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Guo R, Fan Y, Liu B, Qian X, Dai J, Si D, Wang Y, Wang A, Dong G, Jin Y, Xiao J, Ding H, Tang X. MyoFold: Joint myocardial tissue composition and wall motion quantification via a highly folded sequence. Magn Reson Med 2024; 92:1064-1078. [PMID: 38726772 DOI: 10.1002/mrm.30124] [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: 10/09/2023] [Revised: 03/09/2024] [Accepted: 04/03/2024] [Indexed: 06/27/2024]
Abstract
PURPOSE This study aims to develop and evaluate a novel cardiovascular MR sequence, MyoFold, designed for the simultaneous quantifications of myocardial tissue composition and wall motion. METHODS MyoFold is designed as a 2D single breathing-holding sequence, integrating joint T1/T2 mapping and cine imaging. The sequence uses a 2-fold accelerated balanced SSFP (bSSFP) for data readout and incorporates electrocardiogram synchronization to align with the cardiac cycle. MyoFold initially acquires six single-shot inversion-recovery images, completed during the diastole of six successive heartbeats. T2 preparation (T2-prep) is applied to introduce T2 weightings for the last three images. Subsequently, over the following six heartbeats, segmented bSSFP is performed for the movie of the entire cardiac cycle, synchronized with an electrocardiogram. A neural network trained using numerical simulations of MyoFold is used for T1 and T2 calculations. MyoFold was validated through phantom and in vivo experiments, with comparisons made against MOLLI, SASHA, T2-prep bSSFP, and the conventional cine. RESULTS In phantom studies, MyoFold exhibited a 10% overestimation in T1 measurements, whereas T2 measurements demonstrated high accuracy. In vivo experiments revealed that MyoFold T1 had comparable accuracy to SASHA and precision similar to MOLLI. MyoFold demonstrated good agreement with T2-prep bSSFP in myocardial T2 measurements. No significant differences were observed in the quantification of left-ventricle wall thickness and function between MyoFold and the conventional cine. CONCLUSION MyoFold presents as a rapid, simple, and multitasking approach for quantitative cardiovascular MR examinations, offering simultaneous assessment of tissue composition and wall motion. The sequence's multitasking capabilities make it a promising tool for comprehensive cardiac evaluations in clinical settings.
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Affiliation(s)
- Rui Guo
- School of Medical Technology, Beijing Institute of Technology, Beijing, China
| | - Yingwei Fan
- School of Medical Technology, Beijing Institute of Technology, Beijing, China
| | - Bowei Liu
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China
| | - Xiaofeng Qian
- School of Medical Technology, Beijing Institute of Technology, Beijing, China
| | - Jiahuan Dai
- School of Medical Technology, Beijing Institute of Technology, Beijing, China
| | - Dongyue Si
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China
| | - Yuanyuan Wang
- School of Optics and Photonics, Beijing Institute of Technology, Beijing, China
| | - Ancong Wang
- School of Medical Technology, Beijing Institute of Technology, Beijing, China
| | - Guozhao Dong
- School of Medical Technology, Beijing Institute of Technology, Beijing, China
| | - Yongsheng Jin
- Department of Infectious Diseases, The Affiliated Hospital of Yan'an University, Shaanxi, China
| | - Jingjing Xiao
- Bio-Med Informatics Research Center and Clinical Research Center, Xinqiao Hospital, Army Medical University, Chongqing, China
| | - Haiyan Ding
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China
| | - Xiaoying Tang
- School of Medical Technology, Beijing Institute of Technology, Beijing, China
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Gao J, Gong Y, Emu Y, Chen Z, Chen H, Yang F, Ding Z, Hua S, Jin W, Hu C. High Spatial-Resolution and Acquisition-Efficiency Cardiac MR T1 Mapping Based on Radial bSSFP and a Low-Rank Tensor Constraint. J Magn Reson Imaging 2024. [PMID: 39143028 DOI: 10.1002/jmri.29564] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2024] [Revised: 07/29/2024] [Accepted: 07/29/2024] [Indexed: 08/16/2024] Open
Abstract
BACKGROUND Cardiac T1 mapping is valuable for evaluating myocardial fibrosis, yet its resolution and acquisition efficiency are limited, potentially obscuring visualization of small pathologies. PURPOSE To develop a technique for high-resolution cardiac T1 mapping with a less-than-100-millisecond acquisition window based on radial MOdified Look-Locker Inversion recovery (MOLLI) and a calibrationless space-contrast-coil locally low-rank tensor (SCC-LLRT) constrained reconstruction. STUDY TYPE Prospective. SUBJECTS/PHANTOM Sixteen healthy subjects (age 25 ± 3 years, 44% females) and 12 patients with suspected cardiomyopathy (age 57 ± 15 years, 42% females), NiCl2-agar phantom. FIELD STRENGTH/SEQUENCE 3-T, standard MOLLI, radial MOLLI, inversion-recovery spin-echo, late gadolinium enhancement. ASSESSMENT SCC-LLRT was compared to a conventional locally low-rank (LLR) method through simulations using Normalized Root-Mean-Square Error (NRMSE) and Structural Similarity Index Measure (SSIM). Radial MOLLI was compared to standard MOLLI across phantom, healthy subjects, and patients. Three independent readers subjectively evaluated the quality of T1 maps using a 5-point scale (5 = best). STATISTICAL TESTS Paired t-test, Wilcoxon signed-rank test, intraclass correlation coefficient analysis, linear regression, Bland-Altman analysis. P < 0.05 was considered statistically significant. RESULTS In simulations, SCC-LLRT demonstrated a significant improvement in NRMSE and SSIM compared to LLR. In phantom, both radial MOLLI and standard MOLLI provided consistent T1 estimates across different heart rates. In healthy subjects, radial MOLLI exhibited a significantly lower mean T1 (1115 ± 39 msec vs. 1155 ± 36 msec), similar T1 SD (74 ± 14 msec vs. 67 ± 23 msec, P = 0.20), and similar T1 reproducibility (28 ± 18 msec vs. 22 ± 15 msec, P = 0.34) compared to standard MOLLI. In patients, the proposed method significantly improved the sharpness of myocardial boundaries (4.50 ± 0.65 vs. 3.25 ± 0.43), the conspicuity of papillary muscles and fine structures (4.33 ± 0.74 vs. 3.33 ± 0.47), and artifacts (4.75 ± 0.43 vs. 3.83 ± 0.55). The reconstruction time for a single slice was 5.2 hours. DATA CONCLUSION The proposed method enables high-resolution cardiac T1 mapping with a short acquisition window and improved image quality. EVIDENCE LEVEL 1 TECHNICAL EFFICACY: Stage 1.
