Skip to main content

Advertisement

SpringerLink
Log in

Zebrafish larvae heartbeat detection from body deformation in low resolution and low frequency video

  • Original Article
  • Published:
Medical & Biological Engineering & Computing Aims and scope Submit manuscript

Abstract

Zebrafish (Danio rerio) is a powerful animal model used in many areas of genetics and disease research. Despite its advantages for cardiac research, the heartbeat pattern of zebrafish larvae under different stress conditions is not well documented quantitatively. Several effective automated heartbeat detection methods have been developed to reduce the workload for larva heartbeat analysis. However, most require complex experimental setups and necessitate direct observation of the larva heart. In this paper, we propose the Zebrafish Heart Rate Automatic Method (Z-HRAM), which detects and tracks the heartbeats of immobilized, ventrally positioned zebrafish larvae without direct larva heart observation. Z-HRAM tracks localized larva body deformation that is highly correlated with heart movement. Multiresolution dense optical flow-based motion tracking and principal component analysis are used to identify heartbeats. Here, we present results of Z-HRAM on estimating heart rate from video recordings of seizure-induced larvae, which were of low resolution (1024 × 760) and low frame rate (3 to 4 fps). Heartbeats detected from Z-HRAM were shown to correlate reliably with those determined through corresponding electrocardiogram and manual video inspection. We conclude that Z-HRAM is a robust, computationally efficient, and easily applicable tool for studying larva cardiac function in general laboratory conditions.

Flowchart of the automatic zebrafish heartbeat detection

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
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13

Similar content being viewed by others

References

  1. Afrikanova T, Serruys A-SK, Buenafe OEM, Clinckers R, Smolders I, de Witte PAM, Crawford AD, Esguerra CV (2013) Validation of the zebrafish pentylenetetrazol seizure model: locomotor versus electrographic responses to antiepileptic drugs. PLoS One 8:1–8. https://doi.org/10.1371/journal.pone.0054166

    Article  CAS  Google Scholar 

  2. Howe K, Clark MD, Torroja CF, Torrance J, Berthelot C, Muffato M, Collins JE, Humphray S, McLaren K, Matthews L, McLaren S, Sealy I, Caccamo M, Churcher C, Scott C, Barrett JC, Koch R, Rauch GJ, White S, Chow W, Kilian B, Quintais LT, Guerra-Assunção JA, Zhou Y, Gu Y, Yen J, Vogel JH, Eyre T, Redmond S, Banerjee R, Chi J, Fu B, Langley E, Maguire SF, Laird GK, Lloyd D, Kenyon E, Donaldson S, Sehra H, Almeida-King J, Loveland J, Trevanion S, Jones M, Quail M, Willey D, Hunt A, Burton J, Sims S, McLay K, Plumb B, Davis J, Clee C, Oliver K, Clark R, Riddle C, Elliot D, Threadgold G, Harden G, Ware D, Begum S, Mortimore B, Kerry G, Heath P, Phillimore B, Tracey A, Corby N, Dunn M, Johnson C, Wood J, Clark S, Pelan S, Griffiths G, Smith M, Glithero R, Howden P, Barker N, Lloyd C, Stevens C, Harley J, Holt K, Panagiotidis G, Lovell J, Beasley H, Henderson C, Gordon D, Auger K, Wright D, Collins J, Raisen C, Dyer L, Leung K, Robertson L, Ambridge K, Leongamornlert D, McGuire S, Gilderthorp R, Griffiths C, Manthravadi D, Nichol S, Barker G, Whitehead S, Kay M, Brown J, Murnane C, Gray E, Humphries M, Sycamore N, Barker D, Saunders D, Wallis J, Babbage A, Hammond S, Mashreghi-Mohammadi M, Barr L, Martin S, Wray P, Ellington A, Matthews N, Ellwood M, Woodmansey R, Clark G, Cooper J, Tromans A, Grafham D, Skuce C, Pandian R, Andrews R, Harrison E, Kimberley A, Garnett J, Fosker N, Hall R, Garner P, Kelly D, Bird C, Palmer S, Gehring I, Berger A, Dooley CM, Ersan-Ürün Z, Eser C, Geiger H, Geisler M, Karotki L, Kirn A, Konantz J, Konantz M, Oberländer M, Rudolph-Geiger S, Teucke M, Lanz C, Raddatz G, Osoegawa K, Zhu B, Rapp A, Widaa S, Langford C, Yang F, Schuster SC, Carter NP, Harrow J, Ning Z, Herrero J, Searle SM, Enright A, Geisler R, Plasterk RH, Lee C, Westerfield M, de Jong PJ, Zon LI, Postlethwait JH, Nüsslein-Volhard C, Hubbard TJ, Roest Crollius H, Rogers J, Stemple DL (2013) The zebrafish reference genome sequence and its relationship to the human genome. Nature 496:498–503. https://doi.org/10.1038/nature12111

