Skip to main content
SpringerLink
Log in

Comparison of left ventricular manual versus automated derived longitudinal strain: implications for clinical practice and research

  • Original Paper
  • Published:
The International Journal of Cardiovascular Imaging Aims and scope Submit manuscript

Abstract

Systolic global longitudinal strain (GLS) is emerging as a useful metric of ventricular function in heart failure and usually assessed using post-processing software. The purpose of this study was to investigate whether longitudinal strain (LS) derived using manual-tracings of ventricular lengths (manual-LS) can be reliable and time efficient when compared to LS obtained by post-processing software (software-LS). Apical 4-chamber view images were retrospectively examined in 50 healthy controls, 100 patients with dilated cardiomyopathy (DCM), and 100 with hypertrophic cardiomyopathy (HCM). We measured endocardial and mid-wall manual-LS and software-LS, using peak of average regional curve [software-LS(a)] and global ventricular lengths [software-LS(l)] according to definition of Lagragian strain. We compared manual-LS and software-LS by using Bland–Altman plot and coefficient of variation (COV). In addition, test–retest was also performed for further assessment of variability in measurements. While manual-LS was obtained in all subjects, software-LS could be obtained in 238 subjects (95 %). The time spent for obtaining manual-LS was significantly shorter than for the software-LS (94 ± 39 s vs. 141 ± 79 s, P < 0.001). Overall, manual-LS had an excellent correlation with both software-LS (a) (R2 = 0.93, P < 0.001) and software-LS(l) (R2 = 0.84, P < 0.001). The bias (95 %CI) between endocardial manual-LS and software-LS(a) was 0.4 % [−2.8, 3.6 %] in absolute and 3.5 % [−17.0, 24.0 %] in relative difference while it was 0.4 % [−2.5, 3.3 %] and 3.4 % [−16.2, 23.1 %], respectively with software-LS(l). Mid-wall manual-LS and mid-wall software-LS(a) also had good agreement [a bias (95 % CI) for absolute value of 0.1 % [−2.1, 2.5 %] in HCM, and 0.2 % [−2.2, 2.6 %] in controls]. The COV for manual and software derived LS were below 6 %. Test–retest showed good variability for both methods (COVs were 5.8 and 4.7 for endocardial and mid-wall manual-LS, and 4.6 and 4.9 for endocardial and mid-wall software-LS(a), respectively. Manual-LS appears to be as reproducible as software-LS; this may be of value especially when global strain is the metric of interest.

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
Fig. 5

Similar content being viewed by others

Abbreviations

COV:

Coefficient of variation

DCM:

Dilated cardiomyopathy

EF:

Ejection fraction

HCM:

Hypertrophic cardiomyopathy

LS:

Longitudinal strain

LV:

Left ventricular

LVEDV:

Left ventricular end-diastolic volume

LVESV:

Left ventricular end-systolic volume

References

  1. Dumesnil JG, Shoucri RM, Laurenceau JL, Turcot J (1979) A mathematical model of the dynamic geometry of the intact left ventricle and its application to clinical data. Circulation 59:1024–1034

    Article  CAS  PubMed  Google Scholar 

  2. Mor-Avi V, Lang RM, Badano LP et al (2011) Current and evolving echocardiographic techniques for the quantitative evaluation of cardiac mechanics: ASE/EAE consensus statement on methodology and indications endorsed by the Japanese Society of Echocardiography. J Am Soc Echocardiogr 24:277–313

    Article  PubMed  Google Scholar 

  3. Voigt JU, Pedrizzetti G, Lysyansky P et al (2015) Definitions for a common standard for 2D speckle tracking echocardiography: consensus document of the EACVI/ASE/industry task force to standardize deformation imaging. J Am Soc Echocardiogr 28:183–193

    Article  PubMed  Google Scholar 

  4. Nagata Y, Takeuchi M, Mizukoshi K et al (2015) Intervendor variability of two-dimensional strain using vendor-specific and vendor-independent software. J Am Soc Echocardiogr 28:630–641

    Article  PubMed  Google Scholar 

  5. Yang H, Marwick TH, Fukuda N et al (2015) Improvement in strain concordance between two major vendors after the strain standardization initiative. J Am Soc Echocardiogr 28(642–8):e7

    PubMed  Google Scholar 

  6. Thomas JD (2015) Strain imaging in echocardiography: converging on congruence? J Am Soc Echocardiogr 28:649–651

    Article  PubMed  Google Scholar 

  7. Risum N, Ali S, Olsen NT et al (2012) Variability of global left ventricular deformation analysis using vendor dependent and independent two-dimensional speckle-tracking software in adults. J Am Soc Echocardiogr y 25:1195–1203

    Article  Google Scholar 

  8. Saito M, Negishi K, Eskandari M et al (2015) Association of left ventricular strain with 30-day mortality and readmission in patients with heart failure. J Am Soc Echocardiogr 28:652–666

    Article  PubMed  Google Scholar 

  9. Dahou A, Bartko PE, Capoulade R et al (2015) Usefulness of global left ventricular longitudinal strain for risk stratification in low ejection fraction, low-gradient aortic stenosis: results from the multicenter True or Pseudo-Severe Aortic Stenosis study. Circ Cardiovasc Imaging 8:e002117

    Article  PubMed  Google Scholar 

  10. Yoshikawa H, Suzuki M, Hashimoto G et al (2012) Midwall ejection fraction for assessing systolic performance of the hypertrophic left ventricle. Cardiovas ultrasound 10:45

    Article  Google Scholar 

  11. Jung HO, Sheehan FH, Bolson EL, Waiss MP, Otto CM (2006) Evaluation of midwall systolic function in left ventricular hypertrophy: a comparison of 3-dimensional versus 2-dimensional echocardiographic indices. J Am Soc Echocardiogr 19:802–810