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Affiliation(s)
- Juan Gao
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Yiwen Gong
- Department of Cardiovascular Medicine, Heart Failure Center, Ruijin Hospital and Ruijin Hospital Lu Wan Branch, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yixin Emu
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Zhuo Chen
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Haiyang Chen
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Fan Yang
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Zekang Ding
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Sha Hua
- Department of Cardiovascular Medicine, Heart Failure Center, Ruijin Hospital and Ruijin Hospital Lu Wan Branch, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Wei Jin
- Department of Cardiovascular Medicine, Heart Failure Center, Ruijin Hospital and Ruijin Hospital Lu Wan Branch, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Chenxi Hu
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
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Zhang JH, Neumann T, Schaeffter T, Kolbitsch C, Kerkering KM. Respiratory motion-corrected T1 mapping of the abdomen. MAGMA (NEW YORK, N.Y.) 2024; 37:637-649. [PMID: 39133420 PMCID: PMC11417068 DOI: 10.1007/s10334-024-01196-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/19/2024] [Revised: 07/25/2024] [Accepted: 07/26/2024] [Indexed: 08/13/2024]
Abstract
OBJECTIVE The purpose of this study was to investigate an approach for motion-corrected T1 mapping of the abdomen that allows for free breathing data acquisition with 100% scan efficiency. MATERIALS AND METHODS Data were acquired using a continuous golden radial trajectory and multiple inversion pulses. For the correction of respiratory motion, motion estimation based on a surrogate was performed from the same data used for T1 mapping. Image-based self-navigation allowed for binning and reconstruction of respiratory-resolved images, which were used for the estimation of respiratory motion fields. Finally, motion-corrected T1 maps were calculated from the data applying the estimated motion fields. The method was evaluated in five healthy volunteers. For the assessment of the image-based navigator, we compared it to a simultaneously acquired ultrawide band radar signal. Motion-corrected T1 maps were evaluated qualitatively and quantitatively for different scan times. RESULTS For all volunteers, the motion-corrected T1 maps showed fewer motion artifacts in the liver as well as sharper kidney structures and blood vessels compared to uncorrected T1 maps. Moreover, the relative error to the reference breathhold T1 maps could be reduced from up to 25% for the uncorrected T1 maps to below 10% for the motion-corrected maps for the average value of a region of interest, while the scan time could be reduced to 6-8 s. DISCUSSION The proposed approach allows for respiratory motion-corrected T1 mapping in the abdomen and ensures accurate T1 maps without the need for any breathholds.
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Affiliation(s)
- Jana Huiyue Zhang
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Germany.
- Department of Biomedical Engineering, Technical University of Berlin, Berlin, Germany.
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland.
| | - Tom Neumann
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Germany
| | - Tobias Schaeffter
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Germany
- Department of Biomedical Engineering, Technical University of Berlin, Berlin, Germany
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Christoph Kolbitsch
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Germany
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
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Razzaq S, Haririsanati L, Eyre K, Garg R, Chetrit M, Friedrich MG. Inter-scanner comparability of Z-scores for native myocardial T1 and T2 mapping. J Cardiovasc Magn Reson 2024; 26:100004. [PMID: 38211657 PMCID: PMC11211228 DOI: 10.1016/j.jocmr.2023.100004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2023] [Accepted: 12/10/2023] [Indexed: 01/13/2024] Open
Abstract
BACKGROUND Cardiovascular Magnetic Resonance (CMR) native T1 and T2 mapping serve as robust, contrast-agent-free diagnostic tools, but hardware- and software-specific sources of variability limit the generalizability of data across CMR platforms, consequently limiting the interpretability of patient-specific parametric data. Z-scores are used to describe the relationship of observed values to the mean results as obtained in a sufficiently large normal sample. They have been successfully used to describe the severity of quantifiable abnormalities in medicine, specifically in children and adolescents. The objective of this study was to observe whether z-scores can improve the comparability of T1 and T2 mapping values across CMR scanners, field strengths, and sequences from different vendors in the same participant rather than different participants (as seen in previous studies). METHODS Fifty-one healthy volunteers (26 men/25 women, mean age = 43 ± 13.51) underwent three CMR exams on three different scanners, using a Modified Look-Locker Inversion Recovery (MOLLI) 5-(3)- 3 sequence to quantify myocardial T1. For T2 mapping, a True Fast Imaging with steady-state free precession (TRUFI) sequence was used on a 3 T Skyra™ (Siemens), and a T2 Fast Spin Echo (FSE) sequence was used on 1.5 T Artist™ (GE) and 3.0 T Premier™ (GE) scanners. The averages of basal and mid-ventricular short axis slices were used to derive means and standard deviations of global mapping values. We used intra-class comparisons (ICC), repeated measures ANOVA, and paired Student's t-tests for statistical analyses. RESULTS There was a significant improvement in intra-subject comparability of T1 (ICC of 0.11 (95% CI= -0.018, -0.332) vs 0.78 (95% CI= 0.650, 0.866)) and T2 (ICC of 0.35 (95% CI= -0.053, 0.652) vs 0.83 (95% CI= 0.726, 0.898)) when using z-scores across all three scanners. While the absolute global T1 and T2 values showed a statistically significant difference between scanners (p < 0.001), no such differences were identified using z-scores (T1z: p = 0.771; T2z: p = 0.985). Furthermore, when images were not corrected for motion, T1 z-scores showed significant inter-scanner variability (p < 0.001), resolved by motion correction. CONCLUSION Employing z-scores for reporting myocardial T1 and T2 removes the variation of quantitative mapping results across different MRI systems and field strengths, improving the clinical utility of myocardial tissue characterization in patients with suspected myocardial disease.
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Affiliation(s)
- Saad Razzaq
- Faculty of Medicine and Health Sciences, McGill University, 845 Sherbrooke St W, Montreal, Quebec H3A 0G4, Canada; McGill University Health Centre, 1001 Decarie Blvd., Montreal, Quebec H4A 3J1, Canada
| | - Leila Haririsanati
- McGill University Health Centre, 1001 Decarie Blvd., Montreal, Quebec H4A 3J1, Canada
| | - Katerina Eyre
- McGill University Health Centre, 1001 Decarie Blvd., Montreal, Quebec H4A 3J1, Canada
| | - Ria Garg
- Department of Internal Medicine, Geisinger Commonwealth School of Medicine, 525 Pine St, Scranton, PA 18510, United States
| | - Michael Chetrit
- Faculty of Medicine and Health Sciences, McGill University, 845 Sherbrooke St W, Montreal, Quebec H3A 0G4, Canada; McGill University Health Centre, 1001 Decarie Blvd., Montreal, Quebec H4A 3J1, Canada
| | - Matthias G Friedrich
- McGill University Health Centre, 1001 Decarie Blvd., Montreal, Quebec H4A 3J1, Canada; Departments of Medicine and Diagnostic Radiology, McGill University, 845 Sherbrooke St W, Montreal, Quebec H3A 0G4, Canada.
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Sheagren CD, Cao T, Patel JH, Chen Z, Lee HL, Wang N, Christodoulou AG, Wright GA. Motion-compensated T 1 mapping in cardiovascular magnetic resonance imaging: a technical review. Front Cardiovasc Med 2023; 10:1160183. [PMID: 37790594 PMCID: PMC10542904 DOI: 10.3389/fcvm.2023.1160183] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2023] [Accepted: 08/22/2023] [Indexed: 10/05/2023] Open
Abstract
T 1 mapping is becoming a staple magnetic resonance imaging method for diagnosing myocardial diseases such as ischemic cardiomyopathy, hypertrophic cardiomyopathy, myocarditis, and more. Clinically, most T 1 mapping sequences acquire a single slice at a single cardiac phase across a 10 to 15-heartbeat breath-hold, with one to three slices acquired in total. This leaves opportunities for improving patient comfort and information density by acquiring data across multiple cardiac phases in free-running acquisitions and across multiple respiratory phases in free-breathing acquisitions. Scanning in the presence of cardiac and respiratory motion requires more complex motion characterization and compensation. Most clinical mapping sequences use 2D single-slice acquisitions; however newer techniques allow for motion-compensated reconstructions in three dimensions and beyond. To further address confounding factors and improve measurement accuracy, T 1 maps can be acquired jointly with other quantitative parameters such as T 2 , T 2 ∗ , fat fraction, and more. These multiparametric acquisitions allow for constrained reconstruction approaches that isolate contributions to T 1 from other motion and relaxation mechanisms. In this review, we examine the state of the literature in motion-corrected and motion-resolved T 1 mapping, with potential future directions for further technical development and clinical translation.
