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Scholand N, Schaten P, Graf C, Mackner D, Holme HCM, Blumenthal M, Mao A, Assländer J, Uecker M. Rational approximation of golden angles: Accelerated reconstructions for radial MRI. Magn Reson Med 2024. [PMID: 39250418 DOI: 10.1002/mrm.30247] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2024] [Revised: 07/12/2024] [Accepted: 07/25/2024] [Indexed: 09/11/2024]
Abstract
PURPOSE To develop a generic radial sampling scheme that combines the advantages of golden ratio sampling with simplicity of equidistant angular patterns. The irrational angle between consecutive spokes in golden ratio-based sampling schemes enables a flexible retrospective choice of temporal resolution, while preserving good coverage of k-space for each individual bin. Nevertheless, irrational increments prohibit precomputation of the point-spread function (PSF), can lead to numerical problems, and require more complex processing steps. To avoid these problems, a new sampling scheme based on a rational approximation of golden angles (RAGA) is developed. METHODS The theoretical properties of RAGA sampling are mathematically derived. Sidelobe-to-peak ratios (SPR) are numerically computed and compared to the corresponding golden ratio sampling schemes. The sampling scheme is implemented in the BART toolbox and in a radial gradient-echo sequence. Feasibility is shown for quantitative imaging in a phantom and a cardiac scan of a healthy volunteer. RESULTS RAGA sampling can accurately approximate golden ratio sampling and has almost identical PSF and SPR. In contrast to golden ratio sampling, each frame can be reconstructed with the same equidistant trajectory using different sampling masks, and the angle of each acquired spoke can be encoded as a small index, which simplifies processing of the acquired data. CONCLUSION RAGA sampling provides the advantages of golden ratio sampling while simplifying data processing, rendering it a valuable tool for dynamic and quantitative MRI.
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Affiliation(s)
- Nick Scholand
- Institute of Biomedical Imaging, Graz University of Technology, Graz, Austria
- Center for Biomedical Imaging, Department of Radiology, NYU School of Medicine, New York, New York, USA
- German Centre for Cardiovascular Research (DZHK), partner site Lower Saxony, Göttingen, Germany
| | - Philip Schaten
- Institute of Biomedical Imaging, Graz University of Technology, Graz, Austria
| | - Christina Graf
- Institute of Biomedical Imaging, Graz University of Technology, Graz, Austria
- Department of Pediatrics, The University of British Columbia, Vancouver, British Columbia, Canada
- Department of Physics and Astronomy, The University of British Columbia, Vancouver, British Columbia, Canada
| | - Daniel Mackner
- Institute of Biomedical Imaging, Graz University of Technology, Graz, Austria
| | - H Christian M Holme
- Institute of Biomedical Imaging, Graz University of Technology, Graz, Austria
| | - Moritz Blumenthal
- Institute of Biomedical Imaging, Graz University of Technology, Graz, Austria
- Institute for Diagnostic and Interventional Radiology, University Medical Center Göttingen, Göttingen, Germany
| | - Andrew Mao
- Center for Biomedical Imaging, Department of Radiology, NYU School of Medicine, New York, New York, USA
- Center for Advanced Imaging Innovation and Research (CAI2R), Department of Radiology, New York University School of Medicine, New York, New York, USA
- Vilcek Institute of Graduate Biomedical Sciences, New York University School of Medicine, New York, New York, USA
| | - Jakob Assländer
- Center for Biomedical Imaging, Department of Radiology, NYU School of Medicine, New York, New York, USA
- Center for Advanced Imaging Innovation and Research (CAI2R), Department of Radiology, New York University School of Medicine, New York, New York, USA
| | - Martin Uecker
- Institute of Biomedical Imaging, Graz University of Technology, Graz, Austria
- German Centre for Cardiovascular Research (DZHK), partner site Lower Saxony, Göttingen, Germany
- Institute for Diagnostic and Interventional Radiology, University Medical Center Göttingen, Göttingen, Germany
- BioTechMed-Graz, Graz, Austria
- Cluster of Excellence "Multiscale Bioimaging: from Molecular Machines to Networks of Excitable Cells" (MBExC), University of Göttingen, Göttingen, Germany
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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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Zhang C, Piccini D, Demirel OB, Bonanno G, Roy CW, Yaman B, Moeller S, Shenoy C, Stuber M, Akçakaya M. Large-scale 3D non-Cartesian coronary MRI reconstruction using distributed memory-efficient physics-guided deep learning with limited training data. MAGMA (NEW YORK, N.Y.) 2024; 37:429-438. [PMID: 38743377 DOI: 10.1007/s10334-024-01157-8] [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: 10/10/2023] [Revised: 02/19/2024] [Accepted: 03/13/2024] [Indexed: 05/16/2024]
Abstract
OBJECT To enable high-quality physics-guided deep learning (PG-DL) reconstruction of large-scale 3D non-Cartesian coronary MRI by overcoming challenges of hardware limitations and limited training data availability. MATERIALS AND METHODS While PG-DL has emerged as a powerful image reconstruction method, its application to large-scale 3D non-Cartesian MRI is hindered by hardware limitations and limited availability of training data. We combine several recent advances in deep learning and MRI reconstruction to tackle the former challenge, and we further propose a 2.5D reconstruction using 2D convolutional neural networks, which treat 3D volumes as batches of 2D images to train the network with a limited amount of training data. Both 3D and 2.5D variants of the PG-DL networks were compared to conventional methods for high-resolution 3D kooshball coronary MRI. RESULTS Proposed PG-DL reconstructions of 3D non-Cartesian coronary MRI with 3D and 2.5D processing outperformed all conventional methods both quantitatively and qualitatively in terms of image assessment by an experienced cardiologist. The 2.5D variant further improved vessel sharpness compared to 3D processing, and scored higher in terms of qualitative image quality. DISCUSSION PG-DL reconstruction of large-scale 3D non-Cartesian MRI without compromising image size or network complexity is achieved, and the proposed 2.5D processing enables high-quality reconstruction with limited training data.
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Affiliation(s)
- Chi Zhang
- Electrical and Computer Engineering, University of Minnesota, 200 Union Street S.E., Minneapolis, MN, 55455, USA
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, USA
| | - Davide Piccini
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- Advanced Clinical Imaging Technology, Siemens Healthineers International, Lausanne, Switzerland
| | - Omer Burak Demirel
- Electrical and Computer Engineering, University of Minnesota, 200 Union Street S.E., Minneapolis, MN, 55455, USA
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, USA
| | - Gabriele Bonanno
- Advanced Clinical Imaging Technology, Siemens Healthineers International, Lausanne, Switzerland
| | - Christopher W Roy
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Burhaneddin Yaman
- Electrical and Computer Engineering, University of Minnesota, 200 Union Street S.E., Minneapolis, MN, 55455, USA
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, USA
| | - Steen Moeller
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, USA
| | - Chetan Shenoy
- Department of Medicine (Cardiology), University of Minnesota, Minneapolis, MN, 55455, USA
| | - Matthias Stuber
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- Center for Biomedical Imaging, Lausanne, Switzerland
| | - Mehmet Akçakaya
- Electrical and Computer Engineering, University of Minnesota, 200 Union Street S.E., Minneapolis, MN, 55455, USA.
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, USA.
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Zhou Z, Hu P, Qi H. Stop moving: MR motion correction as an opportunity for artificial intelligence. MAGMA (NEW YORK, N.Y.) 2024; 37:397-409. [PMID: 38386151 DOI: 10.1007/s10334-023-01144-5] [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: 09/28/2023] [Revised: 12/09/2023] [Accepted: 12/19/2023] [Indexed: 02/23/2024]
Abstract
Subject motion is a long-standing problem of magnetic resonance imaging (MRI), which can seriously deteriorate the image quality. Various prospective and retrospective methods have been proposed for MRI motion correction, among which deep learning approaches have achieved state-of-the-art motion correction performance. This survey paper aims to provide a comprehensive review of deep learning-based MRI motion correction methods. Neural networks used for motion artifacts reduction and motion estimation in the image domain or frequency domain are detailed. Furthermore, besides motion-corrected MRI reconstruction, how estimated motion is applied in other downstream tasks is briefly introduced, aiming to strengthen the interaction between different research areas. Finally, we identify current limitations and point out future directions of deep learning-based MRI motion correction.
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Affiliation(s)
- Zijian Zhou
- School of Biomedical Engineering, ShanghaiTech University, 4th Floor, BME Building, 393 Middle Huaxia Road, Pudong District, Shanghai, 201210, China
- Shanghai Clinical Research and Trial Center, ShanghaiTech University, Shanghai, China
| | - Peng Hu
- School of Biomedical Engineering, ShanghaiTech University, 4th Floor, BME Building, 393 Middle Huaxia Road, Pudong District, Shanghai, 201210, China.
- Shanghai Clinical Research and Trial Center, ShanghaiTech University, Shanghai, China.
| | - Haikun Qi
- School of Biomedical Engineering, ShanghaiTech University, 4th Floor, BME Building, 393 Middle Huaxia Road, Pudong District, Shanghai, 201210, China.
- Shanghai Clinical Research and Trial Center, ShanghaiTech University, Shanghai, China.
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5
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Aizaz M, van der Pol JAJ, Schneider A, Munoz C, Holtackers RJ, van Cauteren Y, van Langen H, Meeder JG, Rahel BM, Wierts R, Botnar RM, Prieto C, Moonen RPM, Kooi ME. Extended MRI-based PET motion correction for cardiac PET/MRI. EJNMMI Phys 2024; 11:36. [PMID: 38581561 PMCID: PMC10998820 DOI: 10.1186/s40658-024-00637-z] [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: 08/22/2023] [Accepted: 03/25/2024] [Indexed: 04/08/2024] Open
Abstract
PURPOSE A 2D image navigator (iNAV) based 3D whole-heart sequence has been used to perform MRI and PET non-rigid respiratory motion correction for hybrid PET/MRI. However, only the PET data acquired during the acquisition of the 3D whole-heart MRI is corrected for respiratory motion. This study introduces and evaluates an MRI-based respiratory motion correction method of the complete PET data. METHODS Twelve oncology patients scheduled for an additional cardiac 18F-Fluorodeoxyglucose (18F-FDG) PET/MRI and 15 patients with coronary artery disease (CAD) scheduled for cardiac 18F-Choline (18F-FCH) PET/MRI were included. A 2D iNAV recorded the respiratory motion of the myocardium during the 3D whole-heart coronary MR angiography (CMRA) acquisition (~ 10 min). A respiratory belt was used to record the respiratory motion throughout the entire PET/MRI examination (~ 30-90 min). The simultaneously acquired iNAV and respiratory belt signal were used to divide the acquired PET data into 4 bins. The binning was then extended for the complete respiratory belt signal. Data acquired at each bin was reconstructed and combined using iNAV-based motion fields to create a respiratory motion-corrected PET image. Motion-corrected (MC) and non-motion-corrected (NMC) datasets were compared. Gating was also performed to correct cardiac motion. The SUVmax and TBRmax values were calculated for the myocardial wall or a vulnerable coronary plaque for the 18F-FDG and 18F-FCH datasets, respectively. RESULTS A pair-wise comparison showed that the SUVmax and TBRmax values of the motion corrected (MC) datasets were significantly higher than those for the non-motion-corrected (NMC) datasets (8.2 ± 1.0 vs 7.5 ± 1.0, p < 0.01 and 1.9 ± 0.2 vs 1.2 ± 0.2, p < 0.01, respectively). In addition, the SUVmax and TBRmax of the motion corrected and gated (MC_G) reconstructions were also higher than that of the non-motion-corrected but gated (NMC_G) datasets, although for the TBRmax this difference was not statistically significant (9.6 ± 1.3 vs 9.1 ± 1.2, p = 0.02 and 2.6 ± 0.3 vs 2.4 ± 0.3, p = 0.16, respectively). The respiratory motion-correction did not lead to a change in the signal to noise ratio. CONCLUSION The proposed respiratory motion correction method for hybrid PET/MRI improved the image quality of cardiovascular PET scans by increased SUVmax and TBRmax values while maintaining the signal-to-noise ratio. Trial registration METC162043 registered 01/03/2017.
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Affiliation(s)
- Mueez Aizaz
- CARIM, Cardiovascular Research Institute Maastricht, Maastricht University, Maastricht, The Netherlands
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Center+, Maastricht, The Netherlands
| | - Jochem A J van der Pol
- CARIM, Cardiovascular Research Institute Maastricht, Maastricht University, Maastricht, The Netherlands
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Center+, Maastricht, The Netherlands
| | - Alina Schneider
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Camila Munoz
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Robert J Holtackers
- CARIM, Cardiovascular Research Institute Maastricht, Maastricht University, Maastricht, The Netherlands
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Center+, Maastricht, The Netherlands
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Yvonne van Cauteren
- CARIM, Cardiovascular Research Institute Maastricht, Maastricht University, Maastricht, The Netherlands
- Department of Cardiology, VieCuri Medical Centre, Venlo, The Netherlands
| | - Herman van Langen
- Department of Medical Physics and Devices, VieCuri Medical Centre, Venlo, The Netherlands
| | - Joan G Meeder
- Department of Cardiology, VieCuri Medical Centre, Venlo, The Netherlands
| | - Braim M Rahel
- Department of Cardiology, VieCuri Medical Centre, Venlo, The Netherlands
| | - Roel Wierts
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Center+, Maastricht, The Netherlands
| | - René M Botnar
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
- Escuela de Ingeniería, Pontificia Universidad Católica de Chile, Santiago, Chile
- Millenium Institute for Intelligent Healthcare Engineering iHEALTH, Santiago, Chile
- Instituto de Ingeniería Biológica y Médica, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Claudia Prieto
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
- Escuela de Ingeniería, Pontificia Universidad Católica de Chile, Santiago, Chile
- Millenium Institute for Intelligent Healthcare Engineering iHEALTH, Santiago, Chile
| | - Rik P M Moonen
- CARIM, Cardiovascular Research Institute Maastricht, Maastricht University, Maastricht, The Netherlands
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Center+, Maastricht, The Netherlands
| | - M Eline Kooi
- CARIM, Cardiovascular Research Institute Maastricht, Maastricht University, Maastricht, The Netherlands.
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Center+, Maastricht, The Netherlands.
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Falcão MBL, Mackowiak ALC, Rossi GMC, Prša M, Tenisch E, Rumac S, Bacher M, Rutz T, van Heeswijk RB, Speier P, Markl M, Bastiaansen JAM, Stuber M, Roy CW. Combined free-running four-dimensional anatomical and flow magnetic resonance imaging with native contrast using Synchronization of Neighboring Acquisitions by Physiological Signals. J Cardiovasc Magn Reson 2024; 26:101006. [PMID: 38309581 PMCID: PMC11211232 DOI: 10.1016/j.jocmr.2024.101006] [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: 12/06/2023] [Accepted: 01/25/2024] [Indexed: 02/05/2024] Open
Abstract
BACKGROUND Four-dimensional (4D) flow magnetic resonance imaging (MRI) often relies on the injection of gadolinium- or iron-oxide-based contrast agents to improve vessel delineation. In this work, a novel technique is developed to acquire and reconstruct 4D flow data with excellent dynamic visualization of blood vessels but without the need for contrast injection. Synchronization of Neighboring Acquisitions by Physiological Signals (SyNAPS) uses pilot tone (PT) navigation to retrospectively synchronize the reconstruction of two free-running three-dimensional radial acquisitions, to create co-registered anatomy and flow images. METHODS Thirteen volunteers and two Marfan syndrome patients were scanned without contrast agent using one free-running fast interrupted steady-state (FISS) sequence and one free-running phase-contrast MRI (PC-MRI) sequence. PT signals spanning the two sequences were recorded for retrospective respiratory motion correction and cardiac binning. The magnitude and phase images reconstructed, respectively, from FISS and PC-MRI, were synchronized to create SyNAPS 4D flow datasets. Conventional two-dimensional (2D) flow data were acquired for reference in ascending (AAo) and descending aorta (DAo). The blood-to-myocardium contrast ratio, dynamic vessel area, net volume, and peak flow were used to compare SyNAPS 4D flow with Native 4D flow (without FISS information) and 2D flow. A score of 0-4 was given to each dataset by two blinded experts regarding the feasibility of performing vessel delineation. RESULTS Blood-to-myocardium contrast ratio for SyNAPS 4D flow magnitude images (1.5 ± 0.3) was significantly higher than for Native 4D flow (0.7 ± 0.1, p < 0.01) and was comparable to 2D flow (2.3 ± 0.9, p = 0.02). Image quality scores of SyNAPS 4D flow from the experts (M.P.: 1.9 ± 0.3, E.T.: 2.5 ± 0.5) were overall significantly higher than the scores from Native 4D flow (M.P.: 1.6 ± 0.6, p = 0.03, E.T.: 0.8 ± 0.4, p < 0.01) but still significantly lower than the scores from the reference 2D flow datasets (M.P.: 2.8 ± 0.4, p < 0.01, E.T.: 3.5 ± 0.7, p < 0.01). The Pearson correlation coefficient between the dynamic vessel area measured on SyNAPS 4D flow and that from 2D flow was 0.69 ± 0.24 for the AAo and 0.83 ± 0.10 for the DAo, whereas the Pearson correlation between Native 4D flow and 2D flow measurements was 0.12 ± 0.48 for the AAo and 0.08 ± 0.39 for the DAo. Linear correlations between SyNAPS 4D flow and 2D flow measurements of net volume (r2 = 0.83) and peak flow (r2 = 0.87) were larger than the correlations between Native 4D flow and 2D flow measurements of net volume (r2 = 0.79) and peak flow (r2 = 0.76). CONCLUSION The feasibility and utility of SyNAPS were demonstrated for joint whole-heart anatomical and flow MRI without requiring electrocardiography gating, respiratory navigators, or contrast agents. Using SyNAPS, a high-contrast anatomical imaging sequence can be used to improve 4D flow measurements that often suffer from poor delineation of vessel boundaries in the absence of contrast agents.
