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Ogier AC, Montón Quesada I, Sieber X, Calarnou P, Ledoux JB, Milani B, Antiochos P, Schwitter J, Roy CW, Yerly J, Stuber M, van Heeswijk RB. Free-running 5D whole-heart MRI for isotropic cardiac function measurements at 3T without contrast agents. Magn Reson Med 2025; 93:2386-2400. [PMID: 40035180 DOI: 10.1002/mrm.30469] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2024] [Revised: 01/14/2025] [Accepted: 01/31/2025] [Indexed: 03/05/2025]
Abstract
PURPOSE To optimize and characterize an interrupted 5D free-running framework at 3 T for detailed cardiac function assessment without the use of breath holding or contrast agents. METHODS A free-running 3D radial gradient echo sequence was periodically interrupted with aT 2 $$ {\mathrm{T}}_2 $$ preparation and a recovery module to optimize native blood-to-myocardium contrast at 3 T. Lipid signal was suppressed using a numerically optimized water-excitation RF pulse to reduce lipid streaking artifacts and to improve overall image quality. Optimal acquisition parameters were established for a 5-min scan time using extended phase graph simulations. A compressed sensing-based reconstruction incorporating cardiac and respiratory inter-bin deformation fields was employed to generate 5D images of the whole heart. The sharpness and contrast between the left ventricular blood pool and myocardium, along with the functional measurements of the left ventricle from the 5D datasets, were compared to routine 2D cine imaging in 16 healthy volunteers and three patients referred for clinically indicated CMR. RESULTS The proposed method resulted in lower contrast( 0 . 57 ± 0 . 12 $$ \Big(0.57\pm 0.12 $$ vs.2 . 09 ± 0 . 74 , p < 0 . 001 ) $$ 2.09\pm 0.74,p<0.001\Big) $$ and sharpness( 3 . 76 ± 1 . 11 mm $$ \Big(3.76\pm 1.11\kern0.3em \mathrm{mm} $$ vs.2 . 74 ± 0 . 95 mm , p < 0 . 001 ) $$ 2.74\pm 0.95\kern0.3em \mathrm{mm},p<0.001\Big) $$ , but enabled similar left-ventricle ejection fraction assessment( bias = 1 . 3 % $$ \Big(\mathrm{bias}=1.3\% $$ , limits ofagreement = [ - 3 . 3 % , 5 . 9 % ] $$ \mathrm{agreement}=\left[-3.3\%,5.9\%\right] $$ , intraclass correlationcoefficient = 0 . 87 , p = 0 . 03 ) $$ \mathrm{coefficient}=0.87,p=0.03\Big) $$ with high reproducibility compared to 2D cine. CONCLUSION The proposed contrast-free, interrupted free-running 5D imaging provides left ventricular functional assessments comparable to 2D cine at 3 T, while offering an improved patient experience through shorter scan times and free breathing.
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Affiliation(s)
- Augustin C Ogier
- Department of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Isabel Montón Quesada
- Department of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Xavier Sieber
- Department of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Pauline Calarnou
- Department of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Jean-Baptiste Ledoux
- Department of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- CIBM Center for Biomedical Imaging (CIBM), Lausanne, Switzerland
| | - Bastien Milani
- Department of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Panagiotis Antiochos
- Heart and Vessel Department, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Juerg Schwitter
- Heart and Vessel Department, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Christopher W Roy
- Department of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Jérôme Yerly
- Department of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- CIBM Center for Biomedical Imaging (CIBM), Lausanne, Switzerland
| | - Matthias Stuber
- Department of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- CIBM Center for Biomedical Imaging (CIBM), Lausanne, Switzerland
| | - Ruud B van Heeswijk
- Department of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
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Romanin L, Prsa M, Roy CW, Sieber X, Yerly J, Milani B, Rutz T, Si-Mohamed S, Tenisch E, Piccini D, Stuber M. Exploring the limits of scan time reduction for ferumoxytol-enhanced whole-heart angiography in congenital heart disease patients. J Cardiovasc Magn Reson 2025; 27:101854. [PMID: 39920923 PMCID: PMC11889962 DOI: 10.1016/j.jocmr.2025.101854] [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: 07/29/2024] [Revised: 12/24/2024] [Accepted: 02/04/2025] [Indexed: 02/10/2025] Open
Abstract
BACKGROUND One major challenge in cardiovascular magnetic resonance is reducing scan times to be more compatible with clinical workflows. In 3D magnetic resonance imaging (MRI), strategies to shorten scan times mostly rely on ECG-triggering or self-navigation for motion management, but are affected by heart rate variabilities or respiratory drifts. A similarity-driven multi-dimensional binning algorithm (SIMBA) was introduced for 3D whole-heart angiography from ferumoxytol-enhanced free-running MRI. This study explores acceleration limits using SIMBA, and its compressed-sensing extension extra-dimensional motion-compensation (XD-MC)-SIMBA, while preserving image quality. METHODS Data from 6-min free-running acquisitions of 30 congenital heart disease (CHD) patients were retrospectively undersampled to simulate 5-, 4-, 3-, 2-, and 1-min datasets. SIMBA and XD-MC-SIMBA reconstructions were applied. and the consistency of the data selection together with sharpness metrics were computed as a function of undersampling. Image quality was rated on a 5-point Likert scale. Shorter 3-minute acquisitions were prospectively acquired in nine CHD patients. RESULTS SIMBA's motion state selection was consistent across undersampling levels, with only 2 of 30 cases showing completely different selections. Image quality metrics decreased with increased undersampling, with SIMBA scoring lower compared to XD-MC-SIMBA. The diagnostic quality was good, with lower scores for 2- and 1-min datasets. Using XD-MC-SIMBA, 43% (31/72) of cases showed improved scores compared to SIMBA and 58% (7/12) of 1-min datasets improved to good or excellent quality. CONCLUSIONS This study demonstrates that ferumoxytol-enhanced free-running MRI can be highly accelerated for 3D angiography in CHD.With the aid of compressed sensing, XD-MC-SIMBA supports the acceleration down to 3 minutes or less.