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Lieschke GJ, Currie PD (2007) Animal models of human disease: zebrafish swim into view. Nat Rev Genet 8:353–367. https://doi.org/10.1038/nrg2091

    Article  CAS  PubMed  Google Scholar 

  4. Baraban SC, Taylor MR, Castro PA, Baier H (2005) Pentylenetetrazole induced changes in zebrafish behavior, neural activity and c-fos expression. Neuroscience 131:759–768. https://doi.org/10.1016/j.neuroscience.2004.11.031

    Article  CAS  PubMed  Google Scholar 

  5. De Luca E, Zaccaria GM, Hadhoud M et al (2014) ZebraBeat: a flexible platform for the analysis of the cardiac rate in zebrafish embryos. Sci Rep 4:1–13. https://doi.org/10.1038/srep04898

    Article  CAS  Google Scholar 

  6. Wilkinson RN, Jopling C, van Eeden FJ (2014) Zebrafish as a model of cardiac disease. Prog Mol Biol Transl Sci 124:65–91. https://doi.org/10.1016/B978-0-12-386930-2.00004-5

    Article  CAS  PubMed  Google Scholar 

  7. Singleman C, Holtzman NG (2012) Analysis of post-embryonic heart development and maturation in the zebrafish, Danio rerio. Dev Dyn Off Publ Am Assoc Anat 241:1993–2004. https://doi.org/10.1002/dvdy.23882

    Article  CAS  Google Scholar 

  8. Bakkers J (2011) Zebrafish as a model to study cardiac development and human cardiac disease. Cardiovasc Res 91:279–288. https://doi.org/10.1093/cvr/cvr098

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Milan DJ, Jones IL, Ellinor PT, MacRae CA (2006) In vivo recording of adult zebrafish electrocardiogram and assessment of drug-induced QT prolongation. Am J Physiol Heart Circ Physiol 291:H269–H273. https://doi.org/10.1152/ajpheart.00960.2005

    Article  CAS  PubMed  Google Scholar 

  10. Chan PK, Lin CC, Cheng SH (2009) Noninvasive technique for measurement of heartbeat regularity in zebrafish (Danio rerio) embryos. BMC Biotechnol 9:1–10. https://doi.org/10.1186/1472-6750-9-11

    Article  Google Scholar 

  11. Pylatiuk C, Sanchez D, Mikut R, Alshut R, Reischl M, Hirth S, Rottbauer W, Just S (2014) Automatic zebrafish heartbeat detection and analysis for zebrafish embryos. Zebrafish 11:379–383. https://doi.org/10.1089/zeb.2014.1002

    Article  PubMed  PubMed Central  Google Scholar 

  12. Balakrishnan G, Durand F, Guttag J (2013) Detecting pulse from head motions in video. IEEE Conf CVPR:3430–3437

  13. Westerfield M (2007) The zebrafish book. University of Oregon Press, Eugene

    Google Scholar 

  14. Kimmel CB, Ballard WW, Kimmel SR, Ullmann B, Schilling TF (1995) Stages of embryonic development of the zebrafish. Dev Dyn 203:253–310. https://doi.org/10.1002/aja.1002030302

    Article  CAS  PubMed  Google Scholar 

  15. Farnebäck G (2003) Two-frame motion estimation based on polynomial expansion. Proc SCIA’03:363–370

  16. Cho SJ, Byun D, Nam TS et al (2017) Zebrafish as an animal model in epilepsy studies with multichannel EEG recordings. Sci Rep 7:1–10. https://doi.org/10.1038/s41598-017-03482

