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Wang J, Salerno M. Deep learning-based rapid image reconstruction and motion correction for high-resolution cartesian first-pass myocardial perfusion imaging at 3T. Magn Reson Med 2024; 92:1104-1114. [PMID: 38576068 DOI: 10.1002/mrm.30106] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2023] [Revised: 03/19/2024] [Accepted: 03/19/2024] [Indexed: 04/06/2024]
Abstract
PURPOSE To develop and evaluate a deep learning (DL) -based rapid image reconstruction and motion correction technique for high-resolution Cartesian first-pass myocardial perfusion imaging at 3T with whole-heart coverage for both single-slice (SS) and simultaneous multi-slice (SMS) acquisitions. METHODS 3D physics-driven unrolled network architectures were utilized for the reconstruction of high-resolution Cartesian perfusion imaging. The SS and SMS multiband (MB) = 2 networks were trained from 135 slices from 20 subjects. Structural similarity index (SSIM), peak SNR (PSNR), and normalized RMS error (NRMSE) were assessed, and prospective images were blindly graded by two experienced cardiologists (5, excellent; 1, poor). For respiratory motion correction, a 2D U-Net based motion corrected network was proposed, and the temporal fidelity and second-order derivative were calculated to assess the performance of the motion correction. RESULTS Excellent performance was demonstrated in the proposed technique with high SSIM and PSNR, and low NRMSE. Image quality scores were (4.3 [4.3, 4.4], 4.5 [4.4, 4.6], 4.3 [4.3, 4.4], and 4.5 [4.3, 4.5]) for SS DL and SS L1-SENSE, MB = 2 DL and MB = 2 SMS-L1-SENSE, respectively, showing no statistically significant difference (p > 0.05 for SS and SMS) between (SMS)-L1-SENSE and the proposed DL technique. The network inference time was around 4 s per dynamic perfusion series with 40 frames while the time of (SMS)-L1-SENSE with GPU acceleration was approximately 30 min. CONCLUSION The proposed DL-based image reconstruction and motion correction technique enabled rapid and high-quality reconstruction for SS and SMS MB = 2 high-resolution Cartesian first-pass perfusion imaging at 3T.
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Affiliation(s)
- Junyu Wang
- Department of Cardiovascular Medicine, Stanford University, Stanford, California, USA
| | - Michael Salerno
- Department of Cardiovascular Medicine, Stanford University, Stanford, California, USA
- Department of Radiology, Cardiovascular Imaging, Stanford University, Stanford, California, USA
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Adam NL, Kowalik G, Tyler A, Mooiweer R, Neofytou AP, McElroy S, Kunze K, Speier P, Stäb D, Neji R, Nazir MS, Razavi R, Chiribiri A, Roujol S. Fast reconstruction of SMS bSSFP myocardial perfusion images using noise map estimation network (NoiseMapNet): a head-to-head comparison with parallel imaging and iterative reconstruction. Front Cardiovasc Med 2024; 11:1350345. [PMID: 39055659 PMCID: PMC11269255 DOI: 10.3389/fcvm.2024.1350345] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Accepted: 06/13/2024] [Indexed: 07/27/2024] Open
Abstract
Background Simultaneous multi-slice (SMS) bSSFP imaging enables stress myocardial perfusion imaging with high spatial resolution and increased spatial coverage. Standard parallel imaging techniques (e.g., TGRAPPA) can be used for image reconstruction but result in high noise level. Alternatively, iterative reconstruction techniques based on temporal regularization (ITER) improve image quality but are associated with reduced temporal signal fidelity and long computation time limiting their online use. The aim is to develop an image reconstruction technique for SMS-bSSFP myocardial perfusion imaging combining parallel imaging and image-based denoising using a novel noise map estimation network (NoiseMapNet), which preserves both sharpness and temporal signal profiles and that has low computational cost. Methods The proposed reconstruction of SMS images consists of a standard temporal parallel imaging reconstruction (TGRAPPA) with motion correction (MOCO) followed by image denoising using NoiseMapNet. NoiseMapNet is a deep learning network based on a 2D Unet architecture and aims to predict a noise map from an input noisy image, which is then subtracted from the noisy image to generate the denoised image. This approach was evaluated in 17 patients who underwent stress perfusion imaging using a SMS-bSSFP sequence. Images were reconstructed with (a) TGRAPPA with MOCO (thereafter referred to as TGRAPPA), (b) iterative reconstruction with integrated motion compensation (ITER), and (c) proposed NoiseMapNet-based reconstruction. Normalized mean squared error (NMSE) with respect to TGRAPPA, myocardial sharpness, image quality, perceived SNR (pSNR), and number of diagnostic segments were evaluated. Results NMSE of NoiseMapNet was lower than using ITER for both myocardium (0.045 ± 0.021 vs. 0.172 ± 0.041, p < 0.001) and left ventricular blood pool (0.025 ± 0.014 vs. 0.069 ± 0.020, p < 0.001). There were no significant differences between all methods for myocardial sharpness (p = 0.77) and number of diagnostic segments (p = 0.36). ITER led to higher image quality than NoiseMapNet/TGRAPPA (2.7 ± 0.4 vs. 1.8 ± 0.4/1.3 ± 0.6, p < 0.001) and higher pSNR than NoiseMapNet/TGRAPPA (3.0 ± 0.0 vs. 2.0 ± 0.0/1.3 ± 0.6, p < 0.001). Importantly, NoiseMapNet yielded higher pSNR (p < 0.001) and image quality (p < 0.008) than TGRAPPA. Computation time of NoiseMapNet was only 20s for one entire dataset. Conclusion NoiseMapNet-based reconstruction enables fast SMS image reconstruction for stress myocardial perfusion imaging while preserving sharpness and temporal signal profiles.
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Affiliation(s)
- Naledi Lenah Adam
- School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King’s College London, London, United Kingdom
| | - Grzegorz Kowalik
- School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King’s College London, London, United Kingdom
| | - Andrew Tyler
- School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King’s College London, London, United Kingdom
| | - Ronald Mooiweer
- School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King’s College London, London, United Kingdom
- MR Research Collaborations, Siemens Healthcare Limited, Camberley, United Kingdom
| | - Alexander Paul Neofytou
- School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King’s College London, London, United Kingdom
| | - Sarah McElroy
- School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King’s College London, London, United Kingdom
- MR Research Collaborations, Siemens Healthcare Limited, Camberley, United Kingdom
| | - Karl Kunze
- School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King’s College London, London, United Kingdom
- MR Research Collaborations, Siemens Healthcare Limited, Camberley, United Kingdom
| | - Peter Speier
- Cardiovascular Predevelopment, Siemens Healthcare GmbH, Erlangen, Germany
| | - Daniel Stäb
- MR Research Collaborations, Siemens Healthcare Limited, Melbourne, VIC, Australia
| | - Radhouene Neji
- School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King’s College London, London, United Kingdom
- MR Research Collaborations, Siemens Healthcare Limited, Camberley, United Kingdom
| | - Muhummad Sohaib Nazir
- School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King’s College London, London, United Kingdom
- Royal Brompton Hospital, Guy’s and St Thomas NHS Foundation Trust, London, United Kingdom
| | - Reza Razavi
- School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King’s College London, London, United Kingdom
| | - Amedeo Chiribiri
- School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King’s College London, London, United Kingdom
| | - Sébastien Roujol
- School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King’s College London, London, United Kingdom
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Scannell CM, Crawley R, Alskaf E, Breeuwer M, Plein S, Chiribiri A. High-resolution quantification of stress perfusion defects by cardiac magnetic resonance. EUROPEAN HEART JOURNAL. IMAGING METHODS AND PRACTICE 2024; 2:qyae001. [PMID: 38283662 PMCID: PMC10810243 DOI: 10.1093/ehjimp/qyae001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/15/2023] [Accepted: 01/04/2024] [Indexed: 01/30/2024]
Abstract
Aims Quantitative stress perfusion cardiac magnetic resonance (CMR) is becoming more widely available, but it is still unclear how to integrate this information into clinical decision-making. Typically, pixel-wise perfusion maps are generated, but diagnostic and prognostic studies have summarized perfusion as just one value per patient or in 16 myocardial segments. In this study, the reporting of quantitative perfusion maps is extended from the standard 16 segments to a high-resolution bullseye. Cut-off thresholds are established for the high-resolution bullseye, and the identified perfusion defects are compared with visual assessment. Methods and results Thirty-four patients with known or suspected coronary artery disease were retrospectively analysed. Visual perfusion defects were contoured on the CMR images and pixel-wise quantitative perfusion maps were generated. Cut-off values were established on the high-resolution bullseye consisting of 1800 points and compared with the per-segment, per-coronary, and per-patient resolution thresholds. Quantitative stress perfusion was significantly lower in visually abnormal pixels, 1.11 (0.75-1.57) vs. 2.35 (1.82-2.9) mL/min/g (Mann-Whitney U test P < 0.001), with an optimal cut-off of 1.72 mL/min/g. This was lower than the segment-wise optimal threshold of 1.92 mL/min/g. The Bland-Altman analysis showed that visual assessment underestimated large perfusion defects compared with the quantification with good agreement for smaller defect burdens. A Dice overlap of 0.68 (0.57-0.78) was found. Conclusion This study introduces a high-resolution bullseye consisting of 1800 points, rather than 16, per patient for reporting quantitative stress perfusion, which may improve sensitivity. Using this representation, the threshold required to identify areas of reduced perfusion is lower than for segmental analysis.
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Affiliation(s)
- Cian M Scannell
- Department of Biomedical Engineering, Eindhoven University of Technology, Groene Loper 5, 5612 AEEindhoven, The Netherlands
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
| | - Richard Crawley
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
| | - Ebraham Alskaf
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
| | - Marcel Breeuwer
- Department of Biomedical Engineering, Eindhoven University of Technology, Groene Loper 5, 5612 AEEindhoven, The Netherlands
| | - Sven Plein
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
- Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds LS2 9JT, UK
| | - Amedeo Chiribiri
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK
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Demirel ÖB, Weingärtner S, Moeller S, Akçakaya M. Improved Simultaneous Multi-slice imaging with Composition of k-space Interpolations (SMS-COOKIE) for myocardial T1 mapping. PLoS One 2023; 18:e0283972. [PMID: 37478080 PMCID: PMC10361528 DOI: 10.1371/journal.pone.0283972] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2022] [Accepted: 03/21/2023] [Indexed: 07/23/2023] Open
Abstract
The aim of this study is to develop and evaluate a regularized Simultaneous Multi-Slice (SMS) reconstruction method for improved Cardiac Magnetic Resonance Imaging (CMR). The proposed reconstruction method, SMS with COmpOsition of k-space IntErpolations (SMS-COOKIE) combines the advantages of Iterative Self-consistent Parallel Imaging Reconstruction (SPIRiT) and split slice-Generalized Autocalibrating Partially Parallel Acquisitions (GRAPPA), while allowing regularization for further noise reduction. The proposed SMS-COOKIE was implemented with and without regularization, and validated using a Saturation Pulse-Prepared Heart rate Independent inversion REcovery (SAPPHIRE) myocardial T1 mapping sequence. The performance of the proposed reconstruction method was compared to ReadOut (RO)-SENSE-GRAPPA and split slice-GRAPPA, on both retrospectively and prospectively three-fold SMS-accelerated data with an additional two-fold in-plane acceleration. All SMS reconstruction methods yielded similar T1 values compared to single band imaging. SMS-COOKIE showed lower spatial variability in myocardial T1 with significant improvement over RO-SENSE-GRAPPA and split slice-GRAPPA (P < 10-4). The proposed method with additional locally low rank (LLR) regularization reduced the spatial variability, again with significant improvement over RO-SENSE-GRAPPA and split slice-GRAPPA (P < 10-4). In conclusion, improved reconstruction quality was achieved with the proposed SMS-COOKIE, which also provided lower spatial variability with significant improvement over split slice-GRAPPA.
