_38 – volume: 41 start-page: 1129 year: 2015 ident: 1159_CR10 publication-title: J Magn Reson Imaging doi: 10.1002/jmri.24625 – volume: 25 start-page: 44 year: 2019 ident: 1159_CR22 publication-title: Nat Med doi: 10.1038/s41591-018-0300-7 – volume: 18 start-page: 51 issue: 1 year: 2016 ident: 1159_CR2 publication-title: J Cardiovasc Magn Reson doi: 10.1186/s12968-016-0269-7 – volume: 43 start-page: 128 year: 2016 ident: 1159_CR15 publication-title: J Magn Reson Imaging doi: 10.1002/jmri.24979 – volume: 17 start-page: 1370 year: 2016 ident: 1159_CR16 publication-title: Eur Heart J Cardiovasc Imaging doi: 10.1093/ehjci/jew042 – volume: 16 start-page: 871 year: 2015 ident: 1159_CR17 publication-title: Eur Heart J Cardiovasc Imaging doi: 10.1093/ehjci/jev006 – volume: 70 start-page: 989 year: 2015 ident: 1159_CR12 publication-title: Clin Radiol doi: 10.1016/j.crad.2015.05.006 – volume: 28 start-page: 5137 year: 2018 ident: 1159_CR19 publication-title: Eur Radiol doi: 10.1007/s00330-018-5538-4 – volume: 100 start-page: 1673 year: 2014 ident: 1159_CR4 publication-title: Heart doi: 10.1136/heartjnl-2014-305538 – volume: 290 start-page: 81 year: 2019 ident: 1159_CR21 publication-title: Radiology doi: 10.1148/radiol.2018180513 – volume: 29 start-page: 3658 year: 2019 ident: 1159_CR24 publication-title: Eur Radiol doi: 10.1007/s00330-019-06019-9 – volume: 39 start-page: 1688 year: 2013 ident: 1159_CR8 publication-title: Ultrasound Med Biol doi: 10.1016/j.ultrasmedbio.2013.02.463 – volume: 18 start-page: 30 year: 2016 ident: 1159_CR25 publication-title: J Cardiovasc Magn Reson doi: 10.1186/s12968-016-0249-y – volume: 18 start-page: 30 issue: 1 year: 2016 ident: 1159_CR14 publication-title: J Cardiovasc Magn Reson doi: 10.1186/s12968-016-0249-y – volume: 19 start-page: 24 year: 2017 ident: 1159_CR6 publication-title: J Cardiovasc Magn Reson doi: 10.1186/s12968-017-0333-y |
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Myocardial strains can be calculated using cardiovascular magnetic resonance (CMR) feature-tracking (FT) algorithms. They show excellent intra- and... Myocardial strains can be calculated using cardiovascular magnetic resonance (CMR) feature-tracking (FT) algorithms. They show excellent intra- and... ObjectivesMyocardial strains can be calculated using cardiovascular magnetic resonance (CMR) feature-tracking (FT) algorithms. They show excellent intra- and... |
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| SubjectTerms | Agreements Algorithms Analysis of Variance Biomechanical Phenomena - physiology Cardiac Radiology Cardiomyopathy, Dilated - diagnostic imaging Cardiomyopathy, Dilated - physiopathology Case-Control Studies Coefficient of variation Contouring Correlation coefficients Diagnostic Radiology Female Humans Imaging Interventional Radiology Magnetic resonance Magnetic Resonance Imaging, Cine - methods Male Mathematical analysis Medicine Medicine & Public Health Middle Aged Myocardial Contraction - physiology Myocardial infarction Myocardial Infarction - diagnostic imaging Myocardial Infarction - physiopathology Neuroradiology Radiology Reproducibility of Results Software Software packages Statistical analysis Stress, Mechanical Tracking Ultrasound Ventricular Dysfunction, Left - diagnostic imaging Ventricular Dysfunction, Left - physiopathology Ventricular Function, Left - physiology |
| Title | Left ventricular global myocardial strain assessment: Are CMR feature-tracking algorithms useful in the clinical setting? |
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