Skip to main content
SpringerLink
Log in

The prognostic value of myocardial salvage index by cardiac magnetic resonance in ST-segment elevation myocardial infarction patients: a systematic review and meta-analysis

  • Cardiac
  • Published:
European Radiology Aims and scope Submit manuscript

Abstract

Objective

To assess the prognostic value of myocardial salvage index (MSI) by cardiac magnetic resonance (CMR) in ST-segment elevation myocardial infarction (STEMI) patients.

Methods

We systematically searched PubMed, Embase, Web of Science, Cochrane Central, China National Knowledge Infrastructure, and Wanfang Data to identify primary studies reporting MSI in STEMI patients with major adverse cardiovascular events (MACE) comprised of death, myocardial reinfarction, and congestive heart failure. The MSI and MACE rates were pooled. The bias of risk was assessed using the Quality In Prognosis Studies tool. The evidence level was rated based on the meta-analysis of hazard ratio (HR) and 95% confidence interval (CI) of MSI for predicting MACE.

Results

Eighteen studies were included covering twelve unique cohorts. Eleven cohorts measured MSI using T2-weighted imaging and T1-weighted late gadolinium enhancement, while one cohort applied T2-mapping and T1-mapping. The pooled MSI (95% CI) was 44% (39 to 49%; 11 studies, 2946 patients), and the pooled MACE rate (95% CI) was 10% (7 to 14%; 12 studies, 311/3011 events/patients). Seven prognostic studies overall showed low risk of bias. The HR (95% CI) per 1% increase of MSI for MACE was 0.95 (0.92 to 0.98; 5 studies, 150/885 events/patients), and HR (95% CI) of MSI < median versus MSI > median for MACE was 5.62 (3.74 to 8.43; 6 studies, 166/1570 events/patients), both rated as weak evidence.

Conclusions

MSI presents potential in predicting MACE in STEMI patients. The prognostic value of MSI using advanced CMR techniques for adverse cardiovascular events needs further investigation.

Clinical relevance statement

Seven studies supported the MSI to serve as a predictor for MACE in STEMI patients, indicating its potential as a risk stratification tool to help manage expectations for these patients in clinical practice.

Key Points

• The pooled infarct size (95% CI) and area at risk (95% CI) were 21% (18 to 23%; 11 studies, 2783 patients) and 38% (34 to 43%; 10 studies, 2022 patients), respectively.

• The pooled rates (95% CI) of cardiac mortality, myocardial reinfarction, and congestive heart failure were 2% (1 to 3%; 11 studies, 86/2907 events/patients), 4% (3 to 6%; 12 studies, 127/3011 events/patients), and 3% (1 to 5%; 12 studies, 94/3011 events/patients), respectively.

• The HRs (95% CI) per 1% increase of MSI for cardiac mortality and congestive heart failure were 0.93 (0.91 to 0.96; 1 study, 14/202 events/patients) and 0.96 (0.93 to 0.99; 1 study, 11/104 events/patients), respectively, but the prognostic value of MSI for myocardial re-infraction has not been measured.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

Abbreviations

AAR:

Area at risk

CI:

Confidence interval

CMR:

Cardiac magnetic resonance

HR:

Hazard ratio

IS:

Infarct size

LGE:

Late gadolinium enhancement

MACE:

Major adverse cardiovascular events

MSI:

Myocardial salvage index

PCI:

Percutaneous coronary intervention

QUIPS:

Quality In Prognosis Studies

STEMI:

ST-segment elevation myocardial infarction

References

  1. Vogel B, Claessen BE, Arnold SV et al (2019) ST-segment elevation myocardial infarction. Nat Rev Dis Primers 5(1):39. https://doi.org/10.1038/s41572-019-0090-3

    Article  PubMed  Google Scholar 

  2. GBD (2019) Diseases and Injuries Collaborators (2020) Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019. Lancet 396(10258):1204–1222. https://doi.org/10.1016/S0140-6736(20)30925-9

