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European Radiology
Published in: European Radiology 8/2022

24-02-2022 | Cardiomyopathy | Magnetic Resonance

State-of-the-art myocardial strain by CMR feature tracking: clinical applications and future perspectives

Authors: Jing Xu, Wenjing Yang, Shihua Zhao, Minjie Lu

Published in: European Radiology | Issue 8/2022

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Abstract

Based on conventional cine sequences of cardiac magnetic resonance (CMR), feature tracking (FT) is an emerging tissue tracking technique that evaluates myocardial motion and deformation quantitatively by strain, strain rate, torsion, and dyssynchrony. It has been widely accepted in modern literature that strain analysis can offer incremental information in addition to classic global and segmental functional analysis. Furthermore, CMR-FT facilitates measurement of all cardiac chambers, including the relatively thin-walled atria and the right ventricle, which has been a difficult measurement to obtain with the reference standard technique of myocardial tagging. CMR-FT objectively quantifies cardiovascular impairment and characterizes myocardial function in a novel way through direct assessment of myocardial fiber deformation. The purpose of this review is to discuss the current status of clinical applications of myocardial strain by CMR-FT in a variety of cardiovascular diseases.

Key Points

• CMR-FT is of great value for differential diagnosis and provides incremental value for evaluating the progression and severity of diseases.
• CMR-FT guides the early diagnosis of various cardiovascular diseases and provides the possibility for the early detection of myocardial impairment and additional information regarding subclinical cardiac abnormalities.
• Direct assessment of myocardial fiber deformation using CMR-FT has the potential to provide prognostic information incremental to common clinical and CMR risk factors.
Appendix
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Literature
1.
von Knobelsdorff-Brenkenhoff F, Schulz-Menger J (2016) Role of cardiovascular magnetic resonance in the guidelines of the European Society of Cardiology. J Cardiovasc Magn Reson 18:6CrossRef
2.
von Knobelsdorff-Brenkenhoff F, Pilz G, Schulz-Menger J (2017) Representation of cardiovascular magnetic resonance in the AHA / ACC guidelines. J Cardiovasc Magn Reson 19:70CrossRef
3.
Amzulescu MS, De Craene M, Langet H et al (2019) Myocardial strain imaging: review of general principles, validation, and sources of discrepancies. Eur Heart J Cardiovasc Imaging 20:605–619PubMedPubMedCentralCrossRef
4.
Zerhouni EA, Parish DM, Rogers WJ, Yang A, Shapiro EP (1988) Human heart: tagging with MR imaging--a method for noninvasive assessment of myocardial motion. Radiology 169:59–63PubMedCrossRef
5.
6.
Kihlberg J, Gupta V, Haraldsson H et al (2020) Clinical validation of three cardiovascular magnetic resonance techniques to measure strain and torsion in patients with suspected coronary artery disease. J Cardiovasc Magn Reson 22:83PubMedPubMedCentralCrossRef
7.
Osman NF, Sampath S, Atalar E, Prince JL (2001) Imaging longitudinal cardiac strain on short-axis images using strain-encoded MRI. Magn Reson Med 46:324–334PubMedCrossRef
8.
Voigt JU, Cvijic M (2019) 2- and 3-dimensional myocardial strain in cardiac health and disease. J Am Coll Cardiol Img 12:1849–1863CrossRef
9.
Pedrizzetti G, Claus P, Kilner PJ, Nagel E (2016) Principles of cardiovascular magnetic resonance feature tracking and echocardiographic speckle tracking for informed clinical use. J Cardiovasc Magn Reson 18:51PubMedPubMedCentralCrossRef
10.
Claus P, Omar AMS, Pedrizzetti G, Sengupta PP, Nagel E (2015) Tissue tracking technology for assessing cardiac mechanics: principles, normal values, and clinical applications. J Am Coll Cardiol Img 8:1444–1460CrossRef
11.
Truong V, Palmer C, Wolking S et al (2020) Normal left atrial strain and strain rate using cardiac magnetic resonance feature tracking in healthy volunteers. Eur Heart J Cardiovasc Imaging 21:446–453PubMed
12.
Bucius P, Erley J, Tanacli R et al (2020) Comparison of feature tracking, fast-SENC, and myocardial tagging for global and segmental left ventricular strain. ESC heart fail 7:523–532PubMedCrossRef
13.
