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Cao T, Hu Z, Mao X, Chen Z, Kwan AC, Xie Y, Berman DS, Li D, Christodoulou AG. Alternating low-rank tensor reconstruction for improved multiparametric mapping with cardiovascular MR Multitasking. Magn Reson Med 2024; 92:1421-1439. [PMID: 38726884 PMCID: PMC11262969 DOI: 10.1002/mrm.30131] [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: 09/14/2023] [Revised: 03/20/2024] [Accepted: 04/08/2024] [Indexed: 05/15/2024]
Abstract
PURPOSE To develop a novel low-rank tensor reconstruction approach leveraging the complete acquired data set to improve precision and repeatability of multiparametric mapping within the cardiovascular MR Multitasking framework. METHODS A novel approach that alternated between estimation of temporal components and spatial components using the entire data set acquired (i.e., including navigator data and imaging data) was developed to improve reconstruction. The precision and repeatability of the proposed approach were evaluated on numerical simulations, 10 healthy subjects, and 10 cardiomyopathy patients at multiple scan times for 2D myocardial T1/T2 mapping with MR Multitasking and were compared with those of the previous navigator-derived fixed-basis approach. RESULTS In numerical simulations, the proposed approach outperformed the previous fixed-basis approach with lower T1 and T2 error against the ground truth at all scan times studied and showed better motion fidelity. In human subjects, the proposed approach showed no significantly different sharpness or T1/T2 measurement and significantly improved T1 precision by 20%-25%, T2 precision by 10%-15%, T1 repeatability by about 30%, and T2 repeatability by 25%-35% at 90-s and 50-s scan times The proposed approach at the 50-s scan time also showed comparable results with that of the previous fixed-basis approach at the 90-s scan time. CONCLUSION The proposed approach improved precision and repeatability for quantitative imaging with MR Multitasking while maintaining comparable motion fidelity, T1/T2 measurement, and septum sharpness and had the potential for further reducing scan time from 90 s to 50 s.
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Affiliation(s)
- Tianle Cao
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA
- Department of Radiological Sciences, David Geffen School of Medicine at UCLA, Los Angeles, California, USA
- Department of Bioengineering, University of California, Los Angeles, Los Angeles, California, USA
| | - Zheyuan Hu
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA
- Department of Radiological Sciences, David Geffen School of Medicine at UCLA, Los Angeles, California, USA
- Department of Bioengineering, University of California, Los Angeles, Los Angeles, California, USA
| | - Xianglun Mao
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - Zihao Chen
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA
- Department of Radiological Sciences, David Geffen School of Medicine at UCLA, Los Angeles, California, USA
- Department of Bioengineering, University of California, Los Angeles, Los Angeles, California, USA
| | - Alan C. Kwan
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA
- Departments of Imaging and Cardiology, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - Yibin Xie
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - Daniel S. Berman
- Departments of Imaging and Cardiology, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - Debiao Li
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA
- Department of Bioengineering, University of California, Los Angeles, Los Angeles, California, USA
| | - Anthony G. Christodoulou
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA
- Department of Radiological Sciences, David Geffen School of Medicine at UCLA, Los Angeles, California, USA
- Department of Bioengineering, University of California, Los Angeles, Los Angeles, California, USA
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Guan X, Yang HJ, Zhang X, Wang N, Han H, Tang R, Hu Z, Youssef K, Vora K, Krishnam MS, Christodoulou AG, Li D, Sharif B, Dharmakumar R. Non-electrocardiogram-gated, free-breathing, off-resonance reduced, high-resolution, whole-heart myocardial T 2 * mapping at 3 T within 5 min. Magn Reson Med 2024; 91:1936-1950. [PMID: 38174593 DOI: 10.1002/mrm.29968] [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: 04/12/2023] [Revised: 11/21/2023] [Accepted: 11/26/2023] [Indexed: 01/05/2024]
Abstract
PURPOSE Widely used conventional 2D T2 * approaches that are based on breath-held, electrocardiogram (ECG)-gated, multi-gradient-echo sequences are prone to motion artifacts in the presence of incomplete breath holding or arrhythmias, which is common in cardiac patients. To address these limitations, a 3D, non-ECG-gated, free-breathing T2 * technique that enables rapid whole-heart coverage was developed and validated. METHODS A continuous random Gaussian 3D k-space sampling was implemented using a low-rank tensor framework for motion-resolved 3D T2 * imaging. This approach was tested in healthy human volunteers and in swine before and after intravenous administration of ferumoxytol. RESULTS Spatial-resolution matched T2 * images were acquired with 2-3-fold reduction in scan time using the proposed T2 * mapping approach relative to conventional T2 * mapping. Compared with the conventional approach, T2 * images acquired with the proposed method demonstrated reduced off-resonance and flow artifacts, leading to higher image quality and lower coefficient of variation in T2 *-weighted images of the myocardium of swine and humans. Mean myocardial T2 * values determined using the proposed and conventional approaches were highly correlated and showed minimal bias. CONCLUSION The proposed non-ECG-gated, free-breathing, 3D T2 * imaging approach can be performed within 5 min or less. It can overcome critical image artifacts from undesirable cardiac and respiratory motion and bulk off-resonance shifts at the heart-lung interface. The proposed approach is expected to facilitate faster and improved cardiac T2 * mapping in those with limited breath-holding capacity or arrhythmias.