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Affiliation(s)
- Ömer Burak Demirel
- Electrical and Computer Engineering, University of Minnesota, Minneapolis, Minnesota, United States of America
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, Minnesota, United States of America
| | - Sebastian Weingärtner
- Department of Imaging Physics, Delft University of Technology, Delft, The Netherlands
| | - Steen Moeller
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, Minnesota, United States of America
| | - Mehmet Akçakaya
- Electrical and Computer Engineering, University of Minnesota, Minneapolis, Minnesota, United States of America
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, Minnesota, United States of America
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Pan Z, Ma X, Dai E, Auerbach EJ, Guo H, Uğurbil K, Wu X. Reconstruction for 7T high-resolution whole-brain diffusion MRI using two-stage N/2 ghost correction and L1-SPIRiT without single-band reference. Magn Reson Med 2023; 89:1915-1930. [PMID: 36594439 PMCID: PMC9992311 DOI: 10.1002/mrm.29573] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Revised: 11/28/2022] [Accepted: 12/19/2022] [Indexed: 01/04/2023]
Abstract
PURPOSE To combine a new two-stage N/2 ghost correction and an adapted L1-SPIRiT method for reconstruction of 7T highly accelerated whole-brain diffusion MRI (dMRI) using only autocalibration scans (ACS) without the need of additional single-band reference (SBref) scans. METHODS The proposed ghost correction consisted of a 3-line reference approach in stage 1 and the reference-free entropy method in stage 2. The adapted L1-SPIRiT method was formulated within the 3D k-space framework. Its efficacy was examined by acquiring two dMRI data sets at 1.05-mm isotropic resolutions with a total acceleration of 6 or 9 (i.e., 2-fold or 3-fold slice and 3-fold in-plane acceleration). Diffusion analysis was performed to derive DTI metrics and estimate fiber orientation distribution functions (fODFs). The results were compared with those of 3D k-space GRAPPA using only ACS, all in reference to 3D k-space GRAPPA using both ACS and SBref (serving as a reference). RESULTS The proposed ghost correction eliminated artifacts more robustly than conventional approaches. Our adapted L1-SPIRiT method outperformed 3D k-space GRAPPA when using only ACS, improving image quality to what was achievable with 3D k-space GRAPPA using both ACS and SBref scans. The improvement in image quality further resulted in an improvement in estimation performances for DTI and fODFs. CONCLUSION The combination of our new ghost correction and adapted L1-SPIRiT method can reliably reconstruct 7T highly accelerated whole-brain dMRI without the need of SBref scans, increasing acquisition efficiency and reducing motion sensitivity.
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Affiliation(s)
- Ziyi Pan
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China
| | - Xiaodong Ma
- Center for Magnetic Resonance Research, Radiology, Medical School, University of Minnesota, Minneapolis, MN, United States
| | - Erpeng Dai
- Department of Radiology, Stanford University, Stanford, CA, United States
| | - Edward J. Auerbach
- Center for Magnetic Resonance Research, Radiology, Medical School, University of Minnesota, Minneapolis, MN, United States
| | - Hua Guo
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China
| | - Kâmil Uğurbil
- Center for Magnetic Resonance Research, Radiology, Medical School, University of Minnesota, Minneapolis, MN, United States
| | - Xiaoping Wu
- Center for Magnetic Resonance Research, Radiology, Medical School, University of Minnesota, Minneapolis, MN, United States
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Huang Q, Tian Y, Mendes J, Ranjan R, Adluru G, DiBella E. Quantitative myocardial perfusion with a hybrid 2D simultaneous multi-slice sequence. Magn Reson Imaging 2023; 98:7-16. [PMID: 36563888 PMCID: PMC10474933 DOI: 10.1016/j.mri.2022.12.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Accepted: 12/17/2022] [Indexed: 12/24/2022]
Abstract
PURPOSE To evaluate a novel 2D simultaneous multi-slice (SMS) myocardial perfusion acquisition and compare directly to a published quantitative 3D stack-of-stars (SoS) acquisition. METHODS A hybrid saturation recovery radial 2D SMS sequence following a single saturation was created for the quantification of myocardial blood flow (MBF). This sequence acquired three slices simultaneously and generated an arterial input function (AIF) using the first 24 rays. Validation was done in a novel way by alternating heartbeats between the hybrid 2D SMS and the 3D SoS acquisitions. Initial studies were done to study the effects of using only every other beat for the 2D SMS in two subjects, and for the 3D SoS in four subjects. The proposed alternating acquisitions were then performed in ten dog studies at rest, four dog studies at adenosine stress, and two human resting studies. Quantitative MBF analysis was performed for 2D SMS and 3D SoS separately, using a compartment model. RESULTS Acquiring every-other-beat data resulted in 6 ± 5% ("ideal") and 11 ± 8% ("practical") perfusion changes for both 2D SMS and 3D SoS methods. For alternating acquisitions, 2D SMS and 3D SoS quantitative perfusion values were comparable for both the twelve rest studies (2D SMS: 0.69 ± 0.16 vs 3D: 0.69 ± 0.15 ml/g/min, p = 0.55) and the four stress studies (2D SMS: 1.28 ± 0.22 vs 3D: 1.30 ± 0.24 ml/g/min, p = 0.61). CONCLUSION Every-other-beat acquisition changed estimated perfusion values relatively little for both sequences. The quantitative hybrid radial 2D SMS myocardial first-pass perfusion imaging sequence gave results similar to 3D perfusion when compared directly with an alternating beat acquisition.
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Affiliation(s)
- Qi Huang
- Utah Center for Advanced Imaging Research (UCAIR), Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, UT, USA; Department of Biomedical Engineering, University of Utah, Salt Lake City, UT, USA.
| | - Ye Tian
- Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA, USA
| | - Jason Mendes
- Utah Center for Advanced Imaging Research (UCAIR), Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, UT, USA
| | - Ravi Ranjan
- Division of Cardiovascular Medicine, University of Utah, Salt Lake City, UT, USA
| | - Ganesh Adluru
- Utah Center for Advanced Imaging Research (UCAIR), Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, UT, USA; Department of Biomedical Engineering, University of Utah, Salt Lake City, UT, USA
| | - Edward DiBella
- Utah Center for Advanced Imaging Research (UCAIR), Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, UT, USA; Department of Biomedical Engineering, University of Utah, Salt Lake City, UT, USA
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Tian Y, Cui SX, Lim Y, Lee NG, Zhao Z, Nayak KS. Contrast-optimal simultaneous multi-slice bSSFP cine cardiac imaging at 0.55 T. Magn Reson Med 2023; 89:746-755. [PMID: 36198043 PMCID: PMC9712243 DOI: 10.1002/mrm.29472] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Revised: 09/06/2022] [Accepted: 09/06/2022] [Indexed: 12/13/2022]
Abstract
PURPOSE To determine if contemporary 0.55 T MRI supports the use of contrast-optimal flip angles (FA) for simultaneous multi-slice (SMS) balanced SSFP (bSSFP) cardiac function assessment, which is impractical at conventional field strengths because of excessive SAR and/or banding artifacts. METHODS Blipped-CAIPI bSSFP was combined with spiral sampling for ventricular function assessment at 0.55 T. Cine movies with single band and SMS factors of 2 and 3 (SMS 2 and 3), and FA ranging from 60° to 160°, were acquired in seven healthy volunteers. Left ventricular blood and myocardial signal intensity (SI) normalized by background noise and blood-myocardium contrast were measured and compared across acquisition settings. RESULTS Myocardial SI was slightly higher in single band than in SMS and decreased with an increasing FA. Blood SI increased as the FA increased for single band, and increment was small for FA ≥120°. Blood SI for SMS 2 and 3 increased with an increasing FA up to ∼100°. Blood-myocardium contrast increased with an increasing FA for single band, peaked at FA = 160° (systole: 28.43, diastole: 29.15), attributed mainly to reduced myocardial SI when FA ≥120°. For SMS 2, contrast peaked at 120° (systole: 21.43, diastole: 19.85). For SMS 3, contrast peaked at 120° in systole (16.62) and 100° in diastole (19.04). CONCLUSIONS Contemporary 0.55 T MR scanners equipped with high-performance gradient systems allow the use of contrast-optimal FA for SMS accelerated bSSFP cine examinations without compromising image quality. The contrast-optimal FA was found to be 140° to 160° for single band and 100° to 120° for SMS 2 and 3.
