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Published in: Journal of Cardiovascular Magnetic Resonance 1/2018

Open Access 01-12-2018 | Research

Simple motion correction strategy reduces respiratory-induced motion artifacts for k-t accelerated and compressed-sensing cardiovascular magnetic resonance perfusion imaging

Authors: Ruixi Zhou, Wei Huang, Yang Yang, Xiao Chen, Daniel S. Weller, Christopher M. Kramer, Sebastian Kozerke, Michael Salerno

Published in: Journal of Cardiovascular Magnetic Resonance | Issue 1/2018

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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.
Literature
1.
go back to reference Atkinson DJ, Burstein D, Edelman RR. First-pass cardiac perfusion: evaluation with ultrafast MR imaging. Radiology. 1990;174:757–62.CrossRefPubMed Atkinson DJ, Burstein D, Edelman RR. First-pass cardiac perfusion: evaluation with ultrafast MR imaging. Radiology. 1990;174:757–62.CrossRefPubMed
2.
go back to reference Schwitter J, Nanz D, Kneifel S, Bertschinger K, Büchi M, Knüsel PR, Marincek B, Lüscher TF, von Schulthess GK. Assessment of myocardial perfusion in coronary artery disease by magnetic resonance. Circulation. 2001;103:2230–5.CrossRefPubMed Schwitter J, Nanz D, Kneifel S, Bertschinger K, Büchi M, Knüsel PR, Marincek B, Lüscher TF, von Schulthess GK. Assessment of myocardial perfusion in coronary artery disease by magnetic resonance. Circulation. 2001;103:2230–5.CrossRefPubMed
3.
go back to reference Watkins S, McGeoch R, Lyne J, Steedman T, Good R, McLaughlin MJ, et al. Validation of magnetic resonance myocardial perfusion imaging with fractional flow reserve for the detection of significant coronary heart disease. Circulation. 2009;120:2207–13.CrossRefPubMed Watkins S, McGeoch R, Lyne J, Steedman T, Good R, McLaughlin MJ, et al. Validation of magnetic resonance myocardial perfusion imaging with fractional flow reserve for the detection of significant coronary heart disease. Circulation. 2009;120:2207–13.CrossRefPubMed
4.
go back to reference Salerno M, Taylor A, Yang Y, Kuruvilla S, Ragosta M, Meyer CH, et al. Adenosine stress cardiovascular magnetic resonance with variable-density spiral pulse sequences accurately detects coronary artery disease initial clinical evaluation. Circ Cardiovasc Imaging. 2014;7:639–46.CrossRefPubMedPubMedCentral Salerno M, Taylor A, Yang Y, Kuruvilla S, Ragosta M, Meyer CH, et al. Adenosine stress cardiovascular magnetic resonance with variable-density spiral pulse sequences accurately detects coronary artery disease initial clinical evaluation. Circ Cardiovasc Imaging. 2014;7:639–46.CrossRefPubMedPubMedCentral
5.
go back to reference Kellman P, Arai AE. Imaging sequences for first pass perfusion—a review. J Cardiovasc Magn Reson. 2007;9:525–37.CrossRefPubMed Kellman P, Arai AE. Imaging sequences for first pass perfusion—a review. J Cardiovasc Magn Reson. 2007;9:525–37.CrossRefPubMed
6.
go back to reference Pruessmann KP, Weiger M, Scheidegger MB, Boesiger P. SENSE: Sensitivity encoding for fast MRI. Magn Reson Med. 1999;42:952–62.CrossRefPubMed Pruessmann KP, Weiger M, Scheidegger MB, Boesiger P. SENSE: Sensitivity encoding for fast MRI. Magn Reson Med. 1999;42:952–62.CrossRefPubMed
7.
go back to reference Griswold MA, Jakob PM, Heidemann RM, Nittka M, Jellus V, Wang J, et al. Generalized autocalibrating partially parallel acquisitions (GRAPPA). Magn Reson Med. 2002;47:1202–10.CrossRefPubMed Griswold MA, Jakob PM, Heidemann RM, Nittka M, Jellus V, Wang J, et al. Generalized autocalibrating partially parallel acquisitions (GRAPPA). Magn Reson Med. 2002;47:1202–10.CrossRefPubMed
8.