    Article  Google Scholar 

  3. Roth GA, Mensah GA, Johnson CO et al (2020) GBD-NHLBI-JACC Global Burden of Cardiovascular Diseases Writing Group Global burden of cardiovascular diseases and risk factors, 1990–2019: update from the GBD 2019 study. J Am Coll Cardiol 76(25):2982–3021. https://doi.org/10.1016/j.jacc.2020.11.010

    Article  PubMed  PubMed Central  Google Scholar 

  4. Ibanez B, James S, Agewall S et al (2018) 2017 ESC Guidelines for the management of acute myocardial infarction in patients presenting with ST-segment elevation: the task force for the management of acute myocardial infarction in patients presenting with ST-segment elevation of the European Society of Cardiology (ESC). Eur Heart J 39(2):119–177. https://doi.org/10.1093/eurheartj/ehx393

    Article  PubMed  Google Scholar 

  5. Lawton JS, Tamis-Holland JE, Bangalore S et al (2022) 2021 ACC/AHA/SCAI guideline for coronary artery revascularization: a report of the American College of Cardiology/American Heart Association joint committee on clinical practice guidelines. Circulation 145(3):e18–e114. https://doi.org/10.1161/CIR.0000000000001038

    Article  PubMed  Google Scholar 

  6. Reinstadler SJ, Thiele H, Eitel I (2015) Risk stratification by cardiac magnetic resonance imaging after ST-elevation myocardial infarction. Curr Opin Cardiol 30(6):681–689. https://doi.org/10.1097/HCO.0000000000000227

    Article  PubMed  Google Scholar 

  7. Kendziora B, Stier H, Schlattmann P, Dewey M (2020) MRI for measuring therapy efficiency after revascularisation in ST-segment elevation myocardial infarction: a systematic review and meta-regression analysis. BMJ Open 10(9):e034359. https://doi.org/10.1136/bmjopen-2019-034359

    Article  PubMed  PubMed Central  Google Scholar 

  8. Bhatt DL, Lopes RD, Harrington RA (2022) Diagnosis and treatment of acute coronary syndromes: a review. JAMA 327(7):662–675. https://doi.org/10.1001/jama.2022.0358

    Article  PubMed  Google Scholar 

  9. Niccoli G, Montone RA, Ibanez B et al (2019) Optimized treatment of ST-elevation myocardial infarction. Circ Res 125(2):245–258. https://doi.org/10.1161/CIRCRESAHA.119.315344

    Article  CAS  PubMed  Google Scholar 

  10. Ibanez B, Aletras AH, Arai AE et al (2019) Cardiac MRI endpoints in myocardial infarction experimental and clinical trials: JACC scientific expert panel. J Am Coll Cardiol 74(2):238–256. https://doi.org/10.1016/j.jacc.2019.05.024

    Article  PubMed  PubMed Central  Google Scholar 

  11. Beijnink CWH, van der Hoeven NW, Konijnenberg LSF et al (2021) Cardiac MRI to visualize myocardial damage after ST-segment elevation myocardial infarction: a review of its histologic validation. Radiology 301(1):4–18. https://doi.org/10.1148/radiol.2021204265

    Article  PubMed  Google Scholar 

  12. Carlsson M, Ubachs J, Hedström E, Heiberg E, Jovinge S, Arheden H (2009) Myocardium at risk after acute infarction in humans on cardiac magnetic resonance: quantitative assessment during follow-up and validation with single-photon emission computed tomography. JACC Cardiovasc Imaging 2(5):569-576. https://doi.org/10.1016/j.jcmg.2008.11.018

  13. Thiele H, Kappl MJ, Conradi S, Niebauer J, Hambrecht R, Schuler G (2006) Reproducibility of chronic and acute infarct size measurement by delayed enhancement-magnetic resonance imaging. J Am Coll Cardiol 47(8):1641–1645. https://doi.org/10.1016/j.jacc.2005.11.065