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Affiliation(s)
- Ludovica Romanin
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland; Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland
| | - Milan Prsa
- Division of Pediatric Cardiology, Woman-Mother-Child Department, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Christopher W Roy
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Xavier Sieber
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Jérôme Yerly
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland; Center for Biomedical Imaging (CIBM), Lausanne, Switzerland
| | - Bastien Milani
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Tobias Rutz
- Service of Cardiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Salim Si-Mohamed
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland; University Lyon, INSA-Lyon, University Claude Bernard Lyon 1, UJM-Saint Etienne, CNRS, Inserm, CREATIS, Villeurbanne, France; Department of Radiology, Louis Pradel Hospital, Bron, France
| | - Estelle Tenisch
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Davide Piccini
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland; Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland
| | - Matthias Stuber
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland; Center for Biomedical Imaging (CIBM), Lausanne, Switzerland.
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Chen J, Xia D, Huang C, Shanbhogue K, Chandarana H, Feng L. Free-breathing time-resolved 4D MRI with improved T1-weighting contrast. NMR IN BIOMEDICINE 2024; 37:e5247. [PMID: 39183645 DOI: 10.1002/nbm.5247] [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: 06/21/2024] [Revised: 08/06/2024] [Accepted: 08/08/2024] [Indexed: 08/27/2024]
Abstract
This work proposes MP-Grasp4D (magnetization-prepared golden-angle radial sparse parallel 4D) MRI, a free-breathing, inversion recovery (IR)-prepared, time-resolved 4D MRI technique with improved T1-weighted contrast. MP-Grasp4D MRI acquisition incorporates IR preparation into a radial gradient echo sequence. MP-Grasp4D employs a golden-angle navi-stack-of-stars sampling scheme, where imaging data of rotating radial stacks and navigator stacks (acquired at a consistent rotation angle) are alternately acquired. The navigator stacks are used to estimate a temporal basis for low-rank subspace-constrained reconstruction. This allows for the simultaneous capture of both IR-induced contrast changes and respiratory motion. One temporal frame of the imaging volume in MP-Grasp4D MRI is reconstructed from a single stack and an adjacent navigator stack on average, resulting in a nominal temporal resolution of 0.16 seconds per volume. Images corresponding to the optimal inversion time (TI) can be retrospectively selected for providing the best image contrast. Reader studies were conducted to assess the performance of MP-Grasp4D MRI in liver imaging across 30 subjects in comparison with standard Grasp4D MRI without IR preparation. MP-Grasp4D MRI received significantly higher scores (P < 0.05) than Grasp4D in all assessment categories. There was a moderate to almost perfect agreement (kappa coefficient from 0.42 to 0.9) between the two readers for image quality assessment. When the scan time is reduced, MP-Grasp4D MRI preserves image contrast and quality, demonstrating additional acceleration capability. MP-Grasp4D MRI improves T1-weighted contrast for free-breathing time-resolved 4D MRI and eliminates the need for explicit motion compensation. This method is expected to be valuable in different MRI applications such as MR-guided radiotherapy.
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Affiliation(s)
- Jingjia Chen
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, New York, USA
- Center for Advanced Imaging Innovation and Research (CAI2R), Department of Radiology, New York University Grossman School of Medicine, New York, New York, USA
| | - Ding Xia
- Icahn School of Medicine at Mount Sinai, Biomedical Engineering and Imaging Institute, New York, New York, USA
| | - Chenchan Huang
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, New York, USA
- Center for Advanced Imaging Innovation and Research (CAI2R), Department of Radiology, New York University Grossman School of Medicine, New York, New York, USA
| | - Krishna Shanbhogue
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, New York, USA
- Center for Advanced Imaging Innovation and Research (CAI2R), Department of Radiology, New York University Grossman School of Medicine, New York, New York, USA
| | - Hersh Chandarana
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, New York, USA
- Center for Advanced Imaging Innovation and Research (CAI2R), Department of Radiology, New York University Grossman School of Medicine, New York, New York, USA
| | - Li Feng
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, New York, USA
- Center for Advanced Imaging Innovation and Research (CAI2R), Department of Radiology, New York University Grossman School of Medicine, New York, New York, USA
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Voges I, Raimondi F, McMahon CJ, Ait-Ali L, Babu-Narayan SV, Botnar RM, Burkhardt B, Gabbert DD, Grosse-Wortmann L, Hasan H, Hansmann G, Helbing WA, Krupickova S, Latus H, Martini N, Martins D, Muthurangu V, Ojala T, van Ooij P, Pushparajah K, Rodriguez-Palomares J, Sarikouch S, Grotenhuis HB, Greil FG, Bohbot Y, Cikes M, Dweck M, Donal E, Grapsa J, Keenan N, Petrescu AM, Szabo L, Ricci F, Uusitalo V. Clinical impact of novel cardiovascular magnetic resonance technology on patients with congenital heart disease: a scientific statement of the Association for European Pediatric and Congenital Cardiology and the European Association of Cardiovascular Imaging of the European Society of Cardiology. Eur Heart J Cardiovasc Imaging 2024; 25:e274-e294. [PMID: 38985851 DOI: 10.1093/ehjci/jeae172] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/28/2024] [Accepted: 07/01/2024] [Indexed: 07/12/2024] Open
Abstract
Cardiovascular magnetic resonance (CMR) imaging is recommended in patients with congenital heart disease (CHD) in clinical practice guidelines as the imaging standard for a large variety of diseases. As CMR is evolving, novel techniques are becoming available. Some of them are already used clinically, whereas others still need further evaluation. In this statement, the authors give an overview of relevant new CMR techniques for the assessment of CHD. Studies with reference values for these new techniques are listed in the Supplementary data online, supplement.