go back to reference Kellman P, Epstein FH, McVeigh ER. Adaptive sensitivity encoding incorporating temporal filtering (TSENSE). Magn Reson Med. 2001;45:846–52.CrossRefPubMed Kellman P, Epstein FH, McVeigh ER. Adaptive sensitivity encoding incorporating temporal filtering (TSENSE). Magn Reson Med. 2001;45:846–52.CrossRefPubMed
9.
go back to reference Breuer FA, Kellman P, Griswold MA, Jakob PM. Dynamic autocalibrated parallel imaging using temporal GRAPPA (TGRAPPA). Magn Reson Med. 2005;53:981–5.CrossRefPubMed Breuer FA, Kellman P, Griswold MA, Jakob PM. Dynamic autocalibrated parallel imaging using temporal GRAPPA (TGRAPPA). Magn Reson Med. 2005;53:981–5.CrossRefPubMed
10.
go back to reference Tsao J, Boesiger P, Pruessmann KP. K-t BLAST and k-t SENSE: dynamic MRI with high frame rate exploiting spatiotemporal correlations. Magn Reson Med. 2003;50:1031–42.CrossRefPubMed Tsao J, Boesiger P, Pruessmann KP. K-t BLAST and k-t SENSE: dynamic MRI with high frame rate exploiting spatiotemporal correlations. Magn Reson Med. 2003;50:1031–42.CrossRefPubMed
11.
go back to reference Pedersen H, Kozerke S, Ringgaard S, Nehrke K, Won YK. K-t PCA: temporally constrained k-t BLAST reconstruction using principal component analysis. Magn Reson Med. 2009;62:706–16.CrossRefPubMed Pedersen H, Kozerke S, Ringgaard S, Nehrke K, Won YK. K-t PCA: temporally constrained k-t BLAST reconstruction using principal component analysis. Magn Reson Med. 2009;62:706–16.CrossRefPubMed
12.
go back to reference Plein S, Ryf S, Schwitter J, Radjenovic A, Boesiger P, Kozerke S. Dynamic contrast-enhanced myocardial perfusion MRI accelerated with k-t SENSE. Magn Reson Med. 2007;58:777–85.CrossRefPubMed Plein S, Ryf S, Schwitter J, Radjenovic A, Boesiger P, Kozerke S. Dynamic contrast-enhanced myocardial perfusion MRI accelerated with k-t SENSE. Magn Reson Med. 2007;58:777–85.CrossRefPubMed
13.
go back to reference Manka R, Vitanis V, Boesiger P, Flammer AJ, Plein S, Kozerke S. Clinical feasibility of accelerated, high spatial resolution myocardial perfusion imaging. JACC Cardiovasc. Imaging. Elsevier Inc. 2010;3:710–7.CrossRef Manka R, Vitanis V, Boesiger P, Flammer AJ, Plein S, Kozerke S. Clinical feasibility of accelerated, high spatial resolution myocardial perfusion imaging. JACC Cardiovasc. Imaging. Elsevier Inc. 2010;3:710–7.CrossRef
14.
go back to reference Jogiya R, Schuster A, Zaman A, Motwani M, Kouwenhoven M, Nagel E, et al. Three-dimensional balanced steady state free precession myocardial perfusion cardiovascular magnetic resonance at 3T using dual-source parallel RF transmission: initial experience. J Cardiovasc Magn Reson. 2014;16(1):90.CrossRefPubMedPubMedCentral Jogiya R, Schuster A, Zaman A, Motwani M, Kouwenhoven M, Nagel E, et al. Three-dimensional balanced steady state free precession myocardial perfusion cardiovascular magnetic resonance at 3T using dual-source parallel RF transmission: initial experience. J Cardiovasc Magn Reson. 2014;16(1):90.CrossRefPubMedPubMedCentral
15.
go back to reference Lustig M, Donoho DL, Santos JM, Pauly JM. Compressed sensing MRI. Signal Process Mag IEEE. 2008;25:72–82.CrossRef Lustig M, Donoho DL, Santos JM, Pauly JM. Compressed sensing MRI. Signal Process Mag IEEE. 2008;25:72–82.CrossRef
16.
