Quantification of intramyocardial hemorrhage volume using magnetic resonance imaging with three-dimensional T1-weighted sequence in patients with ischemia-reperfusion injury: a semi-automated image processing technique

  • Hideo Arai
  • Masateru KawakuboEmail author
  • Ko Abe
  • Hikaru Hatashima
  • Kenichi Sanui
  • Hiroshi Nishimura
  • Toshiaki Kadokami
Original Paper


Although intramyocardial hemorrhage (IMH) is a poor prognostic factor caused by ischemia reperfusion injury, little evidence is available regarding the association between IMH volume and biomarkers. In the present study, we measured IMH volume using three-dimensional (3D) T1-weighted magnetic resonance imaging (T1-MRI) and investigated its association with biomarkers. Moreover, the accuracy of semi-automatic measurement of IMH volume was validated. We retrospectively enrolled 33 consecutive patients (mean age 67 ± 11 years) who underwent cardiac MRI after reperfusion therapy for acute myocardial infarction. IMH was observed in 4 patients (12.1%). Receiver operating characteristics (ROC) analysis of creatine kinase (CK) and CK-muscle/brain (CK-MB) tests for detecting IMH were performed. IMH volume measured using semi-automatic methods by a 2 standard deviation (SD) threshold was compared to manual measurements using the Spearman’s correlation coefficient (ρ) and Bland–Altman analyses. ROC analysis revealed optimal cutoff values of CK: 2460 IU/l and CK-MB: 231 IU/l (area under the curve: 0.95 and 0.91; sensitivity: 86% and 79%; specificity: 100% for both). IMH volume with the 2SD threshold correlated with that of the manual measurement [5.84 g (3.30 to 9.00) g vs. 8.07 g (5.37 to 9.33); ρ: 0.85, p < 0.01; bias (limit of agreement): − 0.01 g (− 0.51 to 0.49); intraclass correlation coefficients 0.84 (0.75 to 0.90)]. Our findings could help identify the risk of IMH after reperfusion therapy with biomarkers. 3D T1-MRI can semi-automatically provide accurate IMH volume without being time-consuming.


Intramyocardial hemorrhage Biomarker Quantification Semi-automated threshold method Magnetic resonance imaging Acute myocardial infarction 



This work was supported by The Japanese Circulation Society (JCS) Grant for medical technologists in 2017.

Compliance with ethical standards

Conflict of interest

All the authors declares that they have no conflict of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. The study was approved by the institutional review board, and the requirement for patient consent was waived. An online provision, on the hospital homepage, was prospectively made available to the patients for opting out of the study.


