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Hamilton JI, Lima da Cruz G, Rashid I, Walker J, Rajagopalan S, Seiberlich N. Deep image prior cine MR fingerprinting with B 1 + spin history correction. Magn Reson Med 2024; 91:2010-2027. [PMID: 38098428 PMCID: PMC10950517 DOI: 10.1002/mrm.29979] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Revised: 11/29/2023] [Accepted: 11/29/2023] [Indexed: 03/07/2024]
Abstract
PURPOSE To develop a deep image prior (DIP) reconstruction for B1 + -corrected 2D cine MR fingerprinting (MRF). METHODS The proposed method combines low-rank (LR) modeling with a DIP to generate cardiac phase-resolved parameter maps without motion correction, employing self-supervised training to enforce consistency with undersampled spiral k-space data. Two implementations were tested: one approach (DIP) for cine T1 , T2 , and M0 mapping, and a second approach (DIP with effective B1 + estimation [DIP-B1]) that also generated an effective B1 + map to correct for errors due to RF transmit inhomogeneities, through-plane motion, and blood flow. Cine MRF data were acquired in 14 healthy subjects and four reconstructions were compared: LR, low-rank motion-corrected (LRMC), DIP, and DIP-B1. Results were compared to diastolic ECG-triggered MRF, MOLLI, and T2 -prep bSSFP. Additionally, bright-blood and dark-blood images calculated from cine MRF maps were used to quantify ventricular function and compared to reference cine measurements. RESULTS DIP and DIP-B1 outperformed other cine MRF reconstructions with improved noise suppression and delineation of high-resolution details. Within-segment variability in the myocardium (reported as the coefficient of variation for T1 /T2 ) was lowest for DIP-B1 (2.3/8.3%) followed by DIP (2.7/8.7%), LRMC (3.5/10.5%), and LR (15.3/39.6%). Spatial homogeneity improved with DIP-B1 having the lowest intersegment variability (2.6/4.1%). The mean bias in ejection fraction was -1.1% compared to reference cine scans. CONCLUSION A DIP reconstruction for 2D cine MRF enabled cardiac phase-resolved mapping of T1 , T2 , M0 , and the effective B1 + with improved noise suppression and precision compared to LR and LRMC.
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Affiliation(s)
- Jesse I. Hamilton
- Department of Radiology, University of Michigan, Ann Arbor, MI, USA
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA
| | | | - Imran Rashid
- School of Medicine, Case Western Reserve University, Cleveland, OH, USA
- Harrington Heart and Vascular Institute, Cleveland, OH, USA
| | - Jonathan Walker
- School of Medicine, Case Western Reserve University, Cleveland, OH, USA
- Harrington Heart and Vascular Institute, Cleveland, OH, USA
| | - Sanjay Rajagopalan
- School of Medicine, Case Western Reserve University, Cleveland, OH, USA
- Harrington Heart and Vascular Institute, Cleveland, OH, USA
| | - Nicole Seiberlich
- Department of Radiology, University of Michigan, Ann Arbor, MI, USA
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA
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2
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Christodoulou AG, Cruz G, Arami A, Weingärtner S, Artico J, Peters D, Seiberlich N. The future of cardiovascular magnetic resonance: All-in-one vs. real-time (Part 1). J Cardiovasc Magn Reson 2024; 26:100997. [PMID: 38237900 PMCID: PMC11211239 DOI: 10.1016/j.jocmr.2024.100997] [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: 12/21/2023] [Accepted: 01/10/2024] [Indexed: 02/26/2024] Open
Abstract
Cardiovascular magnetic resonance (CMR) protocols can be lengthy and complex, which has driven the research community to develop new technologies to make these protocols more efficient and patient-friendly. Two different approaches to improving CMR have been proposed, specifically "all-in-one" CMR, where several contrasts and/or motion states are acquired simultaneously, and "real-time" CMR, in which the examination is accelerated to avoid the need for breathholding and/or cardiac gating. The goal of this two-part manuscript is to describe these two different types of emerging rapid CMR. To this end, the vision of each is described, along with techniques which have been devised and tested along the pathway of clinical implementation. The pros and cons of the different methods are presented, and the remaining open needs of each are detailed. Part 1 will tackle the "all-in-one" approaches, and Part 2 the "real-time" approaches along with an overall summary of these emerging methods.