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Affiliation(s)
- Inga Voges
- Department of Congenital Heart Disease and Pediatric Cardiology, University Hospital Schleswig-Holstein, Campus Kiel, Germany
- German Center for Cardiovascular Research (DZHK), Partner Site Hamburg/Lübeck/Kiel, Kiel, Germany
| | | | - Colin J McMahon
- Department of Paediatric Cardiology, Children's Health Ireland at Crumlin, Dublin 12, Ireland
| | - Lamia Ait-Ali
- Institute of Clinical Physiology CNR, Massa, Italy
- Heart Hospital, G. Monastery foundation, Massa, Italy
| | - Sonya V Babu-Narayan
- Royal Brompton Hospital, Part of Guy's and St Thomas' NHS Foundation Trust, Sydney Street, London SW3 6NP, UK
- National Heart and Lung Institute, Imperial College, London, UK
| | - René M Botnar
- School of Biomedical Engineering and Imaging Sciences, King's College London, St. Thomas' Hospital, London, UK
- Institute for Biological and Medical Engineering and School of Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Barbara Burkhardt
- Pediatric Heart Center, University Children's Hospital Zurich, Zurich, Switzerland
| | - Dominik D Gabbert
- Department of Congenital Heart Disease and Pediatric Cardiology, University Hospital Schleswig-Holstein, Campus Kiel, Germany
- German Center for Cardiovascular Research (DZHK), Partner Site Hamburg/Lübeck/Kiel, Kiel, Germany
| | - Lars Grosse-Wortmann
- Division of Cardiology, Oregon Health and Science University Hospital, Portland, OR, USA
| | - Hosan Hasan
- Department of Pediatric Cardiology and Critical Care, Hannover Medical School, Hannover, Germany
- European Pediatric Pulmonary Vascular Disease Network, Berlin, Germany
| | - Georg Hansmann
- Department of Pediatric Cardiology and Critical Care, Hannover Medical School, Hannover, Germany
- European Pediatric Pulmonary Vascular Disease Network, Berlin, Germany
| | - Willem A Helbing
- Department of Pediatrics, Division of Cardiology, and Department of Radiology, Erasmus MC-Sophia Children's Hospital, Rotterdam, The Netherlands
| | - Sylvia Krupickova
- Royal Brompton Hospital, Part of Guy's and St Thomas' NHS Foundation Trust, Sydney Street, London SW3 6NP, UK
- National Heart and Lung Institute, Imperial College, London, UK
- Department of Paediatric Cardiology, Royal Brompton Hospital, Sydney Street, London SW3 6NP, UK
| | - Heiner Latus
- Clinic for Pediatric Cardiology and Congenital Heart Disease Klinikum, Stuttgart Germany
| | - Nicola Martini
- Department of Radiology, Fondazione G. Monasterio CNR-Regione Toscana, Pisa, Italy
- U.O.C. Bioingegneria, Fondazione G. Monasterio CNR-Regione Toscana, Pisa, Italy
| | - Duarte Martins
- Pediatric Cardiology Department, Hospital de Santa Cruz, Centro Hospitalar Lisboa Ocidental, Lisbon, Portugal
| | - Vivek Muthurangu
- Centre for Translational Cardiovascular Imaging, Institute of Cardiovascular Science, University College London, London, UK
| | - Tiina Ojala
- New Children's Hospital Pediatric Research Center, Helsinki University Hospital, Helsinki, Finland
| | - Pim van Ooij
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, Location AMC, Amsterdam, The Netherlands
- Department of Pediatric Cardiology, Wilhelmina Children's Hospital/University Medical Center Utrecht, Utrecht, The Netherlands
| | - Kuberan Pushparajah
- School of Biomedical Engineering and Imaging Sciences, King's College London, St. Thomas' Hospital, London, UK
- Department of Congenital Heart Disease, Evelina London Children's Hospital, Westminster Bridge Road, London SE1 7EH, UK
| | - Jose Rodriguez-Palomares
- CIBER Cardiovascular, Instituto de Salud Carlos III, Madrid, Spain
- European Reference Network for Rare and Low Prevalence Complex Diseases of the Heart, Amsterdam, The Netherlands
- Servicio de Cardiología, Hospital Universitario Vall Hebrón, Institut de Recerca Vall Hebrón (VHIR), Departamento de Medicina, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Samir Sarikouch
- Department for Cardiothoracic, Transplant, and Vascular Surgery, Hannover Medical School, Hannover, Germany
| | - Heynric B Grotenhuis
- Department of Pediatric Cardiology, Wilhelmina Children's Hospital/University Medical Center Utrecht, Utrecht, The Netherlands
| | - F Gerald Greil
- Department of Pediatrics, UT Southwestern/Children's Health, Dallas, TX, USA
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Holtackers RJ, Stuber M. Free-Running Cardiac and Respiratory Motion-Resolved Imaging: A Paradigm Shift for Managing Motion in Cardiac MRI? Diagnostics (Basel) 2024; 14:1946. [PMID: 39272732 PMCID: PMC11394669 DOI: 10.3390/diagnostics14171946] [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: 08/16/2024] [Revised: 08/30/2024] [Accepted: 08/30/2024] [Indexed: 09/15/2024] Open
Abstract
Cardiac magnetic resonance imaging (MRI) is widely used for non-invasive assessment of cardiac morphology, function, and tissue characteristics due to its exquisite soft-tissue contrast. However, it remains time-consuming and requires proficiency, making it costly and limiting its widespread use. Traditional cardiac MRI is inefficient as signal acquisition is often limited to specific cardiac phases and requires complex view planning, parameter adjustments, and management of both respiratory and cardiac motion. Recent efforts have aimed to make cardiac MRI more efficient and accessible. Among these innovations, the free-running framework enables 5D whole-heart imaging without the need for an electrocardiogram signal, respiratory breath-holding, or complex planning. It uses a fully self-gated approach to extract cardiac and respiratory signals directly from the acquired image data, allowing for more efficient coverage in time and space without the need for electrocardiogram gating, triggering, navigators, or breath-holds. This review provides a comprehensive overview of the free-running framework, detailing its history, concepts, recent improvements, and clinical applications.
