Key result
Free-breathing single-beat cardiac cine MRI with generative AI matches conventional imaging for accurate biventricular measurements.
Why the study?
Does free-breathing single-beat cardiac cine MRI with deep learning reconstruction maintain accurate biventricular measurements and image quality compared to conventional multibreath-hold k-space-segmented cine MRI?
Cross-Sectional (n=136)
Does free-breathing single-beat cardiac cine MRI with deep learning reconstruction maintain accurate biventricular measurements and image quality compared to conventional multibreath-hold k-space-segmented cine MRI?
Effect estimate: r = 0.89-0.99
p-value: p=<.001
Free-breathing single-beat cardiac cine MRI with deep learning reconstruction significantly reduces scan time to 30 seconds while maintaining accurate biventricular measurements and high diagnostic quality compared to conventional methods.
Supports feasibility of AI-enhanced free-breathing cine MRI; leaves open prospective validation before clinical adoption.
To develop and evaluate a free-breathing, highly accelerated, multisection, single-beat cine sequence for cardiac MRI. This prospective study, conducted from July 2022 to December 2023, included participants with various cardiac conditions as well as healthy participants who were imaged using a 3-T MRI system. A single-beat sequence was implemented, collecting data for each section in one heartbeat. Images were acquired with an in-plane spatiotemporal resolution of 1.9 × 1.9 mm 2 and 37 msec and reconstructed using resolution enhancement generative adversarial inline neural network (REGAIN), a deep learning model. Multibreath-hold k-space–segmented (4.2-fold acceleration) and free-breathing single-beat (14.8-fold acceleration) cine images were collected, both reconstructed with REGAIN. Left ventricular (LV) and right ventricular (RV) parameters between the two methods were evaluated with linear regression, Bland-Altman analysis, and Pearson correlation. Three expert cardiologists independently scored diagnostic and image quality. Scan and rescan reproducibility was evaluated in a subset of participants 1 year apart using the intraclass correlation coefficient (ICC). This study included 136 participants (mean age [SD], 54 years ± 15; 69 female, 67 male), 40 healthy and 96 with cardiac conditions. k-Space–segmented and single-beat scan times were 2.6 minutes ± 0.8 and 0.5 minute ± 0.1, respectively. Strong correlations ( P < .001) were observed between k-space–segmented and single-beat cine parameters in both LV ( r = 0.97–0.99) and RV ( r = 0.89–0.98). Scan and rescan reproducibility of single-beat cine was excellent (ICC, 0.97–1.0). Agreement among readers was high, with 125 of 136 (92%) images consistently assessed as diagnostic and 133 of 136 (98%) consistently rated as having good image quality by all readers. Free-breathing 30-second single-beat cardiac cine MRI yielded accurate biventricular measurements, reduced scan time, and maintained high diagnostic and image quality compared with conventional multibreath-hold k-space–segmented cine images. Keywords: MR-Imaging, Cardiac, Heart, Imaging Sequences, Comparative Studies, Technology Assessment Supplemental material is available for this article.
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Ghanbari et al. (2025) conducted a cross-sectional in Cardiac conditions (n=136). Free-breathing single-beat cardiac cine MRI vs. Multibreath-hold k-space-segmented cine MRI was evaluated on Left ventricular (LV) and right ventricular (RV) parameters (r = 0.89-0.99, p=<.001). Free-breathing single-beat cardiac cine MRI strongly correlated with conventional multibreath-hold imaging for biventricular parameters (r=0.89-0.99, P<0.001) while reducing scan time to 0.5 minutes.
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