Free-breathing, Highly Accelerated, Single-beat, Multisection Cardiac Cine MRI with Generative Artificial Intelligence

Purpose To develop and evaluate a free-breathing, highly accelerated, multisection, single-beat cine sequence for cardiac MRI. Materials and Methods 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<sup>2</sup> 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). Results 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 (<i>P</i> < .001) were observed between k-space-segmented and single-beat cine parameters in both LV (<i>r</i> = 0.97-0.99) and RV (<i>r</i> = 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. Conclusion 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. <b>Keywords:</b> MR-Imaging, Cardiac, Heart, Imaging Sequences, Comparative Studies, Technology Assessment <i>Supplemental material is available for this article.</i> © RSNA, 2025.

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Publication Details

Journal
Radiology Cardiothoracic Imaging
Published
2025-04-01
DOI
https://doi.org/10.1148/ryct.240272
Citations
4
Primary Topic
Advanced MRI Techniques and Applications
Type
article
Field-Weighted Citation Impact
5.44

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article

Free-breathing, Highly Accelerated, Single-beat, Multisection Cardiac Cine MRI with Generative Artificial Intelligence

Warren J. Manning, Reza Nezafat, Christopher W. Hoeger, Patrick Pierce et al.
4 citations
Radiology Cardiothoracic Imaging
Advanced MRI Techniques and Applications
5.44
article

Free-breathing, Highly Accelerated, Single-beat, Multisection Cardiac Cine MRI with Generative Artificial Intelligence

Warren J. Manning, Reza Nezafat, Christopher W. Hoeger, Patrick Pierce, Fahime Ghanbari, Connie W. Tsao, Long Ngo, Adele Carty, Juan C. Rodríguez, Manuel A. Morales, Jordan Street, Scott Fitzgerald Johnson
article en
4 citations

Abstract

Purpose To develop and evaluate a free-breathing, highly accelerated, multisection, single-beat cine sequence for cardiac MRI. Materials and Methods 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<sup>2</sup> 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). Results 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 (<i>P</i> < .001) were observed between k-space-segmented and single-beat cine parameters in both LV (<i>r</i> = 0.97-0.99) and RV (<i>r</i> = 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. Conclusion 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. <b>Keywords:</b> MR-Imaging, Cardiac, Heart, Imaging Sequences, Comparative Studies, Technology Assessment <i>Supplemental material is available for this article.</i> © RSNA, 2025.

Radiology Cardiothoracic ImagingVol. 7(2)
Beth Israel Deaconess Medical Center (US)
National Institutes of Health
Openalex Percentile: Top 5%
Advanced MRI Techniques and Applications
5.44
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