Harrild DM, Han Y, Geva T, Zhou J, Marcus E, Powell AJ (2012) Comparison of cardiac MRI tissue tracking and myocardial tagging for assessment of regional ventricular strain. Int J Card Imaging 28:2009–2018CrossRef
14.
Schuster A, Hor KN, Kowallick JT, Beerbaum P, Kutty S (2016) Cardiovascular magnetic resonance myocardial feature tracking: concepts and clinical applications. Circ Cardiovasc Imaging 9:e004077PubMedCrossRef
15.
Flachskampf FA, Blankstein R, Grayburn PA et al (2019) Global longitudinal shortening: a positive step towards reducing confusion surrounding global longitudinal strain. JACC Cardiovasc Imaging 12:1566–1567PubMedPubMedCentralCrossRef
16.
17.
Vo HQ, Marwick TH, Negishi K (2018) MRI-derived myocardial strain measures in normal subjects. J Am Coll Cardiol Img 11:196–205CrossRef
18.
Augustine D, Lewandowski AJ, Lazdam M et al (2013) Global and regional left ventricular myocardial deformation measures by magnetic resonance feature tracking in healthy volunteers: comparison with tagging and relevance of gender. J Cardiovasc Magn Reson 15:8PubMedPubMedCentralCrossRef
19.
Andre F, Steen H, Matheis P et al (2015) Age- and gender-related normal left ventricular deformation assessed by cardiovascular magnetic resonance feature tracking. J Cardiovasc Magn Reson 17:25PubMedPubMedCentralCrossRef
20.
Taylor RJ, Moody WE, Umar F et al (2015) Myocardial strain measurement with feature-tracking cardiovascular magnetic resonance: normal values. Eur Heart J Cardiovasc Imaging 16:871–881PubMedCrossRef
21.
Liu H, Yang D, Wan K et al (2017) Distribution pattern of left-ventricular myocardial strain analyzed by a cine MRI based deformation registration algorithm in healthy Chinese volunteers. Sci Rep 7:45314PubMedPubMedCentralCrossRef
22.
Peng J, Zhao X, Zhao L et al (2018) Normal values of myocardial deformation assessed by cardiovascular magnetic resonance feature tracking in a healthy Chinese population: a multicenter study. Front Physiol 9:1181PubMedPubMedCentralCrossRef
23.
Liu B, Dardeer AM, Moody WE et al (2018) Reference ranges for three-dimensional feature tracking cardiac magnetic resonance: comparison with two-dimensional methodology and relevance of age and gender. Int J Card Imaging 34:761–775
24.
Mangion K, Burke N, McComb C, Carrick D, Woodward R, Berry C (2019) Feature-tracking myocardial strain in healthy adults- a magnetic resonance study at 3.0 tesla. Sci Rep 9:3239PubMedPubMedCentralCrossRef
25.
Obokata M, Nagata Y, Wu VC et al (2016) Direct comparison of cardiac magnetic resonance feature tracking and 2D/3D echocardiography speckle tracking for evaluation of global left ventricular strain. Eur Heart J Cardiovasc Imaging 17:525–532PubMedCrossRef
26.
Barreiro-Perez M, Curione D, Symons R, Claus P, Voigt JU, Bogaert J (2018) Left ventricular global myocardial strain assessment comparing the reproducibility of four commercially available CMR-feature tracking algorithms. Eur Radiol 28:5137–5147PubMedCrossRef
27.
28.
Kowallick JT, Morton G, Lamata P et al (2015) Quantification of atrial dynamics using cardiovascular magnetic resonance: inter-study reproducibility. J Cardiovasc Magn Reson 17:36PubMedPubMedCentralCrossRef
29.
Morais P, Marchi A, Bogaert JA et al (2017) Cardiovascular magnetic resonance myocardial feature tracking using a non-rigid, elastic image registration algorithm: assessment of variability in a real-life clinical setting. J Cardiovasc Magn Reson 19:24PubMedPubMedCentralCrossRef
30.
Li L, Chen X, Yin G et al (2020) Early detection of left atrial dysfunction assessed by CMR feature tracking in hypertensive patients. Eur Radiol 30:702–711PubMedCrossRef
31.
Liu H, Wang J, Pan Y, Ge Y, Guo Z, Zhao S (2020) Early and quantitative assessment of myocardial deformation in essential hypertension patients by using cardiovascular magnetic resonance feature tracking. Sci Rep 10:3582PubMedPubMedCentralCrossRef
32.
