Skip to main content
SpringerLink
Log in

Model checking for trigger loss detection during Doppler ultrasound-guided fetal cardiovascular MRI

  • Review Article
  • Published:
International Journal of Computer Assisted Radiology and Surgery Aims and scope Submit manuscript

Abstract

Purpose

Ultrasound (US) is the state of the art in prenatal diagnosis to depict fetal heart diseases. Cardiovascular magnetic resonance imaging (CMRI) has been proposed as a complementary diagnostic tool. Currently, only trigger-based methods allow the temporal and spatial resolutions necessary to depict the heart over time. Of these methods, only Doppler US (DUS)-based triggering is usable with higher field strengths. DUS is sensitive to motion. This may lead to signal and, ultimately, trigger loss. If too many triggers are lost, the image acquisition is stopped, resulting in a failed imaging sequence. Moreover, losing triggers may prolong image acquisition. Hence, if no actual trigger can be found, injected triggers are added to the signal based on the trigger history.

Method

We use model checking, a technique originating from the computer science domain that formally checks if a model satisfies given requirements, to simultaneously model heart and respiratory motion and to decide whether respiration has a prominent effect on the signal. Using bounds on the physiological parameters and their variability, the method detects when changes in the signal are due to respiration. We use this to decide when to inject a trigger.

Results

In a real-world scenario, we can reduce the number of falsely injected triggers by 94% from more than 87% to less than 5%. On a subset of motion that would allow CMRI, the number can be further reduced to below 0.2%. In a study using simulations with a robot, we show that our method works for different types of motions, motion ranges, starting positions and heartbeat traces.

Conclusion

While DUS is a promising approach for fetal CMRI, correct trigger injection is critical. Our model checking method can reduce the number of wrongly injected triggers substantially, providing a key prerequisite for fast and artifact free CMRI.

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

Similar content being viewed by others

References

  1. Alnuaimi SA, Jimaa S, Khandoker AH (2017) Fetal cardiac doppler signal processing techniques: challenges and future research directions. Front Bioeng Biotechnol 5:82

    Article  PubMed  PubMed Central  Google Scholar 

  2. Alur R, Dill DL (1994) A theory of timed automata. Theor Comput Sci 126(2):183–235

    Article  Google Scholar 

  3. Antoni ST, Rinast J, Ma X, Schupp S, Schlaefer A (2016) Online model checking for monitoring surrogate-based respiratory motion tracking in radiation therapy. Int J Comput Assist Radiol Surg 11(11):2085–2096

    Article  PubMed  Google Scholar 

  4. Baier C, Katoen JP (2008) Principles of model checking. The MIT Press, London

    Google Scholar 

  5. Cimatti A (2001) Industrial applications of model checking. Springer, Berlin, pp 153–168

    Google Scholar 

  6. Dürichen R, Wissel T, Ernst F, Schlaefer A, Schweikard A (2014) Multivariate respiratory motion prediction. Phys Med Biol 59(20):6043–6060

    Article  PubMed  Google Scholar 

  7. Ernst F (2012) Compensating for quasi-periodic motion in robotic radiosurgery. Springer, New York

    Book  Google Scholar 

  8. Ferreira PF, Gatehouse PD, Mohiaddin RH, Firmin DN (2013) Cardiovascular magnetic resonance artefacts. J Cardiovasc Magn Reson 15(1):41

    Article  PubMed  PubMed Central  Google Scholar 

  9. Firpo C, Hoffman JI, Silverman NH (2001) Evaluation of fetal heart dimensions from 12 weeks to term. Am J Cardiol 87(5):594–600

    Article  CAS  PubMed  Google Scholar 

  10. Frauenrath T, Hezel F, Renz W, d’Orth TdG, Dieringer M, von Knobelsdorff-Brenkenhoff F, Prothmann M, Schulz Menger J, Niendorf T (2010) Acoustic cardiac triggering: a practical solution for synchronization and gating of cardiovascular magnetic resonance at 7 Tesla. J Cardiovasc Magn Reson 12:67

    Article  PubMed  PubMed Central  Google Scholar 

  11. Hornberger LK, Sahn DJ (2007) Rhythm abnormalities of the fetus. Heart (Br Card Soc) 93(10):1294–1300

    Article  Google Scholar 

  12. Jansz MS, Seed M, van Amerom JFP, Wong D, Grosse-Wortmann L, Yoo SJ, Macgowan CK (2010) Metric optimized gating for fetal cardiac MRI. Magn Reson Med 64(5):1304–1314

