# Gating-Free Ultra-Fast Fetal Cardiac MRI with Sub-Nyquist Sampling for Live in Utero Imaging and Cardiovascular Phenotyping of Fetal Mice

> **NIH NIH R21** · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · 2020 · $199,609

## Abstract

Congenital heart defects (CHD) are the most common birth defects, affecting nearly 1% of live births. The
survival rates for CHD patients have greatly improved with surgical advances, shifting medical burden to the
care of adult survivors of CHD. The greatest challenge is the poor neurological outcomes of CHD patients.
While the etiology remains largely unknown, it is likely to be influenced by genetic factors, compromised hemo-
dynamics, and cumulative injury from hypoxia and surgical trauma. Mechanistic insight into the structure-func-
tion relationship between heart and brain development and their interaction in CHD is an important area of re-
search that is poorly studied. Mouse models will no doubt be invaluable for such studies, as mice have the
same cardiac anatomy as humans, similar architecture and pathways for the central nervous system, and a
genome that is 99% identical, ensuring most biological processes and molecular pathways are conserved. Fe-
tal MRI is emerging as an important prenatal imaging modality complementing prenatal ultrasound for the diag-
nosis of congenital anomalies. Although still the predominant clinical imaging modality for prenatal screening
given its low cost and ready availability, fetal ultrasound is limited by its prescribed acoustic windows, penetra-
tion depth, low contrast, and ineffective tissue characterization. In contrast, fetal MRI are not affected by these
limitations. However, live MRI in utero is greatly hampered by the challenge of fetal cardiac motion. In this
study, we propose to overcome this problem by developing a gating-free ultra-fast 4D time-resolved fetal MRI
using sub-Nyquist sparse sampling for live in utero cardiovascular and brain imaging of fetal mice. We will em-
ploy a novel regional partial separability (PS) model to capture fetal and maternal motion and allow sparse (k,
t)-space sampling. The two key features of this PS fetal MRI approach are (1) the ability to express incoherent
fetal and maternal motion with reduced degrees of freedom; and (2) a unique sub-Nyquist sparse sampling
scheme to accelerate acquisition and increase detection sensitivity. This will allow assessments of anatomical
structures, such as in the heart and brain, and also the assessment of cardiovascular hemodynamic function
and its interaction with the developing brain. As this imaging method is noninvasive, longitudinal follow-up can
be pursued to examine whether changes in hemodynamic function may be correlated with emerging brain ab-
normalities. We will develop this novel imaging method using wildtype mice, and then further validate its utility
in characterizing the cardiac and brain defect phenotypes in two CHD mutant models, including the Ohia mu-
tant mouse model of hypoplastic left heart syndrome (HLHS), one of the most lethal CHD. Upon validating the
use of sub-Nyqist sparse sampling in the analysis of fetal brain and heart phenotypes in the HLHS mutant
mice, this technique can be clinically transla...

## Key facts

- **NIH application ID:** 9881284
- **Project number:** 5R21EB023507-02
- **Recipient organization:** UNIVERSITY OF PITTSBURGH AT PITTSBURGH
- **Principal Investigator:** Yijen Lin Wu
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $199,609
- **Award type:** 5
- **Project period:** 2019-03-01 → 2022-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9881284

## Citation

> US National Institutes of Health, RePORTER application 9881284, Gating-Free Ultra-Fast Fetal Cardiac MRI with Sub-Nyquist Sampling for Live in Utero Imaging and Cardiovascular Phenotyping of Fetal Mice (5R21EB023507-02). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/9881284. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*