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Affiliation(s)
- Robert J Holtackers
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Rue de Bugnon 46, 1011 Lausanne, Switzerland
- Department of Radiology & Nuclear Medicine, Maastricht University Medical Center, P. Debyelaan 25, 6229 HX Maastricht, The Netherlands
- Cardiovascular Research Institute Maastricht (CARIM), Maastricht University, Universiteitssingel 50, 6200 MD Maastricht, The Netherlands
| | - Matthias Stuber
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Rue de Bugnon 46, 1011 Lausanne, Switzerland
- Center for Biomedical Imaging (CIBM), EPFL AVP CP CIBM Station 6, 1015 Lausanne, Switzerland
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Ghoul A, Pan J, Lingg A, Kubler J, Krumm P, Hammernik K, Rueckert D, Gatidis S, Kustner T. Attention-Aware Non-Rigid Image Registration for Accelerated MR Imaging. IEEE TRANSACTIONS ON MEDICAL IMAGING 2024; 43:3013-3026. [PMID: 39088484 DOI: 10.1109/tmi.2024.3385024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/03/2024]
Abstract
Accurate motion estimation at high acceleration factors enables rapid motion-compensated reconstruction in Magnetic Resonance Imaging (MRI) without compromising the diagnostic image quality. In this work, we introduce an attention-aware deep learning-based framework that can perform non-rigid pairwise registration for fully sampled and accelerated MRI. We extract local visual representations to build similarity maps between the registered image pairs at multiple resolution levels and additionally leverage long-range contextual information using a transformer-based module to alleviate ambiguities in the presence of artifacts caused by undersampling. We combine local and global dependencies to perform simultaneous coarse and fine motion estimation. The proposed method was evaluated on in-house acquired fully sampled and accelerated data of 101 patients and 62 healthy subjects undergoing cardiac and thoracic MRI. The impact of motion estimation accuracy on the downstream task of motion-compensated reconstruction was analyzed. We demonstrate that our model derives reliable and consistent motion fields across different sampling trajectories (Cartesian and radial) and acceleration factors of up to 16x for cardiac motion and 30x for respiratory motion and achieves superior image quality in motion-compensated reconstruction qualitatively and quantitatively compared to conventional and recent deep learning-based approaches. The code is publicly available at https://github.com/lab-midas/GMARAFT.
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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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Romanin L, Milani B, Roy CW, Yerly J, Bustin A, Si-mohamed S, Prsa M, Rutz T, Tenisch E, Schwitter J, Stuber M, Piccini D. Similarity-driven motion-resolved reconstruction for ferumoxytol-enhanced whole-heart MRI in congenital heart disease. PLoS One 2024; 19:e0304612. [PMID: 38870171 PMCID: PMC11175540 DOI: 10.1371/journal.pone.0304612] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2023] [Accepted: 05/15/2024] [Indexed: 06/15/2024] Open
Abstract
A similarity-driven multi-dimensional binning algorithm (SIMBA) reconstruction of free-running cardiac magnetic resonance imaging data was previously proposed. While very efficient and fast, the original SIMBA focused only on the reconstruction of a single motion-consistent cluster, discarding the remaining data acquired. However, the redundant data clustered by similarity may be exploited to further improve image quality. In this work, we propose a novel compressed sensing (CS) reconstruction that performs an effective regularization over the clustering dimension, thanks to the integration of inter-cluster motion compensation (XD-MC-SIMBA). This reconstruction was applied to free-running ferumoxytol-enhanced datasets from 24 patients with congenital heart disease, and compared to the original SIMBA, the same XD-MC-SIMBA reconstruction but without motion compensation (XD-SIMBA), and a 5D motion-resolved CS reconstruction using the free-running framework (FRF). The resulting images were compared in terms of lung-liver and blood-myocardium sharpness, blood-myocardium contrast ratio, and visible length and sharpness of the coronary arteries. Moreover, an automated image quality score (IQS) was assigned using a pretrained deep neural network. The lung-liver sharpness and blood-myocardium sharpness were significantly higher in XD-MC-SIMBA and FRF. Consistent with these findings, the IQS analysis revealed that image quality for XD-MC-SIMBA was improved in 18 of 24 cases, compared to SIMBA. We successfully tested the hypothesis that multiple motion-consistent SIMBA clusters can be exploited to improve the quality of ferumoxytol-enhanced cardiac MRI when inter-cluster motion-compensation is integrated as part of a CS reconstruction.
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Affiliation(s)
- Ludovica Romanin
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland
| | - Bastien Milani
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Christopher W. Roy
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Jérôme Yerly
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- Center for Biomedical Imaging (CIBM), Lausanne, Switzerland
| | - Aurélien Bustin
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- IHU LIRYC, Electrophysiology and Heart Modeling Institute, Université de Bordeaux – INSERM U1045, Pessac, France
- Department of Cardiovascular Imaging, Hôpital Cardiologique du Haut-Lévêque, CHU de Bordeaux, Pessac, France
| | - Salim Si-mohamed
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- University Lyon, INSA-Lyon, University Claude Bernard Lyon 1, UJM-Saint Etienne, CNRS, Inserm, CREATIS UMR 5220, U1206, Villeurbanne, France
- Department of Radiology, Louis Pradel Hospital, Hospices Civils de Lyon, Bron, France
| | - Milan Prsa
- Division of Pediatric Cardiology, Woman-Mother-Child Department, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Tobias Rutz
- Division of Cardiology, Cardiovascular Department, Lausanne University Hospital, Lausanne, Switzerland
| | - Estelle Tenisch
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Juerg Schwitter
- Division of Cardiology, Cardiovascular Department, Lausanne University Hospital, Lausanne, Switzerland
- Faculty of Biology&Medicine, University of Lausanne, UniL, Lausanne, Switzerland
- Cardiac MR Center of the University Hospital Lausanne, Lausanne, Switzerland
| | - Matthias Stuber
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- Center for Biomedical Imaging (CIBM), Lausanne, Switzerland
| | - Davide Piccini
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland
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9