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Affiliation(s)
- Anthony G Christodoulou
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA; Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Gastao Cruz
- Michigan Institute for Imaging Technology and Translation, Department of Radiology, University of Michigan, Ann Arbor, MI, USA
| | - Ayda Arami
- Department of Imaging Physics, Delft University of Technology, Delft, the Netherlands; Department of Radiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Sebastian Weingärtner
- Department of Imaging Physics, Delft University of Technology, Delft, the Netherlands
| | | | - Dana Peters
- Radiology & Biomedical Imaging, Yale University, New Haven, CT, USA
| | - Nicole Seiberlich
- Michigan Institute for Imaging Technology and Translation, Department of Radiology, University of Michigan, Ann Arbor, MI, USA.
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3
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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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4
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Radjenovic A, Christodoulou AG. Editorial: Simultaneous multiparametric and multidimensional cardiovascular magnetic resonance imaging. Front Cardiovasc Med 2023; 10:1205994. [PMID: 37342436 PMCID: PMC10277742 DOI: 10.3389/fcvm.2023.1205994] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2023] [Accepted: 05/17/2023] [Indexed: 06/22/2023] Open
Affiliation(s)
- Aleksandra Radjenovic
- School of Cardiovascular & Metabolic Health, University of Glasgow, Glasgow, United Kingdom
| | - Anthony G. Christodoulou
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, United States
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5
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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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6
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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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7
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Weingärtner S, Demirel ÖB, Gama F, Pierce I, Treibel TA, Schulz-Menger J, Akçakaya M. Cardiac phase-resolved late gadolinium enhancement imaging. Front Cardiovasc Med 2022; 9:917180. [PMID: 36247474 PMCID: PMC9557076 DOI: 10.3389/fcvm.2022.917180] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2022] [Accepted: 09/13/2022] [Indexed: 11/25/2022] Open
Abstract
Late gadolinium enhancement (LGE) with cardiac magnetic resonance (CMR) imaging is the clinical reference for assessment of myocardial scar and focal fibrosis. However, current LGE techniques are confined to imaging of a single cardiac phase, which hampers assessment of scar motility and does not allow cross-comparison between multiple phases. In this work, we investigate a three step approach to obtain cardiac phase-resolved LGE images: (1) Acquisition of cardiac phase-resolved imaging data with varying T1 weighting. (2) Generation of semi-quantitative T1* maps for each cardiac phase. (3) Synthetization of LGE contrast to obtain functional LGE images. The proposed method is evaluated in phantom imaging, six healthy subjects at 3T and 20 patients at 1.5T. Phantom imaging at 3T demonstrates consistent contrast throughout the cardiac cycle with a coefficient of variation of 2.55 ± 0.42%. In-vivo results show reliable LGE contrast with thorough suppression of the myocardial tissue is healthy subjects. The contrast between blood and myocardium showed moderate variation throughout the cardiac cycle in healthy subjects (coefficient of variation 18.2 ± 3.51%). Images were acquired at 40–60 ms and 80 ms temporal resolution, at 3T and 1.5, respectively. Functional LGE images acquired in patients with myocardial scar visualized scar tissue throughout the cardiac cycle, albeit at noticeably lower imaging resolution and noise resilience than the reference technique. The proposed technique bears the promise of integrating the advantages of phase-resolved CMR with LGE imaging, but further improvements in the acquisition quality are warranted for clinical use.