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Affiliation(s)
- Ye Tian
- Ming Hsieh Department of Electrical and Computer Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, USA
| | - Sophia X. Cui
- Siemens Medical Solutions USA Inc., Los Angeles, CA, USA
| | - Yongwan Lim
- Ming Hsieh Department of Electrical and Computer Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, USA
| | - Nam G. Lee
- Department of Biomedical Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, USA
| | - Ziwei Zhao
- Ming Hsieh Department of Electrical and Computer Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, USA
| | - Krishna S. Nayak
- Ming Hsieh Department of Electrical and Computer Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, USA,Department of Biomedical Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, USA
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Bentatou Z, Troalen T, Bernard M, Guye M, Pini L, Bartoli A, Jacquier A, Kober F, Rapacchi S. Simultaneous multi-slice T1 mapping using MOLLI with blipped CAIPIRINHA bSSFP. Magn Reson Imaging 2023; 95:90-102. [PMID: 32304799 DOI: 10.1016/j.mri.2020.03.006] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2020] [Revised: 03/02/2020] [Accepted: 03/25/2020] [Indexed: 12/15/2022]
Abstract
BACKGROUND This study evaluates the possibility for replacing conventional 3 slices, 3 breath-holds MOLLI cardiac T1 mapping with single breath-hold 3 simultaneous multi-slice (SMS3) T1 mapping using blipped-CAIPIRINHA SMS-bSSFP MOLLI sequence. As a major drawback, SMS-bSSFP presents unique artefacts arising from side-lobe slice excitations that are explained by imperfect RF modulation rendering and bSSFP low flip angle enhancement. Amplitude-only RF modulation (AM) is proposed to reduce these artefacts in SMS-MOLLI compared to conventional Wong multi-band RF modulation (WM). MATERIALS AND METHODS Phantoms and ten healthy volunteers were imaged at 1.5 T using a modified blipped-CAIPIRINHA SMS-bSSFP MOLLI sequence with 3 simultaneous slices. WM-SMS3 and AM-SMS3 were compared to conventional single-slice (SMS1) MOLLI. First, SNR degradation and T1 accuracy were measured in phantoms. Second, artefacts from side-lobe excitations were evaluated in a phantom designed to reproduce fat presence near the heart. Third, the occurrence of these artefacts was observed in volunteers, and their impact on T1 quantification was compared between WM-SMS3 and AM-SMS3 with conventional MOLLI as a reference. RESULTS In the phantom, larger slice gaps and slice thicknesses yielded higher SNR. There was no significant difference of T1 values between conventional MOLLI and SMS3-MOLLI (both WM and AM). Positive banding artefacts were identified from fat neighbouring the targeted FOV due to side-lobe excitations from WM and the unique bSSFP signal profile. AM RF pulses reduced these artefacts by 38%. In healthy volunteers, AM-SMS3-MOLLI showed similar artefact reduction compared to WM-SMS3-MOLLI (3 ± 2 vs 5 ± 3 corrupted LV segments out of 16). In-vivo native T1 values obtained from conventional MOLLI and AM-SMS3-MOLLI were equivalent in LV myocardium (SMS1-T1 = 935.5 ± 36.1 ms; AM-SMS3-T1 = 933.8 ± 50.2 ms; P = 0.436) and LV blood pool (SMS1-T1 = 1475.4 ± 35.9 ms; AM-SMS3-T1 = 1452.5 ± 70.3 ms; P = 0.515). Identically, no differences were found between SMS1 and SMS3 postcontrast T1 values in the myocardium (SMS1-T1 = 556.0 ± 19.7 ms; SMS3-T1 = 521.3 ± 28.1 ms; P = 0.626) and the blood (SMS1-T1 = 478 ± 65.1 ms; AM-SMS3-T1 = 447.8 ± 81.5; P = 0.085). CONCLUSIONS Compared to WM RF modulation, AM SMS-bSSFP MOLLI was able to reduce side-lobe artefacts considerably, providing promising results to image the three levels of the heart in a single breath hold. However, few artefacts remained even using AM-SMS-bSSFP due to residual RF imperfections. The proposed blipped-CAIPIRINHA MOLLI T1 mapping sequence provides accurate in vivo T1 quantification in line with those obtained with a single slice acquisition.
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Affiliation(s)
- Zakarya Bentatou
- Aix Marseille Univ, CNRS, CRMBM, Marseille, France; APHM, Hôpital Universitaire Timone, CEMEREM, Marseille, France; Siemens Healthcare SAS, Saint-Denis, France.
| | | | | | - Maxime Guye
- Aix Marseille Univ, CNRS, CRMBM, Marseille, France; APHM, Hôpital Universitaire Timone, CEMEREM, Marseille, France.
| | - Lauriane Pini
- Aix Marseille Univ, CNRS, CRMBM, Marseille, France; APHM, Hôpital Universitaire Timone, CEMEREM, Marseille, France.
| | - Axel Bartoli
- APHM, Hôpital Universitaire Timone, Service de Radiologie, Marseille, France.
| | - Alexis Jacquier
- Aix Marseille Univ, CNRS, CRMBM, Marseille, France; APHM, Hôpital Universitaire Timone, Service de Radiologie, Marseille, France.
| | - Frank Kober
- Aix Marseille Univ, CNRS, CRMBM, Marseille, France.
| | - Stanislas Rapacchi
- Aix Marseille Univ, CNRS, CRMBM, Marseille, France; APHM, Hôpital Universitaire Timone, CEMEREM, Marseille, France.
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Demirel OB, Yaman B, Shenoy C, Moeller S, Weingärtner S, Akçakaya M. Signal intensity informed multi-coil encoding operator for physics-guided deep learning reconstruction of highly accelerated myocardial perfusion CMR. Magn Reson Med 2023; 89:308-321. [PMID: 36128896 PMCID: PMC9617789 DOI: 10.1002/mrm.29453] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Revised: 07/21/2022] [Accepted: 08/21/2022] [Indexed: 01/11/2023]
Abstract
PURPOSE To develop a physics-guided deep learning (PG-DL) reconstruction strategy based on a signal intensity informed multi-coil (SIIM) encoding operator for highly-accelerated simultaneous multislice (SMS) myocardial perfusion cardiac MRI (CMR). METHODS First-pass perfusion CMR acquires highly-accelerated images with dynamically varying signal intensity/SNR following the administration of a gadolinium-based contrast agent. Thus, using PG-DL reconstruction with a conventional multi-coil encoding operator leads to analogous signal intensity variations across different time-frames at the network output, creating difficulties in generalization for varying SNR levels. We propose to use a SIIM encoding operator to capture the signal intensity/SNR variations across time-frames in a reformulated encoding operator. This leads to a more uniform/flat contrast at the output of the PG-DL network, facilitating generalizability across time-frames. PG-DL reconstruction with the proposed SIIM encoding operator is compared to PG-DL with conventional encoding operator, split slice-GRAPPA, locally low-rank (LLR) regularized reconstruction, low-rank plus sparse (L + S) reconstruction, and regularized ROCK-SPIRiT. RESULTS Results on highly accelerated free-breathing first pass myocardial perfusion CMR at three-fold SMS and four-fold in-plane acceleration show that the proposed method improves upon the reconstruction methods use for comparison. Substantial noise reduction is achieved compared to split slice-GRAPPA, and aliasing artifacts reduction compared to LLR regularized reconstruction, L + S reconstruction and PG-DL with conventional encoding. Furthermore, a qualitative reader study indicated that proposed method outperformed all methods. CONCLUSION PG-DL reconstruction with the proposed SIIM encoding operator improves generalization across different time-frames /SNRs in highly accelerated perfusion CMR.
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Affiliation(s)
- Omer Burak Demirel
- Department of Electrical and Computer EngineeringUniversity of MinnesotaMinneapolisMinnesotaUSA,Center for Magnetic Resonance ResearchUniversity of MinnesotaMinneapolisMinnesotaUSA
| | - Burhaneddin Yaman
- Department of Electrical and Computer EngineeringUniversity of MinnesotaMinneapolisMinnesotaUSA,Center for Magnetic Resonance ResearchUniversity of MinnesotaMinneapolisMinnesotaUSA
| | - Chetan Shenoy
- Department of Medicine (Cardiology)University of MinnesotaMinneapolisMinnesotaUSA
| | - Steen Moeller
- Center for Magnetic Resonance ResearchUniversity of MinnesotaMinneapolisMinnesotaUSA
| | | | - Mehmet Akçakaya
- Department of Electrical and Computer EngineeringUniversity of MinnesotaMinneapolisMinnesotaUSA,Center for Magnetic Resonance ResearchUniversity of MinnesotaMinneapolisMinnesotaUSA
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10
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Sun C, Robinson A, Wang Y, Bilchick KC, Kramer CM, Weller D, Salerno M, Epstein FH. A Slice-Low-Rank Plus Sparse (slice-L + S) Reconstruction Method for k-t Undersampled Multiband First-Pass Myocardial Perfusion MRI. Magn Reson Med 2022; 88:1140-1155. [PMID: 35608225 PMCID: PMC9325064 DOI: 10.1002/mrm.29281] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2021] [Revised: 03/14/2022] [Accepted: 04/11/2022] [Indexed: 11/19/2022]
Abstract
PURPOSE The synergistic use of k-t undersampling and multiband (MB) imaging has the potential to provide extended slice coverage and high spatial resolution for first-pass perfusion MRI. The low-rank plus sparse (L + S) model has shown excellent performance for accelerating single-band (SB) perfusion MRI. METHODS A MB data consistency method employing ESPIRiT maps and through-plane coil information was developed. This data consistency method was combined with the temporal L + S constraint to form the slice-L + S method. Slice-L + S was compared to SB L + S and the sequential operations of split slice-GRAPPA and SB L + S (seq-SG-L + S) using synthetic data formed from multislice SB images. Prospectively k-t undersampled MB data were also acquired and reconstructed using seq-SG-L + S and slice-L + S. RESULTS Using synthetic data with total acceleration rates of 6-12, slice-L + S outperformed SB L + S and seq-SG-L + S (N = 7 subjects) with respect to normalized RMSE and the structural similarity index (P < 0.05 for both). For the specific case with MB factor = 3 and rate 3 undersampling, or for SB imaging with rate 9 undersampling (N = 7 subjects), the normalized RMSE values were 0.037 ± 0.007, 0.042 ± 0.005, and 0.031 ± 0.004; and the structural similarity index values were 0.88 ± 0.03, 0.85 ± 0.03, and 0.89 ± 0.02 for SB L + S, seq-SG-L + S, and slice-L + S, respectively (P < 0.05 for both). For prospectively undersampled MB data, slice-L + S provided better image quality than seq-SG-L + S for rate 6 (N = 7) and rate 9 acceleration (N = 7) as scored by blinded experts. CONCLUSION Slice-L + S outperformed SB-L + S and seq-SG-L + S and provides 9 slice coverage of the left ventricle with a spatial resolution of 1.5 mm × 1.5 mm with good image quality.
