Dynamic imaging of the fetal heart using metric optimized gating.

TLDR: The purpose of this work was to develop and validate metric‐optimized gating (MOG) for cine imaging of the fetal heart.

Abstract: Purpose Advances in fetal cardiovascular magnetic resonance imaging have been limited by the absence of a reliable cardiac gating signal. The purpose of this work was to develop and validate metric-optimized gating (MOG) for cine imaging of the fetal heart. Theory and Methods Cine MR and electrocardiogram data were acquired in healthy adult volunteers for validation of the MOG method. Comparison of MOG and electrocardiogram reconstructions was performed based on the image quality for each method, and the difference between MOG and electrocardiogram trigger times. Fetal images were also acquired, their quality evaluated by experienced radiologists, and the theoretical error in the MOG trigger times were calculated. Results Excellent agreement between electrocardiogram and MOG reconstructions was observed. The experimental errors in adult MOG trigger times for all five volunteers were ± (7, 25, 17, 8, and 13) ms. Fetal images captured normal and diseased cardiac dynamics. Conclusion MOG for cine imaging of the fetal myocardium was developed and validated in adults. Using MOG, the first gated MR images of the human fetal myocardium were obtained. Small moving structures were visualized during radial contraction, thus capturing normal fetal cardiac wall motion and permitting assessment of cardiac function. Magn Reson Med 70:1598–1607, 2013. © 2013 Wiley Periodicals, Inc.

Figures

Figure 3: The effect of misgating (a) Single frame from a retrospectively reconstructed set of adult images acquired with ECG gating and Cartesian sampling. (b) M-mode display of intensities along the vertical dash line in (a) showing the temporal evolution of the signal. (c, d) Data reconstructed with an incorrect estimate of the heart rate, showing a loss of both spatial and temporal resolution.

Figure 8: MOG reconstructions of a healthy human fetal heart. (a) A short axis view at the mid ventricular level is shown at end-systole and end-diastole. (b) Magnified end diastolic image from (a). (c) Plot of signal intensity versus time for the dashed line in (b).

Figure 9: MOG reconstructions of human fetal subject with a congenital heart defect. (a) A short axis view at the mid ventricular level is shown at end-systole and end-diastole. (b) Magnified end diastolic image from (a). (c) Plot of signal intensity versus time for the dashed line in (b).

Figure 1: Diagram of the fetal circulation. Flow direction is indicated by the black arrows. Relative oxygen concentration is given by vessel color decreasing from red to blue (13).

Figure 10: Preliminary results: ROI selection. (a) ROI example (dashed line), where the entropy is only evaluated over pixels that contain cardiac anatomy. (b) Demonstration of the change in entropy (evaluated over the ROI in a) that occurs when Cartesian k-space data are interpolated and reconstructed based on R-wave triggers that are shifted from their true ECG values. (c) ROI example (dashed line), where the entropy is evaluated over pixels extending ~20 % beyond the cardiac anatomy in either direction. (d) Same as (b) but for the ROI shown in (c).

Figure 5: Comparison of MOG and ECG adult volunteer reconstructions. Endsystolic (S) and diastolic (D) images are shown for each sampling strategy: (a, b) Cartesian without parallel imaging (c, d), Cartesian sampling with GRAPPA (e, f), and Radial sampling without parallel imaging. In all cases the temporal evolution of signal along the white dashed line is plotted.

Full text

Dynamic Imaging of the Fetal Heart Using Metric Optimized Gating
by
Christopher Roy
A thesis submitted in conformity with the requirements
for the degree of Master of Science
Department of Medical Biophysics
University of Toronto
© Copyright by Christopher William Roy 2012

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Dynamic Imaging of the Fetal Heart Using Metric Optimized Gating
Christopher Roy
Master of Science
Department of Medical Biophysics
University of Toronto
2012
Abstract
Advances in fetal cardiovascular MRI have been limited by the absence of a reliable cardiac
gating signal. Recently, metric optimized gating (MOG) has been proposed as a solution to
this limitation. In this thesis, I have developed and validated MOG for high resolution cine
imaging of the fetal heart. ECG gated cine MR data of the adult heart were acquired from
healthy volunteers. This enabled image reconstruction of the same data using both MOG
and conventional ECG. Comparison of the two reconstruction methods was performed
qualitatively, by comparing images reconstructed with each method, and quantitatively,
based on the difference between MOG and ECG trigger times. Fetal images were also
acquired, their quality evaluated by experienced radiologists, and the theoretical error in
the MOG trigger times calculated. Excellent agreement between ECG and MOG
reconstructions was observed. Using MOG, the world’s first gated MR images of the human
fetal heart were obtained. Small moving structures were visualized during radial
contraction, thus capturing normal fetal cardiac wall motion and permitting assessment of
cardiac function.

iii
Acknowledgements
This work was supported through a studentship in part by the Ontario Opportunity Trust
Fund – Hospital for Sick Children Foundation Student Scholarship Program and a
Alexander Graham Bell Canada Graduate Scholarship from the Natural Sciences and
Engineering Research Council of Canada.
To the members of my student committee, Mark Henkelman and Graham Wright, thank you
for guiding, challenging, and supporting me throughout this project.
To Mike Seed, Bahiyah Al Nafisi, Lars Grosse-Wortmann, and Shi-Joon Yoo, thank you for
your enthusiastic support. I feel extremely fortunate to be a part of the on-going
collaboration between the clinical staff at Sick Kids and the Macgowan lab. Thank you Mike
for your valuable insight, guidance, and frequent help acquiring and interpreting clinical
data.
Thank you to my friends in the Macgowan lab: Peter Leimbigler, Chris Wernick and Joshua
van Amerom. You have provided a fantastic work environment and valuable feedback at all
stages of this project. Thank you Josh for all your help in and out of the lab.
I owe a tremendous amount of thanks to my supervisor Chris Macgowan. Without his
guidance and support this project would not have been possible. Thank you for being an
excellent teacher, friend, and for always giving me hours of your time when I ask for a
couple seconds. I am extremely grateful to have had the chance to learn from you.