    Article  PubMed  Google Scholar 

  14. Messroghli DR, Walters K, Plein S et al (2007) Myocardial T1 mapping: application to patients with acute and chronic myocardial infarction. Magn Reson Med 58(1):34–40. https://doi.org/10.1002/mrm.21272

    Article  PubMed  Google Scholar 

  15. Carrick D, Haig C, Rauhalammi S et al (2016) Prognostic significance of infarct core pathology revealed by quantitative non-contrast in comparison with contrast cardiac magnetic resonance imaging in reperfused ST-elevation myocardial infarction survivors. Eur Heart J 37(13):1044–1059. https://doi.org/10.1093/eurheartj/ehv372

    Article  PubMed  Google Scholar 

  16. Kendziora B, Dewey M (2020) Prognostic value of the myocardial salvage index measured by T2-weighted and T1-weighted late gadolinium enhancement magnetic resonance imaging after ST-segment elevation myocardial infarction: a systematic review and meta-regression analysis. PLoS One 15(2):e0228736. https://doi.org/10.1371/journal.pone.0228736

    Article  PubMed  PubMed Central  Google Scholar 

  17. Page MJ, McKenzie JE, Bossuyt PM et al (2021) The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ 372:n71. https://doi.org/10.1136/bmj.n71

    Article  PubMed  PubMed Central  Google Scholar 

  18. Rethlefsen ML, Kirtley S, Waffenschmidt S et al (2021) PRISMA-S Group PRISMA-S: an extension to the PRISMA statement for reporting literature searches in systematic reviews. Syst Rev 10(1):39. https://doi.org/10.1186/s13643-020-01542-z

    Article  PubMed  PubMed Central  Google Scholar 

  19. Hayden JA, van der Windt DA, Cartwright JL, Côté P, Bombardier C (2013) Assessing bias in studies of prognostic factors. Ann Intern Med 158(4):280–286. https://doi.org/10.7326/0003-4819-158-4-201302190-00009

    Article  PubMed  Google Scholar 

  20. Ma LL, Wang YY, Yang ZH, Huang D, Weng H, Zeng XT (2020) Methodological quality (risk of bias) assessment tools for primary and secondary medical studies: what are they and which is better? Mil Med Res 7(1):7. https://doi.org/10.1186/s40779-020-00238-8

    Article  PubMed  PubMed Central  Google Scholar 

  21. Zeng X, Zhang Y, Kwong JS et al (2015) The methodological quality assessment tools for preclinical and clinical studies, systematic review and meta-analysis, and clinical practice guideline: a systematic review. J Evid Based Med 8(1):2–10. https://doi.org/10.1111/jebm.12141

    Article  PubMed  Google Scholar 

  22. Tong T. Estimating the sample mean and standard deviation from the sample size, median, range and/or interquartile range. Accessed via https://www.math.hkbu.edu.hk/~tongt/papers/median2mean.html on Oct 2022

  23. Shi J, Luo D, Wan X et al (2020) Detecting the skewness of data from the sample size and the five-number summary. arXiv preprint. https://arxiv.org/abs/2010.05749

  24. Shi J, Luo D, Wan X et al (2020) Optimally estimating the sample standard deviation from the five-number summary. Res Synth Methods 11(5):641–654. https://doi.org/10.1002/jrsm.1429

    Article  PubMed  Google Scholar 

  25. Luo D, Wan X, Liu J, Tong T (2018) Optimally estimating the sample mean from the sample size, median, mid-range, and/or mid-quartile range. Stat Methods Med Res 27(6):1785–1805. https://doi.org/10.1177/0962280216669183

    Article  PubMed  Google Scholar 

  26. Wan X, Wang W, Liu J, Tong T (2014) Estimating the sample mean and standard deviation from the sample size, median, range and/or interquartile range. BMC Med Res Methodol 14:135. https://doi.org/10.1186/1471-2288-14-135

    Article  PubMed  PubMed Central  Google Scholar 

  27. Tierney JF, Stewart LA, Ghersi D, Burdett S, Sydes MR (2007) Practical methods for incorporating summary time-to-event data into meta-analysis. Trials 8:16. https://doi.org/10.1186/1745-6215-8-16