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Affiliation(s)
- Mariana B L Falcão
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Adèle L C Mackowiak
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland; Department of Diagnostic, Interventional and Pediatric Radiology (DIPR), Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland; Translation Imaging Center (TIC), Swiss Institute for Translational and Entrepreneurial Medicine, Bern, Switzerland
| | - Giulia M C Rossi
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Milan Prša
- Woman, Mother, Child Department, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Estelle Tenisch
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Simone Rumac
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Mario Bacher
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland; Siemens Healthcare GmbH, Erlangen, Germany
| | - Tobias Rutz
- Service of Cardiology, Centre de Resonance Magnétique Cardiaque (CRMC), Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Ruud B van Heeswijk
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | | | - Michael Markl
- Department of Radiology, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA; Department of Biomedical Engineering, Northwestern University, Chicago, Illinois, USA
| | - Jessica A M Bastiaansen
- Department of Diagnostic, Interventional and Pediatric Radiology (DIPR), Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland; Translation Imaging Center (TIC), Swiss Institute for Translational and Entrepreneurial Medicine, Bern, Switzerland
| | - Matthias Stuber
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland; Center for Biomedical Imaging (CIBM), Lausanne, Switzerland
| | - Christopher W Roy
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland.
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Pan Y, Varghese J, Tong MS, Yildiz VO, Azzu A, Gatehouse P, Wage R, Nielles-Vallespin S, Pennell DJ, Jin N, Bacher M, Hayes C, Speier P, Simonetti OP. Two-center validation of Pilot Tone based cardiac triggering of a comprehensive cardiovascular magnetic resonance examination. THE INTERNATIONAL JOURNAL OF CARDIOVASCULAR IMAGING 2024; 40:261-273. [PMID: 38082073 DOI: 10.1007/s10554-023-03002-w] [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: 06/28/2023] [Accepted: 10/31/2023] [Indexed: 12/26/2023]
Abstract
The electrocardiogram (ECG) signal is prone to distortions from gradient and radiofrequency interference and the magnetohydrodynamic effect during cardiovascular magnetic resonance imaging (CMR). Although Pilot Tone Cardiac (PTC) triggering has the potential to overcome these limitations, effectiveness across various CMR techniques has yet to be established. To evaluate the performance of PTC triggering in a comprehensive CMR exam. Fifteen volunteers and 20 patients were recruited at two centers. ECG triggered images were collected for comparison in a subset of sequences. The PTC trigger accuracy was evaluated against ECG in cine acquisitions. Two experienced readers scored image quality in PTC-triggered cine, late gadolinium enhancement (LGE), and T1- and T2-weighted dark-blood turbo spin echo (DB-TSE) images. Quantitative cardiac function, flow, and parametric mapping values obtained using PTC and ECG triggered sequences were compared. Breath-held segmented cine used for trigger timing analysis was collected in 15 volunteers and 14 patients. PTC calibration failed in three volunteers and one patient; ECG trigger recording failed in one patient. Out of 1987 total heartbeats, three mismatched trigger PTC-ECG pairs were found. Image quality scores showed no significant difference between PTC and ECG triggering. There was no significant difference found in quantitative measurements in volunteers. In patients, the only significant difference was found in post-contrast T1 (p = 0.04). ICC showed moderate to excellent agreement in all measurements. PTC performance was equivalent to ECG in terms of triggering consistency, image quality, and quantitative image measurements across multiple CMR applications.
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Affiliation(s)
- Yue Pan
- Department of Biomedical Engineering, The Ohio State University, Columbus, OH, USA
- Dorothy M. Davis Heart and Lung Research Institute, The Ohio State University Wexner Medical Center, Columbus, OH, USA
| | - Juliet Varghese
- Department of Biomedical Engineering, The Ohio State University, Columbus, OH, USA
- Dorothy M. Davis Heart and Lung Research Institute, The Ohio State University Wexner Medical Center, Columbus, OH, USA
| | - Matthew S Tong
- Department of Internal Medicine, Division of Cardiovascular Medicine, The Ohio State University Wexner Medical Center, Columbus, OH, USA
| | - Vedat O Yildiz
- Center for Biostatistics, Department of Biomedical Informatics, The Ohio State University College of Medicine, Columbus, OH, USA
| | - Alessia Azzu
- Cardiovascular Magnetic Resonance Unit, Royal Brompton Hospital, London, UK
| | - Peter Gatehouse
- Cardiovascular Magnetic Resonance Unit, Royal Brompton Hospital, London, UK
| | - Rick Wage
- Cardiovascular Magnetic Resonance Unit, Royal Brompton Hospital, London, UK
| | | | - Dudley J Pennell
- Cardiovascular Magnetic Resonance Unit, Royal Brompton Hospital, London, UK
| | - Ning Jin
- Cardiovascular MR R&D, Siemens Medical Solutions USA, Malvern, PA, USA
| | - Mario Bacher
- Siemens Healthineers AG, Erlangen, Germany
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | | | | | - Orlando P Simonetti
- Department of Biomedical Engineering, The Ohio State University, Columbus, OH, USA.
- Dorothy M. Davis Heart and Lung Research Institute, The Ohio State University Wexner Medical Center, Columbus, OH, USA.
- Department of Internal Medicine, Division of Cardiovascular Medicine, The Ohio State University Wexner Medical Center, Columbus, OH, USA.
- Department of Radiology, The Ohio State University Wexner Medical Center, Columbus, OH, USA.
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8
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Wang J, Awad M, Zhou R, Wang Z, Wang X, Feng X, Yang Y, Meyer C, Kramer CM, Salerno M. High-resolution spiral real-time cardiac cine imaging with deep learning-based rapid image reconstruction and quantification. NMR IN BIOMEDICINE 2024; 37:e5051. [PMID: 37926525 DOI: 10.1002/nbm.5051] [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: 02/15/2023] [Revised: 08/20/2023] [Accepted: 09/08/2023] [Indexed: 11/07/2023]
Abstract
The objective of the current study was to develop and evaluate a DEep learning-based rapid Spiral Image REconstruction (DESIRE) and deep learning (DL)-based segmentation approach to quantify the left ventricular ejection fraction (LVEF) for high-resolution spiral real-time cine imaging, including 2D balanced steady-state free precession imaging at 1.5 T and gradient echo (GRE) imaging at 1.5 and 3 T. A 3D U-Net-based image reconstruction network and 2D U-Net-based image segmentation network were proposed and evaluated. Low-rank plus sparse (L+S) served as the reference for the image reconstruction network and manual contouring of the left ventricle was the reference of the segmentation network. To assess the image reconstruction quality, structural similarity index, peak signal-to-noise ratio, normalized root-mean-square error, and blind grading by two experienced cardiologists (5: excellent; 1: poor) were performed. To assess the segmentation performance, quantification of the LVEF on GRE imaging at 3 T was compared with the quantification from manual contouring. Excellent performance was demonstrated by the proposed technique. In terms of image quality, there was no difference between L+S and the proposed DESIRE technique. For quantification analysis, the proposed DL method was not different to the manual segmentation method (p > 0.05) in terms of quantification of LVEF. The reconstruction time for DESIRE was ~32 s (including nonuniform fast Fourier transform [NUFFT]) per dynamic series (40 frames), while the reconstruction time of L+S with GPU acceleration was approximately 3 min. The DL segmentation takes less than 5 s. In conclusion, the proposed DL-based image reconstruction and quantification techniques enabled 1-min image reconstruction for the whole heart and quantification with automatic reconstruction and quantification of the left ventricle function for high-resolution spiral real-time cine imaging with excellent performance.
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Affiliation(s)
- Junyu Wang
- Department of Medicine, Cardiovascular Medicine, Stanford University, Stanford, California, USA
| | - Marina Awad
- Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, USA
| | - Ruixi Zhou
- School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China
| | - Zhixing Wang
- Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, USA
- Department of Radiation Oncology, City of Hope, Duarte, California, USA
| | - Xitong Wang
- Department of Bioengineering, Stanford University, Stanford, California, USA
| | - Xue Feng
- Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, USA
| | - Yang Yang
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
| | - Craig Meyer
- Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, USA
| | - Christopher M Kramer
- Department of Medicine, Division of Cardiovascular, University of Virginia Health System, Charlottesville, Virginia, USA
- Department of Radiology and Medical Imaging, University of Virginia Health System, Charlottesville, Virginia, USA
| | - Michael Salerno
- Department of Medicine, Cardiovascular Medicine, Stanford University, Stanford, California, USA
- Department of Radiology, Cardiovascular Imaging, Stanford University, Stanford, California, USA
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9
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Kadalie E, Trotier AJ, Corbin N, Miraux S, Ribot EJ. Rapid whole brain 3D T 2 mapping respiratory-resolved Double-Echo Steady State (DESS) sequence with improved repeatability. Magn Reson Med 2024; 91:221-236. [PMID: 37794821 DOI: 10.1002/mrm.29847] [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: 03/03/2023] [Revised: 08/11/2023] [Accepted: 08/11/2023] [Indexed: 10/06/2023]
Abstract
PURPOSE To propose a quantitative 3D double-echo steady-state (DESS) sequence that offers rapid and repeatable T2 mapping of the human brain using different encoding schemes that account for respiratory B0 variation. METHODS A retrospective self-gating module was firstly implemented into the standard DESS sequence in order to suppress the respiratory artifact via data binning. A compressed-sensing trajectory (CS-DESS) was then optimized to accelerate the acquisition. Finally, a spiral Cartesian encoding (SPICCS-DESS) was incorporated to further disrupt the coherent respiratory artifact. These different versions were compared to a standard DESS sequence (fully DESS) by assessing the T2 distribution and repeatability in different brain regions of eight volunteers at 3 T. RESULTS The respiratory artifact correction was determined to be optimal when the data was binned into seven respiratory phases. Compared to the fully DESS, T2 distribution was improved for the CS-DESS and SPICCS-DESS with interquartile ranges reduced significantly by a factor ranging from 2 to 12 in the caudate, putamen, and thalamus regions. In the gray and white matter areas, average absolute test-retest T2 differences across all volunteers were respectively 3.5 ± 2% and 3.1 ± 2.1% for the SPICCS-DESS, 4.6 ± 4.6% and 4.9 ± 5.1% for the CS-DESS, and 15% ± 13% and 7.3 ± 5.6% for the fully DESS. The SPICCS-DESS sequence's acquisition time could be reduced by half (<4 min) while maintaining its efficient T2 mapping. CONCLUSION The respiratory-resolved SPICCS-DESS sequence offers rapid, robust, and repeatable 3D T2 mapping of the human brain, which can be especially effective for longitudinal monitoring of cerebral pathologies.
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Affiliation(s)
- Emile Kadalie
- Univ. Bordeaux, CNRS, Centre de Résonance Magnétique des Systèmes Biologiques (CRMSB), UMR 5536, F-33000, Bordeaux, France
| | - Aurélien J Trotier
- Univ. Bordeaux, CNRS, Centre de Résonance Magnétique des Systèmes Biologiques (CRMSB), UMR 5536, F-33000, Bordeaux, France
| | - Nadège Corbin
- Univ. Bordeaux, CNRS, Centre de Résonance Magnétique des Systèmes Biologiques (CRMSB), UMR 5536, F-33000, Bordeaux, France
| | - Sylvain Miraux
- Univ. Bordeaux, CNRS, Centre de Résonance Magnétique des Systèmes Biologiques (CRMSB), UMR 5536, F-33000, Bordeaux, France
| | - Emeline J Ribot
- Univ. Bordeaux, CNRS, Centre de Résonance Magnétique des Systèmes Biologiques (CRMSB), UMR 5536, F-33000, Bordeaux, France
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10
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McGrath C, Bieri O, Kozerke S, Bauman G. Self-gated cine phase-contrast balanced SSFP flow quantification at 0.55 T. Magn Reson Med 2024; 91:174-189. [PMID: 37668108 DOI: 10.1002/mrm.29837] [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: 03/23/2023] [Revised: 07/13/2023] [Accepted: 08/02/2023] [Indexed: 09/06/2023]
Abstract
PURPOSE To implement cine phase-contrast balanced SSFP (PC-bSSFP) for low-field 0.55T cardiac MRI by exploiting the intrinsic flow sensitivity of the bSSFP slice-select gradient and the in-plane phase-cancelation properties of radial trajectories, enabling self-gated and referenceless PC-bSSFP flow quantification at 0.55 T. METHODS A free-running, tiny golden-angle radial PC-bSSFP approach was implemented on 0.55T and 1.5T systems. Cardiac and respiratory self-gating was incorporated to enable electrocardiogram-free scanning during breath-hold and free-breathing. By exploiting the intrinsic in-plane phase-cancelation properties of radial acquisitions and background phase fitting, referenceless single-point PC-bSSFP was realized. In vivo data were acquired in the ascending aorta of healthy subjects at 0.55 T and 1.5 T during breath-hold and free-breathing. Flow data, SNR, and velocity-to-noise ratio were compared relative to data obtained with phase-contrast spoiled gradient-echo variants. RESULTS Velocities acquired with PC-bSSFP compared well with data from phase-contrast spoiled gradient-echo (RMSEv = 5.8 cm/s). PC-bSSFP at 0.55 T resulted in high-quality cine magnitude images and phase maps with sufficient SNR and velocity-to-noise ratio. Breath-hold and free-breathing PC-bSSFP performed very similarly, with comparable flow quantification (RMSEv = 5.7 cm/s). Referenceless single-point PC-bSSFP results agreed well with two-point PC-bSSFP (-1.8 ± 5.2 cm/s) while reducing scan times 2-fold. CONCLUSION PC-bSSFP is feasible on low-field 0.55T systems, producing high-quality cine images while permitting simultaneous aortic flow measurements during breath-hold and free-breathing and without the need for electrocardiogram gating.
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Affiliation(s)
- Charles McGrath
- Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland
| | - Oliver Bieri
- Division of Radiological Physics, Department of Radiology, University Hospital Basel, Basel, Switzerland
- Department of Biomedical Engineering, University of Basel, Basel, Switzerland
| | - Sebastian Kozerke
- Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland
| | - Grzegorz Bauman
- Division of Radiological Physics, Department of Radiology, University Hospital Basel, Basel, Switzerland
- Department of Biomedical Engineering, University of Basel, Basel, Switzerland
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11
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Gast LV, Platt T, Nagel AM, Gerhalter T. Recent technical developments and clinical research applications of sodium ( 23Na) MRI. PROGRESS IN NUCLEAR MAGNETIC RESONANCE SPECTROSCOPY 2023; 138-139:1-51. [PMID: 38065665 DOI: 10.1016/j.pnmrs.2023.04.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/27/2023] [Revised: 04/11/2023] [Accepted: 04/13/2023] [Indexed: 12/18/2023]
Abstract
Sodium is an essential ion that plays a central role in many physiological processes including the transmembrane electrochemical gradient and the maintenance of the body's homeostasis. Due to the crucial role of sodium in the human body, the sodium nucleus is a promising candidate for non-invasively assessing (patho-)physiological changes. Almost 10 years ago, Madelin et al. provided a comprehensive review of methods and applications of sodium (23Na) MRI (Madelin et al., 2014) [1]. More recent review articles have focused mainly on specific applications of 23Na MRI. For example, several articles covered 23Na MRI applications for diseases such as osteoarthritis (Zbyn et al., 2016, Zaric et al., 2020) [2,3], multiple sclerosis (Petracca et al., 2016, Huhn et al., 2019) [4,5] and brain tumors (Schepkin, 2016) [6], or for imaging certain organs such as the kidneys (Zollner et al., 2016) [7], the brain (Shah et al., 2016, Thulborn et al., 2018) [8,9], and the heart (Bottomley, 2016) [10]. Other articles have reviewed technical developments such as radiofrequency (RF) coils for 23Na MRI (Wiggins et al., 2016, Bangerter et al., 2016) [11,12], pulse sequences (Konstandin et al., 2014) [13], image reconstruction methods (Chen et al., 2021) [14], and interleaved/simultaneous imaging techniques (Lopez Kolkovsky et al., 2022) [15]. In addition, 23Na MRI topics have been covered in review articles with broader topics such as multinuclear MRI or ultra-high-field MRI (Niesporek et al., 2019, Hu et al., 2019, Ladd et al., 2018) [16-18]. During the past decade, various research groups have continued working on technical improvements to sodium MRI and have investigated its potential to serve as a diagnostic and prognostic tool. Clinical research applications of 23Na MRI have covered a broad spectrum of diseases, mainly focusing on the brain, cartilage, and skeletal muscle (see Fig. 1). In this article, we aim to provide a comprehensive summary of methodological and hardware developments, as well as a review of various clinical research applications of sodium (23Na) MRI in the last decade (i.e., published from the beginning of 2013 to the end of 2022).
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Affiliation(s)
- Lena V Gast
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany.
| | - Tanja Platt
- Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany.
| | - Armin M Nagel
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany; Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany.
| | - Teresa Gerhalter
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany.
