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.
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.
|Polak, Daniel; Setsompop, Kawin; Cauley, Stephen F et al. (2018) Wave-CAIPI for highly accelerated MP-RAGE imaging. Magn Reson Med 79:401-406|
|Johnson, Matthew B; Sun, Xingshen; Kodani, Andrew et al. (2018) Aspm knockout ferret reveals an evolutionary mechanism governing cerebral cortical size. Nature 556:370-375|
|Zhao, Bo; Setsompop, Kawin; Adalsteinsson, Elfar et al. (2018) Improved magnetic resonance fingerprinting reconstruction with low-rank and subspace modeling. Magn Reson Med 79:933-942|
|Haskell, Melissa W; Cauley, Stephen F; Wald, Lawrence L (2018) TArgeted Motion Estimation and Reduction (TAMER): Data Consistency Based Motion Mitigation for MRI Using a Reduced Model Joint Optimization. IEEE Trans Med Imaging 37:1253-1265|
|Bilgic, Berkin; Ye, Huihui; Wald, Lawrence L et al. (2017) Simultaneous Time Interleaved MultiSlice (STIMS) for Rapid Susceptibility Weighted acquisition. Neuroimage 155:577-586|
|McDaniel, Patrick; Bilgic, Berkin; Fan, Audrey P et al. (2017) Mitigation of partial volume effects in susceptibility-based oxygenation measurements by joint utilization of magnitude and phase (JUMP). Magn Reson Med 77:1713-1727|
|Liao, Congyu; Bilgic, Berkin; Manhard, Mary Kate et al. (2017) 3D MR fingerprinting with accelerated stack-of-spirals and hybrid sliding-window and GRAPPA reconstruction. Neuroimage 162:13-22|
|Turk, Esra Abaci; Luo, Jie; Gagoski, Borjan et al. (2017) Spatiotemporal alignment of in utero BOLD-MRI series. J Magn Reson Imaging 46:403-412|
|Bo Zhao; Bilgic, Berkin; Adalsteinsson, Elfar et al. (2017) Simultaneous multislice magnetic resonance fingerprinting with low-rank and subspace modeling. Conf Proc IEEE Eng Med Biol Soc 2017:3264-3268|
|Im, K; Guimaraes, A; Kim, Y et al. (2017) Quantitative Folding Pattern Analysis of Early Primary Sulci in Human Fetuses with Brain Abnormalities. AJNR Am J Neuroradiol 38:1449-1455|
Showing the most recent 10 out of 23 publications