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Roy CW, Milani B, Yerly J, Si-Mohamed S, Romanin L, Bustin A, Tenisch E, Rutz T, Prsa M, Stuber M. Intra-bin correction and inter-bin compensation of respiratory motion in free-running five-dimensional whole-heart magnetic resonance imaging. J Cardiovasc Magn Reson 2024; 26:101037. [PMID: 38499269 PMCID: PMC10987330 DOI: 10.1016/j.jocmr.2024.101037] [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: 01/08/2024] [Revised: 03/09/2024] [Accepted: 03/11/2024] [Indexed: 03/20/2024] Open
Abstract
BACKGROUND Free-running cardiac and respiratory motion-resolved whole-heart five-dimensional (5D) cardiovascular magnetic resonance (CMR) can reduce scan planning and provide a means of evaluating respiratory-driven changes in clinical parameters of interest. However, respiratory-resolved imaging can be limited by user-defined parameters which create trade-offs between residual artifact and motion blur. In this work, we develop and validate strategies for both correction of intra-bin and compensation of inter-bin respiratory motion to improve the quality of 5D CMR. METHODS Each component of the reconstruction framework was systematically validated and compared to the previously established 5D approach using simulated free-running data (N = 50) and a cohort of 32 patients with congenital heart disease. The impact of intra-bin respiratory motion correction was evaluated in terms of image sharpness while inter-bin respiratory motion compensation was evaluated in terms of reconstruction error, compression of respiratory motion, and image sharpness. The full reconstruction framework (intra-acquisition correction and inter-acquisition compensation of respiratory motion [IIMC] 5D) was evaluated in terms of image sharpness and scoring of image quality by expert reviewers. RESULTS Intra-bin motion correction provides significantly (p < 0.001) sharper images for both simulated and patient data. Inter-bin motion compensation results in significant (p < 0.001) lower reconstruction error, lower motion compression, and higher sharpness in both simulated (10/11) and patient (9/11) data. The combined framework resulted in significantly (p < 0.001) sharper IIMC 5D reconstructions (End-expiration (End-Exp): 0.45 ± 0.09, End-inspiration (End-Ins): 0.46 ± 0.10) relative to the previously established 5D implementation (End-Exp: 0.43 ± 0.08, End-Ins: 0.39 ± 0.09). Similarly, image scoring by three expert reviewers was significantly (p < 0.001) higher using IIMC 5D (End-Exp: 3.39 ± 0.44, End-Ins: 3.32 ± 0.45) relative to 5D images (End-Exp: 3.02 ± 0.54, End-Ins: 2.45 ± 0.52). CONCLUSION The proposed IIMC reconstruction significantly improves the quality of 5D whole-heart MRI. This may be exploited for higher resolution or abbreviated scanning. Further investigation of the diagnostic impact of this framework and comparison to gold standards is needed to understand its full clinical utility, including exploration of respiratory-driven changes in physiological measurements of interest.
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Affiliation(s)
- Christopher W Roy
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.
| | - Bastien Milani
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Jérôme Yerly
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland; Center for Biomedical Imaging (CIBM), Lausanne, Switzerland
| | - Salim Si-Mohamed
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland; University Lyon, INSA-Lyon, University Claude Bernard Lyon 1, UJM-Saint Etienne, CNRS, Inserm, CREATIS UMR 5220, U1206, F-69621, 7 Avenue Jean Capelle O, 69100 Villeurbanne, France; Department of Radiology, Louis Pradel Hospital, Hospices Civils de Lyon, 59 Boulevard Pinel, 69500 Bron, France
| | - Ludovica Romanin
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland; Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland
| | - Aurélien Bustin
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland; IHU LIRYC, Electrophysiology and Heart Modeling Institute, Université de Bordeaux - INSERM U1045, Avenue du Haut Lévêque, 33604 Pessac, France; Department of Cardiovascular Imaging, Hôpital Cardiologique du Haut-Lévêque, CHU de Bordeaux, Avenue de Magellan, 33604 Pessac, France
| | - Estelle Tenisch
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Tobias Rutz
- Service of Cardiology, Heart and Vessel Department, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Milan Prsa
- Division of Pediatric Cardiology, Woman-Mother-Child Department, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Matthias Stuber
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland; Center for Biomedical Imaging (CIBM), Lausanne, Switzerland
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10
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Merton R, Bosshardt D, Strijkers GJ, Nederveen AJ, Schrauben EM, van Ooij P. Reproducibility of 3D thoracic aortic displacement from 3D cine balanced SSFP at 3 T without contrast enhancement. Magn Reson Med 2024; 91:466-480. [PMID: 37831612 DOI: 10.1002/mrm.29856] [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: 05/04/2023] [Revised: 08/02/2023] [Accepted: 08/16/2023] [Indexed: 10/15/2023]
Abstract
PURPOSE Aortic motion has direct impact on the mechanical stresses acting on the aorta. In aortic disease, increased stiffness of the aorta may lead to decreased aortic motion over time, which could be a predictor for aortic dissection or rupture. This study investigates the reproducibility of obtaining 3D displacement and diameter maps quantified using accelerated 3D cine MRI at 3 T. METHODS A noncontrast-enhanced, free-breathing 3D cine sequence based on balanced SSFP and pseudo-spiral undersampling with high spatial isotropic resolution was developed (spatial/temporal resolution [1.6 mm]3 /67 ms). The thoracic aorta of 14 healthy volunteers was prospectively scanned three times at 3 T: twice on the same day and a third time 2 weeks later. Aortic displacement was calculated using iterative closest point nonrigid registration of manual segmentations of the 3D aorta at end-systole and mid-diastole. Interexamination and interobserver regional analysis of mean displacement for five regions of interest was performed using Bland-Altman analysis. Additionally, a complementary voxel-by-voxel analysis was done, allowing a more local inspection of the method. RESULTS No significant differences were found in mean and maximum displacement for any of the regions of interest for the interexamination and interobserver analysis. The maximum displacement measured in the lower half of the ascending aorta was 11.0 ± 3.4 mm (range: 3.0-17.5 mm) for the first scan. The smallest detectable change in mean displacement in the lower half of the ascending aorta was 3 mm. CONCLUSION Detailed 3D cine balanced SSFP at 3 T allows for reproducible quantification of systolic-diastolic mean aortic displacement within acceptable limits.