    Article  PubMed  PubMed Central  Google Scholar 

  28. Mitchell M, Muftakhidinov B, Winchen T et al (2020) Engauge Digitizer. Accessed via http://markummitchell.github.io/engauge-digitizer/ on Oct 2022

  29. Gosling CJ, Solanes A, Fusar-Poli P, Radua J. metaumbrella project. Accessed via https://www.metaumbrella.org on Oct 2022

  30. Fusar-Poli P, Radua J (2018) Ten simple rules for conducting umbrella reviews. Evid Based Ment Health 21(3):95–100. https://doi.org/10.1136/ebmental-2018-300014

    Article  PubMed  PubMed Central  Google Scholar 

  31. Dang Y, Hou Y (2021) The prognostic value of late gadolinium enhancement in heart diseases: an umbrella review of meta-analyses of observational studies. Eur Radiol 31(7):4528–4537. https://doi.org/10.1007/s00330-020-07437-w

    Article  PubMed  Google Scholar 

  32. Oxman AD, Guyatt GH (1992) A consumer’s guide to subgroup analyses. Ann Intern Med 116(1):78–84. https://doi.org/10.7326/0003-4819-116-1-78

    Article  CAS  PubMed  Google Scholar 

  33. Berlin JA, Antman EM (1994) Advantages and limitations of metaanalytic regressions of clinical trials data. Online J Curr Clin Trials. https://doi.org/10.1016/0197-2456(92)90151-o

    Article  PubMed  Google Scholar 

  34. Higgins JP, Thompson SG (2002) Quantifying heterogeneity in a meta-analysis. Stat Med 21(11):1539–1558. https://doi.org/10.1002/sim.1186

    Article  PubMed  Google Scholar 

  35. Bonanad C, Monmeneu JV, Lopez-Lereu MP et al (2016) Prediction of long-term major events soon after a first ST-segment elevation myocardial infarction by cardiovascular magnetic resonance. Eur J Radiol 85(3):585–592. https://doi.org/10.1016/j.ejrad.2015.12.012

    Article  PubMed  Google Scholar 

  36. Chung S, Song YB, Hahn JY et al (2014) Impact of white blood cell count on myocardial salvage, infarct size, and clinical outcomes in patients undergoing primary percutaneous coronary intervention for ST-segment elevation myocardial infarction: a magnetic resonance imaging study. Int J Cardiovasc Imaging 30(1):129–136. https://doi.org/10.1007/s10554-013-0303-x

    Article  PubMed  Google Scholar 

  37. de Waha S, Eitel I, Desch S et al (2014) Prognosis after ST-elevation myocardial infarction: a study on cardiac magnetic resonance imaging versus clinical routine. Trials 15:249. https://doi.org/10.1186/1745-6215-15-249

    Article  PubMed  PubMed Central  Google Scholar 

  38. Eitel I, Desch S, Fuernau G et al (2010) Prognostic significance and determinants of myocardial salvage assessed by cardiovascular magnetic resonance in acute reperfused myocardial infarction. J Am Coll Cardiol 55(22):2470–2479. https://doi.org/10.1016/j.jacc.2010.01.049

    Article  PubMed  Google Scholar 

  39. Eitel I, Kubusch K, Strohm O et al (2011) Prognostic value and determinants of a hypointense infarct core in T2-weighted cardiac magnetic resonance in acute reperfused ST-elevation-myocardial infarction. Circ Cardiovasc Imaging 354–362. https://doi.org/10.1161/CIRCIMAGING.110.960500

  40. Eitel I, Desch S, de Waha S et al (2011) Long-term prognostic value of myocardial salvage assessed by cardiovascular magnetic resonance in acute reperfused myocardial infarction. Heart 97(24):2038–2045. https://doi.org/10.1136/heartjnl-2011-300098