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Affiliation(s)
- Calder D. Sheagren
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
- Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
| | - Tianle Cao
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, United States
- Department of Bioengineering, University of California, Los Angeles, CA, United States
| | - Jaykumar H. Patel
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
- Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
| | - Zihao Chen
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, United States
- Department of Bioengineering, University of California, Los Angeles, CA, United States
| | - Hsu-Lei Lee
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, United States
| | - Nan Wang
- Department of Radiology, Stanford University, Stanford, CA, United States
| | - Anthony G. Christodoulou
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, United States
- Department of Bioengineering, University of California, Los Angeles, CA, United States
| | - Graham A. Wright
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
- Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
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Gröschel J, Trauzeddel RF, Müller M, von Knobelsdorff-Brenkenhoff F, Viezzer D, Hadler T, Blaszczyk E, Daud E, Schulz-Menger J. Multi-site comparison of parametric T1 and T2 mapping: healthy travelling volunteers in the Berlin research network for cardiovascular magnetic resonance (BER-CMR). J Cardiovasc Magn Reson 2023; 25:47. [PMID: 37574535 PMCID: PMC10424349 DOI: 10.1186/s12968-023-00954-9] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2023] [Accepted: 07/10/2023] [Indexed: 08/15/2023] Open
Abstract
BACKGROUND Parametric mapping sequences in cardiovascular magnetic resonance (CMR) allow for non-invasive myocardial tissue characterization. However quantitative myocardial mapping is still limited by the need for local reference values. Confounders, such as field strength, vendors and sequences, make intersite comparisons challenging. This exploratory study aims to assess whether multi-site studies that control confounding factors provide first insights whether parametric mapping values are within pre-defined tolerance ranges across scanners and sites. METHODS A cohort of 20 healthy travelling volunteers was prospectively scanned at three sites with a 3 T scanner from the same vendor using the same scanning protocol and acquisition scheme. A Modified Look-Locker inversion recovery sequence (MOLLI) for T1 and a fast low-angle shot sequence (FLASH) for T2 were used. At one site a scan-rescan was performed to assess the intra-scanner reproducibility. All acquired T1- and T2-mappings were analyzed in a core laboratory using the same post-processing approach and software. RESULTS After exclusion of one volunteer due to an accidentally diagnosed cardiac disease, T1- and T2-maps of 19 volunteers showed no significant differences between the 3 T sites (mean ± SD [95% confidence interval] for global T1 in ms: site I: 1207 ± 32 [1192-1222]; site II: 1207 ± 40 [1184-1225]; site III: 1219 ± 26 [1207-1232]; p = 0.067; for global T2 in ms: site I: 40 ± 2 [39-41]; site II: 40 ± 1 [39-41]; site III 39 ± 2 [39-41]; p = 0.543). CONCLUSION Parametric mapping results displayed initial hints at a sufficient similarity between sites when confounders, such as field strength, vendor diversity, acquisition schemes and post-processing analysis are harmonized. This finding needs to be confirmed in a powered clinical trial. Trial registration ISRCTN14627679 (retrospectively registered).
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Affiliation(s)
- Jan Gröschel
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität Zu Berlin, ECRC Experimental and Clinical Research Center, Lindenberger Weg 80, 13125, Berlin, Germany
- Working Group On Cardiovascular Magnetic Resonance, Experimental and Clinical Research Center, a joint cooperation between Charité Medical Faculty and the Max-Delbrück Center for Molecular Medicine, Lindenberger Weg 80, 13125, Berlin, Germany
- DZHK (German Centre for Cardiovascular Research), Partner Site Berlin, Berlin, Germany
| | - Ralf-Felix Trauzeddel
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität Zu Berlin, ECRC Experimental and Clinical Research Center, Lindenberger Weg 80, 13125, Berlin, Germany
- Working Group On Cardiovascular Magnetic Resonance, Experimental and Clinical Research Center, a joint cooperation between Charité Medical Faculty and the Max-Delbrück Center for Molecular Medicine, Lindenberger Weg 80, 13125, Berlin, Germany
- DZHK (German Centre for Cardiovascular Research), Partner Site Berlin, Berlin, Germany
- Department of Anaesthesiology and Intensive Care Medicine, Campus Benjamin Franklin, Charité, Universitätsmedizin Berlin, corporate member of Freie Universität Berlin Und Humboldt-Universität Zu Berlin, Berlin, Germany
| | - Maximilian Müller
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität Zu Berlin, ECRC Experimental and Clinical Research Center, Lindenberger Weg 80, 13125, Berlin, Germany
- Working Group On Cardiovascular Magnetic Resonance, Experimental and Clinical Research Center, a joint cooperation between Charité Medical Faculty and the Max-Delbrück Center for Molecular Medicine, Lindenberger Weg 80, 13125, Berlin, Germany
| | - Florian von Knobelsdorff-Brenkenhoff
- Working Group On Cardiovascular Magnetic Resonance, Experimental and Clinical Research Center, a joint cooperation between Charité Medical Faculty and the Max-Delbrück Center for Molecular Medicine, Lindenberger Weg 80, 13125, Berlin, Germany
- KIZ, Kardiologie im Zentrum, Eisenmannstr. 4, 80331, Munich, Deutschland
| | - Darian Viezzer
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität Zu Berlin, ECRC Experimental and Clinical Research Center, Lindenberger Weg 80, 13125, Berlin, Germany
- Working Group On Cardiovascular Magnetic Resonance, Experimental and Clinical Research Center, a joint cooperation between Charité Medical Faculty and the Max-Delbrück Center for Molecular Medicine, Lindenberger Weg 80, 13125, Berlin, Germany
- DZHK (German Centre for Cardiovascular Research), Partner Site Berlin, Berlin, Germany
| | - Thomas Hadler
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität Zu Berlin, ECRC Experimental and Clinical Research Center, Lindenberger Weg 80, 13125, Berlin, Germany
- Working Group On Cardiovascular Magnetic Resonance, Experimental and Clinical Research Center, a joint cooperation between Charité Medical Faculty and the Max-Delbrück Center for Molecular Medicine, Lindenberger Weg 80, 13125, Berlin, Germany
- DZHK (German Centre for Cardiovascular Research), Partner Site Berlin, Berlin, Germany
| | - Edyta Blaszczyk
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität Zu Berlin, ECRC Experimental and Clinical Research Center, Lindenberger Weg 80, 13125, Berlin, Germany
- Working Group On Cardiovascular Magnetic Resonance, Experimental and Clinical Research Center, a joint cooperation between Charité Medical Faculty and the Max-Delbrück Center for Molecular Medicine, Lindenberger Weg 80, 13125, Berlin, Germany
- DZHK (German Centre for Cardiovascular Research), Partner Site Berlin, Berlin, Germany
| | - Elias Daud
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität Zu Berlin, ECRC Experimental and Clinical Research Center, Lindenberger Weg 80, 13125, Berlin, Germany
- Working Group On Cardiovascular Magnetic Resonance, Experimental and Clinical Research Center, a joint cooperation between Charité Medical Faculty and the Max-Delbrück Center for Molecular Medicine, Lindenberger Weg 80, 13125, Berlin, Germany
- DZHK (German Centre for Cardiovascular Research), Partner Site Berlin, Berlin, Germany
- The Cardiology Department, Galilee Medical Center, Azrieli Faculty of Medicine Bar-Ilan University, Nahariya, Safed, Israel
| | - Jeanette Schulz-Menger
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität Zu Berlin, ECRC Experimental and Clinical Research Center, Lindenberger Weg 80, 13125, Berlin, Germany.
