Published online May 26, 2018. doi: 10.4330/wjc.v10.i5.35
Peer-review started: February 5, 2018
First decision: March 7, 2018
Revised: March 8, 2018
Accepted: April 22, 2018
Article in press: April 22, 2018
Published online: May 26, 2018
Processing time: 109 Days and 12.7 Hours
Cardiovascular magnetic resonance (CMR) represents the reference standard for cardiac morphology and function assessment. Since introduction in 2009, CMR feature tracking (CMR-FT) has become a frequently used tool in the assessment of myocardial deformation and wall motion on the basis of routinely acquired b-SSFP cine images. Extensive validation has led to excellent intra- and inter-observer as well as inter-study reproducibility. CMR-FT derived myocardial deformation indices such as left ventricular (LV) strain have been shown to be impaired in cardiac diseases such as cardiomyopathies as well as myocardial infarction. Although LV ejection fraction (LVEF) is the routinely and frequently utilized parameter for systolic myocardial function assessment and major adverse clinical event (MACE) prediction, it fails to assess regional differences. Recently, LV strain has emerged as a superior measure for risk assessment and MACE prediction as compared to the established markers e.g., LVEF. This editorial aims to elucidate current discussions in the field of strain assessment in myocardial infarction in the light of recent data from a large prospective multicentre CMR study.
Core tip: Cardiovascular magnetic resonance feature-tracking bears the potential for superior risk evaluation in infarct patients beyond established risk factors such as left ventricular ejection fraction. However, further clinical trials are inevitably needed to establish vendor independent thresholds for clinical routine use in various cardiac diseases.
- Citation: Schuster A, Backhaus SJ, Stiermaier T, Eitel I. Prognostic utility of global longitudinal strain in myocardial infarction. World J Cardiol 2018; 10(5): 35-37
- URL: https://www.wjgnet.com/1949-8462/full/v10/i5/35.htm
- DOI: https://dx.doi.org/10.4330/wjc.v10.i5.35
Since introduction in 2009, cardiovascular magnetic resonance feature tracking (CMR-FT) has been applied in research extensively, and its clinical utility has remarkably increased[1-8]. Whilst there is evidence to suggest that some of the CMR-FT indices including global longitudinal strain (GLS) carry independent prognostic implications in dilated and chronic ischaemic cardiomyopathy as well as tetralogy of Fallot[9-11] evidence in myocardial infarction has only recently become available and shows some degree of controversy[12,13]. Gavara et al[13] demonstrated the association of CMR-FT derived left ventricular GLS with major adverse cardiac events (MACE). However they failed to demonstrate an additional prognostic value over established CMR parameters in a retrospective collective of 323 STEMI patients. It is important to note that these results are expanded with recent prospective data by Eitel et al[12]. Both studies agree on the distinct relationship of myocardial deformation indices with MACE and demonstrate GLS to be the most robust parameter to predict reinfarction, heart failure and cardiac deaths[12,13]. However, the study by Eitel et al[12] suggests an incremental prognostic role of CMR-FT derived GLS over and above classical CMR markers of prognosis irrespectively of clinical risk factors in 1235 acute myocardial infarction (AMI) patients (including STEMI and NSTEMI)[12].
Several factors need to be considered that may potentially account for this discrepancy: (1) Even though CMR-FT algorithms are generally based on optical flow technology[1] there are inherent differences in the way strain is being calculated. Whilst the technique used by Gavara et al[13] is based on the assessment of several myocardial layers between endo and epicardium the technique used by Eitel et al[12] is predominantly based on endocardial boundary tracking[1]. In fact, there is evidence to suggest that small numerical strain differences between both techniques occur in healthy volunteers[14]; (2) since it is well known that 2D deformation imaging techniques are limited in reproducibility on a segmental level mainly because of through plane motion with subsequent fading of features during systole[1], it is interesting to speculate whether the calculation of global strain values from the averages of 16 segmental peak strains as performed by Gavara et al[13] is less accurate than their calculation from averaged global strain curves as performed with alternative CMR-FT software which was utilized in the study by Eitel et al[12]; (3) as opposed to the methodology used by Gavara et al[13] the technique used by Eitel et al[12] is based on the average of three repeated measurements to further reduce variability[13-15]; and (4) the differences in sample size and study design may have resulted in greater statistical power in the prospective trial by Eitel et al[12] explaining the demonstration of additional clinical value of GLS. Notwithstanding these considerations, further refinements of the underlying technology and additional prospective clinical trials defining the relative diagnostic and prognostic yields of these techniques in identical patient collectives are warranted to establish interchangeability of different CMR-FT techniques in risk stratification in various diseases[9-15]. Taken together, considering recent evidence to suggest a significant role in risk stratification[9-12] and presuming that these findings are confirmed in further prospective trials alongside with the achievement of the latter technology refinements, CMR-FT risk stratification may establish itself within routine CMR imaging following AMI and other cardiac pathologies.
