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Abstract #0770

A Multi-Scale Variational Neural Network for accelerating bright- and black-blood 3D whole-heart MRI in patients with congenital heart disease

Niccolo Fuin1, Giovanna Nordio1, Thomas Kuestner1, Radhouene Neji2, Karl Kunze2, Yaso Emmanuel3, Alessandra Frigiola1,3, Rene Botnar1,4, and Claudia Prieto1,4
1Biomedical Engineering Department, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom, 2MR Research Collaborations, Siemens Healthcare Limited, Frimley, United Kingdom, 3Guy’s and St Thomas’ Hospital, NHS Foundation Trust, London, United Kingdom, 4Pontificia Universidad Católica de Chile, Santiago, Chile

Bright- and black-blood MRI sequences provide complementary diagnostic information in patients with congenital heart disease (CHD). A free-breathing 3D whole-heart sequence (MTC-BOOST) has been recently proposed for contrast-free simultaneous bright- and black-blood MRI, demonstrating high-quality depiction of arterial and venous structures. However, high-resolution fully-sampled MTC-BOOST acquisitions require long scan times of ~12min. Here we propose a joint Multi-Scale Variational Neural Network (MS-VNN) which enables the acquisition of high-quality bright- and black blood MTC-BOOST images in ~2-4 minutes, and their joint reconstruction in ~20s. The technique is compared with Compressed-Sensing reconstruction for 5x acceleration, in CHD patients.

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