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 Frigiola^1,3, Rene Botnar^1,4, and Claudia Prieto^1,4

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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