    Article  PubMed  Google Scholar 

  13. Kording F, Ruprecht C, Schoennagel B, Fehrs K, Yamamura J, Adam G, Goebel J, Nassenstein K, Maderwald S, Quick HH, Kraff O (2017) Doppler ultrasound triggering for cardiac MRI at 7T. Magn Reson Med 74:1291

    Google Scholar 

  14. Kording F, Tavares de Sousa M, Yamamura J, Kladeck M, Gerhard A, Ruprecht C, Schoennagel B (2016) Funktionelle fetale kardiale MRT Bildgebung basierend auf Doppler-Ultraschall: Erste Erfahrungen. Fortschr Röntgenstr 188(S 01):RK205\_2

    Google Scholar 

  15. Nacif MS, Zavodni A, Kawel N, Choi EY, Lima JAC, Bluemke DA (2012) Cardiac magnetic resonance imaging and its electrocardiographs (ECG): tips and tricks. Int J Cardiovasc Imaging 28(6):1465–1475

    Article  PubMed  Google Scholar 

  16. Paley MNJ, Morris JE, Jarvis D, Griffiths PD (2013) Fetal electrocardiogram (fECG) gated MRI. Sensors (Basel, Switzerland) 13(9):11,271–11,279

    Article  Google Scholar 

  17. Seeger A, Fenchel MC, Greil GF, Martirosian P, Kramer U, Bretschneider C, Doering J, Claussen CD, Sieverding L, Miller S (2009) Three-dimensional cine MRI in free-breathing infants and children with congenital heart disease. Pediatr Radiol 39(12):1333–1342

    Article  PubMed  Google Scholar 

  18. Sievers B, Wiesner M, Kiria N, Speiser U, Schoen S, Strasser RH (2011) Influence of the trigger technique on ventricular function measurements using 3-Tesla magnetic resonance imaging: comparison of ECG versus pulse wave triggering. Acta Radiol (Stockholm, Sweden: 1987) 52(4):385–392

    Google Scholar 

  19. Untenberger M, Tan Z, Voit D, Joseph AA, Roeloffs V, Merboldt KD, Schätz S, Frahm J (2016) Advances in real-time phase-contrast flow MRI using asymmetric radial gradient echoes. Magn Reson Med 75(5):1901–1908

    Article  CAS  PubMed  Google Scholar 

  20. van Amerom JFP, Lloyd DFA, Price AN, Kuklisova Murgasova M, Aljabar P, Malik SJ, Lohezic M, Rutherford MA, Pushparajah K, Razavi R, Hajnal JV (2018) Fetal cardiac cine imaging using highly accelerated dynamic MRI with retrospective motion correction and outlier rejection. Magn Reson Med 79(1):327–338

    Article  PubMed  Google Scholar 

  21. Yamamura J, Kopp I, Frisch M, Fischer R, Valett K, Hecher K, Adam G, Wedegartner U (2012) Cardiac MRI of the fetal heart using a novel triggering method: initial results in an animal model. J Magn Reson Imaging JMRI 35(5):1071–1076

    Article  PubMed  Google Scholar 

Download references

Author information

Author notes

  1. Sven-Thomas Antoni and Sascha Lehmann have contributed equally to this work. Partially funded by fmthh—Forschungszentrum Medizintechnik Hamburg.

Authors and Affiliations

  1. Institute of Medical Technology, Hamburg University of Technology, Hamburg, Germany

    Sven-Thomas Antoni, Maximilian Neidhardt & Alexander Schlaefer

  2. Institute for Software Systems, Hamburg University of Technology, Hamburg, Germany

    Sascha Lehmann & Sibylle Schupp

  3. Center for Radiology and Endoscopy, Medical Center Hamburg-Eppendorf, Hamburg, Germany

    Kai Fehrs, Christian Ruprecht, Fabian Kording & Gerhard Adam

Authors
  1. Sven-Thomas Antoni
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Sascha Lehmann
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Maximilian Neidhardt
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Kai Fehrs
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Christian Ruprecht
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Fabian Kording
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Gerhard Adam
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Sibylle Schupp
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Alexander Schlaefer
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Sven-Thomas Antoni.

Ethics declarations

Conflict of interest

K. Fehrs, F. Kording and C. Ruprecht are the founders of the company northh medical GmbH. The other authors declare that they have no conflict of interest.

Informed consent

For this type of study, formal consent is not required.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Antoni, ST., Lehmann, S., Neidhardt, M. et al. Model checking for trigger loss detection during Doppler ultrasound-guided fetal cardiovascular MRI. Int J CARS 13, 1755–1766 (2018). https://doi.org/10.1007/s11548-018-1832-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11548-018-1832-5

Keywords

Search

Navigation