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To my friends Peter Beers and Nick Enright, though we no longer get to see each other on a
regular basis, our discussions of life, science and music help keep me grounded and sane.
To my friends and band mates Matt Horsman and Matt Mintzer, thank you for giving me a
creative outlet outside of research.
To Victoria Munnoch, thank you for putting up with the endless hours I spend talking to my
computer, and for always being there when I need you. This work, along with every aspect
of my day to day life would not be possible without you.
Finally, to my incredible family, to my parents Paul and Maureen, my brothers Andrew and
Corey and all of my relatives; thank you for your unwavering love and support.

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Table of Contents
Acknowledgements ...................................................................................................................... iii
Table of Contents ........................................................................................................................... v
List of Tables ................................................................................................................................ vii
List of Figures ............................................................................................................................. viii
List of Abbreviations ..................................................................................................................... x
Chapter 1 Motivation and Background........................................................................................ 1
1.1 Imaging the Fetal Heart .................................................................................................... 1
1.1.1 Clinical Motivation – Fetal Distress ..................................................................... 2
1.1.2 Normal Circulation ................................................................................................ 2
1.1.3 Cardiac Function .................................................................................................... 4
1.1.4 Ultrasound ............................................................................................................. 6
1.1.5 MRI.......................................................................................................................... 7
1.2 Cardiac Gating .................................................................................................................... 9
1.2.1 Conventional retrospective gating ....................................................................... 9
1.2.2 Alternative Solutions ........................................................................................... 10
1.3 Metric Optimized Gating ................................................................................................. 12
1.3.1 Metric-based Autocorrection ............................................................................. 12
1.3.2 MOG Method ........................................................................................................ 12
1.4 Thesis Statement ............................................................................................................. 13
Chapter 2 Cine Imaging of the Heart Using Metric Optimized Gating .................................... 15
2.1 Introduction ..................................................................................................................... 15
2.2 Theory .............................................................................................................................. 15
2.2.1 Image Metrics ...................................................................................................... 15

Frequently asked questions

Q1. What are the contributions in "Dynamic imaging of the fetal heart using metric optimized gating" ?

In this paper, the authors developed and validated metric optimized gating ( MOG ) for high-resolution cine imaging of the fetal heart. 

Q2. Why did the radial MOG reconstruction show a smaller theoretical error?

Because a linear-filling acquisition was used, central rows of k-space were collected near the midpoint of the scan and changes in the corresponding parameters resulted in greater curvature of the entropy landscape and consequently a smaller theoretical error. 

Q3. What is the purpose of combining MRI data from multiple cardiac cycles?

To improve both temporal and spatial resolution, it is then necessary to acquire and retrospectively combine MRI data from multiple cardiac cycles (45). 

Q4. What is the way to measure endocardial border delineation without contrast agents?

Functional cardiac MR imaging with steady-state free precession (SSFP) significantly improves endocardial border delineation without contrast agents. 

Q5. How long did the MOG process take?

For image reconstructions with a higher computational demand (parallel imaging, radial data), total MOG processing time lasted approximately 2 hours per slice. 

Q6. What was the theoretical error in the adult MR data?

The temporal resolution of the adult MR acquisition (46 ms) exceeded that needed for accurate interpolation of cardiac wall motion (i.e., the majority of cardiac motion is bounded by ±20 Hz) and thus, the theoretical error in the adult data was mainly a function of SNR and metric sensitivity (68–70). 

Q7. What are the main factors that limit the resolution of a fetal MRI?

a large field of view (FOV) is needed to avoid image wrap from the maternal abdomen and second, the possibility of fetal motion during the examination puts considerable constraint on scan time. 

Q8. What is the trade-off between a given model and the actual data?

For a given model there is an inherent trade-off between flexibility (ability to account for beat to beat heart rate variation) and post-processing time (time required to optimize each parameter). 

Q9. What are the main aspects of the MOG method that may be improved?

Of these three aspects, improvements made to ROI selection and search algorithm may facilitate the implementation of MOG in a clinical setting while improvements made to metric selection may improve the error in MOG parameters. 

Q10. What is the advantage of the Nelder-Mead simplex algorithm?

This method is attractive in that it does not require any derivative calculations but instead performs a simplex based search where the optimum value is reached when the vertices of the simplex (cost-function values) are minimized to a pre-determined termination value. 

Q11. What are the widely available parallel imaging schemes?

Several parallel imaging schemes have been proposed but the most widely available are generalized auto-calibrating partially parallel acquisition (GRAPPA) and sensitivity encoding (SENSE). 

Q12. What are the main reasons why fetal CMR is not a regular screening tool?

3.6 The Future of Fetal Imaging Considerations given to cost and availability will likely prevent fetal CMR from becoming a regular screening tool.