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12
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Li X, Wu F, Günther S, Looso M, Kuenne C, Zhang T, Wiesnet M, Klatt S, Zukunft S, Fleming I, Poschet G, Wietelmann A, Atzberger A, Potente M, Yuan X, Braun T. Inhibition of fatty acid oxidation enables heart regeneration in adult mice. Nature 2023; 622:619-626. [PMID: 37758950 PMCID: PMC10584682 DOI: 10.1038/s41586-023-06585-5] [Citation(s) in RCA: 37] [Impact Index Per Article: 37.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2021] [Accepted: 08/30/2023] [Indexed: 09/29/2023]
Abstract
Postnatal maturation of cardiomyocytes is characterized by a metabolic switch from glycolysis to fatty acid oxidation, chromatin reconfiguration and exit from the cell cycle, instating a barrier for adult heart regeneration1,2. Here, to explore whether metabolic reprogramming can overcome this barrier and enable heart regeneration, we abrogate fatty acid oxidation in cardiomyocytes by inactivation of Cpt1b. We find that disablement of fatty acid oxidation in cardiomyocytes improves resistance to hypoxia and stimulates cardiomyocyte proliferation, allowing heart regeneration after ischaemia-reperfusion injury. Metabolic studies reveal profound changes in energy metabolism and accumulation of α-ketoglutarate in Cpt1b-mutant cardiomyocytes, leading to activation of the α-ketoglutarate-dependent lysine demethylase KDM5 (ref. 3). Activated KDM5 demethylates broad H3K4me3 domains in genes that drive cardiomyocyte maturation, lowering their transcription levels and shifting cardiomyocytes into a less mature state, thereby promoting proliferation. We conclude that metabolic maturation shapes the epigenetic landscape of cardiomyocytes, creating a roadblock for further cell divisions. Reversal of this process allows repair of damaged hearts.
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Affiliation(s)
- Xiang Li
- Department of Cardiac Development and Remodeling, Max Planck Institute for Heart and Lung Research, Bad Nauheim, Germany
| | - Fan Wu
- Department of Cardiac Development and Remodeling, Max Planck Institute for Heart and Lung Research, Bad Nauheim, Germany
| | - Stefan Günther
- Department of Cardiac Development and Remodeling, Max Planck Institute for Heart and Lung Research, Bad Nauheim, Germany
| | - Mario Looso
- Department of Cardiac Development and Remodeling, Max Planck Institute for Heart and Lung Research, Bad Nauheim, Germany
| | - Carsten Kuenne
- Department of Cardiac Development and Remodeling, Max Planck Institute for Heart and Lung Research, Bad Nauheim, Germany
| | - Ting Zhang
- Department of Cardiac Development and Remodeling, Max Planck Institute for Heart and Lung Research, Bad Nauheim, Germany
| | - Marion Wiesnet
- Department of Cardiac Development and Remodeling, Max Planck Institute for Heart and Lung Research, Bad Nauheim, Germany
| | - Stephan Klatt
- Institute for Vascular Signaling, Centre for Molecular Medicine, Goethe-University, Frankfurt am Main, Germany
| | - Sven Zukunft
- Institute for Vascular Signaling, Centre for Molecular Medicine, Goethe-University, Frankfurt am Main, Germany
| | - Ingrid Fleming
- Institute for Vascular Signaling, Centre for Molecular Medicine, Goethe-University, Frankfurt am Main, Germany
| | - Gernot Poschet
- Metabolomics Core Technology Platform, Centre for Organismal Studies (COS), Heidelberg University, Heidelberg, Germany
| | - Astrid Wietelmann
- Department of Cardiac Development and Remodeling, Max Planck Institute for Heart and Lung Research, Bad Nauheim, Germany
| | - Ann Atzberger
- Department of Cardiac Development and Remodeling, Max Planck Institute for Heart and Lung Research, Bad Nauheim, Germany
| | - Michael Potente
- Angiogenesis and Metabolism Laboratory, Max Planck Institute for Heart and Lung Research, Bad Nauheim, Germany
- Max Delbrück Center for Molecular Medicine, Helmholtz Association of German Research Centres, Berlin, Germany
- Berlin Institute of Health, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Xuejun Yuan
- Department of Cardiac Development and Remodeling, Max Planck Institute for Heart and Lung Research, Bad Nauheim, Germany.
- Instituto de Investigacion en Biomedicina de Buenos Aires (IBioBA) - CONICET - Partner Institute of the Max Planck Society, Buenos Aires, Argentina.
| | - Thomas Braun
- Department of Cardiac Development and Remodeling, Max Planck Institute for Heart and Lung Research, Bad Nauheim, Germany.
- Instituto de Investigacion en Biomedicina de Buenos Aires (IBioBA) - CONICET - Partner Institute of the Max Planck Society, Buenos Aires, Argentina.
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13
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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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14
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Bissell MM, Raimondi F, Ait Ali L, Allen BD, Barker AJ, Bolger A, Burris N, Carhäll CJ, Collins JD, Ebbers T, Francois CJ, Frydrychowicz A, Garg P, Geiger J, Ha H, Hennemuth A, Hope MD, Hsiao A, Johnson K, Kozerke S, Ma LE, Markl M, Martins D, Messina M, Oechtering TH, van Ooij P, Rigsby C, Rodriguez-Palomares J, Roest AAW, Roldán-Alzate A, Schnell S, Sotelo J, Stuber M, Syed AB, Töger J, van der Geest R, Westenberg J, Zhong L, Zhong Y, Wieben O, Dyverfeldt P. 4D Flow cardiovascular magnetic resonance consensus statement: 2023 update. J Cardiovasc Magn Reson 2023; 25:40. [PMID: 37474977 PMCID: PMC10357639 DOI: 10.1186/s12968-023-00942-z] [Citation(s) in RCA: 42] [Impact Index Per Article: 42.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Accepted: 05/30/2023] [Indexed: 07/22/2023] Open
Abstract
Hemodynamic assessment is an integral part of the diagnosis and management of cardiovascular disease. Four-dimensional cardiovascular magnetic resonance flow imaging (4D Flow CMR) allows comprehensive and accurate assessment of flow in a single acquisition. This consensus paper is an update from the 2015 '4D Flow CMR Consensus Statement'. We elaborate on 4D Flow CMR sequence options and imaging considerations. The document aims to assist centers starting out with 4D Flow CMR of the heart and great vessels with advice on acquisition parameters, post-processing workflows and integration into clinical practice. Furthermore, we define minimum quality assurance and validation standards for clinical centers. We also address the challenges faced in quality assurance and validation in the research setting. We also include a checklist for recommended publication standards, specifically for 4D Flow CMR. Finally, we discuss the current limitations and the future of 4D Flow CMR. This updated consensus paper will further facilitate widespread adoption of 4D Flow CMR in the clinical workflow across the globe and aid consistently high-quality publication standards.
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Affiliation(s)
- Malenka M Bissell
- Department of Biomedical Imaging Science, Leeds Institute of Cardiovascular and Metabolic Medicine (LICAMM), LIGHT Laboratories, Clarendon Way, University of Leeds, Leeds, LS2 9NL, UK.
| | | | - Lamia Ait Ali
- Institute of Clinical Physiology CNR, Massa, Italy
- Foundation CNR Tuscany Region G. Monasterio, Massa, Italy
| | - Bradley D Allen
- Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Alex J Barker
- Department of Radiology, Children's Hospital Colorado, University of Colorado Anschutz Medical Center, Aurora, USA
| | - Ann Bolger
- Department of Medicine, University of California, San Francisco, CA, USA
- Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden
| | - Nicholas Burris
- Department of Radiology, University of Michigan, Ann Arbor, USA
| | - Carl-Johan Carhäll
- Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden
- Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden
| | | | - Tino Ebbers
- Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden
- Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden
| | | | - Alex Frydrychowicz
- Department of Radiology and Nuclear Medicine, University Hospital Schleswig-Holstein, Campus Lübeck and Universität Zu Lübeck, Lübeck, Germany
| | - Pankaj Garg
- Norwich Medical School, University of East Anglia, Norwich, UK
| | - Julia Geiger
- Department of Diagnostic Imaging, University Children's Hospital, Zurich, Switzerland
- Children's Research Center, University Children's Hospital Zurich, Zurich, Switzerland
| | - Hojin Ha
- Department of Mechanical and Biomedical Engineering, Kangwon National University, Chuncheon, South Korea
| | - Anja Hennemuth
- Institute of Computer-Assisted Cardiovascular Medicine, Charité - Universitätsmedizin, Berlin, Germany
- German Center for Cardiovascular Research (DZHK), Partner Site, Berlin, Germany
- Department of Diagnostic and Interventional Radiology and Nuclear Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Michael D Hope
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA
| | - Albert Hsiao
- Department of Radiology, University of California, San Diego, CA, USA
| | - Kevin Johnson
- Departments of Radiology and Medical Physics, University of Wisconsin, Madison, WI, USA
| | - Sebastian Kozerke
- Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland
| | - Liliana E Ma
- Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Michael Markl
- Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Duarte Martins
- Department of Pediatric Cardiology, Hospital de Santa Cruz, Centro Hospitalar Lisboa Ocidental, Lisbon, Portugal
| | - Marci Messina
- Department of Radiology, Northwestern Medicine, Chicago, IL, USA
| | - Thekla H Oechtering
- Department of Radiology and Nuclear Medicine, University Hospital Schleswig-Holstein, Campus Lübeck and Universität Zu Lübeck, Lübeck, Germany
- Departments of Radiology and Medical Physics, University of Wisconsin, Madison, WI, USA
| | - Pim van Ooij
- Department of Radiology & Nuclear Medicine, Amsterdam Cardiovascular Sciences, Amsterdam Movement Sciences, Amsterdam University Medical Centers, Location AMC, Amsterdam, The Netherlands
- Department of Pediatric Cardiology, Division of Pediatrics, Wilhelmina Children's Hospital, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Cynthia Rigsby
- Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
- Department of Medical Imaging, Ann & Robert H Lurie Children's Hospital of Chicago, Chicago, IL, USA
| | - Jose Rodriguez-Palomares
- Department of Cardiology, Hospital Universitari Vall d´Hebron,Vall d'Hebron Institut de Recerca (VHIR), Universitat Autònoma de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica en Red-CV, CIBER CV, Madrid, Spain
| | - Arno A W Roest
- Department of Pediatric Cardiology, Willem-Alexander's Children Hospital, Leiden University Medical Center and Center for Congenital Heart Defects Amsterdam-Leiden, Leiden, The Netherlands
| | | | - Susanne Schnell
- Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
- Department of Medical Physics, Institute of Physics, University of Greifswald, Greifswald, Germany
| | - Julio Sotelo
- School of Biomedical Engineering, Universidad de Valparaíso, Valparaíso, Chile
- Biomedical Imaging Center, Pontificia Universidad Catolica de Chile, Santiago, Chile
- Millennium Institute for Intelligent Healthcare Engineering - iHEALTH, Santiago, Chile
| | - Matthias Stuber
- Département de Radiologie Médicale, Centre Hospitalier Universitaire Vaudois, Lausanne, Switzerland
| | - Ali B Syed
- Department of Radiology, Stanford University, Stanford, CA, USA
| | - Johannes Töger
- Clinical Physiology, Department of Clinical Sciences Lund, Lund University, Skåne University Hospital, Lund, Sweden
| | - Rob van der Geest
- Division of Image Processing, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Jos Westenberg
- CardioVascular Imaging Group (CVIG), Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Liang Zhong
- National Heart Centre Singapore, Duke-NUS Medical School, National University of Singapore, Singapore, Singapore
| | - Yumin Zhong
- Department of Radiology, School of Medicine, Shanghai Children's Medical Center Affiliated With Shanghai Jiao Tong University, Shanghai, People's Republic of China
| | - Oliver Wieben
- Departments of Radiology and Medical Physics, University of Wisconsin, Madison, WI, USA
| | - Petter Dyverfeldt
- Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden
- Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden
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15
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Pan Y, Varghese J, Tong MS, Yildiz VO, Azzu A, Gatehouse P, Wage R, Nielles-Vallespin S, Pennell D, Jin N, Bacher M, Hayes C, Speier P, Simonetti OP. Two-center validation of Pilot Tone Based Cardiac Triggering of a Comprehensive Cardiovascular Magnetic Resonance Examination. RESEARCH SQUARE 2023:rs.3.rs-3121723. [PMID: 37461505 PMCID: PMC10350216 DOI: 10.21203/rs.3.rs-3121723/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/28/2023]
Abstract
Background The electrocardiogram (ECG) signal is prone to distortions from gradient and radiofrequency interference and the magnetohydrodynamic effect during cardiovascular magnetic resonance imaging (CMR). Although Pilot Tone Cardiac (PTC) triggering has the potential to overcome these limitations, effectiveness across various CMR techniques has yet to be established. Purpose To evaluate the performance of PTC triggering in a comprehensive CMR exam. Methods Fifteen volunteers and twenty patients were recruited at two centers. ECG triggered images were collected for comparison in a subset of sequences. The PTC trigger accuracy was evaluated against ECG in cine acquisitions. Two experienced readers scored image quality in PTC-triggered cine, late gadolinium enhancement (LGE), and T1- and T2-weighted dark-blood turbo spin echo (DB-TSE) images. Quantitative cardiac function, flow, and parametric mapping values obtained using PTC and ECG triggered sequences were compared. Results Breath-held segmented cine used for trigger timing analysis was collected in 15 volunteers and 14 patients. PTC calibration failed in three volunteers and one patient; ECG trigger recording failed in one patient. Out of 1987 total heartbeats, three mismatched trigger PTC-ECG pairs were found. Image quality scores showed no significant difference between PTC and ECG triggering. There was no significant difference found in quantitative measurements in volunteers. In patients, the only significant difference was found in post-contrast T1 (p = 0.04). ICC showed moderate to excellent agreement in all measurements. Conclusion PTC performance was equivalent to ECG in terms of triggering consistency, image quality, and quantitative image measurements across multiple CMR applications.
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Kühle H, Cho SKS, Barber N, Goolaub DS, Darby JRT, Morrison JL, Haller C, Sun L, Seed M. Advanced imaging of fetal cardiac function. Front Cardiovasc Med 2023; 10:1206138. [PMID: 37288263 PMCID: PMC10242056 DOI: 10.3389/fcvm.2023.1206138] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2023] [Accepted: 05/09/2023] [Indexed: 06/09/2023] Open
Abstract
Over recent decades, a variety of advanced imaging techniques for assessing cardiovascular physiology and cardiac function in adults and children have been applied in the fetus. In many cases, technical development has been required to allow feasibility in the fetus, while an appreciation of the unique physiology of the fetal circulation is required for proper interpretation of the findings. This review will focus on recent advances in fetal echocardiography and cardiovascular magnetic resonance (CMR), providing examples of their application in research and clinical settings. We will also consider future directions for these technologies, including their ongoing technical development and potential clinical value.
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Affiliation(s)
- Henriette Kühle
- Division of Cardiology, Department of Pediatrics, The Hospital for Sick Children, University of Toronto, Toronto, ON, Canada
- Department of Cardiac and Thoracic Surgery, University Hospital Magdeburg, Otto von Guericke University Magdeburg, Magdeburg, Germany
- Division of Cardiac Surgery, Department of Pediatrics, The Hospital for Sick Children, University of Toronto, Toronto, ON, Canada
| | - Steven K. S. Cho
- Division of Cardiology, Department of Pediatrics, The Hospital for Sick Children, University of Toronto, Toronto, ON, Canada
- Department of Physiology, Faculty of Medicine, University of Toronto, Toronto, ON, Canada
- Early Origins of Adult Health Research Group, University of South Australia, Adelaide, SA, Australia
| | - Nathaniel Barber
- Division of Cardiology, Department of Pediatrics, The Hospital for Sick Children, University of Toronto, Toronto, ON, Canada
| | - Datta Singh Goolaub
- Translational Medicine Program, The Hospital for Sick Children, University of Toronto, Toronto, ON, Canada
| | - Jack R. T. Darby
- Early Origins of Adult Health Research Group, University of South Australia, Adelaide, SA, Australia
| | - Janna L. Morrison
- Department of Physiology, Faculty of Medicine, University of Toronto, Toronto, ON, Canada
- Early Origins of Adult Health Research Group, University of South Australia, Adelaide, SA, Australia
- Research Institute, The Hospital for Sick Children, University of Toronto, Toronto, ON, Canada
| | - Christoph Haller
- Division of Cardiac Surgery, Department of Pediatrics, The Hospital for Sick Children, University of Toronto, Toronto, ON, Canada
| | - Liqun Sun
- Division of Cardiology, Department of Pediatrics, The Hospital for Sick Children, University of Toronto, Toronto, ON, Canada
- Translational Medicine Program, The Hospital for Sick Children, University of Toronto, Toronto, ON, Canada
| | - Mike Seed
- Division of Cardiology, Department of Pediatrics, The Hospital for Sick Children, University of Toronto, Toronto, ON, Canada
- Department of Physiology, Faculty of Medicine, University of Toronto, Toronto, ON, Canada
- Translational Medicine Program, The Hospital for Sick Children, University of Toronto, Toronto, ON, Canada
- Research Institute, The Hospital for Sick Children, University of Toronto, Toronto, ON, Canada
- Department of Diagnostic Imaging, The Hospital for Sick Children, University of Toronto, Toronto, ON, Canada
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17
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Bieri O, Pusterla O, Bauman G. Free-breathing half-radial dual-echo balanced steady-state free precession thoracic imaging with wobbling Archimedean spiral pole trajectories. Z Med Phys 2023; 33:220-229. [PMID: 35190223 PMCID: PMC10311259 DOI: 10.1016/j.zemedi.2022.01.003] [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: 11/27/2021] [Revised: 01/11/2022] [Accepted: 01/14/2022] [Indexed: 10/19/2022]
Abstract
PURPOSE To demonstrate free-breathing thoracic MRI with a minimal-TR balanced steady-state free precession (bSSFP) technique using wobbling Archimedean spiral pole (WASP) trajectories. METHODS Phantom and free-breathing in vivo chest imaging in healthy volunteers was performed at 1.5T with a half-radial, dual-echo, bSSFP sequence, termed bSTAR. For maximum sampling efficiency, a single analog-to-digital converter window along the full bipolar readout was used. To ensure a homogeneous coverage of the k-space over multiple breathing cycles, radial k-space sampling followed short-duration Archimedean spiral interleaves that were randomly titled by a small polar angle and rotated by a golden angle about the polar axis; depticting a wobbling Archimedean spiral pole (WASP) trajectory. In phantom and in vivo experiments, WASP trajectories were compared to spiral phyllotaxis sampling in terms of eddy currents and were used to generate in vivo thorax images at different respiratory phases. RESULTS WASP trajectories provided artifact-free bSTAR imaging in both phantom and in vivo and respiratory self-gated reconstruction was successfully performed in all subjects. The amount of the acquired data allowed the reconstruction of 10 volumes at different respiratory levels with isotropic resolution of 1.77mm from a scan of 5.5minutes (using a TR of 1.32ms), and one high-resolution 1.16mm end-expiratory volume from a scan of 4.7minutes (using a TR of 1.42ms). The very short TR of bSTAR mitigated off-resonance artifacts despite the large field-of-view. CONCLUSION We have demonstrated the feasibility of high-resolution free-breathing thoracic imaging with bSTAR using the wobbling Archimedean spiral pole in healthy subjects at 1.5T.