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Affiliation(s)
- Changyu Sun
- Department of Biomedical EngineeringUniversity of VirginiaCharlottesvilleVirginia
- Department of Biomedical, Biological and Chemical EngineeringUniversity of MissouriColumbiaMissouri
- Department of RadiologyUniversity of MissouriColumbiaMissouri
| | - Austin Robinson
- Department of MedicineUniversity of Virginia Health SystemCharlottesvilleVirginia
| | - Yu Wang
- Department of Biomedical EngineeringUniversity of VirginiaCharlottesvilleVirginia
| | - Kenneth C. Bilchick
- Department of MedicineUniversity of Virginia Health SystemCharlottesvilleVirginia
| | - Christopher M. Kramer
- Department of MedicineUniversity of Virginia Health SystemCharlottesvilleVirginia
- Department of RadiologyUniversity of Virginia Health SystemCharlottesvilleVirginia
| | - Daniel Weller
- Department of Biomedical EngineeringUniversity of VirginiaCharlottesvilleVirginia
- Department of RadiologyUniversity of Virginia Health SystemCharlottesvilleVirginia
- Department of Electrical and Computer EngineeringUniversity of VirginiaCharlottesvilleVirginia
| | - Michael Salerno
- Department of Biomedical EngineeringUniversity of VirginiaCharlottesvilleVirginia
- Department of MedicineUniversity of Virginia Health SystemCharlottesvilleVirginia
- Department of RadiologyUniversity of Virginia Health SystemCharlottesvilleVirginia
| | - Frederick H. Epstein
- Department of Biomedical EngineeringUniversity of VirginiaCharlottesvilleVirginia
- Department of RadiologyUniversity of Virginia Health SystemCharlottesvilleVirginia
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11
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Demirel OB, Yaman B, Moeller S, Weingartner S, Akcakaya M. Signal-Intensity Informed Multi-Coil MRI Encoding Operator for Improved Physics-Guided Deep Learning Reconstruction of Dynamic Contrast-Enhanced MRI. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2022; 2022:1472-1476. [PMID: 36086262 DOI: 10.1109/embc48229.2022.9871668] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Dynamic contrast enhanced (DCE) MRI acquires a series of images following the administration of a contrast agent, and plays an important clinical role in diagnosing various diseases. DCE MRI typically necessitates rapid imaging to provide sufficient spatio-temporal resolution and coverage. Conventional MRI acceleration techniques exhibit limited image quality at such high acceleration rates. Recently, deep learning (DL) methods have gained interest for improving highly-accelerated MRI. However, DCE MRI series show substantial variations in SNR and contrast across images. This hinders the quality and generalizability of DL methods, when applied across time frames. In this study, we propose signal intensity informed multi-coil MRI encoding operator for improved DL reconstruction of DCE MRI. The output of the corresponding inverse problem for this forward operator leads to more uniform contrast across time frames, since the proposed operator captures signal intensity variations across time frames while not altering the coil sensitivities. Our results in perfusion cardiac MRI show that high-quality images are reconstructed at very high acceleration rates, with substantial improvement over existing methods.
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12
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Wang J, Weller DS, Kramer CM, Salerno M. DEep learning-based rapid Spiral Image REconstruction (DESIRE) for high-resolution spiral first-pass myocardial perfusion imaging. NMR IN BIOMEDICINE 2022; 35:e4661. [PMID: 34939246 DOI: 10.1002/nbm.4661] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/28/2021] [Revised: 11/01/2021] [Accepted: 11/16/2021] [Indexed: 06/14/2023]
Abstract
The objective of the current study was to develop and evaluate a DEep learning-based rapid Spiral Image REconstruction (DESIRE) technique for high-resolution spiral first-pass myocardial perfusion imaging with whole-heart coverage, to provide fast and accurate image reconstruction for both single-slice (SS) and simultaneous multislice (SMS) acquisitions. Three-dimensional U-Net-based image enhancement architectures were evaluated for high-resolution spiral perfusion imaging at 3 T. The SS and SMS MB = 2 networks were trained on SS perfusion images from 156 slices from 20 subjects. Structural similarity index (SSIM), peak signal-to-noise ratio (PSNR), and normalized root mean square error (NRMSE) were assessed, and prospective images were blindly graded by two experienced cardiologists (5: excellent; 1: poor). Excellent performance was demonstrated for the proposed technique. For SS, SSIM, PSNR, and NRMSE were 0.977 [0.972, 0.982], 42.113 [40.174, 43.493] dB, and 0.102 [0.080, 0.125], respectively, for the best network. For SMS MB = 2 retrospective data, SSIM, PSNR, and NRMSE were 0.961 [0.950, 0.969], 40.834 [39.619, 42.004] dB, and 0.107 [0.086, 0.133], respectively, for the best network. The image quality scores were 4.5 [4.1, 4.8], 4.5 [4.3, 4.6], 3.5 [3.3, 4], and 3.5 [3.3, 3.8] for SS DESIRE, SS L1-SPIRiT, MB = 2 DESIRE, and MB = 2 SMS-slice-L1-SPIRiT, respectively, showing no statistically significant difference (p = 1 and p = 1 for SS and SMS, respectively) between L1-SPIRiT and the proposed DESIRE technique. The network inference time was ~100 ms per dynamic perfusion series with DESIRE, while the reconstruction time of L1-SPIRiT with GPU acceleration was ~ 30 min. It was concluded that DESIRE enabled fast and high-quality image reconstruction for both SS and SMS MB = 2 whole-heart high-resolution spiral perfusion imaging.
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Affiliation(s)
- Junyu Wang
- Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, USA
| | - Daniel S Weller
- Department of Electrical and Computer Engineering, University of Virginia, Charlottesville, Virginia, USA
| | - Christopher M Kramer
- Department of Medicine, Cardiovascular Division, University of Virginia Health System, Charlottesville, Virginia, USA
- Radiology and Medical Imaging, University of Virginia Health System, Charlottesville, Virginia, USA
| | - Michael Salerno
- Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, USA
- Department of Medicine, Cardiovascular Division, University of Virginia Health System, Charlottesville, Virginia, USA
- Radiology and Medical Imaging, University of Virginia Health System, Charlottesville, Virginia, USA
- Departments of Medicine and Radiology, Stanford University Medical Center, Stanford, California, USA
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13
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Tourais J, Scannell CM, Schneider T, Alskaf E, Crawley R, Bosio F, Sanchez-Gonzalez J, Doneva M, Schülke C, Meineke J, Keupp J, Smink J, Breeuwer M, Chiribiri A, Henningsson M, Correia T. High-Resolution Free-Breathing Quantitative First-Pass Perfusion Cardiac MR Using Dual-Echo Dixon With Spatio-Temporal Acceleration. Front Cardiovasc Med 2022; 9:884221. [PMID: 35571164 PMCID: PMC9099052 DOI: 10.3389/fcvm.2022.884221] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2022] [Accepted: 04/04/2022] [Indexed: 11/21/2022] Open
Abstract
Introduction To develop and test the feasibility of free-breathing (FB), high-resolution quantitative first-pass perfusion cardiac MR (FPP-CMR) using dual-echo Dixon (FOSTERS; Fat-water separation for mOtion-corrected Spatio-TEmporally accelerated myocardial peRfuSion). Materials and Methods FOSTERS was performed in FB using a dual-saturation single-bolus acquisition with dual-echo Dixon and a dynamically variable Cartesian k-t undersampling (8-fold) approach, with low-rank and sparsity constrained reconstruction, to achieve high-resolution FPP-CMR images. FOSTERS also included automatic in-plane motion estimation and T2* correction to obtain quantitative myocardial blood flow (MBF) maps. High-resolution (1.6 x 1.6 mm2) FB FOSTERS was evaluated in eleven patients, during rest, against standard-resolution (2.6 x 2.6 mm2) 2-fold SENSE-accelerated breath-hold (BH) FPP-CMR. In addition, MBF was computed for FOSTERS and spatial wavelet-based compressed sensing (CS) reconstruction. Two cardiologists scored the image quality (IQ) of FOSTERS, CS, and standard BH FPP-CMR images using a 4-point scale (1–4, non-diagnostic – fully diagnostic). Results FOSTERS produced high-quality images without dark-rim and with reduced motion-related artifacts, using an 8x accelerated FB acquisition. FOSTERS and standard BH FPP-CMR exhibited excellent IQ with an average score of 3.5 ± 0.6 and 3.4 ± 0.6 (no statistical difference, p > 0.05), respectively. CS images exhibited severe artifacts and high levels of noise, resulting in an average IQ score of 2.9 ± 0.5. MBF values obtained with FOSTERS presented a lower variance than those obtained with CS. Discussion FOSTERS enabled high-resolution FB FPP-CMR with MBF quantification. Combining motion correction with a low-rank and sparsity-constrained reconstruction results in excellent image quality.
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Affiliation(s)
- Joao Tourais
- Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, Netherlands
- Department of MR R&D – Clinical Science, Philips Healthcare, Best, Netherlands
- Department of Imaging Physics, Magnetic Resonance Systems Lab, Delft University of Technology, Delft, Netherlands
| | - Cian M. Scannell
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | | | - Ebraham Alskaf
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Richard Crawley
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Filippo Bosio
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | | | | | | | | | | | - Jouke Smink
- Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, Netherlands
| | - Marcel Breeuwer
- Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, Netherlands
- Department of MR R&D – Clinical Science, Philips Healthcare, Best, Netherlands
| | - Amedeo Chiribiri
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Markus Henningsson
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
- Division of Cardiovascular Medicine, Department of Medical and Health Sciences, Linkoping University, Linkoping, Sweden
- Center for Medical Image Science and Visualization (CMIV), Linkoping University, Linkoping, Sweden
| | - Teresa Correia
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
- Centre for Marine Sciences (CCMAR), Faro, Portugal
- *Correspondence: Teresa Correia
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14
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McElroy S, Ferrazzi G, Nazir MS, Evans C, Ferreira J, Bosio F, Mughal N, Kunze KP, Neji R, Speier P, Stäb D, Ismail TF, Masci PG, Villa ADM, Razavi R, Chiribiri A, Roujol S. Simultaneous multislice steady-state free precession myocardial perfusion with full left ventricular coverage and high resolution at 1.5 T. Magn Reson Med 2022; 88:663-675. [PMID: 35344593 PMCID: PMC9310832 DOI: 10.1002/mrm.29229] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2021] [Revised: 02/15/2022] [Accepted: 02/22/2022] [Indexed: 12/27/2022]
Abstract
Purpose To implement and evaluate a simultaneous multi‐slice balanced SSFP (SMS‐bSSFP) perfusion sequence and compressed sensing reconstruction for cardiac MR perfusion imaging with full left ventricular (LV) coverage (nine slices/heartbeat) and high spatial resolution (1.4 × 1.4 mm2) at 1.5T. Methods A preliminary study was performed to evaluate the performance of blipped controlled aliasing in parallel imaging (CAIPI) and RF‐CAIPI with gradient‐controlled local Larmor adjustment (GC‐LOLA) in the presence of fat. A nine‐slice SMS‐bSSFP sequence using RF‐CAIPI with GC‐LOLA with high spatial resolution (1.4 × 1.4 mm2) and a conventional three‐slice sequence with conventional spatial resolution (1.9 × 1.9 mm2) were then acquired in 10 patients under rest conditions. Qualitative assessment was performed to assess image quality and perceived signal‐to‐noise ratio (SNR) on a 4‐point scale (0: poor image quality/low SNR; 3: excellent image quality/high SNR), and the number of myocardial segments with diagnostic image quality was recorded. Quantitative measurements of myocardial sharpness and upslope index were performed. Results Fat signal leakage was significantly higher for blipped CAIPI than for RF‐CAIPI with GC‐LOLA (7.9% vs. 1.2%, p = 0.010). All 10 SMS‐bSSFP perfusion datasets resulted in 16/16 diagnostic myocardial segments. There were no significant differences between the SMS and conventional acquisitions in terms of image quality (2.6 ± 0.6 vs. 2.7 ± 0.2, p = 0.8) or perceived SNR (2.8 ± 0.3 vs. 2.7 ± 0.3, p = 0.3). Inter‐reader variability was good for both image quality (ICC = 0.84) and perceived SNR (ICC = 0.70). Myocardial sharpness was improved using the SMS sequence compared to the conventional sequence (0.37 ± 0.08 vs 0.32 ± 0.05, p < 0.001). There was no significant difference between measurements of upslope index for the SMS and conventional sequences (0.11 ± 0.04 vs. 0.11 ± 0.03, p = 0.84). Conclusion SMS‐bSSFP with multiband factor 3 and compressed sensing reconstruction enables cardiac MR perfusion imaging with three‐fold increased spatial coverage and improved myocardial sharpness compared to a conventional sequence, without compromising perceived SNR, image quality, upslope index or number of diagnostic segments.
