Feasibility of Free-breathing Deep Learning-reconstructed Single-Shot Cine MRI in Participants with Arrhythmia: Comparison with Conventional Segmented Cine MRI.
Purpose To evaluate the feasibility of retrospective electrocardiographically (ECG) gated single-shot cine using deep learning-enhanced compressed sensing (AI-CS) versus conventional balanced steady-state free precession (bSSFP) cine, focusing on left ventricular (LV) structure and function. Materials and Methods Between September 1, 2023, and September 28, 2024, participants (including those with suspected arrhythmias) were prospectively recruited to undergo short-axis cine imaging with both bSSFP and AI-CS single-shot sequences on a 1.5-T scanner. LV volumetric parameters (LV end-diastolic volume, end-systolic volume, stroke volume, ejection fraction, and mass) and strain parameters (peak strain in the radial, longitudinal, and circumferential directions and the time to peak strain SD) were measured and compared using Wilcoxon signed rank tests. Results Among 25 healthy volunteers (mean age, 37.88 years ± 16.76 [SD]; 18 female) and 45 participants with suspected arrhythmia (mean age, 53.21 years ± 15.45; 20 female), the AI-CS single-shot cine had better image quality compared with bSSFP cine, particularly in participants with arrhythmia (European Cardiovascular Magnetic Resonance Registry score: 0.32 ± 0.68 for bSSFP cine vs 0.05 ± 0.22 for AI-CS single-shot cine; P < .001), with fewer mistrigger events and cardiac motion artifacts. AI-CS showed good to excellent agreement with bSSFP for biventricular volume and LV mass measurements and provided comparable ejection fraction values to those at echocardiography in cases in which bSSFP failed (37.50% ± 5.28 vs 31.70% ± 6.43; z = -1.864; P = .06). Scan time was significantly reduced with AI-CS (10 seconds ± 2 vs 132 seconds ± 8; P < .001). Conclusion AI-CS single-shot cine demonstrated greater image quality and clinical feasibility compared with bFFSP cine in healthy participants and participants with suspected arrhythmias. Keywords: Artificial Intelligence-assisted Compressed SENSE, Arrhythmias, Left Ventricular Structure, Left Ventricular Function, Cardiac MRI, Balanced Steady-State Free Precession Cine Sequences Supplemental material is available for this article. © RSNA, 2026.