The aim of this project is to develop selection criteria for fetal and urgent postnatal surgical repair of congenital heart defects. Fetal ultrasound provides insufficient information on characteristics of complex cardiac defects which may require fetal intervention in the form of prenatal balloon dilatation of the affected valves, or urgent postnatal stabilisation and surgery. Recently developed dynamic fetal MRI of beating heart anatomy and blood flow has potential for accurate prediction disease trajectories and intervention success. This PhD project aims to develop: 1) automated segmentation of fetal heart and vessels in motion-corrected 3D+time fetal cardiac MRI; 2) extraction of cardiac functional measures of shape, motion and flow; 3) identification of optimal phenotypes to predict disease progression, and surgical intervention outcomes through interpretable machine/deep learning.
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Surgical intervention planning in fetal congenital heart disease