- Working Group On Cardiovascular Magnetic Resonance, Experimental and Clinical Research Center, a joint cooperation between Charité Medical Faculty and the Max-Delbrück Center for Molecular Medicine, Lindenberger Weg 80, 13125, Berlin, Germany.
- DZHK (German Centre for Cardiovascular Research), Partner Site Berlin, Berlin, Germany.
- Department of Cardiology and Nephrology, HELIOS Hospital Berlin-Buch, Berlin, Germany.
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Phair A, Cruz G, Qi H, Botnar RM, Prieto C. Free-running 3D whole-heart T 1 and T 2 mapping and cine MRI using low-rank reconstruction with non-rigid cardiac motion correction. Magn Reson Med 2023; 89:217-232. [PMID: 36198014 PMCID: PMC9828568 DOI: 10.1002/mrm.29449] [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: 03/14/2022] [Revised: 07/14/2022] [Accepted: 08/18/2022] [Indexed: 01/12/2023]
Abstract
PURPOSE To introduce non-rigid cardiac motion correction into a novel free-running framework for the simultaneous acquisition of 3D whole-heart myocardial <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics> <mml:mrow> <mml:msub><mml:mrow><mml:mi>T</mml:mi></mml:mrow> <mml:mrow><mml:mn>1</mml:mn></mml:mrow> </mml:msub> </mml:mrow> <mml:annotation>$$ {T}_1 $$</mml:annotation></mml:semantics> </mml:math> and <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics> <mml:mrow> <mml:msub><mml:mrow><mml:mi>T</mml:mi></mml:mrow> <mml:mrow><mml:mn>2</mml:mn></mml:mrow> </mml:msub> </mml:mrow> <mml:annotation>$$ {T}_2 $$</mml:annotation></mml:semantics> </mml:math> maps and cine images, enabling a <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics><mml:mrow><mml:mo>∼</mml:mo></mml:mrow> <mml:annotation>$$ \sim $$</mml:annotation></mml:semantics> </mml:math> 3-min scan. METHODS Data were acquired using a free-running 3D golden-angle radial readout interleaved with inversion recovery and <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics> <mml:mrow> <mml:msub><mml:mrow><mml:mi>T</mml:mi></mml:mrow> <mml:mrow><mml:mn>2</mml:mn></mml:mrow> </mml:msub> </mml:mrow> <mml:annotation>$$ {T}_2 $$</mml:annotation></mml:semantics> </mml:math> -preparation pulses. After correction for translational respiratory motion, non-rigid cardiac-motion-corrected reconstruction with dictionary-based low-rank compression and patch-based regularization enabled 3D whole-heart <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics> <mml:mrow> <mml:msub><mml:mrow><mml:mi>T</mml:mi></mml:mrow> <mml:mrow><mml:mn>1</mml:mn></mml:mrow> </mml:msub> </mml:mrow> <mml:annotation>$$ {T}_1 $$</mml:annotation></mml:semantics> </mml:math> and <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics> <mml:mrow> <mml:msub><mml:mrow><mml:mi>T</mml:mi></mml:mrow> <mml:mrow><mml:mn>2</mml:mn></mml:mrow> </mml:msub> </mml:mrow> <mml:annotation>$$ {T}_2 $$</mml:annotation></mml:semantics> </mml:math> mapping at any given cardiac phase as well as whole-heart cardiac cine imaging. The framework was validated and compared with established methods in 11 healthy subjects. RESULTS Good quality 3D <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics> <mml:mrow> <mml:msub><mml:mrow><mml:mi>T</mml:mi></mml:mrow> <mml:mrow><mml:mn>1</mml:mn></mml:mrow> </mml:msub> </mml:mrow> <mml:annotation>$$ {T}_1 $$</mml:annotation></mml:semantics> </mml:math> and <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics> <mml:mrow> <mml:msub><mml:mrow><mml:mi>T</mml:mi></mml:mrow> <mml:mrow><mml:mn>2</mml:mn></mml:mrow> </mml:msub> </mml:mrow> <mml:annotation>$$ {T}_2 $$</mml:annotation></mml:semantics> </mml:math> maps and cine images were reconstructed for all subjects. Septal <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics> <mml:mrow> <mml:msub><mml:mrow><mml:mi>T</mml:mi></mml:mrow> <mml:mrow><mml:mn>1</mml:mn></mml:mrow> </mml:msub> </mml:mrow> <mml:annotation>$$ {T}_1 $$</mml:annotation></mml:semantics> </mml:math> values using the proposed approach ( <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics><mml:mrow><mml:mn>1200</mml:mn> <mml:mo>±</mml:mo> <mml:mn>50</mml:mn></mml:mrow> <mml:annotation>$$ 1200\pm 50 $$</mml:annotation></mml:semantics> </mml:math> ms) were higher than those from a 2D MOLLI sequence ( <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics><mml:mrow><mml:mn>1063</mml:mn> <mml:mo>±</mml:mo> <mml:mn>33</mml:mn></mml:mrow> <mml:annotation>$$ 1063\pm 33 $$</mml:annotation></mml:semantics> </mml:math> ms), which is known to underestimate <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics> <mml:mrow> <mml:msub><mml:mrow><mml:mi>T</mml:mi></mml:mrow> <mml:mrow><mml:mn>1</mml:mn></mml:mrow> </mml:msub> </mml:mrow> <mml:annotation>$$ {T}_1 $$</mml:annotation></mml:semantics> </mml:math> , while <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics> <mml:mrow> <mml:msub><mml:mrow><mml:mi>T</mml:mi></mml:mrow> <mml:mrow><mml:mn>2</mml:mn></mml:mrow> </mml:msub> </mml:mrow> <mml:annotation>$$ {T}_2 $$</mml:annotation></mml:semantics> </mml:math> values from the proposed approach ( <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics><mml:mrow><mml:mn>51</mml:mn> <mml:mo>±</mml:mo> <mml:mn>4</mml:mn></mml:mrow> <mml:annotation>$$ 51\pm 4 $$</mml:annotation></mml:semantics> </mml:math> ms) were in good agreement with those from a 2D GraSE sequence ( <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics><mml:mrow><mml:mn>51</mml:mn> <mml:mo>±</mml:mo> <mml:mn>2</mml:mn></mml:mrow> <mml:annotation>$$ 51\pm 2 $$</mml:annotation></mml:semantics> </mml:math> ms). CONCLUSION The proposed technique provides 3D <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics> <mml:mrow> <mml:msub><mml:mrow><mml:mi>T</mml:mi></mml:mrow> <mml:mrow><mml:mn>1</mml:mn></mml:mrow> </mml:msub> </mml:mrow> <mml:annotation>$$ {T}_1 $$</mml:annotation></mml:semantics> </mml:math> and <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics> <mml:mrow> <mml:msub><mml:mrow><mml:mi>T</mml:mi></mml:mrow> <mml:mrow><mml:mn>2</mml:mn></mml:mrow> </mml:msub> </mml:mrow> <mml:annotation>$$ {T}_2 $$</mml:annotation></mml:semantics> </mml:math> maps and cine images with isotropic spatial resolution in a single <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics><mml:mrow><mml:mo>∼</mml:mo></mml:mrow> <mml:annotation>$$ \sim $$</mml:annotation></mml:semantics> </mml:math> 3.3-min scan.