  1. 1.
    Puymirat E, Simon T, Cayla G et al (2017) Acute myocardial infarction: changes in patient characteristics, management, and 6-month outcomes over a period of 20 years in the FAST-MI program (French registry of acute ST-elevation or non-ST-elevation myocardial infarction) 1995 to 2015. Circulation 136:1908–1919. CrossRefPubMedGoogle Scholar
  2. 2.
    Niccoli G, Burzotta F, Galiuto L, Crea F (2009) Myocardial no-reflow in humans. J Am Coll Cardiol 54:281–292. CrossRefPubMedGoogle Scholar
  3. 3.
    Turer AT, Hill JA (2010) Pathogenesis of myocardial ischemia-reperfusion injury and rationale for therapy. Am J Cardiol 106:360–368. CrossRefPubMedPubMedCentralGoogle Scholar
  4. 4.
    Heusch G (2015) Treatment of myocardial ischemia/reperfusion injury by ischemic and pharmacological postconditioning. Compr Physiol 5:1123–1145CrossRefPubMedGoogle Scholar
  5. 5.
    Hausenloy DJ, Yellon DM (2013) Myocardial ischemia-reperfusion injury: a neglected therapeutic target. J Clin Invest 123:92–100. CrossRefPubMedPubMedCentralGoogle Scholar
  6. 6.
    Ganame J, Messalli G, Dymarkowski S et al (2009) Impact of myocardial haemorrhage on left ventricular function and remodelling in patients with reperfused acute myocardial infarction. Eur Heart J 30:1440–1449. CrossRefPubMedGoogle Scholar
  7. 7.
    Hamirani YS, Wong A, Kramer CM, Salerno M (2014) Effect of microvascular obstruction and intramyocardial hemorrhage by CMR on LV remodeling and outcomes after myocardial infarction: a systematic review and meta-analysis. JACC Cardiovasc Imaging 7:940–952. CrossRefPubMedPubMedCentralGoogle Scholar
  8. 8.
    Calvieri C, Masselli G, Monti R et al (2015) Intramyocardial hemorrhage: an enigma for cardiac MRI? Biomed Res Int. CrossRefPubMedPubMedCentralGoogle Scholar
  9. 9.
    Penttilä I, Penttilä K, Rantanen T (2000) Laboratory diagnosis of patients with acute chest pain. Clin Chem Lab Med 38:187–197CrossRefPubMedGoogle Scholar
  10. 10.
    Kali A, Tang RL, Kumar A et al (2013) Detection of acute reperfusion myocardial hemorrhage with cardiac MR imaging: t2 versus T2. Radiology 269:387–395. CrossRefPubMedPubMedCentralGoogle Scholar
  11. 11.
    Mather AN, Fairbairn TA, Ball SG et al (2011) Reperfusion haemorrhage as determined by cardiovascular MRI is a predictor of adverse left ventricular remodelling and markers of late arrhythmic risk. Heart 97:453–459. CrossRefPubMedGoogle Scholar
  12. 12.
    Pedersen SF, Thrysøe SA, Robich MP et al (2012) Assessment of intramyocardial hemorrhage by T1-weighted cardiovascular magnetic resonance in reperfused acute myocardial infarction. J Cardiovasc Magn Reson 14:1–8. CrossRefGoogle Scholar
  13. 13.
    Kim RJ, Wu E, Rafael A, Chen EL, Parker MA, Simonetti O, Klocke FJ, Bonow ROJR (2000) The use of contrast-enhanced magnetic resonance imaging to identify reversible myocardial dysfunction. N Engl J Med 343:1445–1453CrossRefPubMedGoogle Scholar
  14. 14.
    Ganesan AN, Gunton J, Nucifora G et al (2018) Impact of Late Gadolinium Enhancement on mortality, sudden death and major adverse cardiovascular events in ischemic and nonischemic cardiomyopathy: a systematic review and meta-analysis. Int J Cardiol 254:230–237. CrossRefPubMedGoogle Scholar
  15. 15.
    Vermes E, Childs H, Carbone I et al (2013) Auto-threshold quantification of late gadolinium enhancement in patients with acute heart disease. J Magn Reson Imaging 37:382–390. CrossRefPubMedGoogle Scholar
  16. 16.
    Baron N, Kachenoura N, Cluzel P et al (2013) Comparison of various methods for quantitative evaluation of myocardial infarct volume from magnetic resonance delayed enhancement data. Int J Cardiol 167:739–744. CrossRefPubMedGoogle Scholar
  17. 17.
    McAlindon E, Pufulete M, Lawton C et al (2015) Quantification of infarct size and myocardium at risk: evaluation of different techniques and its implications. Eur Hear J Cardiovasc Imaging 16:738–746. CrossRefGoogle Scholar
  18. 18.
    Otsu N (1979) A threshold selection method from gray-level histograms. IEEE Trans Syst Man Cybern 9:62–66. CrossRefGoogle Scholar
  19. 19.
    Kanda Y (2013) Investigation of the freely available easy-to-use software “EZR” for medical statistics. Bone Marrow Transpl 48:452–458. CrossRefGoogle Scholar
  20. 20.
    Miyachi H, Takagi A, Miyauchi K et al (2016) Current characteristics and management of ST elevation and non-ST elevation myocardial infarction in the Tokyo metropolitan area: from the Tokyo CCU network registered cohort. Heart Vessel 31:1740–1751. CrossRefGoogle Scholar
  21. 21.
    Kim MK, Chung WY, Cho YS et al (2011) Serum N-terminal pro-B-type natriuretic peptide levels at the time of hospital admission predict of microvascular obstructions after primary percutaneous coronary intervention for acute ST-segment elevation myocardial infarction. J Interv Cardiol 24:34–41. CrossRefPubMedGoogle Scholar
  22. 22.
    Cuenin L, Lamoureux S, Schaaf M et al (2017) Incidence and significance of spontaneous ST segment re-elevation after reperfused anterior acute myocardial infarction—relationship with infarct size, adverse remodeling, and events at 1 year. Circ J 82:1379–1386. CrossRefPubMedGoogle Scholar
  23. 23.
    Nagao M, Higashino H, Matsuoka H et al (2008) Clinical importance of microvascular obstruction on contrast-enhanced MRI in reperfused acute myocardial infarction. Circ J 72:200–204. CrossRefPubMedGoogle Scholar
  24. 24.
    Bekkers SC, Yazdani SK, Virmani R, Waltenberger J (2010) Microvascular obstruction. J Am Coll Cardiol 55:1649–1660. CrossRefPubMedGoogle Scholar
  25. 25.
    Bulluck H, Rosmini S, Abdel-Gadir A et al (2016) Residual myocardial iron following intramyocardial hemorrhage during the convalescent phase of reperfused ST-segment-elevation myocardial infarction and adverse left ventricular remodeling. Circ Cardiovasc Imaging. CrossRefPubMedPubMedCentralGoogle Scholar
  26. 26.
    Min P-K, Chung H, Park CH et al (2013) Correction with blood T1 is essential when measuring post-contrast myocardial T1 value in patients with acute myocardial infarction. J Cardiovasc Magn Reson 15:1. CrossRefGoogle Scholar
  27. 27.
    Van Den Bos EJ, Baks T, Moelker AD et al (2006) Magnetic resonance imaging of haemorrhage within reperfused myocardial infarcts: possible interference with iron oxide-labelled cell tracking? Eur Heart J 27:1620–1626. CrossRefPubMedGoogle Scholar

Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  1. 1.Fukuokaken Saiseikai Futsukaichi HospitalFukuokaJapan
  2. 2.Department of Health Sciences, Faculty of Medical SciencesKyushu UniversityFukuokaJapan
  3. 3.Oita Prefectural HospitalOitaJapan

Personalised recommendations