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Affiliation(s)
- Oliver Bieri
- Division of Radiological Physics, Department of Radiology, University of Basel Hospital, Basel, Switzerland; Department of Biomedical Engineering, University of Basel, Basel, Switzerland
| | - Orso Pusterla
- Division of Radiological Physics, Department of Radiology, University of Basel Hospital, Basel, Switzerland; Department of Biomedical Engineering, University of Basel, Basel, Switzerland
| | - Grzegorz Bauman
- Division of Radiological Physics, Department of Radiology, University of Basel Hospital, Basel, Switzerland; Department of Biomedical Engineering, University of Basel, Basel, Switzerland.
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18
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Maatman IT, Ypma S, Kachelrieß M, Berker Y, van der Bijl E, Block KT, Hermans JJ, Maas MC, Scheenen TWJ. Single-spoke binning: Reducing motion artifacts in abdominal radial stack-of-stars imaging. Magn Reson Med 2023; 89:1931-1944. [PMID: 36594436 DOI: 10.1002/mrm.29576] [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: 09/21/2022] [Revised: 11/23/2022] [Accepted: 12/19/2022] [Indexed: 01/04/2023]
Abstract
PURPOSE To increase the effectiveness of respiratory gating in radial stack-of-stars MRI, particularly when imaging at high spatial resolutions or with multiple echoes. METHODS Free induction decay (FID) navigators were integrated into a three-dimensional gradient echo radial stack-of-stars pulse sequence. These navigators provided a motion signal with a high temporal resolution, which allowed single-spoke binning (SSB): each spoke at each phase encode step was sorted individually to the corresponding motion state of the respiratory signal. SSB was compared with spoke-angle binning (SAB), in which all phase encode steps of one projection angle were sorted without the use of additional navigator data. To illustrate the benefit of SSB over SAB, images of a motion phantom and of six free-breathing volunteers were reconstructed after motion-gating using either method. Image sharpness was quantitatively compared using image gradient entropies. RESULTS The proposed method resulted in sharper images of the motion phantom and free-breathing volunteers. Differences in gradient entropy were statistically significant (p = 0.03) in favor of SSB. The increased accuracy of motion-gating led to a decrease of streaking artifacts in motion-gated four-dimensional reconstructions. To consistently estimate respiratory signals from the FID-navigator data, specific types of gradient spoiler waveforms were required. CONCLUSION SSB allowed high-resolution motion-corrected MR imaging, even when acquiring multiple gradient echo signals or large acquisition matrices, without sacrificing accuracy of motion-gating. SSB thus relieves restrictions on the choice of pulse sequence parameters, enabling the use of motion-gated radial stack-of-stars MRI in a broader domain of clinical applications.
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Affiliation(s)
- Ivo T Maatman
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Sjoerd Ypma
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Marc Kachelrieß
- Division of X-Ray Imaging and Computed Tomography, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Yannick Berker
- Hopp Children's Cancer Center Heidelberg (KiTZ), Heidelberg, Germany.,Clinical Cooperation Unit Pediatric Oncology, German Cancer Research Center (DKFZ) and German Cancer Consortium (DKTK), Heidelberg, Germany.,National Center for Tumor Diseases (NCT) Heidelberg, Heidelberg, Germany
| | - Erik van der Bijl
- Department of Radiation Oncology, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Kai Tobias Block
- Department of Radiology, NYU Langone Health, New York, New York, USA
| | - John J Hermans
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Marnix C Maas
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Tom W J Scheenen
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, The Netherlands
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19
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Li R, Shao J, Jin YJ, Kawase H, Ong YT, Troidl K, Quan Q, Wang L, Bonnavion R, Wietelmann A, Helmbacher F, Potente M, Graumann J, Wettschureck N, Offermanns S. Endothelial FAT1 inhibits angiogenesis by controlling YAP/TAZ protein degradation via E3 ligase MIB2. Nat Commun 2023; 14:1980. [PMID: 37031213 PMCID: PMC10082778 DOI: 10.1038/s41467-023-37671-x] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2022] [Accepted: 03/27/2023] [Indexed: 04/10/2023] Open
Abstract
Activation of endothelial YAP/TAZ signaling is crucial for physiological and pathological angiogenesis. The mechanisms of endothelial YAP/TAZ regulation are, however, incompletely understood. Here we report that the protocadherin FAT1 acts as a critical upstream regulator of endothelial YAP/TAZ which limits the activity of these transcriptional cofactors during developmental and tumor angiogenesis by promoting their degradation. We show that loss of endothelial FAT1 results in increased endothelial cell proliferation in vitro and in various angiogenesis models in vivo. This effect is due to perturbed YAP/TAZ protein degradation, leading to increased YAP/TAZ protein levels and expression of canonical YAP/TAZ target genes. We identify the E3 ubiquitin ligase Mind Bomb-2 (MIB2) as a FAT1-interacting protein mediating FAT1-induced YAP/TAZ ubiquitination and degradation. Loss of MIB2 expression in endothelial cells in vitro and in vivo recapitulates the effects of FAT1 depletion and causes decreased YAP/TAZ degradation and increased YAP/TAZ signaling. Our data identify a pivotal mechanism of YAP/TAZ regulation involving FAT1 and its associated E3 ligase MIB2, which is essential for YAP/TAZ-dependent angiogenesis.
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Affiliation(s)
- Rui Li
- Max Planck Institute for Heart and Lung Research, Department of Pharmacology, Ludwigstr. 43, 61231, Bad Nauheim, Germany
| | - Jingchen Shao
- Max Planck Institute for Heart and Lung Research, Department of Pharmacology, Ludwigstr. 43, 61231, Bad Nauheim, Germany
| | - Young-June Jin
- Max Planck Institute for Heart and Lung Research, Department of Pharmacology, Ludwigstr. 43, 61231, Bad Nauheim, Germany
| | - Haruya Kawase
- Max Planck Institute for Heart and Lung Research, Department of Pharmacology, Ludwigstr. 43, 61231, Bad Nauheim, Germany
| | - Yu Ting Ong
- Max Planck Institute for Heart and Lung Research, Angiogenesis & Metabolism Laboratory, Ludwigstr. 43, 61231, Bad Nauheim, Germany
| | - Kerstin Troidl
- Max Planck Institute for Heart and Lung Research, Department of Pharmacology, Ludwigstr. 43, 61231, Bad Nauheim, Germany
- Department of Vascular and Endovascular Surgery, Cardiovascular Surgery Clinic, University Hospital Frankfurt and Wolfgang Goethe University Frankfurt, Frankfurt, Germany
| | - Qi Quan
- Max Planck Institute for Heart and Lung Research, Department of Pharmacology, Ludwigstr. 43, 61231, Bad Nauheim, Germany
| | - Lei Wang
- Max Planck Institute for Heart and Lung Research, Department of Pharmacology, Ludwigstr. 43, 61231, Bad Nauheim, Germany
| | - Remy Bonnavion
- Max Planck Institute for Heart and Lung Research, Department of Pharmacology, Ludwigstr. 43, 61231, Bad Nauheim, Germany
| | - Astrid Wietelmann
- Max Planck Institute for Heart and Lung Research, Small Animal Imaging Service Group, Ludwigstr. 43, 61231, Bad Nauheim, Germany
| | - Francoise Helmbacher
- Aix Marseille Université, CNRS, IBDM UMR 7288, Parc Scientifique de Luminy, Case 907, 13288, Marseille, France
| | - Michael Potente
- Max Planck Institute for Heart and Lung Research, Angiogenesis & Metabolism Laboratory, Ludwigstr. 43, 61231, Bad Nauheim, Germany
- Berlin Institute of Health at Charité-Universitätsmedizin Berlin, and Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
| | - Johannes Graumann
- Max Planck Institute for Heart and Lung Research, Biomolecular Mass Spectrometry Service Group, Ludwigstr. 43, 61231, Bad Nauheim, Germany
- Institute of Translational Proteomics, Department of Medicine, Philipps-University Marburg, Karl-von-Frisch-Str. 2, 35043, Marburg, Germany
| | - Nina Wettschureck
- Max Planck Institute for Heart and Lung Research, Department of Pharmacology, Ludwigstr. 43, 61231, Bad Nauheim, Germany
- Center for Molecular Medicine, Goethe University Frankfurt, Theodor-Stern-Kai 7, 60590, Frankfurt, Germany
- Cardiopulmonary Institute, Bad Nauheim, Germany
- German Center for Cardiovascular Research, Partner Site Frankfurt, Bad Nauheim, Germany
| | - Stefan Offermanns
- Max Planck Institute for Heart and Lung Research, Department of Pharmacology, Ludwigstr. 43, 61231, Bad Nauheim, Germany.
- Center for Molecular Medicine, Goethe University Frankfurt, Theodor-Stern-Kai 7, 60590, Frankfurt, Germany.
- Cardiopulmonary Institute, Bad Nauheim, Germany.
- German Center for Cardiovascular Research, Partner Site Frankfurt, Bad Nauheim, Germany.
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20
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Wang X, Rosenzweig S, Roeloffs V, Blumenthal M, Scholand N, Tan Z, Holme HCM, Unterberg-Buchwald C, Hinkel R, Uecker M. Free-breathing myocardial T 1 mapping using inversion-recovery radial FLASH and motion-resolved model-based reconstruction. Magn Reson Med 2023; 89:1368-1384. [PMID: 36404631 PMCID: PMC9892313 DOI: 10.1002/mrm.29521] [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: 11/17/2021] [Revised: 09/22/2022] [Accepted: 10/20/2022] [Indexed: 11/22/2022]
Abstract
PURPOSE To develop a free-breathing myocardialT 1 $$ {\mathrm{T}}_1 $$ mapping technique using inversion-recovery (IR) radial fast low-angle shot (FLASH) and calibrationless motion-resolved model-based reconstruction. METHODS Free-running (free-breathing, retrospective cardiac gating) IR radial FLASH is used for data acquisition at 3T. First, to reduce the waiting time between inversions, an analytical formula is derived that takes the incompleteT 1 $$ {\mathrm{T}}_1 $$ recovery into account for an accurateT 1 $$ {\mathrm{T}}_1 $$ calculation. Second, the respiratory motion signal is estimated from the k-space center of the contrast varying acquisition using an adapted singular spectrum analysis (SSA-FARY) technique. Third, a motion-resolved model-based reconstruction is used to estimate both parameter and coil sensitivity maps directly from the sorted k-space data. Thus, spatiotemporal total variation, in addition to the spatial sparsity constraints, can be directly applied to the parameter maps. Validations are performed on an experimental phantom, 11 human subjects, and a young landrace pig with myocardial infarction. RESULTS In comparison to an IR spin-echo reference, phantom results confirm goodT 1 $$ {\mathrm{T}}_1 $$ accuracy, when reducing the waiting time from 5 s to 1 s using the new correction. The motion-resolved model-based reconstruction further improvesT 1 $$ {\mathrm{T}}_1 $$ precision compared to the spatial regularization-only reconstruction. Aside from showing that a reliable respiratory motion signal can be estimated using modified SSA-FARY, in vivo studies demonstrate that dynamic myocardialT 1 $$ {\mathrm{T}}_1 $$ maps can be obtained within 2 min with good precision and repeatability. CONCLUSION Motion-resolved myocardialT 1 $$ {\mathrm{T}}_1 $$ mapping during free-breathing with good accuracy, precision and repeatability can be achieved by combining inversion-recovery radial FLASH, self-gating and a calibrationless motion-resolved model-based reconstruction.
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Affiliation(s)
- Xiaoqing Wang
- Institute of Biomedical Imaging, Graz University of Technology, Graz, Austria
- Institute for Diagnostic and Interventional Radiology of the University Medical Center Göttingen, Germany
- German Centre for Cardiovascular Research (DZHK), Partner Site Göttingen, Germany
| | - Sebastian Rosenzweig
- Institute for Diagnostic and Interventional Radiology of the University Medical Center Göttingen, Germany
- German Centre for Cardiovascular Research (DZHK), Partner Site Göttingen, Germany
| | - Volkert Roeloffs
- Institute for Diagnostic and Interventional Radiology of the University Medical Center Göttingen, Germany
| | - Moritz Blumenthal
- Institute for Diagnostic and Interventional Radiology of the University Medical Center Göttingen, Germany
| | - Nick Scholand
- Institute of Biomedical Imaging, Graz University of Technology, Graz, Austria
| | - Zhengguo Tan
- Institute for Diagnostic and Interventional Radiology of the University Medical Center Göttingen, Germany
- German Centre for Cardiovascular Research (DZHK), Partner Site Göttingen, Germany
| | | | - Christina Unterberg-Buchwald
- Institute for Diagnostic and Interventional Radiology of the University Medical Center Göttingen, Germany
- German Centre for Cardiovascular Research (DZHK), Partner Site Göttingen, Germany
| | - Rabea Hinkel
- German Centre for Cardiovascular Research (DZHK), Partner Site Göttingen, Germany
- Laboratory Animal Science Unit, Leibniz Institute for Primate Research, Deutsches Primatenzentrum GmbH, Göttingen, Germany
- Institute for Animal Hygiene, Animal Welfare and Farm Animal Behavior, University of Veterinary Medicine, Hannover, Germany
| | - Martin Uecker
- Institute of Biomedical Imaging, Graz University of Technology, Graz, Austria
- Institute for Diagnostic and Interventional Radiology of the University Medical Center Göttingen, Germany
- German Centre for Cardiovascular Research (DZHK), Partner Site Göttingen, Germany
- Cluster of “Excellence Multiscale Bioimaging: from Molecular Machines to Networks of Excitable Cells” (MBExC), University of Göttingen, Germany
- BioTechMed-Graz, Graz, Austria
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21
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Lin K, Sarnari R, Speier P, Hayes C, Davids R, Carr JC, Markl M. Pilot Tone-Triggered MRI for Quantitative Assessment of Cardiac Function, Motion, and Structure. Invest Radiol 2023; 58:239-243. [PMID: 36070525 PMCID: PMC10016086 DOI: 10.1097/rli.0000000000000922] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
OBJECTIVE The aim of this study was to test the hypothesis that there are good agreements between cardiac functional and structural indices derived from magnetic resonance imaging (MRI) sequences triggered with pilot tone (PT) and electrocardiogram (ECG). MATERIALS AND METHODS Sixteen healthy volunteers (11 male, age 21-76 years) underwent a cardiac MRI scan. Cine MRI, T1, and T2 mapping were acquired by using PT and ECG triggering. Quantitative measurements, including left and right ventricular end-diastolic volume, end-systolic volume, stroke volume, ejection fraction, longitudinal strain, left ventricular T1 and T2 values, left and right atrial longitudinal strain, and maximal/minimal volumes, were measured. The interclass correlation coefficient, coefficient of variation, and Bland-Altman plots were used to evaluate the agreements between measurements derived by MRI sequences triggered with 2 methods. RESULTS There were no significant differences among end-diastolic volume, end-systolic volume, stroke volume, ejection fraction, left ventricle mass, T1 and T2 values, or longitudinal strains acquired using PT and ECG. There were good agreements and low variations between the levels of these indices acquired with PT and ECG. Interclass correlation coefficients mainly ranged from 0.73 to 0.98. The coefficients of variation ranged from 1.4% to 22.6%. CONCLUSIONS Pilot tone-triggered MRI provides comparable measurements of cardiac function, motion, and structure as ECG-triggered MRI. Pilot tone has the potential to become a backup of ECG gating in cardiovascular imaging.
