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Abstract #4986

A clinical application of deep learning reconstructed myocardial late gadolinium enhancement on short-breath-hold patients

Xuefang Lu1, Weiyin Vivian Liu2, Yuchen Yan1, Changsheng Liu1, Wei Gong1, Yan Wang1, Yilin Zhao1, Guangnan Quan3, and Yunfei Zha1
1Department of Radiology, Renmin Hospital of Wuhan University, Wuhan, China, 2GE Healthcare, MR Research China, Beijing, China, 3General Electric Medical (China) Co, Beijing, China

Synopsis

Keywords: Myocardium, Image ReconstructionSNR and CNR are essential for radiologists to precisely assess the signal enhancement in myocardia tissues. High-resolution late gadolinium enhancement cardiac magnetic resonance (LGE-CMR) is important but often possess low SNR and takes long scan time. Compared with original PSMDE (PSMDEO), AIRTM Recon DL-based PSMDE (PSMDEDL) effectively and significantly improved SNR, CNR and image quality without extra scan time. High-resolution PSMDEDL images also accelerated diagnossis speed of identifying defected tissues from noisy but normal myocardial tissues and elevated the diagnosis confidence despite no statistically different diagnostic performance between PSMDEDL and PSMDEO images.

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Keywords