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Affiliation(s)
- Xingmin Guan
- Krannert Cardiovascular Research Center, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Hsin-Jung Yang
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - Xinheng Zhang
- Krannert Cardiovascular Research Center, Indiana University School of Medicine, Indianapolis, Indiana, USA
- Department of Bioengineering, University of California Los Angeles, Los Angeles, California, USA
| | - Nan Wang
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - Hui Han
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - Richard Tang
- Krannert Cardiovascular Research Center, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Zhehao Hu
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - Khalid Youssef
- Krannert Cardiovascular Research Center, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Keyur Vora
- Krannert Cardiovascular Research Center, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Mayil S Krishnam
- Department of Radiology, Stanford University, Palo Alto, California, USA
| | - Anthony G Christodoulou
- Department of Bioengineering, University of California Los Angeles, Los Angeles, California, USA
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
| | - Debiao Li
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA
- Department of Bioengineering, University of California Los Angeles, Los Angeles, California, USA
| | - Behzad Sharif
- Krannert Cardiovascular Research Center, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Rohan Dharmakumar
- Krannert Cardiovascular Research Center, Indiana University School of Medicine, Indianapolis, Indiana, USA
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Rashid I, Lima da Cruz G, Seiberlich N, Hamilton JI. Cardiac MR Fingerprinting: Overview, Technical Developments, and Applications. J Magn Reson Imaging 2023:10.1002/jmri.29206. [PMID: 38153855 PMCID: PMC11211246 DOI: 10.1002/jmri.29206] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2023] [Revised: 12/13/2023] [Accepted: 12/14/2023] [Indexed: 12/30/2023] Open
Abstract
Cardiovascular magnetic resonance (CMR) is an established imaging modality with proven utility in assessing cardiovascular diseases. The ability of CMR to characterize myocardial tissue using T1 - and T2 -weighted imaging, parametric mapping, and late gadolinium enhancement has allowed for the non-invasive identification of specific pathologies not previously possible with modalities like echocardiography. However, CMR examinations are lengthy and technically complex, requiring multiple pulse sequences and different anatomical planes to comprehensively assess myocardial structure, function, and tissue composition. To increase the overall impact of this modality, there is a need to simplify and shorten CMR exams to improve access and efficiency, while also providing reproducible quantitative measurements. Multiparametric MRI techniques that measure multiple tissue properties offer one potential solution to this problem. This review provides an in-depth look at one such multiparametric approach, cardiac magnetic resonance fingerprinting (MRF). The article is structured as follows. First, a brief review of single-parametric and (non-Fingerprinting) multiparametric CMR mapping techniques is presented. Second, a general overview of cardiac MRF is provided covering pulse sequence implementation, dictionary generation, fast k-space sampling methods, and pattern recognition. Third, recent technical advances in cardiac MRF are covered spanning a variety of topics, including simultaneous multislice and 3D sampling, motion correction algorithms, cine MRF, synthetic multicontrast imaging, extensions to measure additional clinically important tissue properties (proton density fat fraction, T2 *, and T1ρ ), and deep learning methods for image reconstruction and parameter estimation. The last section will discuss potential clinical applications, concluding with a perspective on how multiparametric techniques like MRF may enable streamlined CMR protocols. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY: Stage 1.
