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Romanin L, Milani B, Roy CW, Yerly J, Bustin A, Si-mohamed S, Prsa M, Rutz T, Tenisch E, Schwitter J, Stuber M, Piccini D. Similarity-driven motion-resolved reconstruction for ferumoxytol-enhanced whole-heart MRI in congenital heart disease. PLoS One 2024; 19:e0304612. [PMID: 38870171 PMCID: PMC11175540 DOI: 10.1371/journal.pone.0304612] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2023] [Accepted: 05/15/2024] [Indexed: 06/15/2024] Open
Abstract
A similarity-driven multi-dimensional binning algorithm (SIMBA) reconstruction of free-running cardiac magnetic resonance imaging data was previously proposed. While very efficient and fast, the original SIMBA focused only on the reconstruction of a single motion-consistent cluster, discarding the remaining data acquired. However, the redundant data clustered by similarity may be exploited to further improve image quality. In this work, we propose a novel compressed sensing (CS) reconstruction that performs an effective regularization over the clustering dimension, thanks to the integration of inter-cluster motion compensation (XD-MC-SIMBA). This reconstruction was applied to free-running ferumoxytol-enhanced datasets from 24 patients with congenital heart disease, and compared to the original SIMBA, the same XD-MC-SIMBA reconstruction but without motion compensation (XD-SIMBA), and a 5D motion-resolved CS reconstruction using the free-running framework (FRF). The resulting images were compared in terms of lung-liver and blood-myocardium sharpness, blood-myocardium contrast ratio, and visible length and sharpness of the coronary arteries. Moreover, an automated image quality score (IQS) was assigned using a pretrained deep neural network. The lung-liver sharpness and blood-myocardium sharpness were significantly higher in XD-MC-SIMBA and FRF. Consistent with these findings, the IQS analysis revealed that image quality for XD-MC-SIMBA was improved in 18 of 24 cases, compared to SIMBA. We successfully tested the hypothesis that multiple motion-consistent SIMBA clusters can be exploited to improve the quality of ferumoxytol-enhanced cardiac MRI when inter-cluster motion-compensation is integrated as part of a CS reconstruction.
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Affiliation(s)
- Ludovica Romanin
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland
| | - Bastien Milani
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Christopher W. Roy
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Jérôme Yerly
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- Center for Biomedical Imaging (CIBM), Lausanne, Switzerland
| | - Aurélien Bustin
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- IHU LIRYC, Electrophysiology and Heart Modeling Institute, Université de Bordeaux – INSERM U1045, Pessac, France
- Department of Cardiovascular Imaging, Hôpital Cardiologique du Haut-Lévêque, CHU de Bordeaux, Pessac, France
| | - Salim Si-mohamed
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- University Lyon, INSA-Lyon, University Claude Bernard Lyon 1, UJM-Saint Etienne, CNRS, Inserm, CREATIS UMR 5220, U1206, Villeurbanne, France
- Department of Radiology, Louis Pradel Hospital, Hospices Civils de Lyon, Bron, France
| | - Milan Prsa
- Division of Pediatric Cardiology, Woman-Mother-Child Department, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Tobias Rutz
- Division of Cardiology, Cardiovascular Department, Lausanne University Hospital, Lausanne, Switzerland
| | - Estelle Tenisch
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Juerg Schwitter
- Division of Cardiology, Cardiovascular Department, Lausanne University Hospital, Lausanne, Switzerland
- Faculty of Biology&Medicine, University of Lausanne, UniL, Lausanne, Switzerland
- Cardiac MR Center of the University Hospital Lausanne, Lausanne, Switzerland
| | - Matthias Stuber
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- Center for Biomedical Imaging (CIBM), Lausanne, Switzerland
| | - Davide Piccini
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland
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2
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Li Z, Sun A, Liu C, Sun H, Wei H, Wang S, Li R. Technical Note: Swing golden angle - A navigator-interleaved golden angle trajectory with eddy current suppression - Application in free-running cardiac MRI. Med Phys 2024. [PMID: 38837254 DOI: 10.1002/mp.17188] [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: 06/21/2023] [Revised: 02/20/2024] [Accepted: 03/23/2024] [Indexed: 06/07/2024] Open
Abstract
