Abstract #4847

A clinical application of deep learning reconstructed LGE combined with coronary calcification scoring in coronary artery disease

Xuefang Lu¹, Yuchen Yan¹, Weiyin Vivian Liu², Changsheng Liu¹, Wei Gong¹, Yan Wang¹, Zhoufeng Peng¹, 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, Machine Learning/Artificial Intelligence, late gadolinum enhancementPreclinical disease is primarily assessed through the coronary artery calcium score (CACS) and used for risk assessment, screening CACS is a reliable indicator for the assessment of coronary artery disease in our study, FWHM analysis of PSMDE_DL and PSMDE_O showed moderate correlation between the percentage of enhancement area and CACS, beneficial for check-up with less imaging time and low radiation screening. This finding should be further validated in a larger sample size. Moreover, threshold techniques such as 2SD to 5SD were sensitive to signal intensity and should be concerned for analysis on deep-learning reconstructed images, especially missing detection rate.

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