Manuscript source: Unsolicited manuscript
Specialty type: Cardiac and cardiovascular systems
Country of origin: Germany
Peer-review report classification
Grade A (Excellent): A
Grade B (Very good): B
Grade C (Good): 0
Grade D (Fair): 0
Grade E (Poor): 0
P- Reviewer: Mani V, Satoh H S- Editor: Cui LJ L- Editor: A E- Editor: Tan WW
1. | Schuster A, Hor KN, Kowallick JT, Beerbaum P, Kutty S. Cardiovascular Magnetic Resonance Myocardial Feature Tracking: Concepts and Clinical Applications. Circ Cardiovasc Imaging. 2016;9:e004077. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 205] [Cited by in F6Publishing: 270] [Article Influence: 33.8] [Reference Citation Analysis (0)] |
2. | Schuster A, Kutty S, Padiyath A, Parish V, Gribben P, Danford DA, Makowski MR, Bigalke B, Beerbaum P, Nagel E. Cardiovascular magnetic resonance myocardial feature tracking detects quantitative wall motion during dobutamine stress. J Cardiovasc Magn Reson. 2011;13:58. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 108] [Cited by in F6Publishing: 104] [Article Influence: 8.0] [Reference Citation Analysis (0)] |
3. | Schuster A, Paul M, Bettencourt N, Morton G, Chiribiri A, Ishida M, Hussain S, Jogiya R, Kutty S, Bigalke B. Cardiovascular magnetic resonance myocardial feature tracking for quantitative viability assessment in ischemic cardiomyopathy. Int J Cardiol. 2013;166:413-420. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 82] [Cited by in F6Publishing: 89] [Article Influence: 6.8] [Reference Citation Analysis (0)] |
4. | Kowallick JT, Kutty S, Edelmann F, Chiribiri A, Villa A, Steinmetz M, Sohns JM, Staab W, Bettencourt N, Unterberg-Buchwald C. Quantification of left atrial strain and strain rate using Cardiovascular Magnetic Resonance myocardial feature tracking: a feasibility study. J Cardiovasc Magn Reson. 2014;16:60. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 173] [Cited by in F6Publishing: 198] [Article Influence: 19.8] [Reference Citation Analysis (0)] |
5. | von Roeder M, Rommel KP, Kowallick JT, Blazek S, Besler C, Fengler K, Lotz J, Hasenfuß G, Lücke C, Gutberlet M. Influence of Left Atrial Function on Exercise Capacity and Left Ventricular Function in Patients With Heart Failure and Preserved Ejection Fraction. Circ Cardiovasc Imaging. 2017;10. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 66] [Cited by in F6Publishing: 103] [Article Influence: 14.7] [Reference Citation Analysis (0)] |
6. | Kutty S, Rangamani S, Venkataraman J, Li L, Schuster A, Fletcher SE, Danford DA, Beerbaum P. Reduced global longitudinal and radial strain with normal left ventricular ejection fraction late after effective repair of aortic coarctation: a CMR feature tracking study. Int J Cardiovasc Imaging. 2013;29:141-150. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 53] [Cited by in F6Publishing: 54] [Article Influence: 4.5] [Reference Citation Analysis (0)] |
7. | Schuster A, Paul M, Bettencourt N, Hussain ST, Morton G, Kutty S, Bigalke B, Chiribiri A, Perera D, Nagel E. Myocardial feature tracking reduces observer-dependence in low-dose dobutamine stress cardiovascular magnetic resonance. PLoS One. 2015;10:e0122858. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 22] [Cited by in F6Publishing: 25] [Article Influence: 2.8] [Reference Citation Analysis (0)] |