BACKGROUND Golden angle (GA) radial trajectory is advantageous for dynamic magnetic resonance imaging (MRI). Recently, several advanced algorithms have been developed based on navigator-interleaved GA trajectory to realize free-running cardiac MRI. However, navigator-interleaved GA trajectory suffers from the eddy-current effect, which reduces the image quality. PURPOSE This work aims to integrate the navigator-interleaved GA trajectory with clinical cardiac MRI acquisition, with the minimum eddy-current artifacts. The ultimate goal is to realize a high-quality free-running cardiac imaging technique. METHODS In this paper, we propose a new "swing golden angle" (swingGA) radial profile order. SwingGA samples the k-space by rotating back and forth at the generalized golden ratio interval, with smoothly interleaved navigator readouts. The sampling efficiency and angle increment distributions were investigated by numerical simulations. Static phantom imaging experiments were conducted to evaluate the eddy current effect, compared with cartesian, golden angle radial (GA), and tiny golden angle (tGA) trajectories. Furthermore, 12 heart-healthy subjects (aged 21-25 years) were recruited for free-running cardiac imaging with different sampling trajectories. Dynamic images were reconstructed by a low-rank subspace-constrained algorithm. The image quality was evaluated by signal-to-noise-ratio and spectrum analysis in the heart region, and compared with traditional clinical cardiac MRI images. RESULTS SwingGA pattern achieves the highest sampling efficiency (mSE > 0.925) and the minimum azimuthal angle increment (mAD < 1.05). SwingGA can effectively suppress eddy currents in static phantom images, with the lowest normalized root mean square error (nRMSE) values among radial trajectories. For the in-vivo cardiac images, swingGA enjoys the highest SNR both in the blood pool and myocardium, and contains the minimum level of high-frequency artifacts. The free-running cardiac images have good consistency with traditional clinical cardiac MRI, and the swingGA sampling pattern achieves the best image quality among all sampling patterns. CONCLUSIONS The proposed swingGA sampling pattern can effectively improve the sampling efficiency and reduce the eddy currents for the navigator-interleaved GA sequence. SwingGA is a promising sampling pattern for free-running cardiac MRI.
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Affiliation(s)
- Zhongsen Li
- Center for Biomedical Imaging Research, School of Biomedical Engineering, Tsinghua University, Beijing, China
| | - Aiqi Sun
- Oden Institute for Computational Engineering and Sciences, University of Texas at Austin, Austin, Texas, USA
| | - Chuyu Liu
- Center for Biomedical Imaging Research, School of Biomedical Engineering, Tsinghua University, Beijing, China
| | - Haozhong Sun
- Center for Biomedical Imaging Research, School of Biomedical Engineering, Tsinghua University, Beijing, China
| | - Haining Wei
- Center for Biomedical Imaging Research, School of Biomedical Engineering, Tsinghua University, Beijing, China
| | - Shuai Wang
- Center for Biomedical Imaging Research, School of Biomedical Engineering, Tsinghua University, Beijing, China
| | - Rui Li
- Center for Biomedical Imaging Research, School of Biomedical Engineering, Tsinghua University, Beijing, China
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Arshad SM, Potter LC, Chen C, Liu Y, Chandrasekaran P, Crabtree C, Tong MS, Simonetti OP, Han Y, Ahmad R. Motion-robust free-running volumetric cardiovascular MRI. Magn Reson Med 2024. [PMID: 38733066 DOI: 10.1002/mrm.30123] [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: 12/01/2023] [Revised: 03/31/2024] [Accepted: 04/01/2024] [Indexed: 05/13/2024]
Abstract
PURPOSE To present and assess an outlier mitigation method that makes free-running volumetric cardiovascular MRI (CMR) more robust to motion. METHODS The proposed method, called compressive recovery with outlier rejection (CORe), models outliers in the measured data as an additive auxiliary variable. We enforce MR physics-guided group sparsity on the auxiliary variable, and jointly estimate it along with the image using an iterative algorithm. For evaluation, CORe is first compared to traditional compressed sensing (CS), robust regression (RR), and an existing outlier rejection method using two simulation studies. Then, CORe is compared to CS using seven three-dimensional (3D) cine, 12 rest four-dimensional (4D) flow, and eight stress 4D flow imaging datasets. RESULTS Our simulation studies show that CORe outperforms CS, RR, and the existing outlier rejection method in terms of normalized mean square error and structural similarity index across 55 different realizations. The expert reader evaluation of 3D cine images demonstrates that CORe is more effective in suppressing artifacts while maintaining or improving image sharpness. Finally, 4D flow images show that CORe yields more reliable and consistent flow measurements, especially in the presence of involuntary subject motion or exercise stress. CONCLUSION An outlier rejection method is presented and tested using simulated and measured data. This method can help suppress motion artifacts in a wide range of free-running CMR applications.