Song Y, Li L, Chen X et al (2022) Early Left Ventricular Diastolic Dysfunction and Abnormal Left Ventricular-left Atrial Coupling in Asymptomatic Patients With Hypertension: A Cardiovascular Magnetic Resonance Feature Tracking Study. J Thorac Imaging 37: 26–33.
33.
Schneeweis C, Qiu J, Schnackenburg B et al (2014) Value of additional strain analysis with feature tracking in dobutamine stress cardiovascular magnetic resonance for detecting coronary artery disease. J Cardiovasc Magn Reson 16:72PubMedPubMedCentralCrossRef
34.
Garg P, Aziz R, Al Musa T et al (2018) Effects of hyperaemia on left ventricular longitudinal strain in patients with suspected coronary artery disease : a first-pass stress perfusion cardiovascular magnetic resonance imaging study. Neth Hear J 26:85–93CrossRef
35.
Tamarappoo B, Samuel TJ, Elboudwarej O et al (2021) Left ventricular circumferential strain and coronary microvascular dysfunction: a report from the Women's Ischemia Syndrome Evaluation Coronary Vascular Dysfunction (WISE-CVD) Project. Int J Cardiol 327:25–30PubMedCrossRef
36.
Khan JN, Singh A, Nazir SA, Kanagala P, Gershlick AH, McCann GP (2015) Comparison of cardiovascular magnetic resonance feature tracking and tagging for the assessment of left ventricular systolic strain in acute myocardial infarction. Eur J Radiol 84:840–848PubMedCrossRef
37.
Maret E, Todt T, Brudin L et al (2009) Functional measurements based on feature tracking of cine magnetic resonance images identify left ventricular segments with myocardial scar. Cardiovasc Ultrasound 7:53PubMedPubMedCentralCrossRef
38.
Tantawy SW, Mohammad SA, Osman AM, El Mozy W, Ibrahim AS (2021) Strain analysis using feature tracking cardiac magnetic resonance (FT-CMR) in the assessment of myocardial viability in chronic ischemic patients. Int J Card Imaging 37:587–596CrossRef
39.
40.
Stathogiannis K, Mor-Avi V, Rashedi N, Lang R, Patel A (2020) Regional myocardial strain by cardiac magnetic resonance feature tracking for detection of scar in ischemic heart disease. Magn Reson Imaging 68:190–196PubMedCrossRef
41.
Vigneault D, Yang E, Jensen P et al (2019) Left ventricular strain is abnormal in preclinical and overt hypertrophic cardiomyopathy: cardiac MR feature tracking. Radiology 290:640–648PubMedCrossRef
42.
43.
Yang Y, Yin G, Jiang Y, Song L, Zhao S, Lu M (2020) Quantification of left atrial function in patients with non-obstructive hypertrophic cardiomyopathy by cardiovascular magnetic resonance feature tracking imaging: a feasibility and reproducibility study. J Cardiovasc Magn Reson 22:1PubMedPubMedCentralCrossRef
44.
Kowallick JT, Kutty S, Edelmann F et al (2014) Quantification of left atrial strain and strain rate using cardiovascular magnetic resonance myocardial feature tracking: a feasibility study. J Cardiovasc Magn Reson 16:60PubMedPubMedCentralCrossRef
45.
Prati G, Vitrella G, Allocca G et al (2015) Right ventricular strain and dyssynchrony assessment in arrhythmogenic right ventricular cardiomyopathy: cardiac magnetic resonance feature-tracking study. Circ Cardiovasc Imaging 8:e003647 discussion e003647PubMedCrossRef
46.
Taha K, Bourfiss M, Te Riele A et al (2020) A head-to-head comparison of speckle tracking echocardiography and feature tracking cardiovascular magnetic resonance imaging in right ventricular deformation. Eur Heart J Cardiovasc Imaging. https://​doi.​org/​10.​1093/​ehjci/​jeaa088
47.
Heermann P, Hedderich DM, Paul M et al (2014) Biventricular myocardial strain analysis in patients with arrhythmogenic right ventricular cardiomyopathy (ARVC) using cardiovascular magnetic resonance feature tracking. J Cardiovasc Magn Reson 16:75PubMedPubMedCentralCrossRef
48.
Chen X, Li L, Cheng H et al (2019) Early left ventricular involvement detected by cardiovascular magnetic resonance feature tracking in arrhythmogenic right ventricular cardiomyopathy: the effects of left ventricular late gadolinium enhancement and right ventricular dysfunction. J Am Heart Assoc 8:e012989PubMedPubMedCentralCrossRef
49.