    Article  Google Scholar 

  17. Robertson GN, McGee CA, Dumbarton TC et al (2007) Development of the swimbladder and its innervation in the zebrafish, Danio rerio. J Morphol 268:967–985. https://doi.org/10.1002/jmor.10558

    Article  CAS  PubMed  Google Scholar 

  18. Lee SJ, Park SH, Chung JF et al (2017) Homocysteine-induced peripheral microcirculation dysfunction in zebrafish and its attenuation by L-arginine. Oncotarget 8:58264–58271. https://doi.org/10.18632/oncotarget.1681

    Article  PubMed  PubMed Central  Google Scholar 

  19. Pu J, Zheng B, Leader JK, Gur D (2008) An ellipse-fitting based method for efficient registration of breast masses on two mammographic views. Med Phys 35:487–494. https://doi.org/10.1118/1.2828188

    Article  PubMed  Google Scholar 

  20. Sołtysiński T, Golnik A, Pałko T (2007) Comparison of multiscale entropy of healthy and cancer tissue imaged by optical polarimeter. Pol J Med Phys Eng 13:65–78. https://doi.org/10.2478/v10013-007-0006-5

    Article  Google Scholar 

  21. Bouguet J (2000) Pyramidal implementation of the Lucas Kanade feature tracker. Intel Corp Microprocess Res Labs. Avaliable via CiteSeer. http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.185.585

  22. Sołtysiński T (2006) Bayesian constrained spectral method for segmentation of noisy medical images. Theory and applications. Studies in Computational Intelligence 107:181–206. https://doi.org/10.1007/978-3-540-77662-8_8

    Article  Google Scholar 

  23. Sołtysiński T (2008) Novel quantitative method for spleen’s morphometry in splenomegaly. In: Artificial Intelligence and Soft Computing-ICAISC 2008, vol 5097, pp 981–991. https://doi.org/10.1007/978-3-540-69731-2_93

    Chapter  Google Scholar 

  24. Sołtysiński T, Kałużynski K, Pałko T (2006) Cardiac ventricle contour reconstruction in ultrasonographic images using Bayesian constrained spectral method. In: Artificial Intelligence and Soft Computing-ICAISC 2006, vol 4029, pp 988–997. https://doi.org/10.1007/11785231_104

    Chapter  Google Scholar 

Download references

Acknowledgements

We would like to thank Cristhian Perez for use of his software in filtering our electrocardiogram data, and Stephan Seo and Neil Jacob for data processing.

Funding

This study was funded by the Foundation for Research of the State of Sao Paulo, Brazil (grant: FAPESP 14/15640-8) and the Brazilian Institute of Neuroscience and Neurotechnology (grant: CEPID-BRAINN 13/07559-3). We are also grateful for the financial assistance provided by the George Mason University Department of Bioengineering and George Mason University Office of Student Scholarship, Creative Activities, and Research (OSCAR).

Author information

Authors and Affiliations

  1. Department of Computer Science, George Mason University, Fairfax, VA, USA

    Qi Xing

  2. Bioengineering Department, George Mason University, Fairfax, VA, USA

    Victor Huynh & Qi Wei

  3. Department of Medical Genetics, School of Medical Sciences, University of Campinas, Campinas, Brazil

    Thales Guimaraes Parolari & Claudia Vianna Maurer-Morelli

  4. Electrical & Computer Engineering Department, Fairfax, VA, USA

    Nathalia Peixoto

Authors
  1. Qi Xing
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Victor Huynh
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Thales Guimaraes Parolari
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Claudia Vianna Maurer-Morelli
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Nathalia Peixoto
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Qi Wei
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Qi Wei.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Research involving animals

This article contains studies with animals performed by some of the authors and approved by the Animal Care and Use Committee of University of Campinas, as stated within the manuscript.

Informed consent

No human subjects studies were performed for this manuscript.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Xing, Q., Huynh, V., Parolari, T.G. et al. Zebrafish larvae heartbeat detection from body deformation in low resolution and low frequency video. Med Biol Eng Comput 56, 2353–2365 (2018). https://doi.org/10.1007/s11517-018-1863-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11517-018-1863-7

Keywords

Search

Navigation