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Affiliation(s)
- Syed M Arshad
- Biomedical Engineering, The Ohio State University, Columbus, Ohio, USA
- Electrical & Computer Engineering, The Ohio State University, Columbus, Ohio, USA
| | - Lee C Potter
- Electrical & Computer Engineering, The Ohio State University, Columbus, Ohio, USA
- Davis Heart and Lung Research Institute, The Ohio State University Wexner Medical Center, Columbus, Ohio, USA
| | - Chong Chen
- Biomedical Engineering, The Ohio State University, Columbus, Ohio, USA
- Electrical & Computer Engineering, The Ohio State University, Columbus, Ohio, USA
| | - Yingmin Liu
- Davis Heart and Lung Research Institute, The Ohio State University Wexner Medical Center, Columbus, Ohio, USA
| | - Preethi Chandrasekaran
- Davis Heart and Lung Research Institute, The Ohio State University Wexner Medical Center, Columbus, Ohio, USA
| | | | - Matthew S Tong
- Internal Medicine, The Ohio State University Wexner Medical Center, Columbus, Ohio, USA
| | - Orlando P Simonetti
- Davis Heart and Lung Research Institute, The Ohio State University Wexner Medical Center, Columbus, Ohio, USA
- Internal Medicine, The Ohio State University Wexner Medical Center, Columbus, Ohio, USA
| | - Yuchi Han
- Internal Medicine, The Ohio State University Wexner Medical Center, Columbus, Ohio, USA
| | - Rizwan Ahmad
- Biomedical Engineering, The Ohio State University, Columbus, Ohio, USA
- Electrical & Computer Engineering, The Ohio State University, Columbus, Ohio, USA
- Davis Heart and Lung Research Institute, The Ohio State University Wexner Medical Center, Columbus, Ohio, USA
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Ming Z, Pogosyan A, Christodoulou AG, Finn JP, Ruan D, Nguyen KL. Dynamic Regularized Adaptive Cluster Optimization (DRACO) for Quantitative Cardiac Cine MRI in Complex Arrhythmias. J Magn Reson Imaging 2024. [PMID: 38708951 DOI: 10.1002/jmri.29425] [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: 12/30/2023] [Revised: 04/17/2024] [Accepted: 04/18/2024] [Indexed: 05/07/2024] Open
Abstract
BACKGROUND Irregular cardiac motion can render conventional segmented cine MRI nondiagnostic. Clustering has been proposed for cardiac motion binning and may be optimized for complex arrhythmias. PURPOSE To develop an adaptive cluster optimization method for irregular cardiac motion, and to generate the corresponding time-resolved cine images. STUDY TYPE Prospective. SUBJECTS Thirteen with atrial fibrillation, four with premature ventricular contractions, and one patient in sinus rhythm. FIELD STRENGTH/SEQUENCE Free-running balanced steady state free precession (bSSFP) with sorted golden-step, reference real-time sequence. ASSESSMENT Each subject underwent both the sorted golden-step bSSFP and the reference Cartesian real-time imaging. Golden-step bSSFP images were reconstructed using the dynamic regularized adaptive cluster optimization (DRACO) method and k-means clustering. Image quality (4-point Likert scale), signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), edge sharpness, and ventricular function were assessed. STATISTICAL TESTS Paired t-tests, Friedman test, regression analysis, Fleiss' Kappa, Bland-Altman analysis. Significance level P < 0.05. RESULTS The DRACO method had the highest percent of images with scores ≥3 (96% for diastolic frame, 93% for systolic frame, and 93% for multiphase cine) and the percentages were significantly higher compared with both the k-means and real-time methods. Image quality scores, SNR, and CNR were significantly different between DRACO vs. k-means and between DRACO vs. real-time. Cardiac function analysis showed no significant differences between DRACO vs. the reference real-time. CONCLUSION DRACO with time-resolved reconstruction generated high quality images and has early promise for quantitative cine cardiac MRI in patients with complex arrhythmias including atrial fibrillation. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY Stage 2.