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Affiliation(s)
- Kai Lin
- Department of Radiology, Northwestern University, Chicago, IL
| | - Roberto Sarnari
- Department of Radiology, Northwestern University, Chicago, IL
| | | | | | | | - James C. Carr
- Department of Radiology, Northwestern University, Chicago, IL
| | - Michael Markl
- Department of Radiology, Northwestern University, Chicago, IL
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22
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Feng L. 4D Golden-Angle Radial MRI at Subsecond Temporal Resolution. NMR IN BIOMEDICINE 2023; 36:e4844. [PMID: 36259951 PMCID: PMC9845193 DOI: 10.1002/nbm.4844] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Revised: 09/29/2022] [Accepted: 10/13/2022] [Indexed: 05/14/2023]
Abstract
Intraframe motion blurring, as a major challenge in free-breathing dynamic MRI, can be reduced if high temporal resolution can be achieved. To address this challenge, this work proposes a highly accelerated 4D (3D + time) dynamic MRI framework with subsecond temporal resolution that does not require explicit motion compensation. The method combines standard stack-of-stars golden-angle radial sampling and tailored GRASP-Pro (Golden-angle RAdial Sparse Parallel imaging with imProved performance) reconstruction. Specifically, 4D dynamic MRI acquisition is performed continuously without motion gating or sorting. The k-space centers in stack-of-stars radial data are organized to guide estimation of a temporal basis, with which GRASP-Pro reconstruction is employed to enforce joint low-rank subspace and sparsity constraints. This new basis estimation strategy is the new feature proposed for subspace-based reconstruction in this work to achieve high temporal resolution (e.g., subsecond/3D volume). It does not require sequence modification to acquire additional navigation data, it is compatible with commercially available stack-of-stars sequences, and it does not need an intermediate reconstruction step. The proposed 4D dynamic MRI approach was tested in abdominal motion phantom, free-breathing abdominal MRI, and dynamic contrast-enhanced MRI (DCE-MRI). Our results have shown that GRASP-Pro reconstruction with the new basis estimation strategy enables highly-accelerated 4D dynamic imaging at subsecond temporal resolution (with five spokes or less for each dynamic frame per image slice) for both free-breathing non-DCE-MRI and DCE-MRI. In the abdominal phantom, better image quality with lower root mean square error and higher structural similarity index was achieved using GRASP-Pro compared with standard GRASP. With the ability to acquire each 3D image in less than 1 s, intraframe respiratory blurring can be intrinsically reduced for body applications with our approach, which eliminates the need for explicit motion detection and motion compensation.
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Affiliation(s)
- Li Feng
- Biomedical Engineering and Imaging Institute and Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
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23
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Zhou W, Sin J, Yan AT, Wang H, Lu J, Li Y, Kim P, Patel AR, Ng MY. Qualitative and Quantitative Stress Perfusion Cardiac Magnetic Resonance in Clinical Practice: A Comprehensive Review. Diagnostics (Basel) 2023; 13:524. [PMID: 36766629 PMCID: PMC9914769 DOI: 10.3390/diagnostics13030524] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Revised: 01/11/2023] [Accepted: 01/28/2023] [Indexed: 02/05/2023] Open
Abstract
Stress cardiovascular magnetic resonance (CMR) imaging is a well-validated non-invasive stress test to diagnose significant coronary artery disease (CAD), with higher diagnostic accuracy than other common functional imaging modalities. One-stop assessment of myocardial ischemia, cardiac function, and myocardial viability qualitatively and quantitatively has been proven to be a cost-effective method in clinical practice for CAD evaluation. Beyond diagnosis, stress CMR also provides prognostic information and guides coronary revascularisation. In addition to CAD, there is a large body of literature demonstrating CMR's diagnostic performance and prognostic value in other common cardiovascular diseases (CVDs), especially coronary microvascular dysfunction (CMD). This review focuses on the clinical applications of stress CMR, including stress CMR scanning methods, practical interpretation of stress CMR images, and clinical utility of stress CMR in a setting of CVDs with possible myocardial ischemia.
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Affiliation(s)
- Wenli Zhou
- Department of Radiology, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, No. 600, Yishan Road, Shanghai 200233, China
| | - Jason Sin
- Department of Diagnostic Radiology, The University of Hong Kong, Hong Kong SAR, China
| | - Andrew T. Yan
- St. Michael’s Hospital, University of Toronto, Toronto, ON M5B 1W8, Canada
| | | | - Jing Lu
- Department of Radiology, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, No. 600, Yishan Road, Shanghai 200233, China
| | - Yuehua Li
- Department of Radiology, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, No. 600, Yishan Road, Shanghai 200233, China
| | - Paul Kim
- Department of Medicine, University of California San Diego, San Diego, CA 92093, USA
| | - Amit R. Patel
- Department of Cardiovascular Medicine, University of Virginia, Charlottesville, VA 22903, USA
| | - Ming-Yen Ng
- Department of Medical Imaging, HKU-Shenzhen Hospital, Shenzhen 518009, China
- Department of Diagnostic Radiology, School of Clinical Medicine, The University of Hong Kong, Hong Kong SAR, China
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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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25
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Subashi E, Feng L, Liu Y, Robertson S, Segars P, Driehuys B, Kelsey CR, Yin FF, Otazo R, Cai J. View-sharing for 4D magnetic resonance imaging with randomized projection-encoding enables improvements of respiratory motion imaging for treatment planning in abdominothoracic radiotherapy. Phys Imaging Radiat Oncol 2023; 25:100409. [PMID: 36655213 PMCID: PMC9841273 DOI: 10.1016/j.phro.2022.12.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2022] [Revised: 12/24/2022] [Accepted: 12/28/2022] [Indexed: 01/03/2023] Open
Abstract
Background and Purpose The accuracy and precision of radiation therapy are dependent on the characterization of organ-at-risk and target motion. This work aims to demonstrate a 4D magnetic resonance imaging (MRI) method for improving spatial and temporal resolution in respiratory motion imaging for treatment planning in abdominothoracic radiotherapy. Materials and Methods The spatial and temporal resolution of phase-resolved respiratory imaging is improved by considering a novel sampling function based on quasi-random projection-encoding and peripheral k-space view-sharing. The respiratory signal is determined directly from k-space, obviating the need for an external surrogate marker. The average breathing curve is used to optimize spatial resolution and temporal blurring by limiting the extent of data sharing in the Fourier domain. Improvements in image quality are characterized by evaluating changes in signal-to-noise ratio (SNR), resolution, target detection, and level of artifact. The method is validated in simulations, in a dynamic phantom, and in-vivo imaging. Results Sharing of high-frequency k-space data, driven by the average breathing curve, improves spatial resolution and reduces artifacts. Although equal sharing of k-space data improves resolution and SNR in stationary features, phases with large temporal changes accumulate significant artifacts due to averaging of high frequency features. In the absence of view-sharing, no averaging and detection artifacts are observed while spatial resolution is degraded. Conclusions The use of a quasi-random sampling function, with view-sharing driven by the average breathing curve, provides a feasible method for self-navigated 4D-MRI at improved spatial resolution.
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Affiliation(s)
- Ergys Subashi
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, United States
| | - Li Feng
- Biomedical Engineering and Imaging Institute, Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Yilin Liu
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, United States
| | - Scott Robertson
- Medical Physics Graduate Program, Duke University Medical Center, Durham, NC, United States
- Department of Radiology, Duke University Medical Center, Durham, NC, United States
| | - Paul Segars
- Medical Physics Graduate Program, Duke University Medical Center, Durham, NC, United States
- Department of Radiology, Duke University Medical Center, Durham, NC, United States
| | - Bastiaan Driehuys
- Medical Physics Graduate Program, Duke University Medical Center, Durham, NC, United States
- Department of Radiology, Duke University Medical Center, Durham, NC, United States
| | - Christopher R Kelsey
- Department of Radiation Oncology, Duke University Medical Center, Durham, NC, United States
| | - Fang-Fang Yin
- Medical Physics Graduate Program, Duke University Medical Center, Durham, NC, United States
- Department of Radiation Oncology, Duke University Medical Center, Durham, NC, United States
| | - Ricardo Otazo
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, United States
| | - Jing Cai
- Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Kowloon, Hong Kong
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26
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Feasibility of flow-related enhancement brain perfusion MRI. PLoS One 2022; 17:e0276912. [DOI: 10.1371/journal.pone.0276912] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2022] [Accepted: 10/17/2022] [Indexed: 11/18/2022] Open
Abstract
Purpose
Brain perfusion imaging is of enormous importance for various neurological diseases. Fast gradient-echo sequences offering flow-related enhancement (FREE) could present a basis to generate perfusion-weighted maps. In this study, we obtained perfusion-weighted maps without contrast media by a previously described postprocessing algorithm from the field of functional lung MRI. At first, the perfusion signal was analyzed in fast low-angle shot (FLASH) and balanced steady-state free precession (bSSFP) sequences. Secondly, perfusion maps were compared to pseudo-continuous arterial spin labeling (pCASL) MRI in a healthy cohort. Thirdly, the feasibility of the new technique was demonstrated in a small selected group of patients with metastases and acute stroke.
Methods
One participant was examined with bSSFP and FLASH sequences at 1.5T and 3T, different flip angles and slice thicknesses. Twenty-five volunteers had bSSFP imaging and pCASL MRI. Three patients with cerebral metastases and one with acute ischemic stroke had bSSFP imaging and were compared to T1 post-contrast images and CT perfusion. Frequency analyses, SNR and perfusion contrast were compared at different flip angles and slice thicknesses. Regional correlations and Sorensen-Dice overlap were calculated in the healthy cohort. Dice overlap of the pathologies in the patient cohort were calculated.
Results
The bSSFP sequence presented detectable perfusion signal within brain vessel and parenchyma together with superior SNR compared to FLASH. Perfusion contrast and its corticomedullary differentiation increased with flip angle. Mean regional correlation was 0.36 and highly significant between FREE maps and pCASL and grey and white matter Dice match were 72% and 60% in the healthy cohort. Pathologies presented good overlap between FREE perfusion-weighted and T1 post-contrast images.
Conclusion
The feasibility of FREE brain perfusion imaging has been shown in a healthy cohort and selected patient cases with brain metastases and acute stroke. The study demonstrates a new approach for non-contrast brain perfusion imaging.
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27
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Wang Q, Guo X, Brooks M, Chuen J, Poon EKW, Ooi A, Lim RP. MRI in CFD for chronic type B aortic dissection: Ready for prime time? Comput Biol Med 2022; 150:106138. [PMID: 36191393 DOI: 10.1016/j.compbiomed.2022.106138] [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: 05/10/2022] [Revised: 08/31/2022] [Accepted: 09/18/2022] [Indexed: 11/24/2022]
Abstract
OBJECTIVES Better tools are needed for risk assessment of Type B aortic dissection (TBAD) to determine optimal treatment for patients with uncomplicated disease. Magnetic resonance imaging (MRI) has the potential to inform computational fluid dynamics (CFD) simulations for TBAD by providing individualised quantification of haemodynamic parameters, for assessment of complication risks. This systematic review aims to present an overview of MRI applications for CFD studies of TBAD. METHODS Following PRISMA guidelines, a search in Medline, Embase, and the Scopus Library identified 136 potentially relevant articles. Studies were included if they used MRI to inform CFD simulation in TBAD. RESULTS There were 20 articles meeting the inclusion criteria. 19 studies used phase contrast MRI (PC-MRI) to provide data for CFD flow boundary conditions. In 12 studies, CFD haemodynamic parameter results were validated against PC-MRI. In eight studies, geometric models were developed from MR angiography. In three studies, aortic wall or intimal flap motion data were derived from PC/cine MRI. CONCLUSIONS MRI provides complementary patient-specific information in CFD haemodynamic studies for TBAD that can be used for personalised care. MRI provides structural, dynamic and flow data to inform CFD for pre-treatment planning, potentially advancing its integration into clinical decision-making. The use of MRI to inform CFD in TBAD surgical planning is promising, however further validation and larger cohort studies are required.
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Affiliation(s)
- Qingdi Wang
- Department of Mechanical Engineering, Melbourne School of Engineering, The University of Melbourne, Melbourne, VIC, 3010, Australia.
| | - Xiaojing Guo
- Department of Mechanical Engineering, Melbourne School of Engineering, The University of Melbourne, Melbourne, VIC, 3010, Australia
| | - Mark Brooks
- Department of Radiology, Austin Health, Heidelberg, VIC, 3084, Australia; School of Medicine, Deakin University, Melbourne, Australia
| | - Jason Chuen
- Department of Surgery, Austin Health, Heidelberg, VIC, 3084, Australia; Department of Surgery, Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, Fitzroy, VIC, 3065, Australia
| | - Eric K W Poon
- Department of Medicine, St Vincent's Hospital, Melbourne Medical School, Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, Fitzroy, VIC, 3065, Australia
| | - Andrew Ooi
- Department of Mechanical Engineering, Melbourne School of Engineering, The University of Melbourne, Melbourne, VIC, 3010, Australia
| | - Ruth P Lim
- Department of Radiology, Austin Health, Heidelberg, VIC, 3084, Australia; Department of Surgery, Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, Fitzroy, VIC, 3065, Australia; Department of Radiology, Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, Melbourne, VIC, 3010, Australia
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28
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Garcia-Gonzalez C, Dieterich C, Maroli G, Wiesnet M, Wietelmann A, Li X, Yuan X, Graumann J, Stellos K, Kubin T, Schneider A, Braun T. ADAR1 Prevents Autoinflammatory Processes in the Heart Mediated by IRF7. Circ Res 2022; 131:580-597. [PMID: 36000401 DOI: 10.1161/circresaha.122.320839] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
BACKGROUND ADAR1 (adenosine deaminase acting on RNA-1)-mediated adenosine to inosine (A-to-I) RNA editing plays an essential role for distinguishing endogenous from exogenous RNAs, preventing autoinflammatory ADAR1 also regulates cellular processes by recoding specific mRNAs, thereby altering protein functions, but may also act in an editing-independent manner. The specific role of ADAR1 in cardiomyocytes and its mode of action in the heart is not fully understood. To determine the role of ADAR1 in the heart, we used different mutant mouse strains, which allows to distinguish immunogenic, editing-dependent, and editing-independent functions of ADAR1. METHODS Different Adar1-mutant mouse strains were employed for gene deletion or specific inactivation of ADAR1 enzymatic activity in cardiomyocytes, either alone or in combination with Ifih1 (interferon induced with helicase C domain 1) or Irf7 (interferon regulatory factor 7) gene inactivation. Mutant mice were investigated by immunofluorescence, Western blot, RNAseq, proteomics, and functional MRI analysis. RESULTS Inactivation of Adar1 in cardiomyocytes resulted in late-onset autoinflammatory myocarditis progressing into dilated cardiomyopathy and heart failure at 6 months of age. Adar1 depletion activated interferon signaling genes but not NFκB (nuclear factor kappa B) signaling or apoptosis and reduced cardiac hypertrophy during pressure overload via induction of Irf7. Additional inactivation of the cytosolic RNA sensor MDA5 (melanoma differentiation-associated gene 5; encoded by the Ifih1 gene) in Adar1 mutant mice prevented activation of interferon signaling gene and delayed heart failure but did not prevent lethality after 8.5 months. In contrast, compound mutants only expressing catalytically inactive ADAR1 in an Ifih1-mutant background were completely normal. Inactivation of Irf7 attenuated the phenotype of Adar1-deficient cardiomyocytes to a similar extent as Ifih1 depletion, identifying IRF7 as the main mediator of autoinflammatory responses caused by the absence of ADAR1 in cardiomyocytes. CONCLUSIONS Enzymatically active ADAR1 prevents IRF7-mediated autoinflammatory reactions in the heart triggered by endogenous nonedited RNAs. In addition to RNA editing, ADAR1 also serves editing-independent roles in the heart required for long-term cardiac function and survival.
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Affiliation(s)
- Claudia Garcia-Gonzalez
- Max Planck Institute for Heart- and Lung Research, Bad Nauheim, Germany (C.G.-G., G.M., M.W., A.W., X.L., X.Y., J.G., A.S., T.B.).,Instituto de Investigación Sanitaria del Principado de Asturias (ISPA), Av. Del Hospital Universitario, Oviedo, Spain (C.G.-G.)
| | - Christoph Dieterich
- Department of Internal Medicine III and Klaus Tschira Institute for Computational Cardiology, Section of Bioinformatics and Systems Cardiology, University Hospital, Heidelberg, Germany (C.D.)
| | - Giovanni Maroli
- Max Planck Institute for Heart- and Lung Research, Bad Nauheim, Germany (C.G.-G., G.M., M.W., A.W., X.L., X.Y., J.G., A.S., T.B.)
| | - Marion Wiesnet
- Max Planck Institute for Heart- and Lung Research, Bad Nauheim, Germany (C.G.-G., G.M., M.W., A.W., X.L., X.Y., J.G., A.S., T.B.)
| | - Astrid Wietelmann
- Max Planck Institute for Heart- and Lung Research, Bad Nauheim, Germany (C.G.-G., G.M., M.W., A.W., X.L., X.Y., J.G., A.S., T.B.)
| | - Xiang Li
- Max Planck Institute for Heart- and Lung Research, Bad Nauheim, Germany (C.G.-G., G.M., M.W., A.W., X.L., X.Y., J.G., A.S., T.B.)
| | - Xuejun Yuan
- Max Planck Institute for Heart- and Lung Research, Bad Nauheim, Germany (C.G.-G., G.M., M.W., A.W., X.L., X.Y., J.G., A.S., T.B.)
| | - Johannes Graumann
- Max Planck Institute for Heart- and Lung Research, Bad Nauheim, Germany (C.G.-G., G.M., M.W., A.W., X.L., X.Y., J.G., A.S., T.B.).,German Centre for Cardiovascular Research (DZHK), Partner Sites Rhine-Main and Heidelberg/Mannheim, Bad Nauheim and Mannheim, Germany (J.G., K.S., T.B.)
| | - Konstantinos Stellos
- German Centre for Cardiovascular Research (DZHK), Partner Sites Rhine-Main and Heidelberg/Mannheim, Bad Nauheim and Mannheim, Germany (J.G., K.S., T.B.).,Department of Cardiovascular Research, European Center for Angioscience, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany (K.S.).,Biosciences Institute, Vascular Biology and Medicine Theme, Faculty of Medical Sciences, Newcastle University, Newcastle Upon Tyne, United Kingdom (K.S.)
| | - Thomas Kubin
- Department of Cardiac Surgery, Kerckhoff Heart Center, Bad Nauheim, Germany (T.K.)
| | - Andre Schneider
- Max Planck Institute for Heart- and Lung Research, Bad Nauheim, Germany (C.G.-G., G.M., M.W., A.W., X.L., X.Y., J.G., A.S., T.B.)
| | - Thomas Braun
- Max Planck Institute for Heart- and Lung Research, Bad Nauheim, Germany (C.G.-G., G.M., M.W., A.W., X.L., X.Y., J.G., A.S., T.B.).,German Centre for Cardiovascular Research (DZHK), Partner Sites Rhine-Main and Heidelberg/Mannheim, Bad Nauheim and Mannheim, Germany (J.G., K.S., T.B.)