go back to reference Adluru G, McGann C, Speier P, Kholmovski EG, Shaaban A, Dibella EVR. Acquisition and reconstruction of undersampled radial data for myocardial perfusion magnetic resonance imaging. J Magn Reson Imaging. 2009;29:466–73.CrossRefPubMedPubMedCentral Adluru G, McGann C, Speier P, Kholmovski EG, Shaaban A, Dibella EVR. Acquisition and reconstruction of undersampled radial data for myocardial perfusion magnetic resonance imaging. J Magn Reson Imaging. 2009;29:466–73.CrossRefPubMedPubMedCentral
17.
go back to reference Otazo R, Kim D, Axel L, Sodickson DK. Combination of compressed sensing and parallel imaging for highly accelerated first-pass cardiac perfusion MRI. Magn Reson Med. 2010;64:767–76.CrossRefPubMedPubMedCentral Otazo R, Kim D, Axel L, Sodickson DK. Combination of compressed sensing and parallel imaging for highly accelerated first-pass cardiac perfusion MRI. Magn Reson Med. 2010;64:767–76.CrossRefPubMedPubMedCentral
18.
go back to reference Sharif B, Arsanjani R, Dharmakumar R, Bairey Merz CN, Berman DS, Li D. All-systolic non-ECG-gated myocardial perfusion MRI: feasibility of multi-slice continuous first-pass imaging. Magn Reson Med. 2015;74:1661–74.CrossRefPubMedPubMedCentral Sharif B, Arsanjani R, Dharmakumar R, Bairey Merz CN, Berman DS, Li D. All-systolic non-ECG-gated myocardial perfusion MRI: feasibility of multi-slice continuous first-pass imaging. Magn Reson Med. 2015;74:1661–74.CrossRefPubMedPubMedCentral
19.
go back to reference Feng L, Sodickson DK, Otazo R. Rapid free-breathing dynamic contrast-enhanced MRI using motion-resolved compressed sensing. 2015 IEEE 12th Int. Symp. Biomed. Imaging. New York, NY, USA: IEEE; 2015. p. 889–92. Feng L, Sodickson DK, Otazo R. Rapid free-breathing dynamic contrast-enhanced MRI using motion-resolved compressed sensing. 2015 IEEE 12th Int. Symp. Biomed. Imaging. New York, NY, USA: IEEE; 2015. p. 889–92.
20.
go back to reference Plein S, Kozerke S, Suerder D, Luescher TF, Greenwood JP, Boesiger P, et al. High spatial resolution myocardial perfusion cardiac magnetic resonance for the detection of coronary artery disease. Eur Heart J. 2008;29:2148–55.CrossRefPubMedPubMedCentral Plein S, Kozerke S, Suerder D, Luescher TF, Greenwood JP, Boesiger P, et al. High spatial resolution myocardial perfusion cardiac magnetic resonance for the detection of coronary artery disease. Eur Heart J. 2008;29:2148–55.CrossRefPubMedPubMedCentral
21.
go back to reference Chen X, Salerno M, Yang Y, Epstein FH. Motion-compensated compressed sensing for dynamic contrast-enhanced MRI using regional spatiotemporal sparsity and region tracking: block low-rank sparsity with motion-guidance (BLOSM). Magn Reson Med. 2014;72:1028–38.CrossRefPubMed Chen X, Salerno M, Yang Y, Epstein FH. Motion-compensated compressed sensing for dynamic contrast-enhanced MRI using regional spatiotemporal sparsity and region tracking: block low-rank sparsity with motion-guidance (BLOSM). Magn Reson Med. 2014;72:1028–38.CrossRefPubMed
22.
go back to reference Pedersen H, Kelle S, Ringgaard S, Schnackenburg B, Nagel E, Nehrke K, et al. Quantification of myocardial perfusion using free-breathing MRI and prospective slice tracking. Magn Reson Med. 2009;61:734–8.CrossRefPubMed Pedersen H, Kelle S, Ringgaard S, Schnackenburg B, Nagel E, Nehrke K, et al. Quantification of myocardial perfusion using free-breathing MRI and prospective slice tracking. Magn Reson Med. 2009;61:734–8.CrossRefPubMed
23.
go back to reference Batchelor PG, Atkinson D, Irarrazaval P, Hill DLG, Hajnal J, Larkman D. Matrix description of general motion correction applied to multishot images. Magn Reson Med. 2005;54:1273–80.CrossRefPubMed Batchelor PG, Atkinson D, Irarrazaval P, Hill DLG, Hajnal J, Larkman D. Matrix description of general motion correction applied to multishot images. Magn Reson Med. 2005;54:1273–80.CrossRefPubMed
24.