    Article  PubMed  Google Scholar 

  12. Carasso S, Yang H, Woo A et al (2008) Systolic myocardial mechanics in hypertrophic cardiomyopathy: novel concepts and implications for clinical status. J Am Soc Echocardiogr 21:675–683

    Article  PubMed  Google Scholar 

  13. Lang RM, Badano LP, Mor-Avi V et al (2015) Recommendations for cardiac chamber quantification by echocardiography in adults: an update from the American society of echocardiography and the European association of cardiovascular imaging. J Am Soc Echocardiogr 28(1–39):e14

    PubMed  Google Scholar 

  14. Rogers WJ Jr, Shapiro EP, Weiss JL et al (1991) Quantification of and correction for left ventricular systolic long-axis shortening by magnetic resonance tissue tagging and slice isolation. Circulation 84:721–731

    Article  PubMed  Google Scholar 

  15. Bland JM, Altman DG (1986) Statistical methods for assessing agreement between two methods of clinical measurement. Lancet 1:307–310

    Article  CAS  PubMed  Google Scholar 

  16. Geyer H, Caracciolo G, Abe H et al (2010) Assessment of myocardial mechanics using speckle tracking echocardiography: fundamentals and clinical applications. J Am Soc Echocardiogr 23:351–369 (quiz 453-5)

    Article  PubMed  Google Scholar 

  17. Mondillo S, Galderisi M, Mele D et al (2011) Speckle-tracking echocardiography: a new technique for assessing myocardial function. J Ultrasound Med 30:71–83

    PubMed  Google Scholar 

  18. Biaggi P, Carasso S, Garceau P et al (2011) Comparison of two different speckle tracking software systems: does the method matter? Echocardiography 28:539–547

    Article  PubMed  Google Scholar 

  19. Manovel A, Dawson D, Smith B, Nihoyannopoulos P (2010) Assessment of left ventricular function by different speckle-tracking software. Eur J Echocardiogr 11:417–421

    Article  PubMed  Google Scholar 

  20. Jasaityte R, Heyde B, D’Hooge J (2013) Current state of three-dimensional myocardial strain estimation using echocardiography. J Am Soc Echocardiogr 26:15–28

    Article  PubMed  Google Scholar 

  21. Palmiero P, Maiello M, Nanda NC (2008) Is echo-determined left ventricular geometry associated with ventricular filling and midwall shortening in hypertensive ventricular hypertrophy? Echocardiography 25:20–26

    PubMed  Google Scholar 

Download references

Acknowledgments

We want to thank the Stanford Cardiovascular Institute as well as the Pai Chan Lee Research Fund for their support.

Author information

Author notes

    Authors and Affiliations

    1. Division of Cardiovascular Medicine, Stanford University School of Medicine, 300 Pasteur Drive Room H2170, Stanford, CA, 94305, USA

      Yukari Kobayashi, Miyuki Ariyama, Yuhei Kobayashi, Genevieve Giraldeau, Dominik Fleischman, Mirta Kozelj, Bojan Vrtovec, Euan Ashley, Ingela Schnittger, David Liang & Francois Haddad

    2. Stanford Cardiovascular Institute, Stanford, CA, USA

      Yukari Kobayashi, Miyuki Ariyama, Yuhei Kobayashi, Genevieve Giraldeau, Dominik Fleischman, Mirta Kozelj, Bojan Vrtovec, Euan Ashley, Tatiana Kuznetsova, Ingela Schnittger, David Liang & Francois Haddad

    3. Research Unit Hypertension and Cardiovascular Epidemiology, KU Leuven Department of Cardiovascular Sciences, University of Leuven, Louvain, Belgium

      Tatiana Kuznetsova

    Authors
    1. Yukari Kobayashi
      View author publications

      You can also search for this author in PubMed Google Scholar

    2. Miyuki Ariyama
      View author publications

      You can also search for this author in PubMed Google Scholar

    3. Yuhei Kobayashi
      View author publications

      You can also search for this author in PubMed Google Scholar

    4. Genevieve Giraldeau
      View author publications

      You can also search for this author in PubMed Google Scholar

    5. Dominik Fleischman
      View author publications

      You can also search for this author in PubMed Google Scholar

    6. Mirta Kozelj
      View author publications

      You can also search for this author in PubMed Google Scholar

    7. Bojan Vrtovec
      View author publications

      You can also search for this author in PubMed Google Scholar

    8. Euan Ashley
      View author publications

      You can also search for this author in PubMed Google Scholar

    9. Tatiana Kuznetsova
      View author publications

      You can also search for this author in PubMed Google Scholar

    10. Ingela Schnittger
      View author publications

      You can also search for this author in PubMed Google Scholar

    11. David Liang
      View author publications

      You can also search for this author in PubMed Google Scholar

    12. Francois Haddad
      View author publications

      You can also search for this author in PubMed Google Scholar

    Corresponding author

    Correspondence to Yukari Kobayashi.

    Ethics declarations

    Conflict of interest

    None.

    Additional information

    David Liang and Francois Haddad have equally contributed to mentoring the project and are equivalent last authors.

    Rights and permissions

    Reprints and permissions

    About this article

    Check for updates. Verify currency and authenticity via CrossMark

    Cite this article

    Kobayashi, Y., Ariyama, M., Kobayashi, Y. et al. Comparison of left ventricular manual versus automated derived longitudinal strain: implications for clinical practice and research. Int J Cardiovasc Imaging 32, 429–437 (2016). https://doi.org/10.1007/s10554-015-0804-x

    Download citation

    • Received:

    • Accepted:

    • Published:

    • Issue Date:

    • DOI: https://doi.org/10.1007/s10554-015-0804-x

    Keywords

    Search

    Navigation