Real-time phase-contrast flow cardiovascular magnetic resonance with low-rank modeling and parallel imaging. Issue 1 (December 2017)

• Record Type: Journal Article
• Authors: Sun, Aiqi; Zhao, Bo; Li, Yunduo; He, Qiong; Li, Rui; Yuan, Chun
• Is Part Of: Journal of cardiovascular magnetic resonance. Volume 19:Issue 1(2017)
• Page Start: 1
• Page End: 13
• Publication Date: 2017-12
• Subjects: Cardiovascular imaging -- Phase-contrast CMR -- Cine -- Real-time flow imaging -- Model-based reconstruction -- Low-rank modeling -- Parallel imaging; Cardiovascular system -- Magnetic resonance imaging -- Periodicals; 616.1207548
• DOI: 10.1186/s12968-017-0330-1
• Languages: English
• ISSNs: 1097-6647

Abstract

Abstract Background Conventional phase-contrast cardiovascular magnetic resonance (PC-CMR) employs cine-based acquisitions to assess blood flow condition, in which electro-cardiogram (ECG) gating and respiration control are generally required. This often results in lower acquisition efficiency, and limited utility in the presence of cardiovascular pathology (e.g., cardiac arrhythmia). Real-time PC-CMR, without ECG gating and respiration control, is a promising alternative that could overcome limitations of the conventional approach. But real-time PC-CMR involves image reconstruction from highly undersampled (k, t )-space data, which is very challenging. In this study, we present a novel model-based imaging method to enable high-resolution real-time PC-CMR with sparse sampling. Methods The proposed method captures spatiotemporal correlation among flow-compensated and flow-encoded image sequences with a novel low-rank model. The image reconstruction problem is then formulated as a low-rank matrix recovery problem. With proper temporal subspace modeling, it results in a convex optimization formulation. We further integrate this formulation with the SENSE-based parallel imaging model to handle multichannel acquisitions. The performance of the proposed method was systematically evaluated in 2D real-time PC-CMR with flow phantom experiments and in vivo experiments (with healthy subjects). Additionally, we performed a feasibility study of the proposed method on patients with cardiac arrhythmia. Results The proposed method achieves a spatial resolution of 1.8 mm and a temporal resolution of 18 ms for 2D real-time PC-CMR with one directional flow encoding. For the flow phantom experiments, both regular and irregular flow patterns were accurately captured. For the in vivo experiments with healthy subjects, flow dynamics obtained from the proposed method correlated well with those from the cine-based acquisitions. For the experiments with the arrhythmic patients, the proposed method demonstrated excellent capability of resolving the beat-by-beat flow variations, which cannot be obtained from the conventional cine-based method. Conclusion The proposed method enables high-resolution real-time PC-CMR at 2D without ECG gating and respiration control. It accurately resolves beat-by-beat flow variations, which holds great promise for studying patients with irregular heartbeats.