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Affiliation(s)
- Sebastian Weingärtner
- Department of Imaging Physics, Delft University of Technology, Delft, Netherlands
- *Correspondence: Sebastian Weingärtner
| | - Ömer B. Demirel
- Department of Electrical and Computer Engineering, University of Minnesota, Minneapolis, MN, United States
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, United States
| | - Francisco Gama
- Bart's Heart Centre, St. Bartholomew's Hospital, London, United Kingdom
| | - Iain Pierce
- Bart's Heart Centre, St. Bartholomew's Hospital, London, United Kingdom
| | - Thomas A. Treibel
- Bart's Heart Centre, St. Bartholomew's Hospital, London, United Kingdom
- Institute of Cardiovascular Science, University College London, London, United Kingdom
| | - Jeanette Schulz-Menger
- Working Group on Cardiovascular Magnetic Resonance Imaging, Experimental and Clinical Research Center, Joint Cooperation of the Max-Delbrück-Centrum and Charite-Medical University Berlin, Berlin, Germany
- Department of Cardiology and Nephrology, HELIOS Klinikum Berlin-Buch and DZHK, Berlin, Germany
| | - Mehmet Akçakaya
- Department of Electrical and Computer Engineering, University of Minnesota, Minneapolis, MN, United States
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, United States
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8
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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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9
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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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10
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Weingärtner S, Desmond KL, Obuchowski NA, Baessler B, Zhang Y, Biondetti E, Ma D, Golay X, Boss MA, Gunter JL, Keenan KE, Hernando D. Development, validation, qualification, and dissemination of quantitative MR methods: Overview and recommendations by the ISMRM quantitative MR study group. Magn Reson Med 2021; 87:1184-1206. [PMID: 34825741 DOI: 10.1002/mrm.29084] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2021] [Revised: 10/20/2021] [Accepted: 10/27/2021] [Indexed: 12/26/2022]
Abstract
On behalf of the International Society for Magnetic Resonance in Medicine (ISMRM) Quantitative MR Study Group, this article provides an overview of considerations for the development, validation, qualification, and dissemination of quantitative MR (qMR) methods. This process is framed in terms of two central technical performance properties, i.e., bias and precision. Although qMR is confounded by undesired effects, methods with low bias and high precision can be iteratively developed and validated. For illustration, two distinct qMR methods are discussed throughout the manuscript: quantification of liver proton-density fat fraction, and cardiac T1 . These examples demonstrate the expansion of qMR methods from research centers toward widespread clinical dissemination. The overall goal of this article is to provide trainees, researchers, and clinicians with essential guidelines for the development and validation of qMR methods, as well as an understanding of necessary steps and potential pitfalls for the dissemination of quantitative MR in research and in the clinic.
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Affiliation(s)
- Sebastian Weingärtner
- Department of Imaging Physics, Delft University of Technology, Delft, The Netherlands
| | - Kimberly L Desmond
- Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, Ontario, Canada.,Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - Nancy A Obuchowski
- Department of Quantitative Health Sciences, Cleveland Clinic, Cleveland, Ohio, USA
| | - Bettina Baessler
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, Zurich, Switzerland
| | - Yuxin Zhang
- Department of Medical Physics, University of Wisconsin-Madison, Madison, Wisconsin, USA.,Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Emma Biondetti
- Department of Neuroscience, Imaging and Clinical Sciences, D'Annunzio University of Chieti and Pescara, Chieti, Italy
| | - Dan Ma
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA
| | - Xavier Golay
- Brain Repair & Rehabilitation, Institute of Neurology, University College London, United Kingdom.,Gold Standard Phantoms Limited, Rochester, United Kingdom
| | - Michael A Boss
- Center for Research and Innovation, American College of Radiology, Philadelphia, Pennsylvania, USA
| | | | - Kathryn E Keenan
- National Institute of Standards and Technology, Boulder, Colorado, USA
| | - Diego Hernando
- Department of Medical Physics, University of Wisconsin-Madison, Madison, Wisconsin, USA.,Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin, USA
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11
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Zhou R, Weller DS, Yang Y, Wang J, Jeelani H, Mugler JP, Salerno M. Dual-excitation flip-angle simultaneous cine and T 1 mapping using spiral acquisition with respiratory and cardiac self-gating. Magn Reson Med 2021; 86:82-96. [PMID: 33590591 PMCID: PMC8849625 DOI: 10.1002/mrm.28675] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2020] [Revised: 12/18/2020] [Accepted: 12/19/2020] [Indexed: 12/26/2022]
Abstract
PURPOSE To develop a free-breathing cardiac self-gated technique that provides cine images and B1+ slice profile-corrected T1 maps from a single acquisition. METHODS Without breath-holding or electrocardiogram gating, data were acquired continuously on a 3T scanner using a golden-angle gradient-echo spiral pulse sequence, with an inversion RF pulse applied every 4 seconds. Flip angles of 3° and 15° were used for readouts after the first four and second four inversions. Self-gating cardiac triggers were extracted from heart image navigators, and respiratory motion was corrected by rigid registration on each heartbeat. Cine images were reconstructed from the steady-state portion of 15° readouts using a low-rank plus sparse reconstruction. The T1 maps were fit using a projection onto convex sets approach from images reconstructed using slice profile-corrected dictionary learning. This strategy was evaluated in a phantom and 14 human subjects. RESULTS The self-gated signal demonstrated close agreement with the acquired electrocardiogram signal. The image quality for the proposed cine images and standard clinical balanced SSFP images were 4.31 (±0.50) and 4.65 (±0.30), respectively. The slice profile-corrected T1 values were similar to those of the inversion-recovery spin-echo technique in phantom, and had a higher global T1 value than that of MOLLI in human subjects. CONCLUSIONS Cine and T1 mapping using spiral acquisition with respiratory and cardiac self-gating successfully acquired T1 maps and cine images in a single acquisition without the need for electrocardiogram gating or breath-holding. This dual-excitation flip-angle approach provides a novel approach for measuring T1 while accounting for B1+ and slice profile effect on the apparent T1∗ .
