Deep Learning-Based Acceleration of Compressed Sensing for Noncontrast-Enhanced Coronary Magnetic Resonance Angiography in Patients With Suspected Coronary Artery Disease

被引:11
作者
Wu, Xi [1 ,2 ]
Deng, Liping [1 ]
Li, Wanjiang [1 ]
Peng, Pengfei [1 ]
Yue, Xun [1 ,2 ]
Tang, Lu [1 ]
Pu, Qian [1 ]
Ming, Yue [1 ]
Zhang, Xiaoyong [3 ]
Huang, Xiaohua [2 ]
Chen, Yucheng
Huang, Juan [1 ,4 ,5 ]
Sun, Jiayu [1 ,5 ]
机构
[1] Sichuan Univ, Dept Radiol, West China Hosp, Chengdu, Sichuan, Peoples R China
[2] North Sichuan Med Coll, Dept Radiol, Affiliated Hosp, Nanchong, Sichuan, Peoples R China
[3] Philips Healthcare, Clin Sci, Chengdu, Sichuan, Peoples R China
[4] Sichuan Univ, Dept Cardiol, West China Hosp, Chengdu, Sichuan, Peoples R China
[5] Sichuan Univ, Dept Radiol, West China Hosp, 37 Guo Xue Lane, Chengdu, Sichuan, Peoples R China
关键词
coronary artery disease; deep learning; artificial intelligence; compressed sensing; coronary MR angiography; MR-ANGIOGRAPHY; PERFORMANCE; ALGORITHM; PLAQUES;
D O I
10.1002/jmri.28653
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Background: The clinical application of coronary MR angiography (MRA) remains limited due to its long acquisition time and often unsatisfactory image quality. A compressed sensing artificial intelligence (CSAI) framework was recently introduced to overcome these limitations, but its feasibility in coronary MRA is unknown.Purpose: To evaluate the diagnostic performance of noncontrast-enhanced coronary MRA with CSAI in patients with suspected coronary artery disease (CAD).Study Type: Prospective observational study.Population: A total of 64 consecutive patients (mean age +/- standard deviation [SD]: 59 +/- 10 years, 48.4% females) with suspected CAD.Field Strength/Sequence: A 3.0-T, balanced steady-state free precession sequence.Assessment: Three observers evaluated the image quality for 15 coronary segments of the right and left coronary arteries using a 5-point scoring system (1 = not visible; 5 = excellent). Image scores >= 3 were considered diagnostic. Furthermore, the detection of CAD with >= 50% stenosis was evaluated in comparison to reference standard coronary computed tomography angiography (CTA). Mean acquisition times for CSAI-based coronary MRA were measured.Statistical Tests: For each patient, vessel and segment, sensitivity, specificity, and diagnostic accuracy of CSAI-based coronary MRA for detecting CAD with >= 50% stenosis according to coronary CTA were calculated. Intraclass correlation coefficients (ICCs) were used to assess the interobserver agreement.Results: The mean MR acquisition time +/- SD was 8.1 +/- 2.4 minutes. Twenty-five (39.1%) patients had CAD with >= 50% stenosis on coronary CTA and 29 (45.3%) patients on MRA. A total of 885 segments on the CTA images and 818/885 (92.4%) coronary MRA segments were diagnostic (image score >= 3). The sensitivity, specificity, and diagnostic accuracy were as follows: per patient (92.0%, 84.6%, and 87.5%), per vessel (82.9%, 93.4%, and 91.1%), and per segment (77.6%, 98.2%, and 96.6%), respectively. The ICCs for image quality and stenosis assessment were 0.76-0.99 and 0.66-1.00, respectively.Data Conclusion: The image quality and diagnostic performance of coronary MRA with CSAI may show good results in comparison to coronary CTA in patients with suspected CAD.
引用
收藏
页码:1521 / 1530
页数:10
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