Skip to main content

Four-dimensional virtual reality cine cardiac models using free open-source software


This is a proof-of-concept study to create a four-dimensional (4-D) cine model of the heart and visualize it in virtual reality by using freely available open-source software and inexpensive hardware. Four-dimensional cine models allow for real-time visualization of cardiac structures during processes such as complex congenital heart disease. Such models can be used for patient and trainee education, and potentially for surgical planning. Currently, 3-D printed models are more commonly used, but they are static, showing only one selected phase of the cardiac cycle. Second, they are limited by the selection of clipping planes before printing. Four-dimensional segmentation and virtual reality visualization overcome these limitations. Currently, most of the work in virtual/augmented reality models involves the segmentation of one cardiac phase or the use of expensive software for multiphase segmentation. In this study, we show an approach for multiphase cardiac segmentation as well as its display using free open-source software and relatively inexpensive hardware.

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6


  1. 1.

    Smerling J, Marboe CC, Lefkowitch JH et al (2019) Utility of 3D printed cardiac models for medical student education in congenital heart disease: across a spectrum of disease severity. Pediatr Cardiol 40:1258–1265

    Article  Google Scholar 

  2. 2.

    Anwar S, Singh GK, Miller J et al (2018) 3D printing is a transformative technology in congenital heart disease. JACC Basic Transl Sci 3:294–312

    Article  Google Scholar 

  3. 3.

    Ong CS, Krishnan A, Huang CY et al (2018) Role of virtual reality in congenital heart disease. Congenit Heart Dis 13:357–361

    Article  Google Scholar 

  4. 4.

    Hadeed K, Acar P, Dulac Y et al (2018) Cardiac 3D printing for better understanding of congenital heart disease. Arch Cardiovasc Dis 111:1–4

    Article  Google Scholar 

  5. 5.

    Silva JNA, Southworth M, Raptis C, Silva J (2018) Emerging applications of virtual reality in cardiovascular medicine. JACC Basic Transl Sci 3:420–430

    Article  Google Scholar 

  6. 6.

    Pottle J (2019) Virtual reality and the transformation of medical education. Future Healthc J 6:181–185

    Article  Google Scholar 

  7. 7.

    Southworth MK, Silva JR, Silva JNA (2020) Use of extended realities in cardiology. Trends Cardiovasc Med 30:143–148

    Article  Google Scholar 

  8. 8.

    Priya S, Nagpal P, Sharma A et al (2019) Imaging spectrum of double-outlet right ventricle on multislice computed tomography. J Thorac Imaging 34:W89–W99

    Article  Google Scholar 

  9. 9.

    Brun H, Bugge RAB, Suther LKR et al (2019) Mixed reality holograms for heart surgery planning: first user experience in congenital heart disease. Eur Heart J Cardiovasc Imaging 20:883–888

    CAS  Article  Google Scholar 

  10. 10.

    Fedorov A, Beichel R, Kalpathy-Cramer J et al (2012) 3D slicer as an image computing platform for the quantitative imaging network. Magn Reson Imaging 30:1323–1341

    Article  Google Scholar 

  11. 11.

    (2020) Slicer user recommendations. Documentation/4.8/SlicerApplication/HardwareConfiguration. Accessed 29 May 2020

  12. 12.

    Ginty OK, Moore JT, Eskandari M et al (2019) Dynamic, patient-specific mitral valve modelling for planning transcatheter repairs. Int J Comput Assist Radiol Surg 14:1227–1235

    Article  Google Scholar 

  13. 13.

    Sutherland J, Belec J, Sheikh A et al (2019) Applying modern virtual and augmented reality technologies to medical images and models. J Digit Imaging 32:38–53

    Article  Google Scholar 

  14. 14.

    Weech S, Kenny S, Barnett-Cowan M (2019) Presence and cybersickness in virtual reality are negatively related: a review. Front Psychol 10:158

    Article  Google Scholar 

  15. 15.

    Becker J, Ngo T (2016) Mitigating visually-induced motion sickness in virtual reality. Stanford University. Accessed 29 May 2020

  16. 16.

    Nie GY, Duh HB, Liu Y, Wang Y (2019) Analysis on mitigation of visually induced motion sickness by applying dynamical blurring on a user's retina. IEEE Trans Vis Comput Graph.

Download references

Author information



Corresponding author

Correspondence to Sarv Priya.

Ethics declarations

Conflicts of interest


Additional information

Publisher’s note

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

Electronic supplementary material

Online Supplementary Material 1

Step-by-step approach for multi-phase cardiac segmentation and visualization (PDF 1724 kb)

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Priya, S., Nagpal, P. Four-dimensional virtual reality cine cardiac models using free open-source software. Pediatr Radiol 50, 1617–1623 (2020).

Download citation


  • Augmented reality
  • Children
  • Congenital heart disease
  • Dynamic cine cardiac model
  • Four-dimensional models
  • Heart
  • Three-dimensional printing
  • Virtual reality