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Affiliation(s)
- Ruixi Zhou
- Department of Biomedical Engineering, University of Virginia Health System, Charlottesville, VA, United States
| | - Daniel S. Weller
- Department of Electrical and Computer Engineering, University of Virginia, Charlottesville, VA, United States
| | - Yang Yang
- Biomedical Engineering and Imaging Institute and Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Junyu Wang
- Department of Biomedical Engineering, University of Virginia Health System, Charlottesville, VA, United States
| | - Haris Jeelani
- Biomedical Engineering and Imaging Institute and Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - John P. Mugler
- Radiology & Medical Imaging, Biomedical Engineering, University of Virginia Health System, Charlottesville, VA, United States
| | - Michael Salerno
- Cardiology, Radiology & Medical Imaging, Biomedical Engineering, University of Virginia Health System, Charlottesville, VA, United States
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12
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Guo R, Cai X, Kucukseymen S, Rodriguez J, Paskavitz A, Pierce P, Goddu B, Thompson RB, Nezafat R. Free-breathing simultaneous myocardial T 1 and T 2 mapping with whole left ventricle coverage. Magn Reson Med 2020; 85:1308-1321. [PMID: 33078443 DOI: 10.1002/mrm.28506] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2020] [Revised: 08/13/2020] [Accepted: 08/14/2020] [Indexed: 01/20/2023]
Abstract
PURPOSE To develop a free-breathing sequence, that is, Multislice Joint T1 -T2 , for simultaneous measurement of myocardial T1 and T2 for multiple slices to achieve whole left-ventricular coverage. METHODS Multislice Joint T1 -T2 adopts slice-interleaved acquisition to collect 10 single-shot electrocardiogram-triggered images for each slice prepared by saturation and T2 preparation to simultaneously estimate myocardial T1 and T2 and achieve whole left-ventricular coverage. Prospective slice-tracking using a respiratory navigator and retrospective image registration are used to reduce through-plane and in-plane motion, respectively. Multislice Joint T1 -T2 was validated through numerical simulations and phantom and in vivo experiments, and compared with saturation-recovery single-shot acquisition and T2 -prepared balanced Steady-State Free Precession (T2 -prep SSFP) sequences. RESULTS Phantom T1 and T2 from Multislice Joint T1 -T2 had good accuracy and precision, and were insensitive to heart rate. Multislice Joint T1 -T2 yielded T1 and T2 maps of nine left-ventricular slices in 1.4 minutes. The mean left-ventricular T1 difference between saturation-recovery single-shot acquisition and Multislice Joint T1 -T2 across healthy subjects and patients was 191 ms (1564 ± 60 ms versus 1373 ± 50 ms; P < .05) and 111 ms (1535 ± 49 ms vs 1423 ± 49 ms; P < .05), respectively. The mean difference in left-ventricular T2 between T2 -prep SSFP and Multislice Joint T1 -T2 across healthy subjects and patients was -6.3 ms (42.4 ± 1.4 ms vs 48.7 ± 2.5; P < .05) and -5.7 ms (41.6 ± 2.5 ms vs 47.3 ± 2.7; P < .05), respectively. CONCLUSION Multislice Joint T1 -T2 enables quantification of whole left-ventricular T1 and T2 during free breathing within a clinically feasible scan time of less than 2 minutes.