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Affiliation(s)
- Sarah McElroy
- School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King's College London, London, UK
| | | | - Muhummad Sohaib Nazir
- School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King's College London, London, UK
| | - Carl Evans
- School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King's College London, London, UK
| | - Joana Ferreira
- School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King's College London, London, UK
| | - Filippo Bosio
- School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King's College London, London, UK
| | - Nabila Mughal
- School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King's College London, London, UK
| | - Karl P Kunze
- MR Research Collaborations, Siemens Healthcare Limited, Frimley, England, UK
| | - Radhouene Neji
- School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King's College London, London, UK.,MR Research Collaborations, Siemens Healthcare Limited, Frimley, England, UK
| | - Peter Speier
- Magnetic Resonance, Siemens Healthcare GmbH, Erlangen, Germany
| | - Daniel Stäb
- MR Research Collaborations, Siemens Healthcare Limited, Melbourne, Australia
| | - Tevfik F Ismail
- School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King's College London, London, UK
| | - Pier Giorgio Masci
- School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King's College London, London, UK
| | - Adriana D M Villa
- School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King's College London, London, UK
| | - Reza Razavi
- School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King's College London, London, UK
| | - Amedeo Chiribiri
- School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King's College London, London, UK
| | - Sébastien Roujol
- School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King's College London, London, UK
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15
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Ismail TF, Strugnell W, Coletti C, Božić-Iven M, Weingärtner S, Hammernik K, Correia T, Küstner T. Cardiac MR: From Theory to Practice. Front Cardiovasc Med 2022; 9:826283. [PMID: 35310962 PMCID: PMC8927633 DOI: 10.3389/fcvm.2022.826283] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Accepted: 01/17/2022] [Indexed: 01/10/2023] Open
Abstract
Cardiovascular disease (CVD) is the leading single cause of morbidity and mortality, causing over 17. 9 million deaths worldwide per year with associated costs of over $800 billion. Improving prevention, diagnosis, and treatment of CVD is therefore a global priority. Cardiovascular magnetic resonance (CMR) has emerged as a clinically important technique for the assessment of cardiovascular anatomy, function, perfusion, and viability. However, diversity and complexity of imaging, reconstruction and analysis methods pose some limitations to the widespread use of CMR. Especially in view of recent developments in the field of machine learning that provide novel solutions to address existing problems, it is necessary to bridge the gap between the clinical and scientific communities. This review covers five essential aspects of CMR to provide a comprehensive overview ranging from CVDs to CMR pulse sequence design, acquisition protocols, motion handling, image reconstruction and quantitative analysis of the obtained data. (1) The basic MR physics of CMR is introduced. Basic pulse sequence building blocks that are commonly used in CMR imaging are presented. Sequences containing these building blocks are formed for parametric mapping and functional imaging techniques. Commonly perceived artifacts and potential countermeasures are discussed for these methods. (2) CMR methods for identifying CVDs are illustrated. Basic anatomy and functional processes are described to understand the cardiac pathologies and how they can be captured by CMR imaging. (3) The planning and conduct of a complete CMR exam which is targeted for the respective pathology is shown. Building blocks are illustrated to create an efficient and patient-centered workflow. Further strategies to cope with challenging patients are discussed. (4) Imaging acceleration and reconstruction techniques are presented that enable acquisition of spatial, temporal, and parametric dynamics of the cardiac cycle. The handling of respiratory and cardiac motion strategies as well as their integration into the reconstruction processes is showcased. (5) Recent advances on deep learning-based reconstructions for this purpose are summarized. Furthermore, an overview of novel deep learning image segmentation and analysis methods is provided with a focus on automatic, fast and reliable extraction of biomarkers and parameters of clinical relevance.
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Affiliation(s)
- Tevfik F. Ismail
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
- Cardiology Department, Guy's and St Thomas' Hospital, London, United Kingdom
| | - Wendy Strugnell
- Queensland X-Ray, Mater Hospital Brisbane, Brisbane, QLD, Australia
| | - Chiara Coletti
- Magnetic Resonance Systems Lab, Delft University of Technology, Delft, Netherlands
| | - Maša Božić-Iven
- Magnetic Resonance Systems Lab, Delft University of Technology, Delft, Netherlands
- Computer Assisted Clinical Medicine, Heidelberg University, Mannheim, Germany
| | | | - Kerstin Hammernik
- Lab for AI in Medicine, Technical University of Munich, Munich, Germany
- Department of Computing, Imperial College London, London, United Kingdom
| | - Teresa Correia
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
- Centre of Marine Sciences, Faro, Portugal
| | - Thomas Küstner
- Medical Image and Data Analysis (MIDAS.lab), Department of Diagnostic and Interventional Radiology, University Hospital of Tübingen, Tübingen, Germany
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16
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Ferrazzi G, McElroy S, Neji R, Kunze KP, Nazir MS, Speier P, Stäb D, Forman C, Razavi R, Chiribiri A, Roujol S. All-systolic first-pass myocardial rest perfusion at a long saturation time using simultaneous multi-slice imaging and compressed sensing acceleration. Magn Reson Med 2021; 86:663-676. [PMID: 33749026 PMCID: PMC7611406 DOI: 10.1002/mrm.28712] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2020] [Revised: 12/17/2020] [Accepted: 01/11/2021] [Indexed: 12/14/2022]
Abstract
PURPOSE To enable all-systolic first-pass rest myocardial perfusion with long saturation times. To investigate the change in perfusion contrast and dark rim artefacts through simulations and surrogate measurements. METHODS Simulations were employed to investigate optimal saturation time for myocardium-perfusion defect contrast and blood-to-myocardium signal ratios. Two saturation recovery blocks with long/short saturation times (LTS/STS) were employed to image 3 slices at end-systole and diastole. Simultaneous multi-slice balanced steady state free precession imaging and compressed sensing acceleration were combined. The sequence was compared to a 3 slice-by-slice clinical protocol in 10 patients. Quantitative assessment of myocardium-peak pre contrast and blood-to-myocardium signal ratios, as well as qualitative assessment of perceived SNR, image quality, blurring, and dark rim artefacts, were performed. RESULTS Simulations showed that with a bolus of 0.075 mmol/kg, a LTS of 240-470 ms led to a relative increase in myocardium-perfusion defect contrast of 34% ± 9%-28% ± 27% than a STS = 120 ms, while reducing blood-to-myocardium signal ratio by 18% ± 10%-32% ± 14% at peak myocardium. With a bolus of 0.05 mmol/kg, LTS was 320-570 ms with an increase in myocardium-perfusion defect contrast of 63% ± 13%-62% ± 29%. Across patients, LTS led to an average increase in myocardium-peak pre contrast of 59% (P < .001) at peak myocardium and a lower blood-to-myocardium signal ratio of 47% (P < .001) and 15% (P < .001) at peak blood/myocardium. LTS had improved motion robustness (P = .002), image quality (P < .001), and decreased dark rim artefacts (P = .008) than the clinical protocol. CONCLUSION All-systolic rest perfusion can be achieved by combining simultaneous multi-slice and compressed sensing acceleration, enabling 3-slice cardiac coverage with reduced motion and dark rim artefacts. Numerical simulations indicate that myocardium-perfusion defect contrast increases at LTS.
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Affiliation(s)
- Giulio Ferrazzi
- School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King’s College London, London, United Kingdom
- IRCCS San Camillo Hospital, Venice, Italy
| | - Sarah McElroy
- School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King’s College London, London, United Kingdom
| | - Radhouene Neji
- School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King’s College London, London, United Kingdom
- MR Research Collaborations, Siemens Healthcare Limited, Frimley, United Kingdom
| | - Karl P. Kunze
- School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King’s College London, London, United Kingdom
- MR Research Collaborations, Siemens Healthcare Limited, Frimley, United Kingdom
| | - Muhummad Sohaib Nazir
- School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King’s College London, London, United Kingdom
| | - Peter Speier
- Cardiovascular MR predevelopment, Siemens Healthcare GmbH, Erlangen, Germany
| | - Daniel Stäb
- MR Research Collaborations, Siemens Healthcare Limited, Melbourne, Australia
| | - Christoph Forman
- Cardiovascular MR predevelopment, Siemens Healthcare GmbH, Erlangen, Germany
| | - Reza Razavi
- School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King’s College London, London, United Kingdom
| | - Amedeo Chiribiri
- School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King’s College London, London, United Kingdom
| | - Sébastien Roujol
- School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King’s College London, London, United Kingdom
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17
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Wang J, Yang Y, Weller DS, Zhou R, Van Houten M, Sun C, Epstein FH, Meyer CH, Kramer CM, Salerno M. High spatial resolution spiral first-pass myocardial perfusion imaging with whole-heart coverage at 3 T. Magn Reson Med 2021; 86:648-662. [PMID: 33709415 DOI: 10.1002/mrm.28701] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2020] [Revised: 11/16/2020] [Accepted: 01/04/2021] [Indexed: 11/10/2022]
Abstract
PURPOSE To develop and evaluate a high spatial resolution (1.25 × 1.25 mm2 ) spiral first-pass myocardial perfusion imaging technique with whole-heart coverage at 3T, to better assess transmural differences in perfusion between the endocardium and epicardium, to quantify the myocardial ischemic burden, and to improve the detection of obstructive coronary artery disease. METHODS Whole-heart high-resolution spiral perfusion pulse sequences and corresponding motion-compensated reconstruction techniques for both interleaved single-slice (SS) and simultaneous multi-slice (SMS) acquisition with or without outer-volume suppression (OVS) were developed. The proposed techniques were evaluated in 34 healthy volunteers and 8 patients (55 data sets). SS and SMS images were reconstructed using motion-compensated L1-SPIRiT and SMS-Slice-L1-SPIRiT, respectively. Images were blindly graded by 2 experienced cardiologists on a 5-point scale (5, excellent; 1, poor). RESULTS High-quality perfusion imaging was achieved for both SS and SMS acquisitions with or without OVS. The SS technique without OVS had the highest scores (4.5 [4, 5]), which were greater than scores for SS with OVS (3.5 [3.25, 3.75], P < .05), MB = 2 without OVS (3.75 [3.25, 4], P < .05), and MB = 2 with OVS (3.75 [2.75, 4], P < .05), but significantly higher than those for MB = 3 without OVS (4 [4, 4], P = .95). SMS image quality was improved using SMS-Slice-L1-SPIRiT as compared to SMS-L1-SPIRiT (P < .05 for both reviewers). CONCLUSION We demonstrated the successful implementation of whole-heart spiral perfusion imaging with high resolution at 3T. Good image quality was achieved, and the SS without OVS showed the best image quality. Evaluation in patients with expected ischemic heart disease is warranted.