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Affiliation(s)
- Andrew Phair
- School of Biomedical Engineering and Imaging SciencesKing's College LondonLondonUK
| | - Gastão Cruz
- School of Biomedical Engineering and Imaging SciencesKing's College LondonLondonUK
| | - Haikun Qi
- School of Biomedical EngineeringShanghaiTech UniversityShanghaiChina
| | - René M. Botnar
- School of Biomedical Engineering and Imaging SciencesKing's College LondonLondonUK,Instituto de Ingeniería Biológica y MédicaPontificia Universidad Católica de ChileSantiagoChile,Escuela de IngenieríaPontificia Universidad Católica de ChileSantiagoChile,Millennium Institute for Intelligent Healthcare EngineeringSantiagoChile
| | - Claudia Prieto
- School of Biomedical Engineering and Imaging SciencesKing's College LondonLondonUK,Escuela de IngenieríaPontificia Universidad Católica de ChileSantiagoChile,Millennium Institute for Intelligent Healthcare EngineeringSantiagoChile
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8
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Gatefait CGF, Ellison SLR, Nyangoma S, Schmitter S, Kolbitsch C. Optimisation of data acquisition towards continuous cardiac Magnetic Resonance Fingerprinting applications. Phys Med 2023; 105:102514. [PMID: 36608390 DOI: 10.1016/j.ejmp.2022.102514] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/06/2022] [Revised: 11/10/2022] [Accepted: 12/12/2022] [Indexed: 01/06/2023] Open
Abstract
PURPOSE Assess and optimise acquisition parameters for continuous cardiac Magnetic Resonance Fingerprinting (MRF). METHODS Different acquisition schemes (flip angle amplitude, lobe size, T2-preparation pulses) for cardiac MRF were assessed in simulations and phantom and demonstrated in one healthy volunteer. Three different experimental designs were evaluated using central composite and fractional factorial designs. Relative errors for T1 and T2 were calculated for a wide range of realistic T1 and T2 value combinations. The effect of different designs on the accuracy of T1 and T2 was assessed using response surface modelling and Cohen's f calculations. RESULTS Larger flip angle amplitudes lead to an improvement of T2 accuracy and precision for simulations and phantom experiments. Similar effects could also be shown qualitatively in in-vivo scans. Accuracy and precision of T1 were robust to different design parameters with improved values for faster flip angle variation. Cohen's f showed that T2-preparation pulses influence the accuracy of T2. The number of pulses used is the most important parameter. Without T2-preparation pulses, RMSE were 3.0 ± 8.09 % for T1 and 16.24 ± 14.47 % for T2. Using those pulses reduced the RMSE to 2.3 ± 8.4 % for T1 and 14.11 ± 13.46 % for T2. Nonetheless, even if the improvement is significant, RMSE are still too high for reliable quantification. CONCLUSION In contrast to previous study using triggered MRF sequences using < 30° flip angles, large flip angle amplitudes led to better results for continuous cardiac MRF sequences. T2-preparation pulse can improve the accuracy of T2 estimation but lead to longer scan times.
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9
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Hufnagel S, Metzner S, Kerkering KM, Aigner CS, Kofler A, Schulz-Menger J, Schaeffter T, Kolbitsch C. 3D model-based super-resolution motion-corrected cardiac T1 mapping. Phys Med Biol 2022; 67. [PMID: 36265478 DOI: 10.1088/1361-6560/ac9c40] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2022] [Accepted: 10/20/2022] [Indexed: 12/13/2022]
Abstract
Objective. To provide 3D high-resolution cardiac T1 maps using model-based super-resolution reconstruction (SRR).Approach. Due to signal-to-noise ratio limitations and the motion of the heart during imaging, often 2D T1 maps with only low through-plane resolution (i.e. slice thickness of 6-8 mm) can be obtained. Here, a model-based SRR approach is presented, which combines multiple stacks of 2D acquisitions with 6-8 mm slice thickness and generates 3D high-resolution T1 maps with a slice thickness of 1.5-2 mm. Every stack was acquired in a different breath hold (BH) and any misalignment between BH was corrected retrospectively. The novelty of the proposed approach is the BH correction and the application of model-based SRR on cardiac T1 Mapping. The proposed approach was evaluated in numerical simulations and phantom experiments and demonstrated in four healthy subjects.Main results. Alignment of BH states was essential for SRR even in healthy volunteers. In simulations, respiratory motion could be estimated with an RMS error of 0.18 ± 0.28 mm. SRR improved the visualization of small structures. High accuracy and precision (average standard deviation of 69.62 ms) of the T1 values was ensured by SRR while the detectability of small structures increased by 40%.Significance. The proposed SRR approach provided T1 maps with high in-plane and high through-plane resolution (1.3 × 1.3 × 1.5-2 mm3). The approach led to improvements in the visualization of small structures and precise T1 values.
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Affiliation(s)
- Simone Hufnagel
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Germany
| | - Selma Metzner
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Germany
| | | | | | - Andreas Kofler
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Germany
| | - Jeanette Schulz-Menger
- Charité Medical Faculty University Medicine, Berlin, Germany.,Working Group on Cardiovascular Magnetic Resonance, Experimental and Clinical Research Center (ECRC), Charité Humboldt University Berlin, DZHK partner site Berlin, Berlin, Germany.,Department of Cardiology and Nephrology, HELIOS Klinikum Berlin Buch, 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.,Department of Biomedical Engineering, Technical University of Berlin, Berlin, Germany
| | - Christoph Kolbitsch
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Germany
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10
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Li Y, Wu C, Qi H, Si D, Ding H, Chen H. Motion correction for native myocardial T 1 mapping using self-supervised deep learning registration with contrast separation. NMR IN BIOMEDICINE 2022; 35:e4775. [PMID: 35599351 DOI: 10.1002/nbm.4775] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/16/2022] [Revised: 05/15/2022] [Accepted: 05/18/2022] [Indexed: 06/15/2023]
Abstract
In myocardial T1 mapping, undesirable motion poses significant challenges because uncorrected motion can affect T1 estimation accuracy and cause incorrect diagnosis. In this study, we propose and evaluate a motion correction method for myocardial T1 mapping using self-supervised deep learning based registration with contrast separation (SDRAP). A sparse coding based method was first proposed to separate the contrast component from T1 -weighted (T1w) images. Then, a self-supervised deep neural network with cross-correlation (SDRAP-CC) or mutual information as the registration similarity measurement was developed to register contrast separated images, after which signal fitting was performed on the motion corrected T1w images to generate motion corrected T1 maps. The registration network was trained and tested in 80 healthy volunteers with images acquired using the modified Look-Locker inversion recovery (MOLLI) sequence. The proposed SDRAP was compared with the free form deformation (FFD) registration method regarding (1) Dice similarity coefficient (DSC) and mean boundary error (MBE) of myocardium contours, (2) T1 value and standard deviation (SD) of T1 fitting, (3) subjective evaluation score for overall image quality and motion artifact level, and (4) computation time. Results showed that SDRAP-CC achieved the highest DSC of 85.0 ± 3.9% and the lowest MBE of 0.92 ± 0.25 mm among the methods compared. Additionally, SDRAP-CC performed the best by resulting in lower SD value (28.1 ± 17.6 ms) and higher subjective image quality scores (3.30 ± 0.79 for overall quality and 3.53 ± 0.68 for motion artifact) evaluated by a cardiologist. The proposed SDRAP took only 0.52 s to register one slice of MOLLI images, achieving about sevenfold acceleration over FFD (3.7 s/slice).