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Affiliation(s)
- Imran Rashid
- Department of Radiology, University of Michigan, Ann Arbor, MI, USA
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA
| | - Gastao Lima da Cruz
- School of Medicine, Case Western Reserve University, Cleveland, OH, USA
- Harrington Heart and Vascular Institute, University Hospitals, Cleveland, OH, USA
| | - Nicole Seiberlich
- School of Medicine, Case Western Reserve University, Cleveland, OH, USA
- Harrington Heart and Vascular Institute, University Hospitals, Cleveland, OH, USA
| | - Jesse I. Hamilton
- School of Medicine, Case Western Reserve University, Cleveland, OH, USA
- Harrington Heart and Vascular Institute, University Hospitals, Cleveland, OH, USA
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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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Eyre K, Lindsay K, Razzaq S, Chetrit M, Friedrich M. Simultaneous multi-parametric acquisition and reconstruction techniques in cardiac magnetic resonance imaging: Basic concepts and status of clinical development. Front Cardiovasc Med 2022; 9:953823. [PMID: 36277755 PMCID: PMC9582154 DOI: 10.3389/fcvm.2022.953823] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2022] [Accepted: 09/22/2022] [Indexed: 11/13/2022] Open
Abstract
Simultaneous multi-parametric acquisition and reconstruction techniques (SMART) are gaining attention for their potential to overcome some of cardiovascular magnetic resonance imaging's (CMR) clinical limitations. The major advantages of SMART lie within their ability to simultaneously capture multiple "features" such as cardiac motion, respiratory motion, T1/T2 relaxation. This review aims to summarize the overarching theory of SMART, describing key concepts that many of these techniques share to produce co-registered, high quality CMR images in less time and with less requirements for specialized personnel. Further, this review provides an overview of the recent developments in the field of SMART by describing how they work, the parameters they can acquire, their status of clinical testing and validation, and by providing examples for how their use can improve the current state of clinical CMR workflows. Many of the SMART are in early phases of development and testing, thus larger scale, controlled trials are needed to evaluate their use in clinical setting and with different cardiac pathologies.
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Affiliation(s)
- Katerina Eyre
- McGill University Health Centre, Montreal, QC, Canada,Department of Experimental Medicine, McGill University, Montreal, QC, Canada,*Correspondence: Katerina Eyre,
| | - Katherine Lindsay
- McGill University Health Centre, Montreal, QC, Canada,Department of Experimental Medicine, McGill University, Montreal, QC, Canada
| | - Saad Razzaq
- Department of Experimental Medicine, McGill University, Montreal, QC, Canada
| | - Michael Chetrit
- McGill University Health Centre, Montreal, QC, Canada,Department of Experimental Medicine, McGill University, Montreal, QC, Canada
| | - Matthias Friedrich
- McGill University Health Centre, Montreal, QC, Canada,Department of Experimental Medicine, McGill University, Montreal, QC, Canada
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Bhuta S, Patel NJ, Ciricillo JA, Haddad MN, Khokher W, Mhanna M, Patel M, Burmeister C, Malas H, Kammeyer JA. Cardiac Magnetic Resonance Imaging for the Diagnosis of Infective Endocarditis in the COVID-19 Era. Curr Probl Cardiol 2022; 48:101396. [PMID: 36126764 PMCID: PMC9481470 DOI: 10.1016/j.cpcardiol.2022.101396] [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: 09/02/2022] [Accepted: 09/07/2022] [Indexed: 10/30/2022]
Abstract
INTRODUCTION In the COVID-19 pandemic, to minimize aerosol-generating procedures, cardiac magnetic resonance imaging (CMR) was utilized at our institution as an alternative to transesophageal echocardiography (TEE) for diagnosing infective endocarditis (IE). METHODS This retrospective study evaluated the clinical utility of CMR for detecting IE among 14 patients growing typical microorganisms on blood cultures or meeting modified Duke criteria. RESULTS 7 cases were treated for IE. In 2 cases, CMR results were notable for possible leaflet vegetations and were clinically meaningful in guiding antibiotic therapy, obtaining further imaging, and/or pursuing surgical intervention. In 2 cases, vegetations were missed on CMR but detected on TEE. In 3 cases, CMR was nondiagnostic, but patients were treated empirically. There was no difference in antibiotic duration or outcomes over 1 year. CONCLUSION CMR demonstrated mixed results in diagnosing valvular vegetations and guiding clinical decision making. Further prospective controlled trials of CMR vs TEE are warranted.
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Affiliation(s)
- Sapan Bhuta
- The Ohio State University Wexner Medical Center, Columbus, OH, USA
| | - Neha J Patel
- University of Toledo College of Medicine and Life Sciences, Toledo, OH, USA
| | - Jacob A Ciricillo
- University of Toledo College of Medicine and Life Sciences, Toledo, OH, USA
| | - Michael N Haddad
- University of Toledo College of Medicine and Life Sciences, Toledo, OH, USA
| | - Waleed Khokher
- University of Toledo College of Medicine and Life Sciences, Toledo, OH, USA
| | - Mohammed Mhanna
- Division of Cardiology, Department of Medicine, University of Iowa, Iowa City, IA, USA
| | - Mitra Patel
- University of Toledo College of Medicine and Life Sciences, Toledo, OH, USA
| | | | - Hazem Malas
- University of Toledo College of Medicine and Life Sciences, Toledo, OH, USA; ProMedica Toledo Hospital, Toledo, OH, USA
| | - Joel A Kammeyer
- University of Toledo College of Medicine and Life Sciences, Toledo, OH, USA; ProMedica Toledo Hospital, Toledo, OH, USA.
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