go back to reference Rao A, Sanchez-Ortiz GI, Chandrashekara R, Lorenzo-Valdés M, Mohiaddin R, Rueckert D. Comparison of cardiac motion across subjects using non-rigid registration. Med. Image Comput. Comput. Interv. — MICCAI 2002, vol. 2488; 2002. p. 722–9. Rao A, Sanchez-Ortiz GI, Chandrashekara R, Lorenzo-Valdés M, Mohiaddin R, Rueckert D. Comparison of cardiac motion across subjects using non-rigid registration. Med. Image Comput. Comput. Interv. — MICCAI 2002, vol. 2488; 2002. p. 722–9.
25.
go back to reference Rueckert D, Lorenzo-valdt M, Chandrashekara R, Mohiaddin R. Non-rigid registration of cardiac MR: application to motion modelling and atlas-based segmentation. Proc. IEEE Int. Symp. Biomed. Imaging. Washington, DC, USA: IEEE; 2002. p. 6–9. Rueckert D, Lorenzo-valdt M, Chandrashekara R, Mohiaddin R. Non-rigid registration of cardiac MR: application to motion modelling and atlas-based segmentation. Proc. IEEE Int. Symp. Biomed. Imaging. Washington, DC, USA: IEEE; 2002. p. 6–9.
26.
go back to reference Royuela-Del-Val J, Cordero-Grande L, Simmross-Wattenberg F, Martin-Fernandez M, Alberola-Lopez C. Nonrigid groupwise registration for motion estimation and compensation in compressed sensing reconstruction of breath-hold cardiac cine MRI. Magn Reson Med. 2016;75:1525–36.CrossRefPubMed Royuela-Del-Val J, Cordero-Grande L, Simmross-Wattenberg F, Martin-Fernandez M, Alberola-Lopez C. Nonrigid groupwise registration for motion estimation and compensation in compressed sensing reconstruction of breath-hold cardiac cine MRI. Magn Reson Med. 2016;75:1525–36.CrossRefPubMed
27.
go back to reference Hansen MS, Sørensen TS, Arai AE, Kellman P. Retrospective reconstruction of high temporal resolution cine images from real-time MRI using iterative motion correction. Magn Reson Med. 2012;68:741–50.CrossRefPubMed Hansen MS, Sørensen TS, Arai AE, Kellman P. Retrospective reconstruction of high temporal resolution cine images from real-time MRI using iterative motion correction. Magn Reson Med. 2012;68:741–50.CrossRefPubMed
28.
go back to reference Lustig M, Pauly JM. SPIRiT: iterative self-consistent parallel imaging reconstruction from arbitrary k-space. Magn Reson Med. 2010;64:457–71.PubMedPubMedCentral Lustig M, Pauly JM. SPIRiT: iterative self-consistent parallel imaging reconstruction from arbitrary k-space. Magn Reson Med. 2010;64:457–71.PubMedPubMedCentral
29.
go back to reference Smriti R, Stredney D, Schmalbrock P, Clymer BD. Image Registration Using Rigid Registration and Maximization of Mutual Information. Long Beach, CA, USA: MMVR13 The 13th Annu. Med. Meets Virtual Real. Conf; 2005. Smriti R, Stredney D, Schmalbrock P, Clymer BD. Image Registration Using Rigid Registration and Maximization of Mutual Information. Long Beach, CA, USA: MMVR13 The 13th Annu. Med. Meets Virtual Real. Conf; 2005.
30.
go back to reference Walsh DO, Gmitro AF, Marcellin MW. Adaptive reconstruction of phased array MR imagery. Magn Reson Med. 2000;43:682–90.CrossRefPubMed Walsh DO, Gmitro AF, Marcellin MW. Adaptive reconstruction of phased array MR imagery. Magn Reson Med. 2000;43:682–90.CrossRefPubMed
31.
go back to reference Cai J-F, Candes EJ, Shen Z. A singular value thresholding algorithm for matrix completion. Soc Ind Appl Math. 2010;20:1956–82. Cai J-F, Candes EJ, Shen Z. A singular value thresholding algorithm for matrix completion. Soc Ind Appl Math. 2010;20:1956–82.
