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Simple motion correction strategy reduces respiratory-induced motion artifacts for k-t accelerated and compressed-sensing cardiovascular magnetic resonance perfusion imaging.
J Cardiovasc Magn Reson 2018; 20(1):6JC

Abstract

BACKGROUND

Cardiovascular magnetic resonance (CMR) stress perfusion imaging provides important diagnostic and prognostic information in coronary artery disease (CAD). Current clinical sequences have limited temporal and/or spatial resolution, and incomplete heart coverage. Techniques such as k-t principal component analysis (PCA) or k-t sparcity and low rank structure (SLR), which rely on the high degree of spatiotemporal correlation in first-pass perfusion data, can significantly accelerate image acquisition mitigating these problems. However, in the presence of respiratory motion, these techniques can suffer from significant degradation of image quality. A number of techniques based on non-rigid registration have been developed. However, to first approximation, breathing motion predominantly results in rigid motion of the heart. To this end, a simple robust motion correction strategy is proposed for k-t accelerated and compressed sensing (CS) perfusion imaging.

METHODS

A simple respiratory motion compensation (MC) strategy for k-t accelerated and compressed-sensing CMR perfusion imaging to selectively correct respiratory motion of the heart was implemented based on linear k-space phase shifts derived from rigid motion registration of a region-of-interest (ROI) encompassing the heart. A variable density Poisson disk acquisition strategy was used to minimize coherent aliasing in the presence of respiratory motion, and images were reconstructed using k-t PCA and k-t SLR with or without motion correction. The strategy was evaluated in a CMR-extended cardiac torso digital (XCAT) phantom and in prospectively acquired first-pass perfusion studies in 12 subjects undergoing clinically ordered CMR studies. Phantom studies were assessed using the Structural Similarity Index (SSIM) and Root Mean Square Error (RMSE). In patient studies, image quality was scored in a blinded fashion by two experienced cardiologists.

RESULTS

In the phantom experiments, images reconstructed with the MC strategy had higher SSIM (p < 0.01) and lower RMSE (p < 0.01) in the presence of respiratory motion. For patient studies, the MC strategy improved k-t PCA and k-t SLR reconstruction image quality (p < 0.01). The performance of k-t SLR without motion correction demonstrated improved image quality as compared to k-t PCA in the setting of respiratory motion (p < 0.01), while with motion correction there is a trend of better performance in k-t SLR as compared with motion corrected k-t PCA.

CONCLUSIONS

Our simple and robust rigid motion compensation strategy greatly reduces motion artifacts and improves image quality for standard k-t PCA and k-t SLR techniques in setting of respiratory motion due to imperfect breath-holding.

Authors+Show Affiliations

Department of Medicine, University of Virginia Health System, Charlottesville, VA, USA. Department of Biomedical Engineering, University of Virginia Health System, Charlottesville, VA, USA.Department of Medicine, University of Virginia Health System, Charlottesville, VA, USA.Department of Medicine, University of Virginia Health System, Charlottesville, VA, USA. Department of Biomedical Engineering, University of Virginia Health System, Charlottesville, VA, USA.Medical Imaging Technologies, Siemens Healthineers, Princeton, NJ, USA.Department of Electrical and Computer Engineering, University of Virginia, Charlottesville, VA, USA.Department of Medicine, University of Virginia Health System, Charlottesville, VA, USA. Department of Radiology and Medical Imaging, University of Virginia Health System, Charlottesville, VA, USA.Department of Information Technology and Electrical Engineering, Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland.Department of Medicine, University of Virginia Health System, Charlottesville, VA, USA. ms5pc@virginia.edu. Department of Biomedical Engineering, University of Virginia Health System, Charlottesville, VA, USA. ms5pc@virginia.edu. Department of Radiology and Medical Imaging, University of Virginia Health System, Charlottesville, VA, USA. ms5pc@virginia.edu.

Pub Type(s)

