Feasibility of accelerated non-contrast-enhanced whole-heart bSSFP coronary MR angiography by deep learning–constrained compressed sensing

• Published in: European radiology 2023-11, Vol.33 (11), p.8180-8190
• Main Authors: Wu, Xi, Tang, Lu, Li, Wanjiang, He, Shuai, Yue, Xun, Peng, Pengfei, Wu, Tao, Zhang, Xiaoyong, Wu, Zhigang, He, Yong, Chen, Yucheng, Huang, Juan, Sun, Jiayu
• Format: Article
• Language: English
• Subjects: Algorithms; Angiography; Artificial Intelligence; Blood vessels; Cardiac; Cardiovascular disease; Computed tomography; Computed Tomography Angiography - methods; Constriction, Pathologic; Coronary Angiography - methods; Coronary artery disease; Coronary Artery Disease - diagnostic imaging; Deep Learning; Diagnostic Radiology; Diameters; Feasibility; Feasibility Studies; Heart diseases; Homogeneity; Humans; Image acquisition; Image contrast; Image enhancement; Image quality; Imaging; Internal Medicine; Interventional Radiology; Machine learning; Magnetic Resonance Angiography - methods; Magnetic resonance imaging; Medical imaging; Medicine; Medicine & Public Health; Neuroradiology; Noise reduction; Noise sensitivity; Patients; Prospective Studies; Quality assessment; Radiology; Signal to noise ratio; Stenosis; Ultrasound; Wavelet transforms
• ISSN: 1432-1084; 0938-7994; 1432-1084
• DOI: 10.1007/s00330-023-09740-8

Objectives To examine a compressed sensing artificial intelligence (CSAI) framework to accelerate image acquisition in non-contrast-enhanced whole-heart bSSFP coronary magnetic resonance (MR) angiography. Methods Thirty healthy volunteers and 20 patients with suspected coronary artery disease (CAD) scheduled for coronary computed tomography angiography (CCTA) were enrolled. Non-contrast-enhanced coronary MR angiography was performed with CSAI, compressed sensing (CS), and sensitivity encoding (SENSE) methods in healthy participants and with CSAI in patients. Acquisition time, subjective image quality score, and objective image quality measurement (blood pool homogeneity, signal-to-noise ratio [SNR], and contrast-to-noise ratio [CNR]) were compared among the three protocols. The diagnostic performance of CASI coronary MR angiography for predicting significant stenosis (≥ 50% diameter stenosis) on CCTA was evaluated. The Friedman test was performed to compare the three protocols. Results Acquisition time was significantly shorter in the CSAI and CS groups than in the SENSE group (10.2 ± 3.2 min vs. 10.9 ± 2.9 min vs. 13.0 ± 4.1 min, p