The fetal period is a time of unparalleled brain growth and development and is arguably the most important time for defining future cognitive potential. Therefore, when fetal brain development is impaired, as it is in many disorders including congenital heart disease (CHD), abnormalities emerge in utero and contribute to lifelong cognitive impairment that cannot be corrected even with optimal postnatal care. This has led to an overwhelming public health need for methods that detect early in utero anatomical and physiological abnormalities to better counsel parents and to better guide development and optimization of fetal interventions (surgical or medical) to prevent or mitigate such long-term consequences. Although there has been ongoing optimism that fetal MRI could fulfill this role, it still remains severely limited by the unique anatomy of the gravid abdomen, the small size of the fetus and, most importantly, fetal motion. As a result, fetal brain MRI lags far behind postnatal brain imaging. In fact, fetal brain MR evaluations remain primarily limited to fast single-shot T2 sequences that have inherently poor brain contrast with spectroscopy, diffusion and perfusion unreliable or impossible with the current methods. Thus, the potential of fetal MRI to provide robust and accurate structural and physiological assessments remains unrealized. We propose to advance fetal MRI using an integrated approach that addresses the entire imaging acquisition process from hardware to pulse sequence design with the following aims:
Aim 1. Develop MR Hardware and Anatomical Acquisition Methods. We propose to develop the first anthropomorphic fetal MRI phantom to safely test the feasibility of our developments and ensure SAR safety. We will build the first 128-channel receive phased array for the pregnant abdomen to facilitate image acceleration and improve SNR. We will build on the emerging field of parallel transmission (pTx), and be the first to apply it to fetal imaging with the goal of exciting only th region of the fetal head to minimize SAR, enable further acceleration, and provide a target for prospective motion navigation. Additional speed on the image acquisition will be gained with the development of compressed sensing (CS) techniques for fetal imaging. These improvements will enable improved anatomical images (TSE and MPRAGE);
Aim 2. Develop Physiological Acquisition Methods. Use advances in Aim 1 to develop robust diffusion, spectroscopy and perfusion imaging;
and Aim 3. Translate to In Vivo Fetal Brain MRI assessment in Congenital Heart Disease. We will assess the ability or our advances to better detect structural and physiological brain abnormalities in CHD compared to current fetal MRI in the same subjects and compared to the advanced protocol in normal controls. In addition we will attempt to detect physiological changes after fetal interventions in hypoplastic left heart syndrome (HLHS). In summary, our goal is to transform the field of fetal MRI by developing and employing state-of-the-art advances on the acquisition end of the fetal MRI experiment to meet the growing demand for more information as fetal interventions emerge.

Public Health Relevance

Fetal motion severely limits the diagnostic capabilities of fetal neuroimaging, hampering our ability to accurately diagnose disease, select candidates for intervention and assess response to treatments. We propose to transform fetal neuroimaging by combining the latest advances in imaging hardware and software to develop a motion insensitive advanced fetal protocol that includes high-resolution anatomical and physiological imaging.

Agency
National Institute of Health (NIH)
Institute
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Type
Research Project (R01)
Project #
1R01EB017337-01A1
Application #
8696352
Study Section
Special Emphasis Panel (ZRG1-SBIB-N (55))
Program Officer
Liu, Guoying
Project Start
2014-04-01
Project End
2019-03-31
Budget Start
2014-04-01
Budget End
2015-03-31
Support Year
1
Fiscal Year
2014
Total Cost
$1,283,039
Indirect Cost
$151,000
Name
Children's Hospital Boston
Department
Type
DUNS #
076593722
City
Boston
State
MA
Country
United States
Zip Code
02115