Accelerated phase-contrast magnetic resonance imaging with use of resolution enhancement generative adversarial neural network
ABSTRACT: Background: Cardiovascular magnetic resonance (CMR) phase contrast is used to quantify blood flow. We sought to develop a complex-difference reconstruction for inline super-resolution of phase-contrast flow (CRISPFlow) to accelerate phase-contrast imaging. Methods: CRISPFlow was built on...
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| Main Authors: | , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-01-01
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| Series: | Journal of Cardiovascular Magnetic Resonance |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1097664724011554 |
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| Summary: | ABSTRACT: Background: Cardiovascular magnetic resonance (CMR) phase contrast is used to quantify blood flow. We sought to develop a complex-difference reconstruction for inline super-resolution of phase-contrast flow (CRISPFlow) to accelerate phase-contrast imaging. Methods: CRISPFlow was built on the super-resolution generative adversarial network. The model was trained and tested (4:1 ratio) using retrospectively identified phase-contrast images from 2020 patients (56 ± 16 years; 1131 men) referred for clinical 3T CMR at a single center from 2018 to 2023. For testing, ascending aortic flow images collected with 2.5 × 1.9 mm2 resolution using generalized autocalibrating partially parallel acquisitions (GRAPPA) were used to synthesize images with 7.5 × 1.9 mm2 resolution. CRISPFlow subsequently restored spatial resolution. In a prospective validation study of 38 participants (57 ± 15 years; 14 men) and 16 healthy individuals (42 ± 16 years; 6 men), CRISPFlow was applied to phase-contrast images collected with 7.5 × 1.9 mm2 resolution with use of GRAPPA and was compared to GRAPPA-accelerated images collected with 2.3 × 1.9 mm2 resolution. A blur metric was used to quantify sharpness. Aortic flow measurements were obtained semi-automatically. Statistical evaluation included analysis of variance, Bland-Altman analysis, and Pearson correlation coefficient (r). Results: CRISPFlow reconstruction was successful in all cases. CRISPFlow reduced blurring in retrospective (0.35 vs 0.47, P < 0.001) and prospective (0.34 vs 0.48, P < 0.001) images with 7.5 × 1.9 mm2 resolution. Blurring in CRISPFlow images was similar to blurring in images with 2.5 × 1.9 mm2 (0.35 vs 0.35, P = 0.4082) and 2.3 × 1.9 mm2 (0.34 vs 0.32, P < 0.001) resolution. Bland-Altman differences in forward volume (−2 mL [−8 to 3 mL]), regurgitant volume (0 mL [−3 to 2 mL]), and a fraction (0% [−5 to 4%]) showed good agreement between the two techniques in a retrospective cohort. Differences in forward volume (1 mL [−11 to 14 ml]) also showed good agreement in the prospective cohort. There was a strong correlation (all r > 0.90) between GRAPPA and CRISPFlow measurements of flow in both studies. Conclusion: We demonstrated the potential of CRISPFlow to accelerate phase contrast CMR. |
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| ISSN: | 1097-6647 |