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Affiliation(s)
- Junyu Wang
- Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, USA
| | - Yang Yang
- Biomedical Engineering and Imaging Institute and Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, USA.,Department of Medicine, Cardiovascular Division, University of Virginia Health System, Charlottesville, Virginia, USA
| | - Daniel S Weller
- Department of Electrical and Computer Engineering, University of Virginia, Charlottesville, Virginia, USA
| | - Ruixi Zhou
- Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, USA
| | - Matthew Van Houten
- Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, USA
| | - Changyu Sun
- Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, USA
| | - Frederick H Epstein
- Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, USA.,Radiology and Medical Imaging, University of Virginia Health System, Charlottesville, Virginia, USA
| | - Craig H Meyer
- Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, USA.,Radiology and Medical Imaging, University of Virginia Health System, Charlottesville, Virginia, USA
| | - Christopher M Kramer
- Department of Medicine, Cardiovascular Division, University of Virginia Health System, Charlottesville, Virginia, USA.,Radiology and Medical Imaging, University of Virginia Health System, Charlottesville, Virginia, USA
| | - Michael Salerno
- Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, USA.,Department of Medicine, Cardiovascular Division, University of Virginia Health System, Charlottesville, Virginia, USA.,Radiology and Medical Imaging, University of Virginia Health System, Charlottesville, Virginia, USA
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18
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Demirel OB, Weingärtner S, Moeller S, Akçakaya M. Improved simultaneous multislice cardiac MRI using readout concatenated k-space SPIRiT (ROCK-SPIRiT). Magn Reson Med 2021; 85:3036-3048. [PMID: 33566378 DOI: 10.1002/mrm.28680] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2020] [Revised: 12/21/2020] [Accepted: 12/22/2020] [Indexed: 01/31/2023]
Abstract
PURPOSE To develop and evaluate a simultaneous multislice (SMS) reconstruction technique that provides noise reduction and leakage blocking for highly accelerated cardiac MRI. METHODS ReadOut Concatenated k-space SPIRiT (ROCK-SPIRiT) uses the concept of readout concatenation in image domain to represent SMS encoding, and performs coil self-consistency as in SPIRiT-type reconstruction in an extended k-space, while allowing regularization for further denoising. The proposed method is implemented with and without regularization, and validated on retrospectively SMS-accelerated cine imaging with three-fold SMS and two-fold in-plane acceleration. ROCK-SPIRiT is compared with two leakage-blocking SMS reconstruction methods: readout-SENSE-GRAPPA and split slice-GRAPPA. Further evaluation and comparisons are performed using prospectively SMS-accelerated cine imaging. RESULTS Results on retrospectively three-fold SMS and two-fold in-plane accelerated cine imaging show that ROCK-SPIRiT without regularization significantly improves on existing methods in terms of PSNR (readout-SENSE-GRAPPA: 33.5 ± 3.2, split slice-GRAPPA: 34.1 ± 3.8, ROCK-SPIRiT: 35.0 ± 3.3) and SSIM (readout-SENSE-GRAPPA: 84.4 ± 8.9, split slice-GRAPPA: 85.0 ± 8.9, ROCK-SPIRiT: 88.2 ± 6.6 [in percentage]). Regularized ROCK-SPIRiT significantly outperforms all methods, as characterized by these quantitative metrics (PSNR: 37.6 ± 3.8, SSIM: 94.2 ± 4.1 [in percentage]). The prospectively five-fold SMS and two-fold in-plane accelerated data show that ROCK-SPIRiT and regularized ROCK-SPIRiT have visually improved image quality compared with existing methods. CONCLUSION The proposed ROCK-SPIRiT technique reduces noise and interslice leakage in accelerated SMS cardiac cine MRI, improving on existing methods both quantitatively and qualitatively.
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Affiliation(s)
- Omer Burak Demirel
- Department of Electrical and Computer Engineering, University of Minnesota, Minneapolis, Minnesota, USA.,Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, Minnesota, USA
| | - Sebastian Weingärtner
- Department of Electrical and Computer Engineering, University of Minnesota, Minneapolis, Minnesota, USA.,Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, Minnesota, USA.,Department of Imaging Physics, Delft University of Technology, Delft, the Netherlands
| | - Steen Moeller
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, Minnesota, USA
| | - Mehmet Akçakaya
- Department of Electrical and Computer Engineering, University of Minnesota, Minneapolis, Minnesota, USA.,Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, Minnesota, USA
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19
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Mooiweer R, Neji R, McElroy S, Nazir MS, Razavi R, Chiribiri A, Roujol S. A fast navigator (fastNAV) for prospective respiratory motion correction in first-pass myocardial perfusion imaging. Magn Reson Med 2020; 85:2661-2671. [PMID: 33270946 PMCID: PMC7898590 DOI: 10.1002/mrm.28617] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2020] [Revised: 11/05/2020] [Accepted: 11/05/2020] [Indexed: 11/10/2022]
Abstract
PURPOSE To develop and evaluate a fast respiratory navigator (fastNAV) for cardiac MR perfusion imaging with subject-specific prospective slice tracking. METHODS A fastNAV was developed for dynamic contrast-enhanced cardiac MR perfusion imaging by combining spatially nonselective saturation with slice-selective tip-up and slice-selective excitation pulses. The excitation slice was angulated from the tip-up slice in the transverse plane to overlap only in the right hemidiaphragm for suppression of signal outside the right hemidiaphragm. A calibration scan was developed to enable the estimation of subject-specific tracking factors. Perfusion imaging using subject-specific fastNAV-based slice tracking was then compared to a conventional sequence (ie, without slice tracking) in 10 patients under free-breathing conditions. Respiratory motion in perfusion images was quantitatively assessed by measuring the average overlap of the left ventricle across images (avDice, 0:no overlap/1:perfect overlap) and the average displacement of the center of mass of the left ventricle (avCoM). Image quality was subjectively assessed using a 4-point scoring system (1: poor, 4: excellent). RESULTS The fastNAV calibration was successfully performed in all subjects (average tracking factor of 0.46 ± 0.13, R = 0.94 ± 0.03). Prospective motion correction using fastNAV led to higher avDice (0.94 ± 0.02 vs. 0.90 ± 0.03, P < .001) and reduced avCoM (4.03 ± 0.84 vs. 5.22 ± 1.22, P < .001). There were no statistically significant differences between the 2 sequences in terms of image quality (both sequences: median = 3 and interquartile range = 3-4, P = 1). CONCLUSION fastNAV enables fast and robust right hemidiaphragm motion tracking in a perfusion sequence. In combination with subject-specific slice tracking, fastNAV reduces the effect of respiratory motion during free-breathing cardiac MR perfusion imaging.
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Affiliation(s)
- Ronald Mooiweer
- School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King's College London, London, United Kingdom
| | - Radhouene Neji
- School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King's College London, London, United Kingdom.,MR Research Collaborations, Siemens Healthcare Limited, Frimley, United Kingdom
| | - Sarah McElroy
- School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King's College London, London, United Kingdom
| | - Muhummad Sohaib Nazir
- School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King's College London, London, United Kingdom
| | - Reza Razavi
- School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King's College London, London, United Kingdom
| | - Amedeo Chiribiri
- School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King's College London, London, United Kingdom
| | - Sébastien Roujol
- School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King's College London, London, United Kingdom
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20
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McElroy S, Ferrazzi G, Nazir MS, Kunze KP, Neji R, Speier P, Stäb D, Forman C, Razavi R, Chiribiri A, Roujol S. Combined simultaneous multislice bSSFP and compressed sensing for first-pass myocardial perfusion at 1.5 T with high spatial resolution and coverage. Magn Reson Med 2020; 84:3103-3116. [PMID: 32530064 PMCID: PMC7611375 DOI: 10.1002/mrm.28345] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2020] [Revised: 05/14/2020] [Accepted: 05/14/2020] [Indexed: 02/02/2023]
Abstract
PURPOSE To implement and evaluate a pseudorandom undersampling scheme for combined simultaneous multislice (SMS) balanced SSFP (bSSFP) and compressed-sensing (CS) reconstruction to enable myocardial perfusion imaging with high spatial resolution and coverage at 1.5 T. METHODS A prospective pseudorandom undersampling scheme that is compatible with SMS-bSSFP phase-cycling requirements and CS was developed. The SMS-bSSFP CS with pseudorandom and linear undersampling schemes were compared in a phantom. A high-resolution (1.4 × 1.4 mm2 ) six-slice SMS-bSSFP CS perfusion sequence was compared with a conventional (1.9 × 1.9 mm2 ) three-slice sequence in 10 patients. Qualitative assessment of image quality, perceived SNR, and number of diagnostic segments and quantitative measurements of sharpness, upslope index, and contrast ratio were performed. RESULTS In phantom experiments, pseudorandom undersampling resulted in residual artifact (RMS error) reduction by a factor of 7 compared with linear undersampling. In vivo, the proposed sequence demonstrated higher perceived SNR (2.9 ± 0.3 vs. 2.2 ± 0.6, P = .04), improved sharpness (0.35 ± 0.03 vs. 0.32 ± 0.05, P = .01), and a higher number of diagnostic segments (100% vs. 94%, P = .03) compared with the conventional sequence. There were no significant differences between the sequences in terms of image quality (2.5 ± 0.4 vs. 2.8 ± 0.2, P = .08), upslope index (0.11 ± 0.02 vs. 0.10 ± 0.01, P = .3), or contrast ratio (3.28 ± 0.35 vs. 3.36 ± 0.43, P = .7). CONCLUSION A pseudorandom k-space undersampling compatible with SMS-bSSFP and CS reconstruction has been developed and enables cardiac MR perfusion imaging with increased spatial resolution and myocardial coverage, increased number of diagnostic segments and perceived SNR, and no difference in image quality, upslope index, and contrast ratio.