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Affiliation(s)
- Rui Guo
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA
| | - Xiaoying Cai
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA.,Siemens Medical Solutions USA, Inc., Boston, Massachusetts, USA
| | - Selcuk Kucukseymen
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA
| | - Jennifer Rodriguez
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA
| | - Amanda Paskavitz
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA
| | - Patrick Pierce
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA
| | - Beth Goddu
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA
| | - Richard B Thompson
- Department of Biomedical Engineering, University of Alberta, Edmonton, Alberta, Canada
| | - Reza Nezafat
- Department of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA
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13
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Hamilton JI, Jiang Y, Eck B, Griswold M, Seiberlich N. Cardiac cine magnetic resonance fingerprinting for combined ejection fraction, T 1 and T 2 quantification. NMR IN BIOMEDICINE 2020; 33:e4323. [PMID: 32500541 PMCID: PMC7772953 DOI: 10.1002/nbm.4323] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/29/2019] [Revised: 04/23/2020] [Accepted: 04/24/2020] [Indexed: 05/07/2023]
Abstract
This study introduces a technique called cine magnetic resonance fingerprinting (cine-MRF) for simultaneous T1 , T2 and ejection fraction (EF) quantification. Data acquired with a free-running MRF sequence are retrospectively sorted into different cardiac phases using an external electrocardiogram (ECG) signal. A low-rank reconstruction with a finite difference sparsity constraint along the cardiac motion dimension yields images resolved by cardiac phase. To improve SNR and precision in the parameter maps, these images are nonrigidly registered to the same phase and matched to a dictionary to generate T1 and T2 maps. Cine images for computing left ventricular volumes and EF are also derived from the same data. Cine-MRF was tested in simulations using a numerical relaxation phantom. Phantom and in vivo scans of 19 subjects were performed at 3 T during a 10.9 seconds breath-hold with an in-plane resolution of 1.6 x 1.6 mm2 and 24 cardiac phases. Left ventricular EF values obtained with cine-MRF agreed with the conventional cine images (mean bias -1.0%). Average myocardial T1 times in diastole/systole were 1398/1391 ms with cine-MRF, 1394/1378 ms with ECG-triggered cardiac MRF (cMRF) and 1234/1212 ms with MOLLI; and T2 values were 30.7/30.3 ms with cine-MRF, 32.6/32.9 ms with ECG-triggered cMRF and 37.6/41.0 ms with T2 -prepared FLASH. Cine-MRF and ECG-triggered cMRF relaxation times were in good agreement. Cine-MRF T1 values were significantly longer than MOLLI, and cine-MRF T2 values were significantly shorter than T2 -prepared FLASH. In summary, cine-MRF can potentially streamline cardiac MRI exams by combining left ventricle functional assessment and T1 -T2 mapping into one time-efficient acquisition.
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Affiliation(s)
- Jesse I. Hamilton
- Department of Radiology, University of Michigan, Ann Arbor, MI, USA
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA
- Corresponding author at 1137 Catherine Street, Room 1590B, Ann Arbor, MI 48109, JI Hamilton –
| | - Yun Jiang
- Department of Radiology, University of Michigan, Ann Arbor, MI, USA
- Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, OH, USA
| | - Brendan Eck
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA
| | - Mark Griswold
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA
- Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, OH, USA
| | - Nicole Seiberlich
- Department of Radiology, University of Michigan, Ann Arbor, MI, USA
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA
- Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, OH, USA
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14
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Qi H, Bustin A, Cruz G, Jaubert O, Chen H, Botnar RM, Prieto C. Free-running simultaneous myocardial T1/T2 mapping and cine imaging with 3D whole-heart coverage and isotropic spatial resolution. Magn Reson Imaging 2019; 63:159-169. [DOI: 10.1016/j.mri.2019.08.008] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2019] [Revised: 08/10/2019] [Accepted: 08/15/2019] [Indexed: 12/14/2022]
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15
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Yaman B, Weingärtner S, Kargas N, Sidiropoulos ND, Akçakaya M. Low-Rank Tensor Models for Improved Multi-Dimensional MRI: Application to Dynamic Cardiac T 1 Mapping. IEEE TRANSACTIONS ON COMPUTATIONAL IMAGING 2019; 6:194-207. [PMID: 32206691 PMCID: PMC7087548 DOI: 10.1109/tci.2019.2940916] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/11/2023]
Abstract
Multi-dimensional, multi-contrast magnetic resonance imaging (MRI) has become increasingly available for comprehensive and time-efficient evaluation of various pathologies, providing large amounts of data and offering new opportunities for improved image reconstructions. Recently, a cardiac phase-resolved myocardial T 1 mapping method has been introduced to provide dynamic information on tissue viability. Improved spatio-temporal resolution in clinically acceptable scan times is highly desirable but requires high acceleration factors. Tensors are well-suited to describe inter-dimensional hidden structures in such multi-dimensional datasets. In this study, we sought to utilize and compare different tensor decomposition methods, without the use of auxiliary navigator data. We explored multiple processing approaches in order to enable high-resolution cardiac phase-resolved myocardial T 1 mapping. Eight different low-rank tensor approximation and processing approaches were evaluated using quantitative analysis of accuracy and precision in T 1 maps acquired in six healthy volunteers. All methods provided comparable T 1 values. However, the precision was significantly improved using local processing, as well as a direct tensor rank approximation. Low-rank tensor approximation approaches are well-suited to enable dynamic T 1 mapping at high spatio-temporal resolutions.