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Affiliation(s)
- Yuze Li
- Center for Biomedical Imaging Research (CBIR), School of Medicine, Tsinghua University, Beijing, China
| | - Chunyan Wu
- Center for Biomedical Imaging Research (CBIR), School of Medicine, Tsinghua University, Beijing, China
| | - Haikun Qi
- School of Biomedical Engineering, ShanghaiTech University, Shanghai, China
| | - Dongyue Si
- Center for Biomedical Imaging Research (CBIR), School of Medicine, Tsinghua University, Beijing, China
| | - Haiyan Ding
- Center for Biomedical Imaging Research (CBIR), School of Medicine, Tsinghua University, Beijing, China
| | - Huijun Chen
- Center for Biomedical Imaging Research (CBIR), School of Medicine, Tsinghua University, Beijing, China
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11
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Guo R, Qi H, Amyar A, Cai X, Kucukseymen S, Haji-Valizadeh H, Rodriguez J, Paskavitz A, Pierce P, Goddu B, Thompson RB, Nezafat R. Quantification of changes in myocardial T 1 * values with exercise cardiac MRI using a free-breathing non-electrocardiograph radial imaging. Magn Reson Med 2022; 88:1720-1733. [PMID: 35691942 DOI: 10.1002/mrm.29346] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2021] [Revised: 05/09/2022] [Accepted: 05/16/2022] [Indexed: 11/11/2022]
Abstract
PURPOSE To develop and evaluate a free breathing non-electrocardiograph (ECG) myocardial T1 * mapping sequence using radial imaging to quantify the changes in myocardial T1 * between rest and exercise (T1 *reactivity ) in exercise cardiac MRI (Ex-CMR). METHODS A free-running T1 * sequence was developed using a saturation pulse followed by three Look-Locker inversion-recovery experiments. Each Look-Locker continuously acquired data as radial trajectory using a low flip-angle spoiled gradient-echo readout. Self-navigation was performed with a temporal resolution of ∼100 ms for retrospectively extracting respiratory motion. The mid-diastole phase for every cardiac cycle was retrospectively detected on the recorded electrocardiogram signal using an empirical model. Multiple measurements were performed to obtain mean value to reduce effects from the free-breathing acquisition. Finally, data acquired at both mid-diastole and end-expiration are picked and reconstructed by a low-rank plus sparsity constraint algorithm. The performance of this sequence was evaluated by simulations, phantoms, and in vivo studies at rest and after physiological exercise. RESULTS Numerical simulation demonstrated that changes in T1 * are related to the changes in T1 ; however, other factors such as breathing motion could influence T1 * measurements. Phantom T1 * values measured using free-running T1 * mapping sequence had good correlation with spin-echo T1 values and was insensitive to heart rate. In the Ex-CMR study, the measured T1 * reactivity was 10% immediately after exercise and declined over time. CONCLUSION The free-running T1 * mapping sequence allows free-breathing non-ECG quantification of changes in myocardial T1 * with physiological exercise. Although, absolute myocardial T1 * value is sensitive to various confounders such as B1 and B0 inhomogeneity, quantification of its change may be useful in revealing myocardial tissue properties with exercise.
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Affiliation(s)
- Rui Guo
- Department of Medicine, Cardiovascular Division, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA
| | - Haikun Qi
- School of Biomedical Engineering, ShanghaiTech University, Shanghai, China
| | - Amine Amyar
- Department of Medicine, Cardiovascular Division, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA
| | - Xiaoying Cai
- Department of Medicine, Cardiovascular Division, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA.,Siemens Medical Solutions USA, Inc., Boston, MA, USA
| | - Selcuk Kucukseymen
- Department of Medicine, Cardiovascular Division, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA
| | - Hassan Haji-Valizadeh
- Department of Medicine, Cardiovascular Division, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA
| | - Jennifer Rodriguez
- Department of Medicine, Cardiovascular Division, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA
| | - Amanda Paskavitz
- Department of Medicine, Cardiovascular Division, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA
| | - Patrick Pierce
- Department of Medicine, Cardiovascular Division, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA
| | - Beth Goddu
- Department of Medicine, Cardiovascular Division, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA
| | - Richard B Thompson
- Department of Biomedical Engineering, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, Canada
| | - Reza Nezafat
- Department of Medicine, Cardiovascular Division, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA
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12
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Gonzales RA, Zhang Q, Papież BW, Werys K, Lukaschuk E, Popescu IA, Burrage MK, Shanmuganathan M, Ferreira VM, Piechnik SK. MOCOnet: Robust Motion Correction of Cardiovascular Magnetic Resonance T1 Mapping Using Convolutional Neural Networks. Front Cardiovasc Med 2021; 8:768245. [PMID: 34888366 PMCID: PMC8649951 DOI: 10.3389/fcvm.2021.768245] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Accepted: 10/27/2021] [Indexed: 01/27/2023] Open
Abstract
Background: Quantitative cardiovascular magnetic resonance (CMR) T1 mapping has shown promise for advanced tissue characterisation in routine clinical practise. However, T1 mapping is prone to motion artefacts, which affects its robustness and clinical interpretation. Current methods for motion correction on T1 mapping are model-driven with no guarantee on generalisability, limiting its widespread use. In contrast, emerging data-driven deep learning approaches have shown good performance in general image registration tasks. We propose MOCOnet, a convolutional neural network solution, for generalisable motion artefact correction in T1 maps. Methods: The network architecture employs U-Net for producing distance vector fields and utilises warping layers to apply deformation to the feature maps in a coarse-to-fine manner. Using the UK Biobank imaging dataset scanned at 1.5T, MOCOnet was trained on 1,536 mid-ventricular T1 maps (acquired using the ShMOLLI method) with motion artefacts, generated by a customised deformation procedure, and tested on a different set of 200 samples with a diverse range of motion. MOCOnet was compared to a well-validated baseline multi-modal image registration method. Motion reduction was visually assessed by 3 human experts, with motion scores ranging from 0% (strictly no motion) to 100% (very severe motion). Results: MOCOnet achieved fast image registration (<1 second per T1 map) and successfully suppressed a wide range of motion artefacts. MOCOnet significantly reduced motion scores from 37.1±21.5 to 13.3±10.5 (p < 0.001), whereas the baseline method reduced it to 15.8±15.6 (p < 0.001). MOCOnet was significantly better than the baseline method in suppressing motion artefacts and more consistently (p = 0.007). Conclusion: MOCOnet demonstrated significantly better motion correction performance compared to a traditional image registration approach. Salvaging data affected by motion with robustness and in a time-efficient manner may enable better image quality and reliable images for immediate clinical interpretation.