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29
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Feng L. Golden-Angle Radial MRI: Basics, Advances, and Applications. J Magn Reson Imaging 2022; 56:45-62. [PMID: 35396897 PMCID: PMC9189059 DOI: 10.1002/jmri.28187] [Citation(s) in RCA: 25] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Revised: 03/23/2022] [Accepted: 03/24/2022] [Indexed: 12/21/2022] Open
Abstract
In recent years, golden‐angle radial sampling has received substantial attention and interest in the magnetic resonance imaging (MRI) community, and it has become a popular sampling trajectory for both research and clinical use. However, although the number of relevant techniques and publications has grown rapidly, there is still a lack of a review paper that provides a comprehensive overview and summary of the basics of golden‐angle rotation, the advantages and challenges/limitations of golden‐angle radial sampling, and recommendations in using different types of golden‐angle radial trajectories for MRI applications. Such a review paper is expected to be helpful both for clinicians who are interested in learning the potential benefits of golden‐angle radial sampling and for MRI physicists who are interested in exploring this research direction. The main purpose of this review paper is thus to present an overview and summary about golden‐angle radial MRI sampling. The review consists of three sections. The first section aims to answer basic questions such as: what is a golden angle; how is the golden angle calculated; why is golden‐angle radial sampling useful, and what are its limitations. The second section aims to review more advanced trajectories of golden‐angle radial sampling, including tiny golden‐angle rotation, stack‐of‐stars golden‐angle radial sampling, and three‐dimensional (3D) kooshball golden‐angle radial sampling. Their respective advantages and limitations and potential solutions to address these limitations are also discussed. Finally, the third section reviews MRI applications that can benefit from golden‐angle radial sampling and provides recommendations to readers who are interested in implementing golden‐angle radial trajectories in their MRI studies.
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Affiliation(s)
- Li Feng
- BioMedical Engineering and Imaging Institute (BMEII) and Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
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30
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Assessment of Non-contrast-enhanced Dixon Water-fat Separation Compressed Sensing Whole-heart Coronary MR Angiography at 3.0 T: A Single-center Experience. Acad Radiol 2022; 29 Suppl 4:S82-S90. [PMID: 34127363 DOI: 10.1016/j.acra.2021.05.009] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2021] [Revised: 05/08/2021] [Accepted: 05/11/2021] [Indexed: 11/23/2022]
Abstract
RATIONALE AND OBJECTIVES The clinical utility of Dixon water-fat separation coronary MR angiography (CMRA) with compressed sensing (CS) reconstruction has not been determined in a patient population. This study was designed to evaluate the performance of 3.0 T non-contrast-enhanced Dixon water-fat separation CS whole-heart CMRA sequence in vitro and in vivo. MATERIALS AND METHODS In vitro phantom MRI, we compared key parameters of the SENSE and CS images. And in this prospective in vivo study, from November 2019 to October 2020, 94 participants were recruited for 3.0 T non-contrast-enhanced Dixon water-fat separation CS whole-heart CMRA. The accuracy of CMRA for detecting a ≥ 50% reduction in diameter was determined using X-ray coronary angiography (CA) as the reference method. RESULTS Compared with SENSE, CS with an appropriate acceleration factor offers both higher SNR/CNR (p < 0.05) and a shortened acquisition. Fifty-eight patients successfully completed the CMRA and CA. The sensitivity, specificity, positive predictive values, negative predictive values, and accuracy of 3.0 T non-contrast-enhanced Dixon water-fat separation CS whole-heart CMRA according to a patient-based analysis were 96.4%, 66.7%, 73.0%, 95.2% and 81.0%, respectively. The area under the receiver-operator characteristic (ROC) curve (AUC) of 3.0 T non-contrast-enhanced Dixon water-fat separation CS whole-heart CMRA for detecting significant coronary artery stenosis is 0.908, 0.895, and 0.904 in patient-, vessel-, and segment-based analyses respectively. CONCLUSION 3.0 T non-contrast-enhanced Dixon water-fat separation whole-heart CMRA using appropriate CS is a promising noninvasive and radiation-free technique to detect clinically significant coronary stenosis on patients with suspected CAD.
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Ismail TF, Strugnell W, Coletti C, Božić-Iven M, Weingärtner S, Hammernik K, Correia T, Küstner T. Cardiac MR: From Theory to Practice. Front Cardiovasc Med 2022; 9:826283. [PMID: 35310962 PMCID: PMC8927633 DOI: 10.3389/fcvm.2022.826283] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Accepted: 01/17/2022] [Indexed: 01/10/2023] Open
Abstract
Cardiovascular disease (CVD) is the leading single cause of morbidity and mortality, causing over 17. 9 million deaths worldwide per year with associated costs of over $800 billion. Improving prevention, diagnosis, and treatment of CVD is therefore a global priority. Cardiovascular magnetic resonance (CMR) has emerged as a clinically important technique for the assessment of cardiovascular anatomy, function, perfusion, and viability. However, diversity and complexity of imaging, reconstruction and analysis methods pose some limitations to the widespread use of CMR. Especially in view of recent developments in the field of machine learning that provide novel solutions to address existing problems, it is necessary to bridge the gap between the clinical and scientific communities. This review covers five essential aspects of CMR to provide a comprehensive overview ranging from CVDs to CMR pulse sequence design, acquisition protocols, motion handling, image reconstruction and quantitative analysis of the obtained data. (1) The basic MR physics of CMR is introduced. Basic pulse sequence building blocks that are commonly used in CMR imaging are presented. Sequences containing these building blocks are formed for parametric mapping and functional imaging techniques. Commonly perceived artifacts and potential countermeasures are discussed for these methods. (2) CMR methods for identifying CVDs are illustrated. Basic anatomy and functional processes are described to understand the cardiac pathologies and how they can be captured by CMR imaging. (3) The planning and conduct of a complete CMR exam which is targeted for the respective pathology is shown. Building blocks are illustrated to create an efficient and patient-centered workflow. Further strategies to cope with challenging patients are discussed. (4) Imaging acceleration and reconstruction techniques are presented that enable acquisition of spatial, temporal, and parametric dynamics of the cardiac cycle. The handling of respiratory and cardiac motion strategies as well as their integration into the reconstruction processes is showcased. (5) Recent advances on deep learning-based reconstructions for this purpose are summarized. Furthermore, an overview of novel deep learning image segmentation and analysis methods is provided with a focus on automatic, fast and reliable extraction of biomarkers and parameters of clinical relevance.
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Affiliation(s)
- Tevfik F. Ismail
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
- Cardiology Department, Guy's and St Thomas' Hospital, London, United Kingdom
| | - Wendy Strugnell
- Queensland X-Ray, Mater Hospital Brisbane, Brisbane, QLD, Australia
| | - Chiara Coletti
- Magnetic Resonance Systems Lab, Delft University of Technology, Delft, Netherlands
| | - Maša Božić-Iven
- Magnetic Resonance Systems Lab, Delft University of Technology, Delft, Netherlands
- Computer Assisted Clinical Medicine, Heidelberg University, Mannheim, Germany
| | | | - Kerstin Hammernik
- Lab for AI in Medicine, Technical University of Munich, Munich, Germany
- Department of Computing, Imperial College London, London, United Kingdom
| | - Teresa Correia
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
- Centre of Marine Sciences, Faro, Portugal
| | - Thomas Küstner
- Medical Image and Data Analysis (MIDAS.lab), Department of Diagnostic and Interventional Radiology, University Hospital of Tübingen, Tübingen, Germany
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Yoo J, Jin KH, Gupta H, Yerly J, Stuber M, Unser M. Time-Dependent Deep Image Prior for Dynamic MRI. IEEE TRANSACTIONS ON MEDICAL IMAGING 2021; 40:3337-3348. [PMID: 34043506 DOI: 10.1109/tmi.2021.3084288] [Citation(s) in RCA: 31] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
We propose a novel unsupervised deep-learning-based algorithm for dynamic magnetic resonance imaging (MRI) reconstruction. Dynamic MRI requires rapid data acquisition for the study of moving organs such as the heart. We introduce a generalized version of the deep-image-prior approach, which optimizes the weights of a reconstruction network to fit a sequence of sparsely acquired dynamic MRI measurements. Our method needs neither prior training nor additional data. In particular, for cardiac images, it does not require the marking of heartbeats or the reordering of spokes. The key ingredients of our method are threefold: 1) a fixed low-dimensional manifold that encodes the temporal variations of images; 2) a network that maps the manifold into a more expressive latent space; and 3) a convolutional neural network that generates a dynamic series of MRI images from the latent variables and that favors their consistency with the measurements in k -space. Our method outperforms the state-of-the-art methods quantitatively and qualitatively in both retrospective and real fetal cardiac datasets. To the best of our knowledge, this is the first unsupervised deep-learning-based method that can reconstruct the continuous variation of dynamic MRI sequences with high spatial resolution.
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Hong K, Schiffers F, DiCarlo AL, Rigsby CK, Haji-Valizadeh H, Lee DC, Markl M, Katsaggelos AK, Kim D. Accelerating compressed sensing reconstruction of subsampled radial k-space data using geometrically-derived density compensation. Phys Med Biol 2021; 66. [PMID: 34607316 DOI: 10.1088/1361-6560/ac2c9d] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2021] [Accepted: 10/04/2021] [Indexed: 11/12/2022]
Abstract
Objective.To accelerate compressed sensing (CS) reconstruction of subsampled radial k-space data using a geometrically-derived density compensation function (gDCF) without significant loss in image quality.Approach.We developed a theoretical framework to calculate a gDCF based on Nyquist distance along the radial and circumferential directions of a discrete polar coordinate system. Our gDCF was compared against standard DCF (e.g. ramp filter) and another commonly used DCF (modified Shepp-Logan (SL) filter). The resulting image quality produced by each DCF was quantified using normalized root-mean-square-error (NRMSE), blur metric (1 = blurriest; 0 = sharpest), and structural similarity index (SSIM; 1 = perfect match; 0 = no match) compared with the reference. For filtered backprojection (FBP) of phantom data obtained at the Nyquist sampling rate, Cartesian k-space sampling was used as the reference. For CS reconstruction of subsampled cardiac magnetic resonance imaging datasets (real-time cardiac cine data with 11 projections per frame,n = 20 patients; cardiac perfusion data with 30 projections per frame,n = 19 patients), CS reconstruction without DCF was used as the reference.Main results.The NRMSE, SSIM, and blur metrics of the phantom data were good for all DCFs, confirming that our gDCF produces uniform densities at the upper limit (Nyquist). For CS reconstruction of subsampled real-time cine and cardiac perfusion datasets, the image quality metrics (SSIM, NRMSE) were significantly (p < 0.05) higher for our gDCF than other DCFs, and the reconstruction time was significantly (p < 0.05) faster for our gDCF (reference) than no DCF (11.9%-52.9% slower), standard DCF (23.9%-57.6% slower), and modified SL filter (13.5%-34.8% slower).Significance.The proposed gDCF accelerates CS reconstruction of subsampled radial k-space data without significant loss in image quality compared with no DCF as the reference.
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Affiliation(s)
- KyungPyo Hong
- Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Illinois, United States of America
| | - Florian Schiffers
- Department of Computer Science, McCormick School of Engineering and Applied Science, Northwestern University, Evanston, Illinois, United States of America
| | - Amanda L DiCarlo
- Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Illinois, United States of America
| | - Cynthia K Rigsby
- Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Illinois, United States of America.,Department of Medical Imaging, Ann & Robert H. Lurie Children's Hospital of Chicago, Chicago, Illinois, United States of America
| | - Hassan Haji-Valizadeh
- Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Illinois, United States of America
| | - Daniel C Lee
- Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Illinois, United States of America.,Department of Medicine, Division of Cardiology, Northwestern University Feinberg School of Medicine, Chicago, Illinois, United States of America
| | - Michael Markl
- Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Illinois, United States of America.,Department of Biomedical Engineering, McCormick School of Engineering, Northwestern University, Evanston, Illinois, United States of America
| | - Aggelos K Katsaggelos
- Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Illinois, United States of America.,Department of Computer Science, McCormick School of Engineering and Applied Science, Northwestern University, Evanston, Illinois, United States of America.,Department of Electrical and Computer Engineering, McCormick School of Engineering and Applied Science, Northwestern University, Evanston, Illinois, United States of America
| | - Daniel Kim
- Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Illinois, United States of America.,Department of Biomedical Engineering, McCormick School of Engineering, Northwestern University, Evanston, Illinois, United States of America
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Armstrong T, Zhong X, Shih SF, Felker E, Lu DS, Dale BM, Wu HH. Free-breathing 3D stack-of-radial MRI quantification of liver fat and R 2* in adults with fatty liver disease. Magn Reson Imaging 2021; 85:141-152. [PMID: 34662702 DOI: 10.1016/j.mri.2021.10.016] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2021] [Revised: 10/07/2021] [Accepted: 10/12/2021] [Indexed: 02/07/2023]
Abstract
PURPOSE To investigate the agreement, intra-session repeatability, and inter-reader agreement of liver proton-density fat fraction (PDFF) and R2* quantification using free-breathing 3D stack-of-radial MRI, with and without self-gated motion compensation, compared to reference breath-hold techniques in subjects with fatty liver disease (FLD). METHODS In this institutional review board-approved prospective study, thirty-eight adults with FLD and/or iron overload (24 male, 58 ± 12 years) were imaged at 3T using free-breathing stack-of-radial MRI, breath-hold 3D Cartesian MRI, and breath-hold single-voxel MR spectroscopy (SVS). Each sequence was acquired twice in random order. To assess agreement compared to reference breath-hold techniques, the dependency of liver PDFF and/or R2* quantification on the sequence, radial sampling factor, and radial self-gating temporal resolution was assessed by calculating the Bayesian mean difference (MDB) of the posteriors. Intra-session repeatability and inter-reader agreement (two independent readers) were assessed by the coefficient of repeatability (CR) and intraclass correlation coefficient (ICC), respectively. RESULTS Thirty-five participants (21 male, 57 ± 12 years) were included for analysis. Both free-breathing radial MRI techniques (with and without self-gating) achieved ICC ≥ 0.92 for quantifying PDFF and R2*, and quantified PDFF with MDB < 1.2% compared to breath-hold techniques. Free-breathing radial MRI required self-gating to accurately quantify R2* (MDB < 10s-1 with self-gating; MDB < 50s-1 without self-gating). The radial sampling factor affected PDFF and R2* quantification while the radial self-gating temporal resolution only affected R2* quantification. Repeated self-gated free-breathing radial MRI scans achieved CR < 3% and CR < 27 s-1 for PDFF and R2*, respectively. CONCLUSION A free-breathing stack-of-radial MRI technique with self-gating demonstrated agreement, repeatability, and inter-reader agreement compared to reference breath-hold techniques for quantification of liver PDFF and R2* in adults with FLD.
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Affiliation(s)
- Tess Armstrong
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, United States
| | - Xiaodong Zhong
- MR R&D Collaborations, Siemens Medical Solutions USA, Inc., Los Angeles, CA, United States
| | - Shu-Fu Shih
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, United States; Department of Bioengineering, University of California Los Angeles, Los Angeles, CA, United States
| | - Ely Felker
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, United States
| | - David S Lu
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, United States
| | - Brian M Dale
- MR R&D Collaborations, Siemens Medical Solutions USA, Inc., Cary, NC, United States
| | - Holden H Wu
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, United States; Department of Bioengineering, University of California Los Angeles, Los Angeles, CA, United States.