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Affiliation(s)
- Burhaneddin Yaman
- Department of Electrical and Computer Engineering, and Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, 55455
| | - Sebastian Weingärtner
- Department of Electrical and Computer Engineering, and Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, 55455
| | - Nikolaos Kargas
- Department of Electrical and Computer Engineering, University of Minnesota, Minneapolis, MN, 55455
| | - Nicholas D Sidiropoulos
- Department of Electrical and Computer Engineering, University of Virginia, Charlottesville, VA, 22904
| | - Mehmet Akçakaya
- Department of Electrical and Computer Engineering, and Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, 55455
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16
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Zhang J, Wu J, Chen S, Zhang Z, Cai S, Cai C, Chen Z. Robust Single-Shot T 2 Mapping via Multiple Overlapping-Echo Acquisition and Deep Neural Network. IEEE TRANSACTIONS ON MEDICAL IMAGING 2019; 38:1801-1811. [PMID: 30714913 DOI: 10.1109/tmi.2019.2896085] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/13/2023]
Abstract
Quantitative magnetic resonance imaging (MRI) is of great value to both clinical diagnosis and scientific research. However, most MRI experiments remain qualitative, especially dynamic MRI, because repeated sampling with variable weighting parameter makes quantitative imaging time-consuming and sensitive to motion artifacts. A single-shot quantitative T2 mapping method based on multiple overlapping-echo acquisition (dubbed MOLED-4) was proposed to obtain reliable T2 mapping in milliseconds. Different from traditional MRI acceleration methods, such as compressed sensing and parallel imaging, MOLED-4 accelerates quantitative T2 mapping via synchronized multisampling and then deep learning to map the complex nonlinear relationship that is difficult to solve by traditional optimization-based methods. The results of simulation, phantom, and in vivo human brain experiments show the great performance of the proposed method. The principle of MOLED-4 may be extended to other ultrafast quantitative parameter mappings and potentially lead to new dynamic MRI with high efficiency to catch quantitative variation of tissue properties.
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17
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Weingartner S, Demirel OB, Shenoy C, Schad LR, Schulz-Menger J, Akcakaya M. Functional LGE Imaging: Cardiac Phase-Resolved Assessment of Focal Fibrosis. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2019; 2019:3999-4003. [PMID: 31946748 PMCID: PMC6986779 DOI: 10.1109/embc.2019.8857759] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Cardiac Magnetic Resonance Imaging (CMR) is a central tool for diagnosis of various ischemic and non-ischemic cardiomyopathies. CMR protocols commonly comprise assessment of functional properties using cardiac phase-resolved CINE MRI and characterization of myocardial viability using late gadolinium enhancement (LGE) imaging. Conventional LGE imaging requires inversion recovery preparation with a specific inversion time to null the healthy myocardium, which restricts the acquisition to a single cardiac phase. In turn, this necessitates separate scans for cardiac function and viability. In this work, we develop a new method for functional LGE imaging in a single breath-hold using a three-step approach: 1) ECG-triggered multi-contrast data is acquired for each cardiac phase, 2) semi-quantitative relaxation maps are generated, 3) LGE imaging contrast is synthesized based on the semi-quantitative maps. The proposed functional LGE method is evaluated in four healthy subject and 20 patients at 1.5T and 3T. Thorough suppression of the healthy myocardium, as well as 40-80ms temporal resolution are achieved, with no visually apparent temporal blurring at tissue interfaces. Functional LGE in patients with focal scar demonstrates robust hyperenhancement in the scar area throughout all cardiac phases, allowing for visual assessment of scar motility. The proposed technique bears the potential to simplify and speedup common cardiac imaging protocols, while enabling improved data fusion of functional and viability information for improved evaluation of CMR.