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Affiliation(s)
- Renske Merton
- Radiology and Nuclear Medicine, Amsterdam UMC location University of Amsterdam, Amsterdam, the Netherlands
- Amsterdam Cardiovascular Sciences, Amsterdam, the Netherlands
| | - Daan Bosshardt
- Radiology and Nuclear Medicine, Amsterdam UMC location University of Amsterdam, Amsterdam, the Netherlands
- Amsterdam Cardiovascular Sciences, Amsterdam, the Netherlands
| | - Gustav J Strijkers
- Amsterdam Cardiovascular Sciences, Amsterdam, the Netherlands
- Biomedical Physics and Engineering, Amsterdam UMC location University of Amsterdam, Amsterdam, the Netherlands
- Amsterdam Movement Sciences, Amsterdam, the Netherlands
| | - Aart J Nederveen
- Radiology and Nuclear Medicine, Amsterdam UMC location University of Amsterdam, Amsterdam, the Netherlands
- Amsterdam Cardiovascular Sciences, Amsterdam, the Netherlands
- Amsterdam Movement Sciences, Amsterdam, the Netherlands
| | - Eric M Schrauben
- Radiology and Nuclear Medicine, Amsterdam UMC location University of Amsterdam, Amsterdam, the Netherlands
- Amsterdam Cardiovascular Sciences, Amsterdam, the Netherlands
| | - Pim van Ooij
- Radiology and Nuclear Medicine, Amsterdam UMC location University of Amsterdam, Amsterdam, the Netherlands
- Amsterdam Cardiovascular Sciences, Amsterdam, the Netherlands
- Amsterdam Movement Sciences, Amsterdam, the Netherlands
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11
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Silva J, Milovic C, Lambert M, Montalba C, Arrieta C, Irarrazaval P, Uribe S, Tejos C. Toward a realistic in silico abdominal phantom for QSM. Magn Reson Med 2023; 89:2402-2418. [PMID: 36695213 PMCID: PMC10952412 DOI: 10.1002/mrm.29597] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2022] [Revised: 12/18/2022] [Accepted: 01/06/2023] [Indexed: 01/26/2023]
Abstract
PURPOSE QSM outside the brain has recently gained interest, particularly in the abdominal region. However, the absence of reliable ground truths makes difficult to assess reconstruction algorithms, whose quality is already compromised by additional signal contributions from fat, gases, and different kinds of motion. This work presents a realistic in silico phantom for the development, evaluation and comparison of abdominal QSM reconstruction algorithms. METHODS Synthetic susceptibility andR 2 * $$ {R}_2^{\ast } $$ maps were generated by segmenting and postprocessing the abdominal 3T MRI data from a healthy volunteer. Susceptibility andR 2 * $$ {R}_2^{\ast } $$ values in different tissues/organs were assigned according to literature and experimental values and were also provided with realistic textures. The signal was simulated using as input the synthetic QSM andR 2 * $$ {R}_2^{\ast } $$ maps and fat contributions. Three susceptibility scenarios and two acquisition protocols were simulated to compare different reconstruction algorithms. RESULTS QSM reconstructions show that the phantom allows to identify the main strengths and limitations of the acquisition approaches and reconstruction algorithms, such as in-phase acquisitions, water-fat separation methods, and QSM dipole inversion algorithms. CONCLUSION The phantom showed its potential as a ground truth to evaluate and compare reconstruction pipelines and algorithms. The publicly available source code, designed in a modular framework, allows users to easily modify the susceptibility,R 2 * $$ {R}_2^{\ast } $$ and TEs, and thus creates different abdominal scenarios.
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Affiliation(s)
- Javier Silva
- Department of Electrical EngineeringPontificia Universidad Católica de Chile
SantiagoChile
- Biomedical Imaging CenterPontificia Universidad Católica de ChileSantiagoChile
- Millennium Institute for Intelligent Healthcare Engineering (iHEALTH)SantiagoChile
| | - Carlos Milovic
- Millennium Institute for Intelligent Healthcare Engineering (iHEALTH)SantiagoChile
- School of Electrical EngineeringPontificia Universidad Católica de ValparaísoValparaísoChile
| | - Mathias Lambert
- Department of Electrical EngineeringPontificia Universidad Católica de Chile
SantiagoChile
- Biomedical Imaging CenterPontificia Universidad Católica de ChileSantiagoChile
- Millennium Institute for Intelligent Healthcare Engineering (iHEALTH)SantiagoChile
| | - Cristian Montalba
- Biomedical Imaging CenterPontificia Universidad Católica de ChileSantiagoChile
- Millennium Institute for Intelligent Healthcare Engineering (iHEALTH)SantiagoChile
- Department of Radiology, School of MedicinePontificia Universidad Católica de ChileSantiagoChile
| | - Cristóbal Arrieta
- Biomedical Imaging CenterPontificia Universidad Católica de ChileSantiagoChile
- Millennium Institute for Intelligent Healthcare Engineering (iHEALTH)SantiagoChile
| | - Pablo Irarrazaval
- Department of Electrical EngineeringPontificia Universidad Católica de Chile
SantiagoChile
- Biomedical Imaging CenterPontificia Universidad Católica de ChileSantiagoChile
- Millennium Institute for Intelligent Healthcare Engineering (iHEALTH)SantiagoChile
- Institute for Biological and Medical Engineering, Pontificia Universidad Católica de ChileSantiagoChile
| | - Sergio Uribe
- Biomedical Imaging CenterPontificia Universidad Católica de ChileSantiagoChile
- Millennium Institute for Intelligent Healthcare Engineering (iHEALTH)SantiagoChile
- Department of Radiology, School of MedicinePontificia Universidad Católica de ChileSantiagoChile
| | - Cristian Tejos
- Department of Electrical EngineeringPontificia Universidad Católica de Chile
SantiagoChile
- Biomedical Imaging CenterPontificia Universidad Católica de ChileSantiagoChile
- Millennium Institute for Intelligent Healthcare Engineering (iHEALTH)SantiagoChile
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12
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Schick F. Automatic segmentation and volumetric assessment of internal organs and fatty tissue: what are the benefits? MAGNETIC RESONANCE MATERIALS IN PHYSICS, BIOLOGY AND MEDICINE 2022; 35:187-192. [PMID: 34919193 PMCID: PMC8995273 DOI: 10.1007/s10334-021-00986-1] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Revised: 12/03/2021] [Accepted: 12/05/2021] [Indexed: 02/07/2023]