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Terpstra ML, Maspero M, Bruijnen T, Verhoeff JJC, Lagendijk JJW, van den Berg CAT. Real-time 3D motion estimation from undersampled MRI using multi-resolution neural networks. Med Phys 2021; 48:6597-6613. [PMID: 34525223 PMCID: PMC9298075 DOI: 10.1002/mp.15217] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2021] [Revised: 08/12/2021] [Accepted: 08/30/2021] [Indexed: 12/25/2022] Open
Abstract
Purpose: To enable real‐time adaptive magnetic resonance imaging–guided radiotherapy (MRIgRT) by obtaining time‐resolved three‐dimensional (3D) deformation vector fields (DVFs) with high spatiotemporal resolution and low latency (<500 ms). Theory and Methods: Respiratory‐resolved T1‐weighted 4D‐MRI of 27 patients with lung cancer were acquired using a golden‐angle radial stack‐of‐stars readout. A multiresolution convolutional neural network (CNN) called TEMPEST was trained on up to 32× retrospectively undersampled MRI of 17 patients, reconstructed with a nonuniform fast Fourier transform, to learn optical flow DVFs. TEMPEST was validated using 4D respiratory‐resolved MRI, a digital phantom, and a physical motion phantom. The time‐resolved motion estimation was evaluated in‐vivo using two volunteer scans, acquired on a hybrid MR‐scanner with integrated linear accelerator. Finally, we evaluated the model robustness on a publicly‐available four‐dimensional computed tomography (4D‐CT) dataset. Results: TEMPEST produced accurate DVFs on respiratory‐resolved MRI at 20‐fold acceleration, with the average end‐point‐error <2 mm, both on respiratory‐sorted MRI and on a digital phantom. TEMPEST estimated accurate time‐resolved DVFs on MRI of a motion phantom, with an error <2 mm at 28× undersampling. On two volunteer scans, TEMPEST accurately estimated motion compared to the self‐navigation signal using 50 spokes per dynamic (366× undersampling). At this undersampling factor, DVFs were estimated within 200 ms, including MRI acquisition. On fully sampled CT data, we achieved a target registration error of 1.87±1.65 mm without retraining the model. Conclusion: A CNN trained on undersampled MRI produced accurate 3D DVFs with high spatiotemporal resolution for MRIgRT.
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Affiliation(s)
- Maarten L Terpstra
- Department of Radiotherapy, University Medical Center Utrecht, Utrecht, The Netherlands.,Computational Imaging Group for MR Diagnostics & Therapy, Center for Image Sciences, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Matteo Maspero
- Department of Radiotherapy, University Medical Center Utrecht, Utrecht, The Netherlands.,Computational Imaging Group for MR Diagnostics & Therapy, Center for Image Sciences, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Tom Bruijnen
- Department of Radiotherapy, University Medical Center Utrecht, Utrecht, The Netherlands.,Computational Imaging Group for MR Diagnostics & Therapy, Center for Image Sciences, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Joost J C Verhoeff
- Department of Radiotherapy, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Jan J W Lagendijk
- Department of Radiotherapy, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Cornelis A T van den Berg
- Department of Radiotherapy, University Medical Center Utrecht, Utrecht, The Netherlands.,Computational Imaging Group for MR Diagnostics & Therapy, Center for Image Sciences, University Medical Center Utrecht, Utrecht, The Netherlands
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Shoghi KI, Badea CT, Blocker SJ, Chenevert TL, Laforest R, Lewis MT, Luker GD, Manning HC, Marcus DS, Mowery YM, Pickup S, Richmond A, Ross BD, Vilgelm AE, Yankeelov TE, Zhou R. Co-Clinical Imaging Resource Program (CIRP): Bridging the Translational Divide to Advance Precision Medicine. ACTA ACUST UNITED AC 2021; 6:273-287. [PMID: 32879897 PMCID: PMC7442091 DOI: 10.18383/j.tom.2020.00023] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
The National Institutes of Health’s (National Cancer Institute) precision medicine initiative emphasizes the biological and molecular bases for cancer prevention and treatment. Importantly, it addresses the need for consistency in preclinical and clinical research. To overcome the translational gap in cancer treatment and prevention, the cancer research community has been transitioning toward using animal models that more fatefully recapitulate human tumor biology. There is a growing need to develop best practices in translational research, including imaging research, to better inform therapeutic choices and decision-making. Therefore, the National Cancer Institute has recently launched the Co-Clinical Imaging Research Resource Program (CIRP). Its overarching mission is to advance the practice of precision medicine by establishing consensus-based best practices for co-clinical imaging research by developing optimized state-of-the-art translational quantitative imaging methodologies to enable disease detection, risk stratification, and assessment/prediction of response to therapy. In this communication, we discuss our involvement in the CIRP, detailing key considerations including animal model selection, co-clinical study design, need for standardization of co-clinical instruments, and harmonization of preclinical and clinical quantitative imaging pipelines. An underlying emphasis in the program is to develop best practices toward reproducible, repeatable, and precise quantitative imaging biomarkers for use in translational cancer imaging and therapy. We will conclude with our thoughts on informatics needs to enable collaborative and open science research to advance precision medicine.
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Affiliation(s)
- Kooresh I Shoghi
- Department of Radiology, Washington University School of Medicine, St. Louis, MO
| | - Cristian T Badea
- Department of Radiology, Center for In Vivo Microscopy, Duke University Medical Center, Durham, NC
| | - Stephanie J Blocker
- Department of Radiology, Center for In Vivo Microscopy, Duke University Medical Center, Durham, NC
| | | | - Richard Laforest
- Department of Radiology, Washington University School of Medicine, St. Louis, MO
| | - Michael T Lewis
- Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX
| | - Gary D Luker
- Department of Radiology, University of Michigan, Ann Arbor, MI
| | - H Charles Manning
- Vanderbilt Center for Molecular Probes-Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN
| | - Daniel S Marcus
- Department of Radiology, Washington University School of Medicine, St. Louis, MO
| | - Yvonne M Mowery
- Department of Radiation Oncology, Duke University Medical Center, Durham, Durham, NC
| | - Stephen Pickup
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania.,Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA
| | - Ann Richmond
- Department of Pharmacology, Vanderbilt School of Medicine, Nashville, TN
| | - Brian D Ross
- Department of Radiology, University of Michigan, Ann Arbor, MI
| | - Anna E Vilgelm
- Department of Pathology, The Ohio State University, Columbus, OH
| | - Thomas E Yankeelov
- Departments of Biomedical Engineering, Diagnostic Medicine, and Oncology, Oden Institute for Computational Engineering and Sciences, Austin, TX; and.,Livestrong Cancer Institutes, Dell Medical School, The University of Texas at Austin, Austin, TX
| | - Rong Zhou
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania.,Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA
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Hoppe E, Wetzl J, Yoon SS, Bacher M, Roser P, Stimpel B, Preuhs A, Maier A. Deep Learning-Based ECG-Free Cardiac Navigation for Multi-Dimensional and Motion-Resolved Continuous Magnetic Resonance Imaging. IEEE TRANSACTIONS ON MEDICAL IMAGING 2021; 40:2105-2117. [PMID: 33848244 DOI: 10.1109/tmi.2021.3073091] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
For the clinical assessment of cardiac vitality, time-continuous tomographic imaging of the heart is used. To further detect e.g., pathological tissue, multiple imaging contrasts enable a thorough diagnosis using magnetic resonance imaging (MRI). For this purpose, time-continous and multi-contrast imaging protocols were proposed. The acquired signals are binned using navigation approaches for a motion-resolved reconstruction. Mostly, external sensors such as electrocardiograms (ECG) are used for navigation, leading to additional workflow efforts. Recent sensor-free approaches are based on pipelines requiring prior knowledge, e.g., typical heart rates. We present a sensor-free, deep learning-based navigation that diminishes the need for manual feature engineering or the necessity of prior knowledge compared to previous works. A classifier is trained to estimate the R-wave timepoints in the scan directly from the imaging data. Our approach is evaluated on 3-D protocols for continuous cardiac MRI, acquired in-vivo and free-breathing with single or multiple imaging contrasts. We achieve an accuracy of > 98% on previously unseen subjects, and a well comparable image quality with the state-of-the-art ECG-based reconstruction. Our method enables an ECG-free workflow for continuous cardiac scans with simultaneous anatomic and functional imaging with multiple contrasts. It can be potentially integrated without adapting the sampling scheme to other continuous sequences by using the imaging data for navigation and reconstruction.
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Lyu Q, Shan H, Xie Y, Kwan AC, Otaki Y, Kuronuma K, Li D, Wang G. Cine Cardiac MRI Motion Artifact Reduction Using a Recurrent Neural Network. IEEE TRANSACTIONS ON MEDICAL IMAGING 2021; 40:2170-2181. [PMID: 33856986 PMCID: PMC8376223 DOI: 10.1109/tmi.2021.3073381] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/17/2023]
Abstract
Cine cardiac magnetic resonance imaging (MRI) is widely used for the diagnosis of cardiac diseases thanks to its ability to present cardiovascular features in excellent contrast. As compared to computed tomography (CT), MRI, however, requires a long scan time, which inevitably induces motion artifacts and causes patients' discomfort. Thus, there has been a strong clinical motivation to develop techniques to reduce both the scan time and motion artifacts. Given its successful applications in other medical imaging tasks such as MRI super-resolution and CT metal artifact reduction, deep learning is a promising approach for cardiac MRI motion artifact reduction. In this paper, we propose a novel recurrent generative adversarial network model for cardiac MRI motion artifact reduction. This model utilizes bi-directional convolutional long short-term memory (ConvLSTM) and multi-scale convolutions to improve the performance of the proposed network, in which bi-directional ConvLSTMs handle long-range temporal features while multi-scale convolutions gather both local and global features. We demonstrate a decent generalizability of the proposed method thanks to the novel architecture of our deep network that captures the essential relationship of cardiovascular dynamics. Indeed, our extensive experiments show that our method achieves better image quality for cine cardiac MRI images than existing state-of-the-art methods. In addition, our method can generate reliable missing intermediate frames based on their adjacent frames, improving the temporal resolution of cine cardiac MRI sequences.
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Kobayashi N. Magnetic resonance imaging with gradient sound respiration guide. PLoS One 2021; 16:e0254758. [PMID: 34280236 PMCID: PMC8289037 DOI: 10.1371/journal.pone.0254758] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2020] [Accepted: 07/03/2021] [Indexed: 12/31/2022] Open
Abstract
Respiratory motion management is crucial for high-resolution MRI of the heart, lung, liver and kidney. In this article, respiration guide using acoustic sound generated by pulsed gradient waveforms was introduced in the pulmonary ultrashort echo time (UTE) sequence and validated by comparing with retrospective respiratory gating techniques. The validated sound-guided respiration was implemented in non-contrast enhanced renal angiography. In the sound-guided respiration, breathe−in and–out instruction sounds were generated with sinusoidal gradient waveforms with two different frequencies (602 and 321 Hz). Performance of the sound-guided respiration was evaluated by measuring sharpness of the lung-liver interface with a 10–90% rise distance, w10-90, and compared with three respiratory motion managements in a free-breathing UTE scan: without respiratory gating (w/o gating), 0-dimensional k-space navigator (k-point navigator), and image-based self-gating (Img-SG). The sound-guided respiration was implemented in stack-of-stars balanced steady-state free precession with inversion recovery preparation for renal angiography. No subjects reported any discomfort or inconvenience with the sound-guided respiration in pulmonary or renal MRI scans. The lung-liver interface of the UTE images for sound-guided respiration (w10-90 = 6.99 ± 2.90 mm), k-point navigator (8.51 ± 2.71 mm), and Img-SG (7.01 ± 2.06 mm) was significantly sharper than that for w/o gating (17.13 ± 2.91 mm; p < 0.0001 for all of sound-guided respiration, k-point navigator and Img-SG). Sharpness of the lung-liver interface was comparable between sound-guided respiration and Img-SG (p = 0.99), but sound-guided respiration achieved better visualization of pulmonary vasculature. Renal angiography with the sound-guided respiration clearly delineated renal, segmental and interlobar arteries. In conclusion, the gradient sound guided respiration can facilitate a consistent diaphragm position in every breath and achieve performance of respiratory motion management comparable to image-based self-gating.
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Affiliation(s)
- Naoharu Kobayashi
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, United States of America
- * E-mail:
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Feng L, Liu F, Soultanidis G, Liu C, Benkert T, Block KT, Fayad ZA, Yang Y. Magnetization-prepared GRASP MRI for rapid 3D T1 mapping and fat/water-separated T1 mapping. Magn Reson Med 2021; 86:97-114. [PMID: 33580909 PMCID: PMC8197608 DOI: 10.1002/mrm.28679] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2020] [Revised: 12/18/2020] [Accepted: 12/22/2020] [Indexed: 12/22/2022]
Abstract
PURPOSE This study aimed to (i) develop Magnetization-Prepared Golden-angle RAdial Sparse Parallel (MP-GRASP) MRI using a stack-of-stars trajectory for rapid free-breathing T1 mapping and (ii) extend MP-GRASP to multi-echo acquisition (MP-Dixon-GRASP) for fat/water-separated (water-specific) T1 mapping. METHODS An adiabatic non-selective 180° inversion-recovery pulse was added to a gradient-echo-based golden-angle stack-of-stars sequence for magnetization-prepared 3D single-echo or 3D multi-echo acquisition. In combination with subspace-based GRASP-Pro reconstruction, the sequence allows for standard T1 mapping (MP-GRASP) or fat/water-separated T1 mapping (MP-Dixon-GRASP), respectively. The accuracy of T1 mapping using MP-GRASP was evaluated in a phantom and volunteers (brain and liver) against clinically accepted reference methods. The repeatability of T1 estimation was also assessed in the phantom and volunteers. The performance of MP-Dixon-GRASP for water-specific T1 mapping was evaluated in a fat/water phantom and volunteers (brain and liver). RESULTS ROI-based mean T1 values are correlated between the references and MP-GRASP in the phantom (R2 = 1.0), brain (R2 = 0.96), and liver (R2 = 0.73). MP-GRASP achieved good repeatability of T1 estimation in the phantom (R2 = 1.0), brain (R2 = 0.99), and liver (R2 = 0.82). Water-specific T1 is different from in-phase and out-of-phase composite T1 (composite T1 when fat and water signal are mixed in phase or out of phase) both in the phantom and volunteers. CONCLUSION This work demonstrated the initial performance of MP-GRASP and MP-Dixon-GRASP MRI for rapid 3D T1 mapping and 3D fat/water-separated T1 mapping in the brain (without motion) and in the liver (during free breathing). With fat/water-separated T1 estimation, MP-Dixon-GRASP could be potentially useful for imaging patients with fatty-liver diseases.
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Affiliation(s)
- Li Feng
- Biomedical Engineering and Imaging Institute and Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Fang Liu
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Georgios Soultanidis
- Biomedical Engineering and Imaging Institute and Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Chenyu Liu
- Biomedical Engineering and Imaging Institute and Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Thomas Benkert
- MR Application Development, Siemens Healthcare GmbH, Erlangen, Germany
| | - Kai Tobias Block
- MR Application Development, Siemens Healthcare GmbH, Erlangen, Germany
- Center for Advanced Imaging Innovation and Research (CAIR), New York University School of Medicine, New York, NY, USA
| | - Zahi A. Fayad
- Biomedical Engineering and Imaging Institute and Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Yang Yang
- Biomedical Engineering and Imaging Institute and Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
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Kim PK, Hong YJ, Shim HS, Im DJ, Suh YJ, Lee KH, Hur J, Kim YJ, Choi BW, Lee HJ. Serial T1 mapping of right ventricle in pulmonary hypertension: comparison with histology in an animal study. J Cardiovasc Magn Reson 2021; 23:64. [PMID: 34039372 PMCID: PMC8157452 DOI: 10.1186/s12968-021-00755-y] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2020] [Accepted: 04/06/2021] [Indexed: 11/16/2022] Open
Abstract
BACKGROUND Right ventricular (RV) free wall fibrosis is an important component of adverse remodeling with RV dysfunction in pulmonary hypertension (PH). However, no previous reports have compared cardiovascular magnetic resonance (CMR) findings and histological analysis for RV free wall fibrosis in PH. We aimed to assess the feasibility of CMR T1 mapping with extracellular volume fraction (ECV) for evaluating the progression of RV free wall fibrosis in PH, and compared imaging findings to histological collagen density through an animal study. METHODS Among 42 6-week-old Wistar male rats, 30 were classified according to disease duration (baseline before monocrotaline injection, and 2, 4, 6 and 8 weeks after injection) and 12 were used to control for aging (4 and 8 weeks after the baseline). We obtained pre and post-contrast T1 maps for native T1 and ECV of RV and left ventricular (LV) free wall for six animals in each disease-duration group. Collagen density of RV free wall was calculated with Masson's trichrome staining. The Kruskall-Wallis test was performed to compare the groups. Native T1 and ECV to collagen density were analyzed with Spearman's correlation. RESULTS The mean values of native T1, ECV and collagen density of the RV free wall at baseline were 1541 ± 33 ms, 17.2 ± 1.3%, and 4.7 ± 0.5%, respectively. The values of RV free wall did not differ according to aging (P = 0.244, 0.504 and 0.331, respectively). However, the values significantly increased according to disease duration (P < 0.001 for all). Significant correlations were observed between native T1 and collagen density (r = 0.770, P < 0.001), and between ECV and collagen density for the RV free wall (r = 0.815, P < 0.001) in PH. However, there was no significant difference in native T1 and ECV values for the LV free wall according to the disease duration from the baseline (P = 0.349 and 0.240, respectively). CONCLUSIONS We observed significantly increased values for native T1 and ECV of the RV free wall without significant increase of the LV free wall according to the disease duration of PH, and findings were well correlated with histological collagen density.
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Affiliation(s)
- Pan Ki Kim
- Department of Radiology, Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 03722, South Korea
| | - Yoo Jin Hong
- Department of Radiology, Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 03722, South Korea
| | - Hyo Sub Shim
- Department of Pathology, Severance Hospital, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 03722, South Korea
| | - Dong Jin Im
- Department of Radiology, Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 03722, South Korea
| | - Young Joo Suh
- Department of Radiology, Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 03722, South Korea
| | - Kye Ho Lee
- Department of Radiology, Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 03722, South Korea
| | - Jin Hur
- Department of Radiology, Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 03722, South Korea
| | - Young Jin Kim
- Department of Radiology, Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 03722, South Korea
| | - Byoung Wook Choi
- Department of Radiology, Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 03722, South Korea
| | - Hye-Jeong Lee
- Department of Radiology, Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 03722, South Korea.