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18
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Shaw JL, Yang Q, Zhou Z, Deng Z, Nguyen C, Li D, Christodoulou AG. Free-breathing, non-ECG, continuous myocardial T 1 mapping with cardiovascular magnetic resonance multitasking. Magn Reson Med 2018; 81:2450-2463. [PMID: 30450749 DOI: 10.1002/mrm.27574] [Citation(s) in RCA: 45] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2018] [Revised: 09/14/2018] [Accepted: 09/28/2018] [Indexed: 01/24/2023]
Abstract
PURPOSE To evaluate the accuracy and repeatability of a free-breathing, non-electrocardiogram (ECG), continuous myocardial T1 and extracellular volume (ECV) mapping technique adapted from the Multitasking framework. METHODS The Multitasking framework is adapted to quantify both myocardial native T1 and ECV with a free-breathing, non-ECG, continuous acquisition T1 mapping method. We acquire interleaved high-spatial resolution image data and high-temporal resolution auxiliary data following inversion-recovery pulses at set intervals and perform low-rank tensor imaging to reconstruct images at 344 inversion times, 20 cardiac phases, and 6 respiratory phases. The accuracy and repeatability of Multitasking T1 mapping in generating native T1 and ECV maps are compared with conventional techniques in a phantom, a simulation, 12 healthy subjects, and 10 acute myocardial infarction patients. RESULTS In phantoms, Multitasking T1 mapping correlated strongly with the gold-standard spin-echo inversion recovery (R2 = 0.99). A simulation study demonstrated that Multitasking T1 mapping has similar myocardial sharpness to the fully sampled ground truth. In vivo native T1 and ECV values from Multitasking T1 mapping agree well with conventional MOLLI values and show good repeatability for native T1 and ECV mapping for 60 seconds, 30 seconds, or 15 seconds of data. Multitasking native T1 and ECV in myocardial infarction patients correlate positively with values from MOLLI. CONCLUSION Multitasking T1 mapping can quantify native T1 and ECV in the myocardium with free-breathing, non-ECG, continuous scans with good image quality and good repeatability in vivo in healthy subjects, and correlation with MOLLI T1 and ECV in acute myocardial infarction patients.
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Affiliation(s)
- Jaime L Shaw
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California.,Department of Bioengineering, University of California, Los Angeles, California.,Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, California
| | - Qi Yang
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California.,Department of Radiology, Xuanwu Hospital, Beijing, China
| | - Zhengwei Zhou
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California
| | - Zixin Deng
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California.,Department of Bioengineering, University of California, Los Angeles, California
| | - Christopher Nguyen
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California
| | - Debiao Li
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California.,Department of Bioengineering, University of California, Los Angeles, California
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19
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Becker KM, Schulz‐Menger J, Schaeffter T, Kolbitsch C. Simultaneous high‐resolution cardiac T
1
mapping and cine imaging using model‐based iterative image reconstruction. Magn Reson Med 2018; 81:1080-1091. [DOI: 10.1002/mrm.27474] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2018] [Revised: 06/08/2018] [Accepted: 07/09/2018] [Indexed: 12/26/2022]
Affiliation(s)
- Kirsten M. Becker
- Physikalisch‐Technische Bundesanstalt (PTB) Braunschweig and Berlin Germany
| | - Jeanette Schulz‐Menger
- Charité‐Universitätsmedizin Berlin Freie Universität Berlin, Humboldt‐Universität zu Berlin Berlin Institute of Health, DZHK Berlin Germany
- Working Group Cardiovascular Magnetic Resonance, Experimental and Clinical Research Center Charité Medical Faculty Max‐Delbrueck Center for Molecular Medicine HELIOS Klinikum Berlin Buch Department of Cardiology and Nephrology Berlin Germany
| | - Tobias Schaeffter
- Physikalisch‐Technische Bundesanstalt (PTB) Braunschweig and Berlin Germany
- Division of Imaging Sciences and Biomedical Engineering King's College London London United Kingdom
| | - Christoph Kolbitsch
- Physikalisch‐Technische Bundesanstalt (PTB) Braunschweig and Berlin Germany
- Division of Imaging Sciences and Biomedical Engineering King's College London London United Kingdom
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20
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Meßner NM, Budjan J, Loßnitzer D, Papavassiliu T, Schad LR, Weingärtner S, Zöllner FG. Saturation-Recovery Myocardial T 1-Mapping during Systole: Accurate and Robust Quantification in the Presence of Arrhythmia. Sci Rep 2018; 8:5251. [PMID: 29588504 PMCID: PMC5869699 DOI: 10.1038/s41598-018-23506-z] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2017] [Accepted: 03/05/2018] [Indexed: 12/29/2022] Open