    Article  PubMed  Google Scholar 

  41. Eitel I, Wöhrle J, Suenkel H et al (2013) Intracoronary compared with intravenous bolus abciximab application during primary percutaneous coronary intervention in ST-segment elevation myocardial infarction: cardiac magnetic resonance substudy of the AIDA STEMI trial. J Am Coll Cardiol 61(13):1447–1454. https://doi.org/10.1016/j.jacc.2013.01.048

    Article  CAS  PubMed  Google Scholar 

  42. Eitel I, de Waha S, Wöhrle J et al (2014) Comprehensive prognosis assessment by CMR imaging after ST-segment elevation myocardial infarction. J Am Coll Cardiol 64(12):1217–1226. https://doi.org/10.1016/j.jacc.2014.06.1194

    Article  PubMed  Google Scholar 

  43. Grothoff M, Elpert C, Hoffmann J et al (2012) Right ventricular injury in ST-elevation myocardial infarction: risk stratification by visualization of wall motion, edema, and delayed-enhancement cardiac magnetic resonance. Circ Cardiovasc Imaging 5(1):60–68. https://doi.org/10.1161/CIRCIMAGING.111.967810

    Article  PubMed  Google Scholar 

  44. Kamal D, S Ibrahim A, Ahmed Nasr M, S Madkour S (2019) Prognostic value of different cardiac magnetic resonance imaging derived parameters in Egyptian patients with ST-elevation myocardial infarction after successful reperfusion by primary percutaneous intervention. Egypt Heart J 71(1):33. https://doi.org/10.1186/s43044-019-0035-x

  45. Li Y, Wang G, Wang X et al (2022) Prognostic significance of myocardial salvage assessed by cardiac magnetic resonance in reperfused ST-segment elevation myocardial infarction. Front Cardiovasc Med 9:924428. https://doi.org/10.3389/fcvm.2022.924428

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Masci PG, Ganame J, Strata E et al (2010) Myocardial salvage by CMR correlates with LV remodeling and early ST-segment resolution in acute myocardial infarction. JACC Cardiovasc Imaging 3(1):45–51. https://doi.org/10.1016/j.jcmg.2009.06.016

    Article  PubMed  Google Scholar 

  47. Pontone G, Guaricci AI, Andreini D et al (2017) Prognostic stratification of patients with ST-segment-elevation myocardial infarction (PROSPECT): a cardiac magnetic resonance study. Circ Cardiovasc Imaging 10(11):e006428. https://doi.org/10.1161/CIRCIMAGING.117.006428

    Article  PubMed  Google Scholar 

  48. Reinstadler SJ, Stiermaier T, Liebetrau J et al (2018) Prognostic significance of remote myocardium alterations assessed by quantitative noncontrast T1 mapping in ST-segment elevation myocardial infarction. JACC Cardiovasc Imaging 11(3):411–419. https://doi.org/10.1016/j.jcmg.2017.03.015

    Article  PubMed  Google Scholar 

  49. Sohn GH, Kim EK, Hahn JY et al (2014) Impact of overweight on myocardial infarct size in patients undergoing primary percutaneous coronary intervention: a magnetic resonance imaging study. Atherosclerosis 235(2):570–575. https://doi.org/10.1016/j.atherosclerosis.2014.05.961

    Article  CAS  PubMed  Google Scholar 

  50. Song YB, Hahn JY, Gwon HC et al (2012) A high loading dose of clopidogrel reduces myocardial infarct size in patients undergoing primary percutaneous coronary intervention: a magnetic resonance imaging study. Am Heart J 163(3):500–507. https://doi.org/10.1016/j.ahj.2011.12.007

    Article  CAS  PubMed  Google Scholar 

  51. Yoon CH, Chung WY, Suh JW et al (2013) Distal protection device aggravated microvascular obstruction evaluated by cardiac MR after primary percutaneous intervention for ST-elevation myocardial infarction. Int J Cardiol 167(5):2002–2007. https://doi.org/10.1016/j.ijcard.2012.05.029