8. | Steinmetz M, Broder M, Hösch O, Lamata P, Kutty S, Kowallick JT, Staab W, Ritter CO, Hasenfuß G, Paul T. Atrio-ventricular deformation and heart failure in Ebstein's Anomaly - A cardiovascular magnetic resonance study. Int J Cardiol. 2018;257:54-61. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 15] [Cited by in F6Publishing: 16] [Article Influence: 2.7] [Reference Citation Analysis (0)] |
9. | Buss SJ, Breuninger K, Lehrke S, Voss A, Galuschky C, Lossnitzer D, Andre F, Ehlermann P, Franke J, Taeger T. Assessment of myocardial deformation with cardiac magnetic resonance strain imaging improves risk stratification in patients with dilated cardiomyopathy. Eur Heart J Cardiovasc Imaging. 2015;16:307-315. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 163] [Cited by in F6Publishing: 203] [Article Influence: 20.3] [Reference Citation Analysis (0)] |
10. | Romano S, Judd RM, Kim RJ, Kim HW, Klem I, Heitner JF, Shah DJ, Jue J, White BE, Indorkar R. 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. JACC Cardiovasc Imaging. 2018;pii:S1936-878X(17)31147-6. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 138] [Cited by in F6Publishing: 197] [Article Influence: 32.8] [Reference Citation Analysis (1)] |
11. | Orwat S, Diller GP, Kempny A, Radke R, Peters B, Kühne T, Boethig D, Gutberlet M, Dubowy KO, Beerbaum P. Myocardial deformation parameters predict outcome in patients with repaired tetralogy of Fallot. Heart. 2016;102:209-215. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 95] [Cited by in F6Publishing: 101] [Article Influence: 11.2] [Reference Citation Analysis (1)] |
12. | Eitel I, Stiermaier T, Lange T, Romme lK-P, Koschalka A, Kowallick JT, Lotz J, Kutty S, Gutberlet M, Hasenfuss G, Thiele H, Schuster A. Cardiac Magnetic Resonance Myocardial Feature Tracking for Optimized Prediction of Cardiovascular Events Following Myocardial Infarction. JACC Cardiovasc Imaging. 2018;. [DOI] [Cited in This Article: ] [Cited by in Crossref: 101] [Cited by in F6Publishing: 146] [Article Influence: 24.3] [Reference Citation Analysis (0)] |
13. | Gavara J, Rodriguez-Palomares JF, Valente F, Monmeneu JV, Lopez-Lereu MP, Bonanad C, Ferreira-Gonzalez I, Garcia Del Blanco B, Rodriguez-Garcia J, Mutuberria M. Prognostic Value of Strain by Tissue Tracking Cardiac Magnetic Resonance After ST-Segment Elevation Myocardial Infarction. JACC Cardiovasc Imaging. 2017;pii:S1936-878X(17)30985-3. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 68] [Cited by in F6Publishing: 93] [Article Influence: 13.3] [Reference Citation Analysis (0)] |
14. | Schuster A, Stahnke VC, Unterberg-Buchwald C, Kowallick JT, Lamata P, Steinmetz M, Kutty S, Fasshauer M, Staab W, Sohns JM. Cardiovascular magnetic resonance feature-tracking assessment of myocardial mechanics: Intervendor agreement and considerations regarding reproducibility. Clin Radiol. 2015;70:989-998. [PubMed] [DOI] [Cited in This Article: ] [Cited by in Crossref: 128] [Cited by in F6Publishing: 141] [Article Influence: 15.7] [Reference Citation Analysis (0)] |
15. | Gertz RJ, Lange T, Kowallick JT, Backhaus SJ, Steinmetz M, Staab W, Kutty S, Hasenfuß G, Lotz J, Schuster A. Inter-vendor reproducibility of left and right ventricular cardiovascular magnetic resonance myocardial feature-tracking. PLoS ONE. 2018;. [DOI] [Cited in This Article: ] [Cited by in Crossref: 34] [Cited by in F6Publishing: 50] [Article Influence: 8.3] [Reference Citation Analysis (0)] |