Porcari A, Merlo M, Crosera L et al (2020) Strain analysis reveals subtle systolic dysfunction in confirmed and suspected myocarditis with normal LVEF. A cardiac magnetic resonance study. Clin Res Cardiol 109:869–880PubMedCrossRef
50.
Salehi Ravesh M, Eden M, Langguth P et al (2020) Non-contrast enhanced diagnosis of acute myocarditis based on the 17-segment heart model using 2D-feature tracking magnetic resonance imaging. Magn Reson Imaging 65:155–165PubMedCrossRef
51.
Doerner J, Bunck AC, Michels G, Maintz D, Baeßler B (2018) Incremental value of cardiovascular magnetic resonance feature tracking derived atrial and ventricular strain parameters in a comprehensive approach for the diagnosis of acute myocarditis. Eur J Radiol 104:120–128PubMedCrossRef
52.
Mazurkiewicz Ł, Petryka J, Spiewak M et al (2017) Biventricular mechanics in prediction of severe myocardial fibrosis in patients with dilated cardiomyopathy: CMR study. Eur J Radiol 91:71–81PubMedCrossRef
53.
Yu S, Chen X, Yang K et al (2021) Correlation between left ventricular fractal dimension and impaired strain assessed by cardiac MRI feature tracking in patients with left ventricular noncompaction and normal left ventricular ejection fraction. Eur Radiol. https://​doi.​org/​10.​1007/​s00330-021-08346-2
54.
Amaki M, Savino J, Ain DL et al (2014) Diagnostic concordance of echocardiography and cardiac magnetic resonance-based tissue tracking for differentiating constrictive pericarditis from restrictive cardiomyopathy. Circ Cardiovasc Imaging 7:819–827PubMedCrossRef
55.
McDonagh TA, Metra M, Adamo M et al (2021) 2021 ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure. Eur Heart J 42:3599–3726PubMedCrossRef
56.
Tanacli R, Hashemi D, Lapinskas T et al (2019) Range variability in CMR feature tracking multilayer strain across different stages of heart failure. Sci Rep 9:16478PubMedPubMedCentralCrossRef
57.
Ito H, Ishida M, Makino W et al (2020) Cardiovascular magnetic resonance feature tracking for characterization of patients with heart failure with preserved ejection fraction: correlation of global longitudinal strain with invasive diastolic functional indices. J Cardiovasc Magn Reson 22:42PubMedPubMedCentralCrossRef
58.
Mahmod M, Pal N, Rayner J et al (2018) The interplay between metabolic alterations, diastolic strain rate and exercise capacity in mild heart failure with preserved ejection fraction: a cardiovascular magnetic resonance study. J Cardiovasc Magn Reson 20:88PubMedPubMedCentralCrossRef
59.
60.
von Roeder M, Kowallick JT, Rommel KP et al (2020) Right atrial-right ventricular coupling in heart failure with preserved ejection fraction. Clin Res Cardiol 109:54–66CrossRef
61.
He J, Sirajuddin A, Li S et al (2021) Heart failure with preserved ejection fraction in hypertension patients: a myocardial MR strain study. J Magn Reson Imaging 53:527–539PubMedCrossRef
62.
Al Musa T, Uddin A, Swoboda PP et al (2017) Myocardial strain and symptom severity in severe aortic stenosis: insights from cardiovascular magnetic resonance. Quant Imaging Med Surg 7:38–47PubMedPubMedCentralCrossRef
63.
Kim M, Park E, Lee W, Lee S (2020) Cardiac magnetic resonance feature tracking in aortic stenosis: exploration of strain parameters and prognostic value in asymptomatic patients with preserved ejection fraction. Korean J Radiol 21:268–279PubMedPubMedCentralCrossRef
64.
Lin A, Seale H, Hamilton-Craig C, Morris N, Strugnell W (2019) Quantification of biventricular strain and assessment of ventriculo-ventricular interaction in pulmonary arterial hypertension using exercise cardiac magnetic resonance imaging and myocardial feature tracking. J Magn Reson Imaging 49:1427–1436PubMedCrossRef
65.
Kallianos K, Brooks GC, Mukai K et al (2018) Cardiac magnetic resonance evaluation of left ventricular myocardial strain in pulmonary hypertension. Acad Radiol 25:129–135PubMedCrossRef
66.