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13
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Ismail TF, Strugnell W, Coletti C, Božić-Iven M, Weingärtner S, Hammernik K, Correia T, Küstner T. Cardiac MR: From Theory to Practice. Front Cardiovasc Med 2022; 9:826283. [PMID: 35310962 PMCID: PMC8927633 DOI: 10.3389/fcvm.2022.826283] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Accepted: 01/17/2022] [Indexed: 01/10/2023] Open
Abstract
Cardiovascular disease (CVD) is the leading single cause of morbidity and mortality, causing over 17. 9 million deaths worldwide per year with associated costs of over $800 billion. Improving prevention, diagnosis, and treatment of CVD is therefore a global priority. Cardiovascular magnetic resonance (CMR) has emerged as a clinically important technique for the assessment of cardiovascular anatomy, function, perfusion, and viability. However, diversity and complexity of imaging, reconstruction and analysis methods pose some limitations to the widespread use of CMR. Especially in view of recent developments in the field of machine learning that provide novel solutions to address existing problems, it is necessary to bridge the gap between the clinical and scientific communities. This review covers five essential aspects of CMR to provide a comprehensive overview ranging from CVDs to CMR pulse sequence design, acquisition protocols, motion handling, image reconstruction and quantitative analysis of the obtained data. (1) The basic MR physics of CMR is introduced. Basic pulse sequence building blocks that are commonly used in CMR imaging are presented. Sequences containing these building blocks are formed for parametric mapping and functional imaging techniques. Commonly perceived artifacts and potential countermeasures are discussed for these methods. (2) CMR methods for identifying CVDs are illustrated. Basic anatomy and functional processes are described to understand the cardiac pathologies and how they can be captured by CMR imaging. (3) The planning and conduct of a complete CMR exam which is targeted for the respective pathology is shown. Building blocks are illustrated to create an efficient and patient-centered workflow. Further strategies to cope with challenging patients are discussed. (4) Imaging acceleration and reconstruction techniques are presented that enable acquisition of spatial, temporal, and parametric dynamics of the cardiac cycle. The handling of respiratory and cardiac motion strategies as well as their integration into the reconstruction processes is showcased. (5) Recent advances on deep learning-based reconstructions for this purpose are summarized. Furthermore, an overview of novel deep learning image segmentation and analysis methods is provided with a focus on automatic, fast and reliable extraction of biomarkers and parameters of clinical relevance.
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Affiliation(s)
- Tevfik F. Ismail
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
- Cardiology Department, Guy's and St Thomas' Hospital, London, United Kingdom
| | - Wendy Strugnell
- Queensland X-Ray, Mater Hospital Brisbane, Brisbane, QLD, Australia
| | - Chiara Coletti
- Magnetic Resonance Systems Lab, Delft University of Technology, Delft, Netherlands
| | - Maša Božić-Iven
- Magnetic Resonance Systems Lab, Delft University of Technology, Delft, Netherlands
- Computer Assisted Clinical Medicine, Heidelberg University, Mannheim, Germany
| | | | - Kerstin Hammernik
- Lab for AI in Medicine, Technical University of Munich, Munich, Germany
- Department of Computing, Imperial College London, London, United Kingdom
| | - Teresa Correia
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
- Centre of Marine Sciences, Faro, Portugal
| | - Thomas Küstner
- Medical Image and Data Analysis (MIDAS.lab), Department of Diagnostic and Interventional Radiology, University Hospital of Tübingen, Tübingen, Germany
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14
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Dietrich S, Aigner CS, Mayer J, Kolbitsch C, Schulz-Menger J, Schaeffter T, Schmitter S. Motion-compensated fat-water imaging for 3D cardiac MRI at ultra-high fields. Magn Reson Med 2022; 87:2621-2636. [PMID: 35092090 DOI: 10.1002/mrm.29144] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2021] [Revised: 11/23/2021] [Accepted: 12/14/2021] [Indexed: 12/16/2022]
Abstract
PURPOSE Respiratory motion-compensated (MC) 3D cardiac fat-water imaging at 7T. METHODS Free-breathing bipolar 3D triple-echo gradient-recalled-echo (GRE) data with radial phase-encoding (RPE) trajectory were acquired in 11 healthy volunteers (7M\4F, 21-35 years, mean: 30 years) with a wide range of body mass index (BMI; 19.9-34.0 kg/m2 ) and volunteer tailored B 1 + shimming. The bipolar-corrected triple-echo GRE-RPE data were binned into different respiratory phases (self-navigation) and were used for the estimation of non-rigid motion vector fields (MF) and respiratory resolved (RR) maps of the main magnetic field deviations (ΔB0 ). RR ΔB0 maps and MC ΔB0 maps were compared to a reference respiratory phase to assess respiration-induced changes. Subsequently, cardiac binned fat-water images were obtained using a model-based, respiratory motion-corrected image reconstruction. RESULTS The 3D cardiac fat-water imaging at 7T was successfully demonstrated. Local respiration-induced frequency shifts in MC ΔB0 maps are small compared to the chemical shifts used in the multi-peak model. Compared to the reference exhale ΔB0 map these changes are in the order of 10 Hz on average. Cardiac binned MC fat-water reconstruction reduced respiration induced blurring in the fat-water images, and flow artifacts are reduced in the end-diastolic fat-water separated images. CONCLUSION This work demonstrates the feasibility of 3D fat-water imaging at UHF for the entire human heart despite spatial and temporal B 1 + and B0 variations, as well as respiratory and cardiac motion.