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Affiliation(s)
- Sarah McElroy
- School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King’s College London, London, United Kingdom
| | - Giulio Ferrazzi
- School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King’s College London, London, United Kingdom
| | - Muhummad Sohaib Nazir
- School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King’s College London, London, United Kingdom
| | - Karl P. Kunze
- MR Research Collaborations, Siemens Healthcare Limited, Frimley, United Kingdom
| | - Radhouene Neji
- School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King’s College London, London, United Kingdom
- MR Research Collaborations, Siemens Healthcare Limited, Frimley, United Kingdom
| | - Peter Speier
- Magnetic Resonance, Siemens Healthcare GmbH, Erlangen, Germany
| | - Daniel Stäb
- MR Research Collaborations, Siemens Healthcare Pty Ltd, Melbourne, Australia
| | | | - Reza Razavi
- School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King’s College London, London, United Kingdom
| | - Amedeo Chiribiri
- School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King’s College London, London, United Kingdom
| | - Sébastien Roujol
- School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King’s College London, London, United Kingdom
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21
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Metze P, Li H, Speidel T, Buckert D, Rottbauer W, Rasche V. Sliding window reduced FOV reconstruction for real-time cardiac imaging. Z Med Phys 2020; 30:236-244. [PMID: 32067862 DOI: 10.1016/j.zemedi.2020.01.001] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2019] [Revised: 12/11/2019] [Accepted: 01/07/2020] [Indexed: 11/29/2022]
Abstract
BACKGROUND Current functional cardiovascular imaging protocols mostly rely on electrocardiogram (ECG) gating and breathholding. The resulting image quality can substantially suffer from insufficient patient cooperation or severe arrhythmia. Real-time imaging can mitigate these effects but requires highly accelerated techniques, usually relying on non-cartesian trajectories and Compressed Sensing (CS). METHODS We investigate a sliding window reduced field of view (FOV) Echo Planar Imaging (EPI) technique for real-time cardiac MRI. Segmented EPI has been combined with a subtraction technique for reducing the FOV in cardiac applications to the region of the beating heart. Residual respiratory motion, potentially impairing the image quality, has been addressed by continuous update of the static image fraction, which is derived from a low-temporal resolution sliding window reconstruction. For further acceleration, the proposed technique was combined with parallel imaging. RESULTS The sliding window reduced FOV technique was proven feasible to reconstruct images of diagnostic image quality at a temporal resolution of 36.5ms per image. Semi-quantitative evaluation of image quality showed significant improvement over the existing rFOV method (p=0.039). Derived functional parameters show comparable results as with the BH-CINE reference. However, a trend to a slight underestimation of the largest and smallest in-plane volumes is observed. CONCLUSION The proposed technique is feasible of providing real-time cardiac MRI with a temporal resolution better than 40ms without the need of computably complex reconstruction techniques.
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Affiliation(s)
- Patrick Metze
- Department of Internal Medicine II, Ulm University Medical Center, Ulm, Germany.
| | - Hao Li
- Core Facility Small Animal Imaging (CF-SANI), Ulm University, Ulm, Germany.
| | - Tobias Speidel
- Core Facility Small Animal Imaging (CF-SANI), Ulm University, Ulm, Germany.
| | - Dominik Buckert
- Department of Internal Medicine II, Ulm University Medical Center, Ulm, Germany.
| | - Wolfgang Rottbauer
- Department of Internal Medicine II, Ulm University Medical Center, Ulm, Germany.
| | - Volker Rasche
- Department of Internal Medicine II, Ulm University Medical Center, Ulm, Germany; Core Facility Small Animal Imaging (CF-SANI), Ulm University, Ulm, Germany.
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22
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Tian Y, Mendes J, Wilson B, Ross A, Ranjan R, DiBella E, Adluru G. Whole-heart, ungated, free-breathing, cardiac-phase-resolved myocardial perfusion MRI by using Continuous Radial Interleaved simultaneous Multi-slice acquisitions at sPoiled steady-state (CRIMP). Magn Reson Med 2020; 84:3071-3087. [PMID: 32492235 DOI: 10.1002/mrm.28337] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2019] [Revised: 04/28/2020] [Accepted: 05/01/2020] [Indexed: 11/09/2022]
Abstract
PURPOSE To develop a whole-heart, free-breathing, non-electrocardiograph (ECG)-gated, cardiac-phase-resolved myocardial perfusion MRI framework (CRIMP; Continuous Radial Interleaved simultaneous Multi-slice acquisitions at sPoiled steady-state) and test its quantification feasibility. METHODS CRIMP used interleaved radial simultaneous multi-slice (SMS) slice groups to cover the whole heart in 9 or 12 short-axis slices. The sequence continuously acquired data without magnetization preparation, ECG gating or breath-holding, and captured multiple cardiac phases. Images were reconstructed by a motion-compensated patch-based locally low-rank reconstruction. Bloch simulations were performed to study the signal-to-noise ratio/contrast-to-noise ratio (SNR/CNR) for CRIMP and to study the steady-state signal under motion. Seven patients were scanned with CRIMP at stress and rest to develop the sequence. One human and two dogs were scanned at rest with a dual-bolus method to test the quantification feasibility of CRIMP. The dual-bolus scans were performed using both CRIMP and an ungated radial SMS saturation recovery (SMS-SR) sequence with injection dose = 0.075 mmol/kg to compare the sequences in terms of SNR, cardiac phase resolution and quantitative myocardial blood flow (MBF). RESULTS Perfusion images with multiple cardiac phases in all image slices with a temporal resolution of 72 ms/frame were obtained. Simulations and in-vivo acquisitions showed CRIMP kept the inner slices in steady-state regardless of motion. CRIMP outperformed SMS-SR in slice coverage (9 over 6), SNR (mean 20% improvement), and provided cardiac phase resolution. CRIMP and SMS-SR sequences provided comparable MBF values (rest systolic CRIMP = 0.58 ± 0.07, SMS-SR = 0.61 ± 0.16). CONCLUSION CRIMP allows for whole-heart, cardiac-phase-resolved myocardial perfusion images without ECG-gating or breath-holding. The sequence can provide MBF if an accurate arterial input function is obtained separately.
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Affiliation(s)
- Ye Tian
- Utah Center for Advanced Imaging Research (UCAIR), Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, Utah, USA.,Department of Physics and Astronomy, University of Utah, Salt Lake City, Utah, USA
| | - Jason Mendes
- Utah Center for Advanced Imaging Research (UCAIR), Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, Utah, USA
| | - Brent Wilson
- Division of Cardiovascular Medicine, University of Utah, Salt Lake City, Utah, USA
| | - Alexander Ross
- Division of Cardiovascular Medicine, University of Utah, Salt Lake City, Utah, USA
| | - Ravi Ranjan
- Division of Cardiovascular Medicine, University of Utah, Salt Lake City, Utah, USA
| | - Edward DiBella
- Utah Center for Advanced Imaging Research (UCAIR), Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, Utah, USA.,Department of Biomedical Engineering, University of Utah, Salt Lake City, Utah, USA
| | - Ganesh Adluru
- Utah Center for Advanced Imaging Research (UCAIR), Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, Utah, USA.,Department of Biomedical Engineering, University of Utah, Salt Lake City, Utah, USA
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23
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Ferrazzi G, Bassenge JP, Mayer J, Ruh A, Roujol S, Ittermann B, Schaeffter T, Cordero-Grande L, Schmitter S. Autocalibrated cardiac tissue phase mapping with multiband imaging and k-t acceleration. Magn Reson Med 2020; 84:2429-2441. [PMID: 32306471 DOI: 10.1002/mrm.28288] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2020] [Revised: 03/05/2020] [Accepted: 03/28/2020] [Indexed: 12/25/2022]
Abstract
PURPOSE To develop an autocalibrated multiband (MB) CAIPIRINHA acquisition scheme with in-plane k-t acceleration enabling multislice three-directional tissue phase mapping in one breath-hold. METHODS A k-t undersampling scheme was integrated into a time-resolved electrocardiographic-triggered autocalibrated MB gradient-echo sequence. The sequence was used to acquire data on 4 healthy volunteers with MB factors of two (MB2) and three (MB3), which were reconstructed using a joint reconstruction algorithm that tackles both k-t and MB acceleration. Forward simulations of the imaging process were used to tune the reconstruction model hyperparameters. Direct comparisons between MB and single-band tissue phase-mapping measurements were performed. RESULTS Simulations showed that the velocities could be accurately reproduced with MB2 k-t (average ± twice the SD of the RMS error of 0.08 ± 0.22 cm/s and velocity peak reduction of 1.03% ± 6.47% compared with fully sampled velocities), whereas acceptable results were obtained with MB3 k-t (RMS error of 0.13 ± 0.58 cm/s and peak reduction of 2.21% ± 13.45%). When applied to tissue phase-mapping data, the proposed technique allowed three-directional velocity encoding to be simultaneously acquired at two/three slices in a single breath-hold of 18 heartbeats. No statistically significant differences were detected between MB2/MB3 k-t and single-band k-t motion traces averaged over the myocardium. Regional differences were found, however, when using the American Heart Association model for segmentation. CONCLUSION An autocalibrated MB k-t acquisition/reconstruction framework is presented that allows three-directional velocity encoding of the myocardial velocities at multiple slices in one breath-hold.
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Affiliation(s)
- Giulio Ferrazzi
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Germany
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Jean Pierre Bassenge
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Germany
- Working Group on Cardiovascular Magnetic Resonance, Experimental and Clinical Research Center, a joint cooperation between the Charité Medical Faculty and the Max-Delbrück Center for Molecular Medicine, Berlin, Germany
| | - Johannes Mayer
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Germany
| | - Alexander Ruh
- Department of Radiology, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA
| | - Sébastien Roujol
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Bernd Ittermann
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Germany
| | - Tobias Schaeffter
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Germany
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
- FG Medizintechnik, Technische Universität Berlin, Berlin, Germany
| | - Lucilio Cordero-Grande
- Biomedical Image Technologies, ETSI Telecomunicación, Universidad Politécnica de Madrid & CIBER-BBN, Madrid, Spain
- Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Sebastian Schmitter
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Germany
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Restivo MC, Ramasawmy R, Bandettini WP, Herzka DA, Campbell-Washburn AE. Efficient spiral in-out and EPI balanced steady-state free precession cine imaging using a high-performance 0.55T MRI. Magn Reson Med 2020; 84:2364-2375. [PMID: 32291845 DOI: 10.1002/mrm.28278] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2019] [Revised: 03/10/2020] [Accepted: 03/13/2020] [Indexed: 12/22/2022]
Abstract
PURPOSE Low-field MRI offers favorable physical properties for SNR-efficient long readout acquisitions such as spiral and EPI. We used a 0.55 tesla (T) MRI system equipped with high-performance hardware to increase the sampling duty cycle and extend the TR of balanced steady-state free precession (bSSFP) cardiac cine acquisitions, which typically are limited by banding artifacts. METHODS We developed a high-efficiency spiral in-out bSSFP acquisition, with zeroth- and first-gradient moment nulling, and an EPI bSSFP acquisition for cardiac cine imaging using a contemporary MRI system modified to operate at 0.55T. Spiral in-out and EPI bSSFP cine protocols, with TR = 8 ms, were designed to maintain both spatiotemporal resolution and breath-hold length. Simulations, phantom imaging, and healthy volunteer imaging studies (n = 12) were performed to assess SNR and image quality using these high sampling duty-cycle bSSFP sequences. RESULTS Spiral in-out bSSFP performed favorably at 0.55T and generated good image quality, whereas EPI bSSFP suffered motion and flow artifacts. There was no difference in ejection fraction comparing spiral in-out with standard Cartesian imaging. Moreover, human images demonstrated a 79% ± 21% increase in myocardial SNR using spiral in-out bSSFP and 50% ± 14% increase in SNR using EPI bSSFP as compared with the reference Cartesian acquisition. Spiral in-out acquisitions at 0.55T recovered 69% ± 14% of the myocardial SNR at 1.5T. CONCLUSION Efficient bSSFP spiral in-out provided high-quality cardiac cine imaging and SNR recovery on a high-performance 0.55T MRI system.