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Affiliation(s)
- Ricardo A Gonzales
- Oxford Centre for Clinical Magnetic Resonance Research (OCMR), Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Qiang Zhang
- Oxford Centre for Clinical Magnetic Resonance Research (OCMR), Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Bartłomiej W Papież
- Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom.,Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, United Kingdom
| | - Konrad Werys
- Oxford Centre for Clinical Magnetic Resonance Research (OCMR), Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Elena Lukaschuk
- Oxford Centre for Clinical Magnetic Resonance Research (OCMR), Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Iulia A Popescu
- Oxford Centre for Clinical Magnetic Resonance Research (OCMR), Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Matthew K Burrage
- Oxford Centre for Clinical Magnetic Resonance Research (OCMR), Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Mayooran Shanmuganathan
- Oxford Centre for Clinical Magnetic Resonance Research (OCMR), Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Vanessa M Ferreira
- Oxford Centre for Clinical Magnetic Resonance Research (OCMR), Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Stefan K Piechnik
- Oxford Centre for Clinical Magnetic Resonance Research (OCMR), Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, United Kingdom
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13
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Serry FM, Ma S, Mao X, Han F, Xie Y, Han H, Li D, Christodoulou AG. Dual flip-angle IR-FLASH with spin history mapping for B1+ corrected T1 mapping: Application to T1 cardiovascular magnetic resonance multitasking. Magn Reson Med 2021; 86:3182-3191. [PMID: 34309072 PMCID: PMC8568626 DOI: 10.1002/mrm.28935] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2021] [Revised: 06/07/2021] [Accepted: 07/01/2021] [Indexed: 12/27/2022]
Abstract
PURPOSE To develop a single-scan method for B 1 + -corrected T1 mapping and apply it for free-breathing (FB) cardiac MR multitasking without electrocardiogram (ECG) triggering. METHODS One dual flip-angle (2FA) inversion recovery (IR)-FLASH scan provides two observations of T 1 ∗ (apparent T1 ) corresponding to two distinct combinations of the nominal FA α and B 1 + . Spatiotemporally coregistered T1 and B 1 + spin history maps are obtained by fitting the 2FA signal model. T1 estimate accuracy and repeatability for single flip-angle (1FA) and 2FA IR-FLASH sequence MR multitasking were evaluated at 3T. A T1 phantom was first imaged on the scanner table, then on two human subjects' thoraxes in both breath-hold (BH) and FB conditions. IR-turbo spin echo (IR-TSE) static phantom T1 measurements served as reference. In 10 healthy subjects, myocardial T1 was evaluated with ECG-free, FB multitasking sequences alongside ECG-triggered BH MOLLI. RESULTS For phantom-on-table T1 estimates, 2FA agreed better with IR-TSE (intraclass correlation coefficient [ICC] = 0.996, mean error ± SD = -1.6% ± 1.9%) than did 1FA (ICC = 0.922; mean error ± SD = -4.3% ± 12%). For phantom-on-thorax, 2FA was more repeatable and robust to respiration than 1FA (coefficient of variation [CoV] = 1.2% 2FA, = 11.3% 1FA). In vivo, in intrasession T1 repeatability, 2FA (septal CoV = 2.4%, six-segment CoV = 4.4%) outperformed 1FA (septal CoV = 3.1%, six-segment CoV = 5.5%). In six-segment T1 homogeneity, 2FA (CoV = 7.9%) also outperformed 1FA (CoV = 11.1%). CONCLUSION The 2FA IR-FLASH improves T1 estimate accuracy and repeatability over 1FA IR-FLASH, and enables single-scan B 1 + -corrected T1 mapping without BHs or ECG when used with MR multitasking.
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Affiliation(s)
- Fardad Michael Serry
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Sen Ma
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Xianglun Mao
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Fei Han
- Siemens Medical Solutions USA, Inc., Los Angeles, CA, USA
| | - Yibin Xie
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Hui Han
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Debiao Li
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
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14
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Cruz G, Qi H, Jaubert O, Kuestner T, Schneider T, Botnar RM, Prieto C. Generalized low-rank nonrigid motion-corrected reconstruction for MR fingerprinting. Magn Reson Med 2021; 87:746-763. [PMID: 34601737 DOI: 10.1002/mrm.29027] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2021] [Revised: 08/12/2021] [Accepted: 09/09/2021] [Indexed: 12/15/2022]
Abstract
PURPOSE Develop a novel low-rank motion-corrected (LRMC) reconstruction for nonrigid motion-corrected MR fingerprinting (MRF). METHODS Generalized motion-corrected (MC) reconstructions have been developed for steady-state imaging. Here we extend this framework to enable nonrigid MC for transient imaging applications with varying contrast, such as MRF. This is achieved by integrating low-rank dictionary-based compression into the generalized MC model to reconstruct MC singular images, reducing motion artifacts in the resulting parametric maps. The proposed LRMC reconstruction was applied for cardiac motion correction in 2D myocardial MRF (T1 and T2 ) with extended cardiac acquisition window (~450 ms) and for respiratory MC in free-breathing 3D myocardial and 3D liver MRF. Experiments were performed in phantom and 22 healthy subjects. The proposed approach was compared with reference spin echo (phantom) and with 2D electrocardiogram-triggered/breath-hold MOLLI and T2 gradient-and-spin echo conventional maps (in vivo 2D and 3D myocardial MRF). RESULTS Phantom results were in general agreement with reference spin-echo measurements, presenting relative errors of approximately 5.4% and 5.5% for T1 and short T2 (<100 ms), respectively. The proposed LRMC MRF reduced residual blurring artifacts with respect to no MC for cardiac or respiratory motion in all cases (2D and 3D myocardial, 3D abdominal). In 2D myocardial MRF, left-ventricle T1 values were 1150 ± 41 ms for LRMC MRF and 1010 ± 56 ms for MOLLI; T2 values were 43.8 ± 2.3 ms for LRMC MRF and 49.5 ± 4.5 ms for T2 gradient and spin echo. Corresponding measurements for 3D myocardial MRF were 1085 ± 30 ms and 1062 ± 29 ms for T1 , and 43.5 ± 1.9 ms and 51.7 ± 1.7 ms for T2 . For 3D liver, LRMC MRF measured liver T1 at 565 ± 44 ms and liver T2 at 35.4 ± 2.4 ms. CONCLUSION The proposed LRMC reconstruction enabled generalized (nonrigid) MC for 2D and 3D MRF, both for cardiac and respiratory motion. The proposed approach reduced motion artifacts in the MRF maps with respect to no motion compensation and achieved good agreement with reference measurements.
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Affiliation(s)
- Gastao Cruz
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Haikun Qi
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Olivier Jaubert
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Thomas Kuestner
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | | | - Rene Michael Botnar
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom.,Escuela de Ingeniería, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Claudia Prieto
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom.,Escuela de Ingeniería, Pontificia Universidad Católica de Chile, Santiago, Chile
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15
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von Knobelsdorff-Brenkenhoff F, Reiter S, Menini A, Janich MA, Schunke T, Ziegler K, Scheck R, Höfling B, Pilz G. Influence of motion correction on the visual analysis of cardiac magnetic resonance stress perfusion imaging. MAGMA (NEW YORK, N.Y.) 2021; 34:757-766. [PMID: 33839986 DOI: 10.1007/s10334-021-00923-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/28/2020] [Revised: 02/12/2021] [Accepted: 03/17/2021] [Indexed: 06/12/2023]
Abstract
OBJECTIVE Image post-processing corrects for cardiac and respiratory motion (MoCo) during cardiovascular magnetic resonance (CMR) stress perfusion. The study analyzed its influence on visual image evaluation. MATERIALS AND METHODS Sixty-two patients with (suspected) coronary artery disease underwent a standard CMR stress perfusion exam during free-breathing. Image post-processing was performed without (non-MoCo) and with MoCo (image intensity normalization; motion extraction with iterative non-rigid registration; motion warping with the combined displacement field). Images were evaluated regarding the perfusion pattern (perfusion deficit, dark rim artifact, uncertain signal loss, and normal perfusion), the general image quality (non-diagnostic, imperfect, good, and excellent), and the reader's subjective confidence to assess the images (not confident, confident, very confident). RESULTS Fifty-three (non-MoCo) and 52 (MoCo) myocardial segments were rated as 'perfusion deficit', 113 vs. 109 as 'dark rim artifacts', 9 vs. 7 as 'uncertain signal loss', and 817 vs. 824 as 'normal'. Agreement between non-MoCo and MoCo was high with no diagnostic difference per-patient. The image quality of MoCo was rated more often as 'good' or 'excellent' (92 vs. 63%), and the diagnostic confidence more often as "very confident" (71 vs. 45%) compared to non-MoCo. CONCLUSIONS The comparison of perfusion images acquired during free-breathing and post-processed with and without motion correction demonstrated that both methods led to a consistent evaluation of the perfusion pattern, while the image quality and the reader's subjective confidence to assess the images were rated more favorably for MoCo.