32.
go back to reference Avants BB, Tustison N, Song G. Advanced normalization tools (ANTS). Insight J. 2009:1–35. Avants BB, Tustison N, Song G. Advanced normalization tools (ANTS). Insight J. 2009:1–35.
33.
go back to reference Jung H, Sung K, Nayak KS, Kim EY, Ye JC. K-t FOCUSS: a general compressed sensing framework for high resolution dynamic MRI. Magn Reson Med. 2009;61:103–16.CrossRefPubMed Jung H, Sung K, Nayak KS, Kim EY, Ye JC. K-t FOCUSS: a general compressed sensing framework for high resolution dynamic MRI. Magn Reson Med. 2009;61:103–16.CrossRefPubMed
34.
go back to reference Jung H, Ye JC, Kim EY. Improved k-t BLAST and k-t SENSE using FOCUSS. Phys Med Biol. 2007;52:3201–26.CrossRefPubMed Jung H, Ye JC, Kim EY. Improved k-t BLAST and k-t SENSE using FOCUSS. Phys Med Biol. 2007;52:3201–26.CrossRefPubMed
35.
go back to reference Wissmann L, Santelli C, Segars WP, Kozerke SMRXCAT. Realistic numerical phantoms for cardiovascular magnetic resonance. J Cardiovasc Magn Reson. 2014;16:63.CrossRefPubMedPubMedCentral Wissmann L, Santelli C, Segars WP, Kozerke SMRXCAT. Realistic numerical phantoms for cardiovascular magnetic resonance. J Cardiovasc Magn Reson. 2014;16:63.CrossRefPubMedPubMedCentral
36.
go back to reference Wang Z, Bovik AC, Sheikh HR, Simoncelli EP. Image quality assessment: from error visibility to structural similarity. IEEE Trans Image Process. 2004;13:600–12.CrossRefPubMed Wang Z, Bovik AC, Sheikh HR, Simoncelli EP. Image quality assessment: from error visibility to structural similarity. IEEE Trans Image Process. 2004;13:600–12.CrossRefPubMed
37.
go back to reference Asif MS, Hamilton L, Brummer M, Romberg J. Motion-adaptive spatio-temporal regularization for accelerated dynamic MRI. Magn Reson Med. 2013;70:800–12.CrossRefPubMed Asif MS, Hamilton L, Brummer M, Romberg J. Motion-adaptive spatio-temporal regularization for accelerated dynamic MRI. Magn Reson Med. 2013;70:800–12.CrossRefPubMed
38.
go back to reference Usman M, Atkinson D, Odille F, Kolbitsch C, Vaillant G, Schaeffter T, et al. Motion corrected compressed sensing for free-breathing dynamic cardiac MRI. Magn Reson Med. 2013;70:504–16.CrossRefPubMed Usman M, Atkinson D, Odille F, Kolbitsch C, Vaillant G, Schaeffter T, et al. Motion corrected compressed sensing for free-breathing dynamic cardiac MRI. Magn Reson Med. 2013;70:504–16.CrossRefPubMed
39.
go back to reference Yang Y, Chen X, Epstein FH, Meyer CH, Kuruvilla S, Kramer CM, et al. Motion-corrected compressed-sensing enables robust spiral first-pass perfusion imaging with whole heart coverage. New Orleans, LA, USA: J. Cardiovasc. Magn. Reson; 2014. Yang Y, Chen X, Epstein FH, Meyer CH, Kuruvilla S, Kramer CM, et al. Motion-corrected compressed-sensing enables robust spiral first-pass perfusion imaging with whole heart coverage. New Orleans, LA, USA: J. Cardiovasc. Magn. Reson; 2014.
Metadata
Title
Simple motion correction strategy reduces respiratory-induced motion artifacts for k-t accelerated and compressed-sensing cardiovascular magnetic resonance perfusion imaging
Authors
Ruixi Zhou
Wei Huang
Yang Yang
Xiao Chen
Daniel S. Weller
Christopher M. Kramer
Sebastian Kozerke
Michael Salerno
Publication date
01-12-2018
Publisher
BioMed Central
Published in
Journal of Cardiovascular Magnetic Resonance / Issue 1/2018
Electronic ISSN: 1532-429X
DOI
https://doi.org/10.1186/s12968-018-0427-1

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