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Affiliation(s)
- Sebastian Dietrich
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Germany
| | | | - Johannes Mayer
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Germany
| | - Christoph Kolbitsch
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Germany
| | - Jeanette Schulz-Menger
- Experimental and Clinical Research Center, A Joint Cooperation between the Charité Medical Faculty and the Max-Delbrueck Center for Molecular Medicine and HELIOS Hospital Berlin Buch, Berlin, Germany.,DZHK (German Center for Cardiovascular Research), Partner Site Berlin, Berlin, Germany.,Helios Clinics Berlin-Buch Department of Cardiology and Nephrology, Berlin, Germany
| | - Tobias Schaeffter
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Germany.,Department of Medical Engineering, Technische Universität Berlin, Germany
| | - Sebastian Schmitter
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Germany.,Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, Minnesota, USA
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15
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Bonanno G, Weiss RG, Piccini D, Yerly J, Soleimani S, Pan L, Bi X, Hays AG, Stuber M, Schär M. Volumetric coronary endothelial function assessment: a feasibility study exploiting stack-of-stars 3D cine MRI and image-based respiratory self-gating. NMR IN BIOMEDICINE 2021; 34:e4589. [PMID: 34291517 PMCID: PMC8969584 DOI: 10.1002/nbm.4589] [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: 10/13/2020] [Accepted: 06/25/2021] [Indexed: 06/13/2023]
Abstract
Abnormal coronary endothelial function (CEF), manifesting as depressed vasoreactive responses to endothelial-specific stressors, occurs early in atherosclerosis, independently predicts cardiovascular events, and responds to cardioprotective interventions. CEF is spatially heterogeneous along a coronary artery in patients with atherosclerosis, and thus recently developed and tested non-invasive 2D MRI techniques to measure CEF may not capture the extent of changes in CEF in a given coronary artery. The purpose of this study was to develop and test the first volumetric coronary 3D MRI cine method for assessing CEF along the proximal and mid-coronary arteries with isotropic spatial resolution and in free-breathing. This approach, called 3D-Stars, combines a 6 min continuous, untriggered golden-angle stack-of-stars acquisition with a novel image-based respiratory self-gating method and cardiac and respiratory motion-resolved reconstruction. The proposed respiratory self-gating method agreed well with respiratory bellows and center-of-k-space methods. In healthy subjects, 3D-Stars vessel sharpness was non-significantly different from that by conventional 2D radial in proximal segments, albeit lower in mid-portions. Importantly, 3D-Stars detected normal vasodilatation of the right coronary artery in response to endothelial-dependent isometric handgrip stress in healthy subjects. Coronary artery cross-sectional areas measured using 3D-Stars were similar to those from 2D radial MRI when similar thresholding was used. In conclusion, 3D-Stars offers good image quality and shows feasibility for non-invasively studying vasoreactivity-related lumen area changes along the proximal coronary artery in 3D during free-breathing.
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Affiliation(s)
- Gabriele Bonanno
- Division of Cardiology, Department of Medicine, Johns Hopkins University, Baltimore, MD, USA
- Russel H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University, Baltimore, MD, USA
| | - Robert G. Weiss
- Division of Cardiology, Department of Medicine, Johns Hopkins University, Baltimore, MD, USA
- Russel H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University, Baltimore, MD, USA
| | - Davide Piccini
- Advanced Clinical Imaging Technology, Siemens Healthcare, Lausanne, Switzerland
| | - Jérôme Yerly
- Department of Radiology, University Hospital of Lausanne, Lausanne, Switzerland
- Center for Biomedical Imaging (CIBM), University Hospital of Lausanne, Lausanne, Switzerland
| | - Sahar Soleimani
- Russel H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University, Baltimore, MD, USA
| | - Li Pan
- Siemens Medical Solutions USA, Inc, Baltimore, MD, USA
| | - Xiaoming Bi
- Siemens Medical Solutions USA, Inc, Los Angeles, CA, USA
| | - Allison G Hays
- Division of Cardiology, Department of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Matthias Stuber
- Department of Radiology, University Hospital of Lausanne, Lausanne, Switzerland
- Center for Biomedical Imaging (CIBM), University Hospital of Lausanne, Lausanne, Switzerland
| | - Michael Schär
- Russel H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University, Baltimore, MD, USA
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16
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Heerfordt J, Whitehead KK, Bastiaansen JAM, Di Sopra L, Roy CW, Yerly J, Milani B, Fogel MA, Stuber M, Piccini D. Similarity-driven multi-dimensional binning algorithm (SIMBA) for free-running motion-suppressed whole-heart MRA. Magn Reson Med 2021; 86:213-229. [PMID: 33624348 DOI: 10.1002/mrm.28713] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2020] [Revised: 12/19/2020] [Accepted: 01/11/2021] [Indexed: 12/27/2022]
Abstract
PURPOSE Whole-heart MRA techniques typically target predetermined motion states, address cardiac and respiratory dynamics independently, and require either complex planning or computationally demanding reconstructions. In contrast, we developed a fast data-driven reconstruction algorithm with minimal physiological assumptions and compatibility with ungated free-running sequences. THEORY AND METHODS We propose a similarity-driven multi-dimensional binning algorithm (SIMBA) that clusters continuously acquired k-space data to find a motion-consistent subset for whole-heart MRA reconstruction. Free-running 3D radial data sets from 12 non-contrast-enhanced scans of healthy volunteers and six ferumoxytol-enhanced scans of pediatric cardiac patients were reconstructed with non-motion-suppressed regridding of all the acquired data ("All Data"), with SIMBA, and with a previously published free-running framework (FRF) that uses cardiac and respiratory self-gating and compressed sensing. Images were compared for blood-myocardium sharpness and contrast ratio, visibility of coronary artery ostia, and right coronary artery sharpness. RESULTS Both the 20-second SIMBA reconstruction and FRF provided significantly higher blood-myocardium sharpness than All Data in both patients and volunteers (P < .05). The SIMBA reconstruction provided significantly sharper blood-myocardium interfaces than FRF in volunteers (P < .001) and higher blood-myocardium contrast ratio than All Data and FRF, both in volunteers and patients (P < .05). Significantly more ostia could be visualized with both SIMBA (31 of 36) and FRF (34 of 36) than with All Data (4 of 36) (P < .001). Inferior right coronary artery sharpness using SIMBA versus FRF was observed (volunteers: SIMBA 36.1 ± 8.1%, FRF 40.4 ± 8.9%; patients: SIMBA 35.9 ± 7.7%, FRF 40.3 ± 6.1%, P = not significant). CONCLUSION The SIMBA technique enabled a fast, data-driven reconstruction of free-running whole-heart MRA with image quality superior to All Data and similar to the more time-consuming FRF reconstruction.
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Affiliation(s)
- John Heerfordt
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.,Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland
| | - Kevin K Whitehead
- Division of Cardiology, Department of Pediatrics, The Children's Hospital of Philadelphia, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Jessica A M Bastiaansen
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Lorenzo Di Sopra
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Christopher W Roy
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Jérôme Yerly
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.,Center for Biomedical Imaging, Lausanne, Switzerland
| | - Bastien Milani
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Mark A Fogel
- Division of Cardiology, Department of Pediatrics, The Children's Hospital of Philadelphia, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Matthias Stuber
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.,Center for Biomedical Imaging, Lausanne, Switzerland
| | - Davide Piccini
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.,Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland
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