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Affiliation(s)
- Matthew C Restivo
- Cardiovascular Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland
| | - Rajiv Ramasawmy
- Cardiovascular Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland
| | - W Patricia Bandettini
- Cardiovascular Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland
| | - Daniel A Herzka
- Cardiovascular Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland
| | - Adrienne E Campbell-Washburn
- Cardiovascular Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland
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25
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Improved Regularized Reconstruction for Simultaneous Multi-Slice Cardiac MRI T 1 Mapping. PROCEEDINGS OF THE ... EUROPEAN SIGNAL PROCESSING CONFERENCE (EUSIPCO). EUSIPCO (CONFERENCE) 2019; 2019. [PMID: 31893194 DOI: 10.23919/eusipco.2019.8903058] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
Myocardial T 1 mapping is a quantitative MRI technique that has found great clinical utility in the detection of various heart disease. These acquisitions typically require three breath-holds, leading to long scan durations and patient discomfort. Simultaneous multi-slice (SMS) imaging has been shown to reduce the scan time of myocardial T 1 mapping to a single breath-hold without sacrificing coverage, albeit at reduced precision. In this work, we propose a new reconstruction strategy for SMS imaging that combines the advantages of two different k-space interpolation strategies, while allowing for regularization, in order to improve the precision of accelerated mycordial T 1 mapping.
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26
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Sun C, Yang Y, Cai X, Salerno M, Meyer CH, Weller D, Epstein FH. Non-Cartesian slice-GRAPPA and slice-SPIRiT reconstruction methods for multiband spiral cardiac MRI. Magn Reson Med 2019; 83:1235-1249. [PMID: 31565819 DOI: 10.1002/mrm.28002] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2019] [Revised: 08/28/2019] [Accepted: 08/29/2019] [Indexed: 12/25/2022]
Abstract
PURPOSE Spiral MRI has advantages for cardiac imaging, and multiband (MB) spiral MRI of the heart shows promise. However, current reconstruction methods for MB spiral imaging have limitations. We sought to develop improved reconstruction methods for MB spiral cardiac MRI. METHODS Two reconstruction methods were developed. The first is non-Cartesian slice-GRAPPA (NCSG), which uses phase demodulation and gridding operations before application of a Cartesian slice-separating kernel. The second method, slice-SPIRiT, formulates the reconstruction as a minimization problem that enforces in-plane coil consistency and consistency with the acquired MB data, and uses through-plane coil sensitivity information in the iterative solution. These methods were compared with conjugate-gradient SENSE in phantoms and volunteers. Temporal alternation of CAIPIRINHA (controlled aliasing in parallel imaging results in higher acceleration) phase and the use of a temporal filter were also investigated. RESULTS Phantom experiments with 3 simultaneous slices (MB = 3) showed that mean artifact power was highest for conjugate-gradient SENSE, lower for NCSG, and lowest for slice-SPIRiT. For volunteer cine imaging (MB = 3, N = 5), the artifact power was 0.182 ± 0.037, 0.148 ± 0.036, and 0.139 ± 0.034 for conjugate-gradient SENSE, NCSG, and slice-SPIRiT, respectively (P < .05, analysis of variance). Temporal alternation of CAIPIRINHA reduced artifacts for both NCSG and slice-SPIRiT. CONCLUSION The NCSG and slice-SPIRiT methods provide more accurate reconstructions for MB spiral cine imaging compared with conjugate-gradient SENSE. These methods hold promise for non-Cartesian MB imaging.
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Affiliation(s)
- Changyu Sun
- Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia
| | - Yang Yang
- Department of Medicine, University of Virginia Health System, Charlottesville, Virginia.,Translational and Molecular Imaging Institute and Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Xiaoying Cai
- Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia.,Siemens Medical Solutions USA, Boston, Massachusetts
| | - Michael Salerno
- Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia.,Department of Medicine, University of Virginia Health System, Charlottesville, Virginia.,Department of Radiology, University of Virginia Health System, Charlottesville, Virginia
| | - Craig H Meyer
- Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia.,Department of Radiology, University of Virginia Health System, Charlottesville, Virginia
| | - Daniel Weller
- Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia.,Department of Radiology, University of Virginia Health System, Charlottesville, Virginia.,Department of Electrical and Computer Engineering, University of Virginia, Charlottesville, Virginia
| | - Frederick H Epstein
- Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia.,Department of Radiology, University of Virginia Health System, Charlottesville, Virginia
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Nazir MS, Neji R, Speier P, Reid F, Stäb D, Schmidt M, Forman C, Razavi R, Plein S, Ismail TF, Chiribiri A, Roujol S. Simultaneous multi slice (SMS) balanced steady state free precession first-pass myocardial perfusion cardiovascular magnetic resonance with iterative reconstruction at 1.5 T. J Cardiovasc Magn Reson 2018; 20:84. [PMID: 30526627 PMCID: PMC6287353 DOI: 10.1186/s12968-018-0502-7] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2018] [Accepted: 10/24/2018] [Indexed: 12/21/2022] Open
Abstract
BACKGROUND Simultaneous-Multi-Slice (SMS) perfusion imaging has the potential to acquire multiple slices, increasing myocardial coverage without sacrificing in-plane spatial resolution. To maximise signal-to-noise ratio (SNR), SMS can be combined with a balanced steady state free precession (bSSFP) readout. Furthermore, application of gradient-controlled local Larmor adjustment (GC-LOLA) can ensure robustness against off-resonance artifacts and SNR loss can be mitigated by applying iterative reconstruction with spatial and temporal regularisation. The objective of this study was to compare cardiovascular magnetic resonance (CMR) myocardial perfusion imaging using SMS bSSFP imaging with GC-LOLA and iterative reconstruction to 3 slice bSSFP. METHODS Two contrast-enhanced rest perfusion sequences were acquired in random order in 8 patients: 6-slice SMS bSSFP and 3 slice bSSFP. All images were reconstructed with TGRAPPA. SMS images were also reconstructed using a non-linear iterative reconstruction with L1 regularisation in wavelet space (SMS-iter) with 7 different combinations for spatial (λσ) and temporal (λτ) regularisation parameters. Qualitative ratings of overall image quality (0 = poor image quality, 1 = major artifact, 2 = minor artifact, 3 = excellent), perceived SNR (0 = poor SNR, 1 = major noise, 2 = minor noise, 3 = high SNR), frequency of sequence related artifacts and patient related artifacts were undertaken. Quantitative analysis of contrast ratio (CR) and percentage of dark rim artifact (DRA) was performed. RESULTS Among all SMS-iter reconstructions, SMS-iter 6 (λσ 0.001 λτ 0.005) was identified as the optimal reconstruction with the highest overall image quality, least sequence related artifact and higher perceived SNR. SMS-iter 6 had superior overall image quality (2.50 ± 0.53 vs 1.50 ± 0.53, p = 0.005) and perceived SNR (2.25 ± 0.46 vs 0.75 ± 0.46, p = 0.010) compared to 3 slice bSSFP. There were no significant differences in sequence related artifact, CR (3.62 ± 0.39 vs 3.66 ± 0.65, p = 0.88) or percentage of DRA (5.25 ± 6.56 vs 4.25 ± 4.30, p = 0.64) with SMS-iter 6 compared to 3 slice bSSFP. CONCLUSIONS SMS bSSFP with GC-LOLA and iterative reconstruction improved image quality compared to a 3 slice bSSFP with doubled spatial coverage and preserved in-plane spatial resolution. Future evaluation in patients with coronary artery disease is warranted.
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Affiliation(s)
- Muhummad Sohaib Nazir
- School of Biomedical Engineering and Imaging Sciences, King’s College London, 3rd Floor Lambeth Wing, St Thomas’ Hospital, Westminster Bridge Road, London, SW1 7EH UK
| | - Radhouene Neji
- School of Biomedical Engineering and Imaging Sciences, King’s College London, 3rd Floor Lambeth Wing, St Thomas’ Hospital, Westminster Bridge Road, London, SW1 7EH UK
- MR Research Collaborations, Siemens Healthcare Limited, Frimley, UK
| | | | - Fiona Reid
- Division of Health and Social Care Research, King’s College London, London, UK
| | - Daniel Stäb
- Siemens Healthcare Pty Ltd, Melbourne, Australia
| | | | | | - Reza Razavi
- School of Biomedical Engineering and Imaging Sciences, King’s College London, 3rd Floor Lambeth Wing, St Thomas’ Hospital, Westminster Bridge Road, London, SW1 7EH UK
| | - Sven Plein
- School of Biomedical Engineering and Imaging Sciences, King’s College London, 3rd Floor Lambeth Wing, St Thomas’ Hospital, Westminster Bridge Road, London, SW1 7EH UK
- Leeds Institute of Cardiovascular and Metabolic Medicine, LIGHT Laboratories, Clarendon Way, University of Leeds, Leeds, LS2 9JT UK
| | - Tevfik F. Ismail
- School of Biomedical Engineering and Imaging Sciences, King’s College London, 3rd Floor Lambeth Wing, St Thomas’ Hospital, Westminster Bridge Road, London, SW1 7EH UK
| | - Amedeo Chiribiri
- School of Biomedical Engineering and Imaging Sciences, King’s College London, 3rd Floor Lambeth Wing, St Thomas’ Hospital, Westminster Bridge Road, London, SW1 7EH UK
| | - Sébastien Roujol
- School of Biomedical Engineering and Imaging Sciences, King’s College London, 3rd Floor Lambeth Wing, St Thomas’ Hospital, Westminster Bridge Road, London, SW1 7EH UK
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