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Affiliation(s)
| | - Stephanie Reiter
- Department of Cardiology, Academic Teaching Hospital Agatharied of the Ludwig-Maximilians-University Munich, Agatharied, Germany
| | - Anne Menini
- GE Healthcare, Applied Science Lab, Menlo Park, CA, USA
| | | | - Tobias Schunke
- Department of Cardiology, Academic Teaching Hospital Agatharied of the Ludwig-Maximilians-University Munich, Agatharied, Germany
| | - Karl Ziegler
- Department of Cardiology, Academic Teaching Hospital Agatharied of the Ludwig-Maximilians-University Munich, Agatharied, Germany
| | - Roland Scheck
- Department of Radiology, Academic Teaching Hospital Agatharied of the Ludwig-Maximilians-University Munich, Agatharied, Germany
| | - Berthold Höfling
- Department of Cardiology, Academic Teaching Hospital Agatharied of the Ludwig-Maximilians-University Munich, Agatharied, Germany
| | - Günter Pilz
- Department of Cardiology, Academic Teaching Hospital Agatharied of the Ludwig-Maximilians-University Munich, Agatharied, Germany
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16
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Abstract
PURPOSE OF REVIEW Left ventricular hypertrophy (LVH) is a common presentation encountered in clinical practice with a diverse range of potential aetiologies. Differentiation of pathological from physiological hypertrophy can be challenging but is crucial for further management and prognostication. Cardiovascular magnetic resonance (CMR) with advanced myocardial tissue characterisation is a powerful tool that may help to differentiate these aetiologies in the assessment of LVH. RECENT FINDINGS The use of CMR for detailed morphological assessment of LVH is well described. More recently, advanced CMR techniques (late gadolinium enhancement, parametric mapping, diffusion tensor imaging, and myocardial strain) have been used. These techniques are highly promising in helping to differentiate key aetiologies of LVH and provide valuable prognostic information. Recent advancements in CMR tissue characterisation, such as parametric mapping, in combination with detailed morphological assessment and late gadolinium enhancement, provide a powerful resource that may help assess and differentiate important causes of LVH.
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Affiliation(s)
- Matthew K Burrage
- University of Oxford Centre for Clinical Magnetic Resonance Research (OCMR), Radcliffe Department of Medicine, University of Oxford, Level 0, John Radcliffe Hospital, Oxford, OX3 9DU, UK
| | - Vanessa M Ferreira
- University of Oxford Centre for Clinical Magnetic Resonance Research (OCMR), Radcliffe Department of Medicine, University of Oxford, Level 0, John Radcliffe Hospital, Oxford, OX3 9DU, UK.
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17
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Hendriks AA, Kis Z, Glisic M, Bramer WM, Szili-Torok T. Pre-procedural image-guided versus non-image-guided ventricular tachycardia ablation-a review. Neth Heart J 2020; 28:573-583. [PMID: 32930978 PMCID: PMC7596120 DOI: 10.1007/s12471-020-01485-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022] Open
Abstract
BACKGROUND Magnetic resonance imaging and computed tomography in patients with ventricular tachycardia (VT) after myocardial infarction (MI) helps to delineate scar from healthy tissue. Image-guided VT ablation has not yet been studied on a large scale. OBJECTIVE The aim of the meta-analysis was to compare the long-term outcome of image-guided VT ablation with a conventional approach for VT after MI. METHODS Eight electronic bibliographic databases were searched to identify all relevant studies from 2012 until 2018. The search for scientific literature was performed for studies that described the outcome of VT ablation in patients with an ischaemic substrate. The outcome of image-guided ablation was compared with the outcome of conventional ablations. RESULTS Of the 2990 citations reviewed for eligibility, 38 articles-enrolling a total of 7748 patients-were included into the meta-analysis. Five articles included patients with image-guided ablation. VT-free survival was 82% [74-90] in the image-guided VT ablation versus 59% [54-64] in the conventional ablation group (p < 0.001) during a mean follow-up of 35 months. Overall survival was 94% [90-98] in the image-guided versus 82% [76-88] in the conventional VT ablation group (p < 0.001). CONCLUSIONS Image-guided VT ablation in ischaemic VT was associated with a significant benefit in VT-free and overall survival as compared with conventional VT ablation. Visualising myocardial scar facilitates substrate-guided ablation procedures, pre-procedurally and by integrating imaging during the procedure, and may consequently improve long-term outcome.
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Affiliation(s)
- A A Hendriks
- Department of Electrophysiology, Erasmus MC, University Medical Center, Rotterdam, The Netherlands
| | - Z Kis
- Department of Electrophysiology, Erasmus MC, University Medical Center, Rotterdam, The Netherlands
| | - M Glisic
- Department of Epidemiology, Erasmus MC, University Medical Center, Rotterdam, The Netherlands
| | - W M Bramer
- Medical Library, Erasmus MC, University Medical Center, Rotterdam, The Netherlands
| | - T Szili-Torok
- Department of Electrophysiology, Erasmus MC, University Medical Center, Rotterdam, The Netherlands.
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18
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Jaubert O, Cruz G, Bustin A, Schneider T, Koken P, Doneva M, Rueckert D, Botnar RM, Prieto C. Free-running cardiac magnetic resonance fingerprinting: Joint T1/T2 map and Cine imaging. Magn Reson Imaging 2020; 68:173-182. [PMID: 32061964 PMCID: PMC7677167 DOI: 10.1016/j.mri.2020.02.005] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2019] [Revised: 01/21/2020] [Accepted: 02/09/2020] [Indexed: 12/15/2022]
Abstract
PURPOSE To develop and evaluate a novel non-ECG triggered 2D magnetic resonance fingerprinting (MRF) sequence allowing for simultaneous myocardial T1 and T2 mapping and cardiac Cine imaging. METHODS Cardiac MRF (cMRF) has been recently proposed to provide joint T1/T2 myocardial mapping by triggering the acquisition to mid-diastole and relying on a subject-dependent dictionary of MR signal evolutions to generate the maps. In this work, we propose a novel "free-running" (non-ECG triggered) cMRF framework for simultaneous myocardial T1 and T2 mapping and cardiac Cine imaging in a single scan. Free-running cMRF is based on a transient state bSSFP acquisition with tiny golden angle radial readouts, varying flip angle and multiple adiabatic inversion pulses. The acquired data is retrospectively gated into several cardiac phases, which are reconstructed with an approach that combines parallel imaging, low rank modelling and patch-based high-order tensor regularization. Free-running cMRF was evaluated in a standardized phantom and ten healthy subjects. Comparison with reference spin-echo, MOLLI, SASHA, T2-GRASE and Cine was performed. RESULTS T1 and T2 values obtained with the proposed approach were in good agreement with reference phantom values (ICC(A,1) > 0.99). Reported values for myocardium septum T1 were 1043 ± 48 ms, 1150 ± 100 ms and 1160 ± 79 ms for MOLLI, SASHA and free-running cMRF respectively and for T2 of 51.7 ± 4.1 ms and 44.6 ± 4.1 ms for T2-GRASE and free-running cMRF respectively. Good agreement was observed between free-running cMRF and conventional Cine 2D ejection fraction (bias = -0.83%). CONCLUSION The proposed free-running cardiac MRF approach allows for simultaneous assessment of myocardial T1 and T2 and Cine imaging in a single scan.
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Affiliation(s)
- O Jaubert
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom.
| | - G Cruz
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - A Bustin
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - T Schneider
- Philips Healthcare, Guilford, United Kingdom
| | - P Koken
- Philips Research Europe, Hamburg, Germany
| | - M Doneva
- Philips Research Europe, Hamburg, Germany
| | - D Rueckert
- Department of Computing, Imperial College London, London, United Kingdom
| | - R M Botnar
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - C Prieto
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom; Escuela de Ingeniería, Pontificia Universidad Católica de Chile, Santiago, Chile
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