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Godino-Moya A, Menchón-Lara RM, Martín-Fernández M, Prieto C, Alberola-López C. Elastic AlignedSENSE for Dynamic MR Reconstruction: A Proof of Concept in Cardiac Cine. ENTROPY 2021; 23:e23050555. [PMID: 33947089 PMCID: PMC8145958 DOI: 10.3390/e23050555] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/29/2021] [Revised: 04/26/2021] [Accepted: 04/27/2021] [Indexed: 11/25/2022]
Abstract
Numerous methods in the extensive literature on magnetic resonance imaging (MRI) reconstruction exploit temporal redundancy to accelerate cardiac cine. Some of them include motion compensation, which involves high computational costs and long runtimes. In this work, we proposed a method—elastic alignedSENSE (EAS)—for the direct reconstruction of a motion-free image plus a set of nonrigid deformations to reconstruct a 2D cardiac sequence. The feasibility of the proposed approach was tested in 2D Cartesian and golden radial multi-coil breath-hold cardiac cine acquisitions. The proposed approach was compared against parallel imaging compressed sense (sPICS) and group-wise motion corrected compressed sense (GWCS) reconstructions. EAS provides better results on objective measures with considerable less runtime when an acceleration factor is higher than 10×. Subjective assessment of an expert, however, invited proposing the combination of EAS and GWCS as a preferable alternative to GWCS or EAS in isolation.
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Affiliation(s)
- Alejandro Godino-Moya
- Laboratorio de Procesado de Imagen, E.T.S.I. Telecomunicación, Universidad de Valladolid, Paseo Belén 15, 47011 Valladolid, Spain; (R.-M.M.-L.); (M.M.-F.); (C.A.-L.)
- Correspondence:
| | - Rosa-María Menchón-Lara
- Laboratorio de Procesado de Imagen, E.T.S.I. Telecomunicación, Universidad de Valladolid, Paseo Belén 15, 47011 Valladolid, Spain; (R.-M.M.-L.); (M.M.-F.); (C.A.-L.)
| | - Marcos Martín-Fernández
- Laboratorio de Procesado de Imagen, E.T.S.I. Telecomunicación, Universidad de Valladolid, Paseo Belén 15, 47011 Valladolid, Spain; (R.-M.M.-L.); (M.M.-F.); (C.A.-L.)
| | - Claudia Prieto
- School of Biomedical Engineering and Imaging Sciences, King’s College London, London SE1 7EH, UK;
- School of Engineering, Pontificia Universidad Catolica de Chile, Santiago 4860, Chile
| | - Carlos Alberola-López
- Laboratorio de Procesado de Imagen, E.T.S.I. Telecomunicación, Universidad de Valladolid, Paseo Belén 15, 47011 Valladolid, Spain; (R.-M.M.-L.); (M.M.-F.); (C.A.-L.)
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von Kleist H, Buehrer M, Kozerke S, Saengsin K, Harrington JK, Powell AJ, Moghari MH. Cardiac self-gating using blind source separation for 2D cine cardiovascular magnetic resonance imaging. Magn Reson Imaging 2021; 81:42-52. [PMID: 33905835 DOI: 10.1016/j.mri.2021.04.008] [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: 01/10/2021] [Revised: 04/11/2021] [Accepted: 04/21/2021] [Indexed: 10/21/2022]
Abstract
PURPOSE To develop and validate a new cardiac self-gating algorithm using blind source separation for 2D cine steady-state free precession (SSFP) imaging. METHODS A standard cine SSFP sequence was modified so that the center point of k-space was sampled with each excitation. The center points of k-space were processed by 4 blind source separation methods, and used to detect heartbeats and assign k-space data to appropriate time points in the cardiac cycle. The proposed self-gating technique was prospectively validated in 8 patients against the standard electrocardiogram (ECG)-gating method by comparing the cardiac cycle lengths, image quality metrics, and ventricular volume measurements. RESULTS There was close agreement between the cardiac cycle length using the ECG- and self-gating methods (bias 0.0 bpm, 95% limits of agreement ±2.1 bpm). The image quality metrics were not significantly different between the ECG- and self-gated images. The ventricular volumes, stroke volumes, and mass measured from self-gated images were all comparable with those from ECG-gated images (all biases <5%). CONCLUSION The self-gating method yielded comparable cardiac cycle length, image quality, and ventricular measurements compared with standard ECG-gated cine imaging. It may simplify patient preparation, be more robust when there is arrhythmia, and allow cardiac gating at higher field strengths.
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Affiliation(s)
- Henrik von Kleist
- Department of Cardiology, Boston Children's Hospital, and Department of Pediatrics, Harvard Medical School, Boston, MA, USA; Department of Informatics, Technical University of Munich, Garching, Germany.
| | - Martin Buehrer
- Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland
| | - Sebastian Kozerke
- Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland
| | - Kwannapas Saengsin
- Department of Cardiology, Boston Children's Hospital, and Department of Pediatrics, Harvard Medical School, Boston, MA, USA
| | - Jamie K Harrington
- Department of Cardiology, Boston Children's Hospital, and Department of Pediatrics, Harvard Medical School, Boston, MA, USA
| | - Andrew J Powell
- Department of Cardiology, Boston Children's Hospital, and Department of Pediatrics, Harvard Medical School, Boston, MA, USA
| | - Mehdi H Moghari
- Department of Cardiology, Boston Children's Hospital, and Department of Pediatrics, Harvard Medical School, Boston, MA, USA
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Hu Z, van der Kouwe A, Han F, Xiao J, Chen J, Han H, Bi X, Li D, Fan Z. Motion-compensated 3D turbo spin-echo for more robust MR intracranial vessel wall imaging. Magn Reson Med 2021; 86:637-647. [PMID: 33768617 DOI: 10.1002/mrm.28777] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2020] [Revised: 01/31/2021] [Accepted: 02/27/2021] [Indexed: 12/31/2022]
Abstract
PURPOSE (1) To investigate the effect of internal localized movement on 3DMR intracranial vessel wall imaging and (2) to develop a novel motion-compensation approach combining volumetric navigator (vNav) and self-gating (SG) to simultaneously compensate for bulk and localized movements. METHODS A 3D variable-flip-angle turbo spin-echo (ie, SPACE) sequence was modified to incorporate vNav and SG modules. The SG signals from the center k-space line are acquired at the beginning of each TR to detect localized motion-affected TRs. The vNavs from low-resolution 3D EPI are acquired to identify bulk head motion. Fifteen healthy subjects and 3 stroke patients were recruited in this study. Overall image quality (0-poor to 4-excellent) and vessel wall sharpness were compared among the scenarios with and without bulk and/or localized motion and/or the proposed compensation strategies. RESULTS Localized motion reduced wall sharpness, which was significantly mitigated by SG (ie, outer boundary of basilar artery: 0.68 ± 0.27 vs 0.86 ± 0.17; P = .037). When motion occurred, the overall image quality and vessel wall sharpness obtained with vNav-SG SPACE were significantly higher than those obtained with conventional SPACE (ie, basilarartery outer boundary sharpness: 0.73 ± 0.24 vs 0.94 ± 0.24; P = .033), yet comparable to those obtained in motion-free scans (ie, basilarartery outer boundary sharpness: 0.94 ± 0.24 vs 0.96 ± 0.31; P = .815). CONCLUSION Localized movements can induce considerable artifacts in intracranial vessel wall imaging. The vNav-SG approach is capable of compensating for both bulk and localized motions.
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Affiliation(s)
- Zhehao Hu
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA.,Department of Bioengineering, University of California, Los Angeles, California, USA
| | - Andre van der Kouwe
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA.,Department of Radiology, Harvard Medical School, Brookline, Massachusetts, USA
| | - Fei Han
- Siemens Medical Solutions USA, Inc., Los Angeles, California, USA
| | - Jiayu Xiao
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - Junzhou Chen
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA.,Department of Bioengineering, University of California, Los Angeles, California, USA
| | - Hui Han
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - Xiaoming Bi
- Siemens Medical Solutions USA, Inc., Los Angeles, California, USA
| | - Debiao Li
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA.,Department of Bioengineering, University of California, Los Angeles, California, USA
| | - Zhaoyang Fan
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA.,Department of Radiology, University of Southern California Keck School of Medicine, Los Angeles, California, USA
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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: 1.0] [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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Ladrova M, Martinek R, Nedoma J, Hanzlikova P, Nelson MD, Kahankova R, Brablik J, Kolarik J. Monitoring and Synchronization of Cardiac and Respiratory Traces in Magnetic Resonance Imaging: A Review. IEEE Rev Biomed Eng 2021; 15:200-221. [PMID: 33513108 DOI: 10.1109/rbme.2021.3055550] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
Synchronization of human vital signs, namely the cardiac cycle and respiratory excursions, is necessary during magnetic resonance imaging of the cardiovascular system and the abdominal cavity to achieve optimal image quality with minimized artifacts. This review summarizes techniques currently available in clinical practice, as well as methods under development, outlines the benefits and disadvantages of each approach, and offers some unique solutions for consideration.
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Gentle Touch: Noninvasive Approaches to Improve Patient Comfort and Cooperation for Pediatric Imaging. Top Magn Reson Imaging 2021; 29:187-195. [PMID: 32541256 DOI: 10.1097/rmr.0000000000000245] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
Pediatric imaging presents unique challenges related to patient anxiety, cooperation, and safety. Techniques to reduce anxiety and patient motion in adults must often be augmented in pediatrics, because it is always mentioned in the field of pediatrics, children are not miniature adults. This article will review methods that can be considered to improve patient experience and cooperation in imaging studies. Such techniques can range from modifications to the scanner suite, different ways of preparing and interacting with children, collaborating with parents for improved patient care, and technical advances such as accelerated acquisition and motion correction to reduce artifact. Special considerations for specific populations including transgender patients, neonates, and pregnant women undergoing fetal imaging will be described. The unique risks of sedation in children will also be briefly reviewed.
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Wu YL. Cardiac MRI Assessment of Mouse Myocardial Infarction and Regeneration. Methods Mol Biol 2021; 2158:81-106. [PMID: 32857368 DOI: 10.1007/978-1-0716-0668-1_8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
Abstract
Small animal models are indispensable for cardiac regeneration research. Studies in mouse and rat models have provided important insights into the etiology and mechanisms of cardiovascular diseases and accelerated the development of therapeutic strategies. It is vitally important to be able to evaluate the therapeutic efficacy and have reliable surrogate markers for therapeutic development for cardiac regeneration research. Magnetic resonance imaging (MRI), a versatile and noninvasive imaging modality with excellent penetration depth, tissue coverage, and soft-tissue contrast, is becoming a more important tool in both clinical settings and research arenas. Cardiac MRI (CMR) is versatile, noninvasive, and capable of measuring many different aspects of cardiac functions, and, thus, is ideally suited to evaluate therapeutic efficacy for cardiac regeneration. CMR applications include assessment of cardiac anatomy, regional wall motion, myocardial perfusion, myocardial viability, cardiac function assessment, assessment of myocardial infarction, and myocardial injury. Myocardial infarction models in mice are commonly used model systems for cardiac regeneration research. In this chapter, we discuss various CMR applications to evaluate cardiac functions and inflammation after myocardial infarction.
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Affiliation(s)
- Yijen L Wu
- Department of Developmental Biology, Rangos Research Center Animal Imaging Core, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA.
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Preuhs A, Manhart M, Roser P, Hoppe E, Huang Y, Psychogios M, Kowarschik M, Maier A. Appearance Learning for Image-Based Motion Estimation in Tomography. IEEE TRANSACTIONS ON MEDICAL IMAGING 2020; 39:3667-3678. [PMID: 32746114 DOI: 10.1109/tmi.2020.3002695] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
In tomographic imaging, anatomical structures are reconstructed by applying a pseudo-inverse forward model to acquired signals. Geometric information within this process is usually depending on the system setting only, i.e., the scanner position or readout direction. Patient motion therefore corrupts the geometry alignment in the reconstruction process resulting in motion artifacts. We propose an appearance learning approach recognizing the structures of rigid motion independently from the scanned object. To this end, we train a siamese triplet network to predict the reprojection error (RPE) for the complete acquisition as well as an approximate distribution of the RPE along the single views from the reconstructed volume in a multi-task learning approach. The RPE measures the motion-induced geometric deviations independent of the object based on virtual marker positions, which are available during training. We train our network using 27 patients and deploy a 21-4-2 split for training, validation and testing. In average, we achieve a residual mean RPE of 0.013mm with an inter-patient standard deviation of 0.022mm. This is twice the accuracy compared to previously published results. In a motion estimation benchmark the proposed approach achieves superior results in comparison with two state-of-the-art measures in nine out of twelve experiments. The clinical applicability of the proposed method is demonstrated on a motion-affected clinical dataset.
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50
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Pezel T, Sanguineti F, Kinnel M, Landon V, Toupin S, Unterseeh T, Louvard Y, Champagne S, Morice MC, Hovasse T, Garot P, Garot J. Feasibility and Prognostic Value of Vasodilator Stress Perfusion CMR in Patients With Atrial Fibrillation. JACC Cardiovasc Imaging 2020; 14:379-389. [PMID: 33129729 DOI: 10.1016/j.jcmg.2020.07.041] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/14/2020] [Revised: 07/17/2020] [Accepted: 07/29/2020] [Indexed: 01/27/2023]
Abstract
OBJECTIVES The aim of this study was to assess the feasibility and prognostic value of vasodilator stress perfusion cardiovascular magnetic resonance (CMR) in patients with atrial fibrillation (AF). BACKGROUND Because most studies have excluded arrhythmic patients, the prognostic value of stress perfusion CMR in patients with AF is unknown. METHODS Between 2008 and 2018, consecutive patients with suspected or stable chronic coronary artery disease and AF referred for vasodilator stress perfusion CMR were included and followed for the occurrence of major adverse cardiovascular event(s) (MACE), defined as cardiovascular death or nonfatal myocardial infarction. The diagnosis of AF was defined by 12-lead electrocardiography before and after CMR. Univariate and multivariate Cox regressions were performed to determine the prognostic value of inducible ischemia or late gadolinium enhancement (LGE) by CMR. RESULTS Of 639 patients (mean age 72 ± 9 years, 77% men), 602 (94%) completed the CMR protocol, and 538 (89%) completed follow-up (median 5.1 years); 80 had MACE. Using Kaplan-Meier analysis, the presence of ischemia (hazard ratio [HR]: 7.56; 95% confidence interval [CI]: 4.86 to 11.80) or LGE (HR: 2.41; 95% CI: 1.55 to 3.74) was associated with the occurrence of MACE (p < 0.001 for both). In a multivariate Cox regression including clinical and CMR indexes, the presence of ischemia (HR: 5.98; 95% CI: 3.68 to 9.73) or LGE (HR: 2.61; 95% CI: 1.89 to 3.60) was an independent predictor of MACE (p < 0.001 for both). CONCLUSIONS In patients with AF, stress perfusion CMR is feasible and has good discriminative prognostic value to predict the occurrence of MACE.
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Affiliation(s)
- Théo Pezel
- Institut Cardiovasculaire Paris Sud, Cardiovascular Magnetic Resonance Laboratory, Hôpital Privé Jacques CARTIER, Ramsay Santé, Massy, France; Division of Cardiology, Johns Hopkins University, Baltimore, Maryland
| | - Francesca Sanguineti
- Institut Cardiovasculaire Paris Sud, Cardiovascular Magnetic Resonance Laboratory, Hôpital Privé Jacques CARTIER, Ramsay Santé, Massy, France
| | - Marine Kinnel
- Institut Cardiovasculaire Paris Sud, Cardiovascular Magnetic Resonance Laboratory, Hôpital Privé Jacques CARTIER, Ramsay Santé, Massy, France
| | - Valentin Landon
- Institut Cardiovasculaire Paris Sud, Cardiovascular Magnetic Resonance Laboratory, Hôpital Privé Jacques CARTIER, Ramsay Santé, Massy, France
| | | | - Thierry Unterseeh
- Institut Cardiovasculaire Paris Sud, Cardiovascular Magnetic Resonance Laboratory, Hôpital Privé Jacques CARTIER, Ramsay Santé, Massy, France
| | - Yves Louvard
- Institut Cardiovasculaire Paris Sud, Cardiovascular Magnetic Resonance Laboratory, Hôpital Privé Jacques CARTIER, Ramsay Santé, Massy, France
| | - Stéphane Champagne
- Institut Cardiovasculaire Paris Sud, Cardiovascular Magnetic Resonance Laboratory, Hôpital Privé Jacques CARTIER, Ramsay Santé, Massy, France
| | - Marie Claude Morice
- Institut Cardiovasculaire Paris Sud, Cardiovascular Magnetic Resonance Laboratory, Hôpital Privé Jacques CARTIER, Ramsay Santé, Massy, France
| | - Thomas Hovasse
- Institut Cardiovasculaire Paris Sud, Cardiovascular Magnetic Resonance Laboratory, Hôpital Privé Jacques CARTIER, Ramsay Santé, Massy, France
| | - Philippe Garot
- Institut Cardiovasculaire Paris Sud, Cardiovascular Magnetic Resonance Laboratory, Hôpital Privé Jacques CARTIER, Ramsay Santé, Massy, France
| | - Jérôme Garot
- Institut Cardiovasculaire Paris Sud, Cardiovascular Magnetic Resonance Laboratory, Hôpital Privé Jacques CARTIER, Ramsay Santé, Massy, France.
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