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Simulated Half-Fourier Acquisitions Single-shot Turbo Spin Echo (HASTE) of the Fetal Brain: Application to Super-Resolution Reconstruction

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Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, and Perinatal Imaging, Placental and Preterm Image Analysis (UNSURE 2021, PIPPI 2021)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 12959))

Abstract

Accurate characterization of in utero human brain maturation is critical as it involves complex interconnected structural and functional processes that may influence health later in life. Magnetic resonance imaging is a powerful tool complementary to the ultrasound gold standard to monitor the development of the fetus, especially in the case of equivocal neurological patterns. However, the number of acquisitions of satisfactory quality available in this cohort of sensitive subjects remains scarce, thus hindering the validation of advanced image processing techniques. Numerical simulations can mitigate these limitations by providing a controlled environment with a known ground truth. In this work, we present a flexible numerical framework for clinical T2-weighted Half-Fourier Acquisition Single-shot Turbo spin Echo of the fetal brain. The realistic setup, including stochastic motion of the fetus as well as intensity non-uniformities, provides images of the fetal brain throughout development that are comparable to real data acquired in clinical routine. A case study on super-resolution reconstruction of the fetal brain from synthetic motion-corrupted 2D low-resolution series further demonstrates the potential of such a simulator to optimize post-processing methods for fetal brain magnetic resonance imaging.

T. Hilbert, C. W. Roy—These authors contributed equally to this work.

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References

  1. Kwon, E.J., Kim, Y.J.: What is fetal programming?: A lifetime health is under the control of in utero health. Obstet. Gynecol. Sci. 60(6), 506–519 (2017)

    Article  Google Scholar 

  2. O’Donnell, K.J., Meaney, M.J.: Fetal origins of mental health: the developmental origins of health and disease hypothesis. Am. J. Psychiatry 174(4), 319–328 (2017)

    Article  Google Scholar 

  3. Volpe, J.J.: Brain injury in premature infants: a complex amalgam of destructive and developmental disturbances. Lancet Neurol. 8(1), 110–124 (2009)

    Article  Google Scholar 

  4. Gholipour, A., et al.: A normative spatiotemporal MRI atlas of the fetal brain for automatic segmentation and analysis of early brain growth. Sci. Rep. 7(1), 1–13 (2017)

    Article  MathSciNet  Google Scholar 

  5. Gholipour, A., et al.: Fetal MRI: a technical update with educational aspirations. Concepts Magn. Reson. Part A Bridging Educ. Res. 43(6), 237–266 (2014)

    Google Scholar 

  6. Roy, C.W., Marini, D., Segars, W.P., Seed, M., Macgowan, C.K.: Fetal XCMR: a numerical phantom for fetal cardiovascular magnetic resonance imaging. J. Cardiovasc. Magn. Reson. 21(1), 29 (2019)

    Article  Google Scholar 

  7. Drobnjak, I., Gavaghan, D., Süli, E., Pitt-Francis, J., Jenkinson, M.: Development of a functional magnetic resonance imaging simulator for modeling realistic rigid-body motion artifacts. Magn. Reson. Med. 56(2), 364–380 (2006)

    Article  Google Scholar 

  8. Ebner, M., et al.: An automated framework for localization, segmentation and super-resolution reconstruction of fetal brain MRI. Neuroimage 206, 116324 (2020)

    Article  Google Scholar 

  9. Gholipour, A., Estroff, J.A., Warfield, S.K.: Robust super-resolution volume reconstruction from slice acquisitions: application to fetal brain MRI. IEEE Trans. Med. Imaging 29(10), 1739–1758 (2010)

    Article  Google Scholar 

  10. Kuklisova-Murgasova, M., Quaghebeur, G., Rutherford, M.A., Hajnal, J.V., Schnabel, J.A.: Reconstruction of fetal brain MRI with intensity matching and complete outlier removal. Med. Image Anal. 16(8), 1550–1564 (2012)

    Article  Google Scholar 

  11. Tourbier, S., Bresson, X., Hagmann, P., Thiran, J.P., Meuli, R., Cuadra, M.B.: An efficient total variation algorithm for super-resolution in fetal brain MRI with adaptive regularization. NeuroImage 118, 584–597 (2015)

    Google Scholar 

  12. Wissmann, L., Santelli, C., Segars, W.P., Kozerke, S.: MRXCAT: realistic numerical phantoms for cardiovascular magnetic resonance. J. Cardiovasc. Magn. Reson. 16(1), 63 (2014)

    Article  Google Scholar 

  13. Malik, S.J., Teixeira, R.P.A.G., Hajnal, J.V.: Extended phase graph formalism for systems with magnetization transfer and exchange. Magn. Reson. Med. 80(2), 767–779 (2018)

    Article  Google Scholar 

  14. Weigel, M.: Extended phase graphs: dephasing, RF pulses, and echoes - pure and simple. J. Magn. Reson. Imaging 41(2), 266–295 (2015)

    Article  Google Scholar 

  15. Tourbier, S., De Dumast, P., Kebiri, H., Hagmann, P., Bach Cuadra, M.: Medical-Image-Analysis-Laboratory/mialsuperresolutiontoolkit: MIAL Super-Resolution Toolkit v2.0.1. Zenodo (2020)

    Google Scholar 

  16. Blazejewska, A.I., et al.: 3D in utero quantification of T2* relaxation times in human fetal brain tissues for age optimized structural and functional MRI. Magn. Reson. Med. 78(3), 909–916 (2017)