Abstract
Myocardial T1-mapping, a cardiac magnetic resonance imaging technique, facilitates a quantitative measure of fibrosis which is linked to numerous cardiovascular symptoms. To overcome the problems of common techniques, including lack of accuracy and robustness against partial-voluming and heart-rate variability, we introduce a systolic saturation-recovery T1-mapping method. The Saturation-Pulse Prepared Heart-rate independent Inversion-Recovery (SAPPHIRE) T1-mapping method was modified to enable imaging during systole. Phantom measurements were used to evaluate the insensitivity of systolic T1-mapping towards heart-rate variability. In-vivo feasibility and accuracy were demonstrated in ten healthy volunteers with native and post-contrast T1-mappping during systole and diastole. To show benefits in the presence of RR-variability, six arrhythmic patients underwent native T1-mapping. Resulting systolic SAPPHIRE T1-values showed no dependence on arrhythmia in phantom (CoV < 1%). In-vivo, significantly lower T1 (1563 ± 56 ms, precision: 84.8 ms) and ECV-values (0.20 ± 0.03) than during diastole (T1 = 1580 ± 62 ms, p = 0.0124; precision: 60.2 ms, p = 0.03; ECV = 0.21 ± 0.03, p = 0.0098) were measured, with a strong correlation of systolic and diastolic T1 (r = 0.89). In patients, mis-triggering-induced motion caused significant imaging artifacts in diastolic T1-maps, whereas systolic T1-maps displayed resilience to arrythmia. In conclusion, the proposed method enables saturation-recovery T1-mapping during systole, providing increased robustness against partial-voluming compared to diastolic imaging, for the benefit of T1-measurements in arrhythmic patients.
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Affiliation(s)
- Nadja M Meßner
- Computer Assisted Clinical Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany.,DZHK (German Centre for Cardiovascular Research) partner site Heidelberg/Mannheim, Mannheim, Germany
| | - Johannes Budjan
- Department of Clinical Radiology and Nuclear Medicine, University Medical Center Mannheim, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Dirk Loßnitzer
- 1st Department of Medicine Cardiology, University Medical Center Mannheim, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Theano Papavassiliu
- DZHK (German Centre for Cardiovascular Research) partner site Heidelberg/Mannheim, Mannheim, Germany.,1st Department of Medicine Cardiology, University Medical Center Mannheim, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Lothar R Schad
- Computer Assisted Clinical Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Sebastian Weingärtner
- Computer Assisted Clinical Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany. .,Department of Electrical and Computer Engineering, University of Minnesota, Minneapolis, MN, United States. .,Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, United States.
| | - Frank G Zöllner
- Computer Assisted Clinical Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
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Yaman B, Weingärtner S, Kargas N, Sidiropoulos ND, Akçakaya M. Locally Low-Rank Tensor Regularization for High-Resolution Quantitative Dynamic MRI. ... INTERNATIONAL WORKSHOP ON COMPUTATIONAL ADVANCES IN MULTI-SENSOR ADAPTIVE PROCESSING. INTERNATIONAL WORKSHOP ON COMPUTATIONAL ADVANCES IN MULTI-SENSOR ADAPTIVE PROCESSING 2017; 2017:10.1109/CAMSAP.2017.8313075. [PMID: 31893283 PMCID: PMC6938230 DOI: 10.1109/camsap.2017.8313075] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/28/2023]
Abstract
Quantitative dynamic MRI acquisitions have the potential to diagnose diffuse diseases in conjunction with functional abnormalities. However, their resolutions are limited due to the long acquisition time. Such datasets are multi-dimensional, exhibiting interactions between ≥ 4 dimensions, which cannot be easily identified using sparsity or low-rank matrix methods. Hence, low-rank tensors are a natural fit to model such data. But in the presence of multitude of different tissue types in the field-of-view, it is difficult to find an appropriate value of tensor rank, which avoids under- or over-regularization. In this work, we propose a locally low-rank tensor regularization approach to enable high-resolution quantitative dynamic MRI. We show this approach successfully enables dynamic T 1 mapping at high spatio-temporal resolutions.
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Affiliation(s)
- Burhaneddin Yaman
- Department of Electrical and Computer Engineering University of Minnesota, Minneapolis, MN
| | - Sebastian Weingärtner
- Department of Electrical and Computer Engineering University of Minnesota, Minneapolis, MN
| | - Nikolaos Kargas
- Department of Electrical and Computer Engineering University of Minnesota, Minneapolis, MN
| | | | - Mehmet Akçakaya
- Department of Electrical and Computer Engineering University of Minnesota, Minneapolis, MN
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