    Article  PubMed  Google Scholar 

  52. Zhang S, Ma Q, Jiao Y et al (2022) Prognostic value of myocardial salvage index assessed by cardiovascular magnetic resonance in reperfused ST-segment elevation myocardial infarction. Front Cardiovasc Med 9:933733. https://doi.org/10.3389/fcvm.2022.933733

    Article  PubMed  PubMed Central  Google Scholar 

  53. Engblom H, Heiberg E, Erlinge D et al (2016) Sample size in clinical cardioprotection trials using myocardial salvage index, infarct size, or biochemical markers as endpoint. J Am Heart Assoc 5(3):e002708. https://doi.org/10.1161/JAHA.115.002708

    Article  PubMed  PubMed Central  Google Scholar 

  54. Bulluck H, Hammond-Haley M, Weinmann S, Martinez-Macias R, Hausenloy DJ (2017) Myocardial infarct size by CMR in clinical cardioprotection studies: insights from randomized controlled trials. JACC Cardiovasc Imaging 10(3):230–240. https://doi.org/10.1016/j.jcmg.2017.01.008

    Article  PubMed  PubMed Central  Google Scholar 

  55. Garg P, Broadbent DA, Swoboda PP et al (2017) Extra-cellular expansion in the normal, non-infarcted myocardium is associated with worsening of regional myocardial function after acute myocardial infarction. J Cardiovasc Magn Reson 19(1):73. https://doi.org/10.1186/s12968-017-0384-0

    Article  PubMed  PubMed Central  Google Scholar 

  56. Bulluck H, White SK, Rosmini S et al (2015) T1 mapping and T2 mapping at 3T for quantifying the area-at-risk in reperfused STEMI patients. J Cardiovasc Magn Reson 17(1):73. https://doi.org/10.1186/s12968-015-0173-6

    Article  PubMed  PubMed Central  Google Scholar 

  57. Fernández-Jiménez R, Galán-Arriola C, Sánchez-González J et al (2017) Effect of ischemia duration and protective interventions on the temporal dynamics of tissue composition after myocardial infarction. Circ Res 121(4):439–450. https://doi.org/10.1161/CIRCRESAHA.117.310901

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Kim HW, van Assche L, Jennings RB et al (2015) Relationship of T2-weighted MRI myocardial hyperintensity and the ischemic area-at-risk. Circ Res 117(3):254–265. https://doi.org/10.1161/CIRCRESAHA.117.305771

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Bulluck H, Chan MHH, Paradies V et al (2018) Impact of cardioprotective therapies on the edema-based area at risk by CMR in reperfused STEMI. J Am Coll Cardiol 71(24):2856–2858. https://doi.org/10.1016/j.jacc.2018.04.016

    Article  PubMed  Google Scholar 

  60. Göransson C, Ahtarovski KA, Kyhl K et al (2019) Assessment of the myocardial area at risk: comparing T2-weighted cardiovascular magnetic resonance imaging with contrast-enhanced cine (CE-SSFP) imaging-a DANAMI3 substudy. Eur Heart J Cardiovasc Imaging 20(3):361–366. https://doi.org/10.1093/ehjci/jey106

    Article  PubMed  Google Scholar 

  61. Ubachs JF, Sörensson P, Engblom H et al (2012) Myocardium at risk by magnetic resonance imaging: head-to-head comparison of T2-weighted imaging and contrast-enhanced steady-state free precession. Eur Heart J Cardiovasc Imaging 13(12):1008–1015. https://doi.org/10.1093/ehjci/jes091

    Article  PubMed  PubMed Central  Google Scholar 

  62. Ortiz-Pérez JT, Meyers SN, Lee DC et al (2007) Angiographic estimates of myocardium at risk during acute myocardial infarction: validation study using cardiac magnetic resonance imaging. Eur Heart J 28(14):1750–1758. https://doi.org/10.1093/eurheartj/ehm212