Journal Article
Research Support, N.I.H., Extramural

Language

eng

PubMed ID

29386056

Citation

Zhou, Ruixi, et al. "Simple Motion Correction Strategy Reduces Respiratory-induced Motion Artifacts for K-t Accelerated and Compressed-sensing Cardiovascular Magnetic Resonance Perfusion Imaging." Journal of Cardiovascular Magnetic Resonance : Official Journal of the Society for Cardiovascular Magnetic Resonance, vol. 20, no. 1, 2018, p. 6.
Zhou R, Huang W, Yang Y, et al. Simple motion correction strategy reduces respiratory-induced motion artifacts for k-t accelerated and compressed-sensing cardiovascular magnetic resonance perfusion imaging. J Cardiovasc Magn Reson. 2018;20(1):6.
Zhou, R., Huang, W., Yang, Y., Chen, X., Weller, D. S., Kramer, C. M., ... Salerno, M. (2018). Simple motion correction strategy reduces respiratory-induced motion artifacts for k-t accelerated and compressed-sensing cardiovascular magnetic resonance perfusion imaging. Journal of Cardiovascular Magnetic Resonance : Official Journal of the Society for Cardiovascular Magnetic Resonance, 20(1), p. 6. doi:10.1186/s12968-018-0427-1.
Zhou R, et al. Simple Motion Correction Strategy Reduces Respiratory-induced Motion Artifacts for K-t Accelerated and Compressed-sensing Cardiovascular Magnetic Resonance Perfusion Imaging. J Cardiovasc Magn Reson. 2018 02 1;20(1):6. PubMed PMID: 29386056.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Simple motion correction strategy reduces respiratory-induced motion artifacts for k-t accelerated and compressed-sensing cardiovascular magnetic resonance perfusion imaging. AU - Zhou,Ruixi, AU - Huang,Wei, AU - Yang,Yang, AU - Chen,Xiao, AU - Weller,Daniel S, AU - Kramer,Christopher M, AU - Kozerke,Sebastian, AU - Salerno,Michael, Y1 - 2018/02/01/ PY - 2017/08/09/received PY - 2018/01/02/accepted PY - 2018/2/2/entrez PY - 2018/2/2/pubmed PY - 2019/3/15/medline KW - CMR perfusion KW - Image reconstruction KW - K-t acceleration KW - Motion compensation KW - Myocardial perfusion SP - 6 EP - 6 JF - Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance JO - J Cardiovasc Magn Reson VL - 20 IS - 1 N2 - BACKGROUND: Cardiovascular magnetic resonance (CMR) stress perfusion imaging provides important diagnostic and prognostic information in coronary artery disease (CAD). Current clinical sequences have limited temporal and/or spatial resolution, and incomplete heart coverage. Techniques such as k-t principal component analysis (PCA) or k-t sparcity and low rank structure (SLR), which rely on the high degree of spatiotemporal correlation in first-pass perfusion data, can significantly accelerate image acquisition mitigating these problems. However, in the presence of respiratory motion, these techniques can suffer from significant degradation of image quality. A number of techniques based on non-rigid registration have been developed. However, to first approximation, breathing motion predominantly results in rigid motion of the heart. To this end, a simple robust motion correction strategy is proposed for k-t accelerated and compressed sensing (CS) perfusion imaging. METHODS: A simple respiratory motion compensation (MC) strategy for k-t accelerated and compressed-sensing CMR perfusion imaging to selectively correct respiratory motion of the heart was implemented based on linear k-space phase shifts derived from rigid motion registration of a region-of-interest (ROI) encompassing the heart. A variable density Poisson disk acquisition strategy was used to minimize coherent aliasing in the presence of respiratory motion, and images were reconstructed using k-t PCA and k-t SLR with or without motion correction. The strategy was evaluated in a CMR-extended cardiac torso digital (XCAT) phantom and in prospectively acquired first-pass perfusion studies in 12 subjects undergoing clinically ordered CMR studies. Phantom studies were assessed using the Structural Similarity Index (SSIM) and Root Mean Square Error (RMSE). In patient studies, image quality was scored in a blinded fashion by two experienced cardiologists. RESULTS: In the phantom experiments, images reconstructed with the MC strategy had higher SSIM (p < 0.01) and lower RMSE (p < 0.01) in the presence of respiratory motion. For patient studies, the MC strategy improved k-t PCA and k-t SLR reconstruction image quality (p < 0.01). The performance of k-t SLR without motion correction demonstrated improved image quality as compared to k-t PCA in the setting of respiratory motion (p < 0.01), while with motion correction there is a trend of better performance in k-t SLR as compared with motion corrected k-t PCA. CONCLUSIONS: Our simple and robust rigid motion compensation strategy greatly reduces motion artifacts and improves image quality for standard k-t PCA and k-t SLR techniques in setting of respiratory motion due to imperfect breath-holding. SN - 1532-429X UR - https://www.unboundmedicine.com/medline/citation/29386056/Simple_motion_correction_strategy_reduces_respiratory_induced_motion_artifacts_for_k_t_accelerated_and_compressed_sensing_cardiovascular_magnetic_resonance_perfusion_imaging_ L2 - https://jcmr-online.biomedcentral.com/articles/10.1186/s12968-018-0427-1 DB - PRIME DP - Unbound Medicine ER -