Tello K, Dalmer A, Vanderpool R et al (2020) Right ventricular function correlates of right atrial strain in pulmonary hypertension: a combined cardiac magnetic resonance and conductance catheter study. Am J Physiol Heart Circ Physiol 318:H156–h164PubMedCrossRef
67.
Leng S, Dong Y, Wu Y et al (2019) Impaired cardiovascular magnetic resonance-derived rapid semiautomated right atrial longitudinal strain is associated with decompensated hemodynamics in pulmonary arterial hypertension. Circ Cardiovasc Imaging 12:e008582PubMedCrossRef
68.
69.
Tahir E, Starekova J, Muellerleile K et al (2019) Impact of myocardial fibrosis on left ventricular function evaluated by feature-tracking myocardial strain cardiac magnetic resonance in competitive male triathletes with normal ejection fraction. Circ J 83:1553–1562PubMedCrossRef
70.
Liu X, Zhang Q, Yang ZG et al (2017) Assessment of left ventricular deformation in patients with Ebstein's anomaly by cardiac magnetic resonance tissue tracking. Eur J Radiol 89:20–26PubMedCrossRef
71.
van der Ven J, Alsaied T, Juggan S et al (2020) Atrial function in Fontan patients assessed by CMR: relation with exercise capacity and long-term outcomes. Int J Cardiol 312:56–61PubMedCrossRef
72.
Lam HV, Groth M, Mir T et al (2021) Impact of chest wall deformity on cardiac function by CMR and feature-tracking strain analysis in paediatric patients with Marfan syndrome. Eur Radiol 31:3973–3982PubMedCrossRef
73.
Balasubramanian S, Harrild D, Kerur B et al (2018) Impact of surgical pulmonary valve replacement on ventricular strain and synchrony in patients with repaired tetralogy of Fallot: a cardiovascular magnetic resonance feature tracking study. J Cardiovasc Magn Reson 20:37PubMedPubMedCentralCrossRef
74.
Hagdorn Q, Vos J, Beurskens N et al (2019) CMR feature tracking left ventricular strain-rate predicts ventricular tachyarrhythmia, but not deterioration of ventricular function in patients with repaired tetralogy of Fallot. Int J Cardiol 295:1–6PubMedCrossRef
75.
Chen J, Yang ZG, Xu HY, Shi K, Guo YK (2018) Assessment of left ventricular myocardial deformation by cardiac MRI strain imaging reveals myocardial dysfunction in patients with primary cardiac tumors. Int J Cardiol 253:176–182PubMedCrossRef
76.
Rezaeian N, Mohtasham M, Khaleel A, Parnianfard N, Kasani K, Golshan R (2020) Comparison of global strain values of myocardium in beta-thalassemia major patients with iron load using specific feature tracking in cardiac magnetic resonance imaging. Int J Card Imaging 36:1343–1349CrossRef
77.
Shen X, Yuan Y, Yang M et al (2020) Cardiovascular magnetic resonance-derived myocardial strain in asymptomatic heart transplanted patients and its correlation with late gadolinium enhancement. Eur Radiol 30:4337–4346PubMedCrossRef
78.
Reindl M, Tiller C, Holzknecht M et al (2019) Prognostic implications of global longitudinal strain by feature-tracking cardiac magnetic resonance in ST-elevation myocardial infarction. Circ Cardiovasc Imaging 12:e009404PubMedCrossRef
79.
Romano S, Romer B, Evans K et al (2020) Prognostic implications of blunted feature-tracking global longitudinal strain during vasodilator cardiovascular magnetic resonance stress imaging. J Am Coll Cardiol Img 13:58–65CrossRef
80.
Schuster A, Backhaus SJ, Stiermaier T et al (2020) Impact of right atrial physiology on heart failure and adverse events after myocardial infarction. J Clin Med 9
81.
Schuster A, Backhaus SJ, Stiermaier T et al (2019) Left atrial function with MRI enables prediction of cardiovascular events after myocardial infarction: insights from the AIDA STEMI and TATORT NSTEMI trials. Radiology 293:292–302PubMedCrossRef
82.
Backhaus S, Kowallick J, Stiermaier T et al (2020) Cardiac magnetic resonance myocardial feature tracking for optimized risk assessment after acute myocardial infarction in patients with type 2 diabetes. Diabetes 69:1540–1548PubMedCrossRef
83.