    Article  PubMed  Google Scholar 

  63. Fuernau G, Eitel I, Franke V et al (2011) Myocardium at risk in ST-segment elevation myocardial infarction comparison of T2-weighted edema imaging with the MR-assessed endocardial surface area and validation against angiographic scoring. JACC Cardiovasc Imaging 4(9):967–976. https://doi.org/10.1016/j.jcmg.2011.02.023

    Article  PubMed  Google Scholar 

  64. Lønborg J, Engstrøm T, Mathiasen AB, Vejlstrup N (2011) Myocardial area at risk after ST-elevation myocardial infarction measured with the late gadolinium enhancement after scar remodeling and T2-weighted cardiac magnetic resonance imaging. Int J Cardiovasc Imaging 28(6):1455–1464. https://doi.org/10.1007/s10554-011-9952-9

    Article  PubMed  Google Scholar 

  65. Stewart LA, Clarke M, Rovers M et al (2015) PRISMA-IPD Development Group Preferred reporting items for systematic review and meta-analyses of individual participant data: the PRISMA-IPD statement. JAMA 313(16):1657–1665. https://doi.org/10.1001/jama.2015.3656

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

The authors would like to express their gratitude to Mr. Junjie Lu for his advice on statistical analysis, Dr. Shiqi Mao for his suggestions on data visualization, and Dr. Guangcheng Zhang for English language editing.

Funding

This study has received funding from the Yangfan Project of Science and Technology Commission of Shanghai Municipality (22YF1442400); Research Found of Science and Technology Commission of Changing District, Shanghai Municipality (CNKW2022Y15); Medicine and Engineering Combination Project of Shanghai Jiao Tong University (YG2019ZDB09); and Research Fund of Tongren Hospital, Shanghai Jiao Tong University School of Medicine (TRKYRC-XX202204, 2020TRYJ(LB)05).

Author information

Author notes

  1. Zhengguang Xiao, Jingyu Zhong, and Lingna Zhong contributed equally to this work.

  2. Weiwu Yao and Jun Yang are the co-corresponding authors.

Authors and Affiliations

  1. Department of Imaging, Tongren Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200336, China

    Zhengguang Xiao, Jingyu Zhong, Shun Dai, Wenjie Lu, Jun Yang & Weiwu Yao

  2. Electrocardiogram Room, Department of Internal Medicine, International Peace Maternity and Child Health Hospital of China Welfare Institution, Shanghai Jiao Tong University School of Medicine, 20030, Shanghai, China

    Lingna Zhong

  3. Department of Cardiology, Tongren Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200336, China

    Lei Song

  4. Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China

    Huan Zhang

Authors
  1. Zhengguang Xiao
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jingyu Zhong
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Lingna Zhong
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Shun Dai
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Wenjie Lu
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Lei Song
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Huan Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Jun Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Weiwu Yao
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to Jun Yang or Weiwu Yao.

Ethics declarations

Guarantor

The scientific guarantor of this publication is Prof. Weiwu Yao from the Department of Imaging, Tongren Hospital, Shanghai Jiao Tong University School of Medicine.

Conflict of interest

Jingyu Zhong is a member of European Radiology Scientific Editorial Board and has therefore not taken part in the review or selection process of this article. The remaining authors declare no conflicts of interest.

Statistics and biometry

No complex statistical methods were necessary for this paper.

Informed consent

Written informed consent was not required for this study because of the nature of our study, which was a systematic review and meta-analysis.

Ethical approval

Institutional review board approval was not required because of the nature of our study, which was a systematic review and meta-analysis.

Methodology

  • retrospective

  • diagnostic or prognostic study

  • multicenter study

Additional information

Publisher's note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Xiao, Z., Zhong, J., Zhong, L. et al. The prognostic value of myocardial salvage index by cardiac magnetic resonance in ST-segment elevation myocardial infarction patients: a systematic review and meta-analysis. Eur Radiol 33, 8214–8225 (2023). https://doi.org/10.1007/s00330-023-09739-1

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00330-023-09739-1

Keywords

Search

Navigation