    Article  Google Scholar 

  17. Hagmann, C.F., et al.: T2 at MR imaging is an objective quantitative measure of cerebral white matter signal intensity abnormality in preterm infants at term-equivalent age. Radiology 252(1), 209–217 (2009)

    Article  Google Scholar 

  18. Nossin-Manor, R., et al.: Quantitative MRI in the very preterm brain: assessing tissue organization and myelination using magnetization transfer, diffusion tensor and T1 imaging. Neuroimage 64, 505–516 (2013)

    Article  Google Scholar 

  19. Vasylechko, S., et al.: T2* relaxometry of fetal brain at 1.5 Tesla using a motion tolerant method. Magn. Reson. Med. 73(5), 1795–1802 (2015)

    Google Scholar 

  20. Yarnykh, V.L., Prihod’ko, I.Y., Savelov, A.A., Korostyshevskaya, A.M.: Quantitative assessment of normal fetal brain myelination using fast macromolecular proton fraction mapping. Am. J. Neuroradiol. 39(7), 1341–1348 (2018)

    Article  Google Scholar 

  21. BrainWeb: Simulated brain database. https://brainweb.bic.mni.mcgill.ca/brainweb/

  22. Oubel, E., Koob, M., Studholme, C., Dietemann, J.-L., Rousseau, F.: Reconstruction of scattered data in fetal diffusion MRI. Med. Image Anal. 16(1), 28–37 (2012)

    Article  Google Scholar 

  23. Lajous, H., et al.: A magnetic resonance imaging simulation framework of the developing fetal brain. In: Proceedings of the 29th Annual Meeting of the International Society of Magnetic Resonance in Medicine (ISMRM), virtual. Program number 0734 (2021)

    Google Scholar 

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Acknowledgements

This work was supported by the Swiss National Science Foundation (grant 182602). We acknowledge access to the facilities and expertise of the CIBM Center for Biomedical Imaging, a Swiss research center of excellence founded and supported by Lausanne University Hospital (CHUV), University of Lausanne (UNIL), Ecole polytechnique fédérale de Lausanne (EPFL), University of Geneva (UNIGE) and Geneva University Hospitals (HUG).

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Authors and Affiliations

  1. Department of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland

    Hélène Lajous, Tom Hilbert, Christopher W. Roy, Sébastien Tourbier, Priscille de Dumast, Yasser Alemán-Gómez, Hamza Kebiri, Jean-Baptiste Ledoux, Patric Hagmann, Reto Meuli, Vincent Dunet, Mériam Koob, Matthias Stuber, Tobias Kober & Meritxell Bach Cuadra

  2. CIBM Center for Biomedical Imaging, Lausanne, Geneva, Switzerland

    Hélène Lajous, Priscille de Dumast, Hamza Kebiri, Jean-Baptiste Ledoux, Matthias Stuber & Meritxell Bach Cuadra

  3. Advanced Clinical Imaging Technology (ACIT), Siemens Healthcare, Lausanne, Switzerland

    Tom Hilbert & Tobias Kober

  4. Signal Processing Laboratory 5 (LTS5), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland

    Tom Hilbert, Thomas Yu, Tobias Kober & Meritxell Bach Cuadra

Authors
  1. Hélène Lajous
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  2. Tom Hilbert
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  3. Christopher W. Roy
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  4. Sébastien Tourbier
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  9. Jean-Baptiste Ledoux
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  11. Reto Meuli
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  12. Vincent Dunet
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  16. Meritxell Bach Cuadra
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Corresponding author

Correspondence to Hélène Lajous .

Editor information

Editors and Affiliations

  1. University College London/King's College London, London, UK

    Carole H. Sudre

  2. Medical University of Vienna and TU Wien, Vienna, Austria

    Roxane Licandro

  3. University of Tübingen, Tübingen, Germany

    Christian Baumgartner

  4. King's College London, London, UK

    Andrew Melbourne

  5. Massachusetts General Hospital, Harvard Medical School, MIT, Cambridge, MA, USA

    Adrian Dalca

  6. King's College London, London, UK

    Jana Hutter

  7. Microsoft Research/University College London, London, UK

    Ryutaro Tanno

  8. Boston Children's Hospital, Boston, MA, USA

    Esra Abaci Turk

  9. Technical University Denmark, Kongens Lyngby, Denmark

    Koen Van Leemput

  10. Hewlett Packard, Barcelona, Spain

    Jordina Torrents Barrena

  11. Harvard Medical School/Brigham and Women's Hospital, Boston, MA, USA

    William M. Wells

  12. The Hospital For Sick Children, University of Toronto, Toronto, ON, Canada

    Christopher Macgowan

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Lajous, H. et al. (2021). Simulated Half-Fourier Acquisitions Single-shot Turbo Spin Echo (HASTE) of the Fetal Brain: Application to Super-Resolution Reconstruction. In: Sudre, C.H., et al. Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, and Perinatal Imaging, Placental and Preterm Image Analysis. UNSURE PIPPI 2021 2021. Lecture Notes in Computer Science(), vol 12959. Springer, Cham. https://doi.org/10.1007/978-3-030-87735-4_15

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  • DOI: https://doi.org/10.1007/978-3-030-87735-4_15

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-87734-7

  • Online ISBN: 978-3-030-87735-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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