Unveiling the Fetus: Correcting Motion in Fetal MRI

Joshua van Amerom

joshua.vanamerom@sickkids.ca

SickKids Research Institute

Hospital for Sick Children

Toronto, Canada

MRI can provide a unique view of the developing fetus in utero. As an adjunct to ultrasound, fetal MR can provide images that can aid in prenatal diagnosis, improving outcomes by impacting in utero management, delivery planning and postnatal status. In addition, studies utilizing MR and the novel information it can provide contribute to understanding of normal and pathological development.

There are many challenges to capturing a fetus in the in utero setting with MRI, including aliasing and other artifacts, adequate signal and resolution, and safety limitations on scanner performance [Dighe2022; Gholipour2015]. However, the most ubiquitous challenge in fetal MRI is motion.

Displacement and deformation of fetal anatomy occurs due both maternal and fetal movement. Maternal breathing can have a continuous impact on the fetal anatomy depending on diaphragm movement and fetal position. Contractions and other episodic movements may also occur. Most fetal motion is unpredictable, such as bulk and limb movements, breathing movements in preparation for postnatal respiration, swallowing, hiccups, yawning, mouthing. Fetal motion, such as cardiac pulsation, occurs consistently. The combination of all these movements leads to changing fetal position and pose, and image artifact [Malamateniou2013; Stout2021].

Methods to prevent, reduce and compensate for motion in fetal MRI include many familiar from postnatal MR, as well as some unique to the subject. Prospective methods include patient preparation, timing of the scan, breath-holding, the use of fast and motion robust acquisitions, gating to external signals, and scan-time FOV adjustments and quality control [Malamateniou2013; Uus2022]. However, this talk will focus largely on retrospective techniques.

Methods for retrospective motion correction in fetal MR include:

Slice-to-volume reconstruction (SVR) provides a unique solution to fetal motion via motion corrected and compensated volumetric synthesis from many different views of the fetal anatomy of interest [Ebner2020; Jiang2007; Gholipour2010; Kuklisova-Murgasova2012; Rousseau2006]. In this way, SVR creates a self-consistent 3D volume from inconsistent 2D slices. With automated motion correction and outlier rejection, the acquisition of data for SVR can simply the MR exam, replacing a manual prescribe-scan-review-repeat approach in search of motion-free views of desired cross sections of the anatomy of interest in ideal cross section. SVR has been most widely used to generate high quality volumetric images of the fetal brain from single shot fast spin echo images and has also been applied to fetal body and the heart using the same acquisition sequence [Uus2022]. There are also implementations extending the SVR technique to diffusion and functional imaging, parameter mapping, and time-resolved cardiac imaging and blood flow quantification [Calixto2024; Christiaens2019; Roy2019; Goolaub2021; Roberts2020; Uus2022]. Deep learning models for SVR and related techniques have been developed that shift computational burden from inference to training, allowing for faster, fully automated reconstruction [Calixto2024; Meshaka2022; Uus2022].

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