Hinojar R, Fernández-Golfín C, González-Gómez A et al (2017) Prognostic implications of global myocardial mechanics in hypertrophic cardiomyopathy by cardiovascular magnetic resonance feature tracking. Relations to left ventricular hypertrophy and fibrosis. Int J Cardiol 249:467–472PubMedCrossRef
84.
Buss SJ, Breuninger K, Lehrke S et al (2015) Assessment of myocardial deformation with cardiac magnetic resonance strain imaging improves risk stratification in patients with dilated cardiomyopathy. Eur Heart J Cardiovasc Imaging 16:307–315PubMedCrossRef
85.
Romano S, Judd RM, Kim RJ et al (2018) Feature-tracking global longitudinal strain predicts death in a multicenter population of patients with ischemic and nonischemic dilated cardiomyopathy incremental to ejection fraction and late gadolinium enhancement. J Am Coll Cardiol Img 11:1419–1429CrossRef
86.
Shen M, Yang Z, Diao K et al (2019) Left ventricular involvement in arrhythmogenic right ventricular dysplasia/cardiomyopathy predicts adverse clinical outcomes: a cardiovascular magnetic resonance feature tracking study. Sci Rep 9:14235PubMedPubMedCentralCrossRef
87.
88.
Xu L, Pagano JJ, Haykowksy MJ et al (2020) Layer-specific strain in patients with heart failure using cardiovascular magnetic resonance: not all layers are the same. J Cardiovasc Magn Reson 22:81PubMedPubMedCentralCrossRef
89.
Chirinos J, Sardana M, Ansari B et al (2018) Left atrial phasic function by cardiac magnetic resonance feature tracking is a strong predictor of incident cardiovascular events. Circ Cardiovasc Imaging 11:e007512PubMedPubMedCentralCrossRef
90.
Jain S, Kuriakose D, Edelstein I et al (2019) Right atrial phasic function in heart failure with preserved and reduced ejection fraction. JACC Cardiovasc Imaging 12:1460–1470PubMedCrossRef
91.
Shah AM, Claggett B, Sweitzer NK et al (2015) Prognostic importance of impaired systolic function in heart failure with preserved ejection fraction and the impact of spironolactone. Circulation 132:402–414PubMedPubMedCentralCrossRef
92.
93.
94.
Romano S, Judd R, Kim R et al (2020) Feature-tracking global longitudinal strain predicts mortality in patients with preserved ejection fraction: a multicenter study. J Am Coll Cardiol Img 13:940–947CrossRef
95.
96.
97.
Truong VT, Safdar KS, Kalra DK et al (2017) Cardiac magnetic resonance tissue tracking in right ventricle: feasibility and normal values. Magn Reson Imaging 38:189–195PubMedCrossRef
98.
Dobrovie M, Barreiro-Perez M, Curione D et al (2019) Inter-vendor reproducibility and accuracy of segmental left ventricular strain measurements using CMR feature tracking. Eur Radiol 29:6846–6857PubMedCrossRef
99.
Marcos-Garces V, Gavara J, Monmeneu JV et al (2020) Vasodilator stress CMR and all-cause mortality in stable ischemic heart disease: a large retrospective registry. JACC Cardiovasc Imaging 13:1674–1686PubMedCrossRef
100.
Podlesnikar T, Pizarro G, Fernández-Jiménez R et al (2019) Effect of early metoprolol during ST-segment elevation myocardial infarction on left ventricular strain: feature-tracking cardiovascular magnetic resonance substudy from the METOCARD-CNIC Trial. JACC Cardiovasc Imaging 12:1188–1198PubMedCrossRef
101.
Podlesnikar T, Pizarro G, Fernández-Jiménez R et al (2020) Left ventricular functional recovery of infarcted and remote myocardium after ST-segment elevation myocardial infarction (METOCARD-CNIC randomized clinical trial substudy). J Cardiovasc Magn Reson 22:44PubMedPubMedCentralCrossRef
Metadata
Title
State-of-the-art myocardial strain by CMR feature tracking: clinical applications and future perspectives
Authors
Jing Xu
Wenjing Yang
Shihua Zhao
Minjie Lu
Publication date
24-02-2022
Publisher
Springer Berlin Heidelberg
Keyword
Cardiomyopathy
Published in
European Radiology / Issue 8/2022
Print ISSN: 0938-7994
Electronic ISSN: 1432-1084
DOI
https://doi.org/10.1007/s00330-022-08629-2

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