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Affiliation(s)
- Zhengyang Ming
- Physics and Biology in Medicine Graduate Program, University of California, Los Angeles, California, USA
- Department of Radiological Sciences, David Geffen School of Medicine at UCLA, Los Angeles, California, USA
| | - Arutyun Pogosyan
- Division of Cardiology, David Geffen School of Medicine at UCLA and VA Greater Los Angeles Healthcare System, Los Angeles, California, USA
| | - Anthony G Christodoulou
- Department of Radiological Sciences, David Geffen School of Medicine at UCLA, Los Angeles, California, USA
- Department of Bioengineering, University of California, Los Angeles, California, USA
| | - J Paul Finn
- Physics and Biology in Medicine Graduate Program, University of California, Los Angeles, California, USA
- Department of Radiological Sciences, David Geffen School of Medicine at UCLA, Los Angeles, California, USA
| | - Dan Ruan
- Physics and Biology in Medicine Graduate Program, University of California, Los Angeles, California, USA
- Department of Bioengineering, University of California, Los Angeles, California, USA
- Department of Radiation Oncology, David Geffen School of Medicine at UCLA, California, USA
| | - Kim-Lien Nguyen
- Physics and Biology in Medicine Graduate Program, University of California, Los Angeles, California, USA
- Department of Radiological Sciences, David Geffen School of Medicine at UCLA, Los Angeles, California, USA
- Division of Cardiology, David Geffen School of Medicine at UCLA and VA Greater Los Angeles Healthcare System, Los Angeles, California, USA
- Department of Bioengineering, University of California, Los Angeles, California, USA
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Ishida M, Yerly J, Ito H, Takafuji M, Nakamori S, Takase S, Ichiba Y, Komori Y, Dohi K, Piccini D, Bastiaansen JA, Stuber M, Sakuma H. Optimal Protocol for Contrast-enhanced Free-running 5D Whole-heart Coronary MR Angiography at 3T. Magn Reson Med Sci 2024; 23:225-237. [PMID: 36682776 PMCID: PMC11024717 DOI: 10.2463/mrms.tn.2022-0086] [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: 07/14/2022] [Accepted: 11/11/2022] [Indexed: 01/20/2023] Open
Abstract
Free-running 5D whole-heart coronary MR angiography (MRA) is gaining in popularity because it reduces scanning complexity by removing the need for specific slice orientations, respiratory gating, or cardiac triggering. At 3T, a gradient echo (GRE) sequence is preferred in combination with contrast injection. However, neither the injection scheme of the gadolinium (Gd) contrast medium, the choice of the RF excitation angle, nor the dedicated image reconstruction parameters have been established for 3T GRE free-running 5D whole-heart coronary MRA. In this study, a Gd injection scheme, RF excitation angles of lipid-insensitive binominal off-resonance RF excitation (LIBRE) pulse for valid fat suppression and continuous data acquisition, and compressed-sensing reconstruction regularization parameters were optimized for contrast-enhanced free-running 5D whole-heart coronary MRA using a GRE sequence at 3T. Using this optimized protocol, contrast-enhanced free-running 5D whole-heart coronary MRA using a GRE sequence is feasible with good image quality at 3T.
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Affiliation(s)
- Masaki Ishida
- Department of Radiology, Mie University Hospital, Tsu, Mie, Japan
| | - Jérôme Yerly
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- Center for Biomedical Imaging (CIBM), Lausanne, Switzerland
| | - Haruno Ito
- Department of Radiology, Mie University Hospital, Tsu, Mie, Japan
| | | | - Shiro Nakamori
- Department of Cardiology, Mie University Hospital, Tsu, Mie, Japan
| | - Shinichi Takase
- Department of Radiology, Mie University Hospital, Tsu, Mie, Japan
| | | | | | - Kaoru Dohi
- Department of Cardiology, Mie University Hospital, Tsu, Mie, Japan
| | - Davide Piccini
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- Center for Biomedical Imaging (CIBM), Lausanne, Switzerland
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland
| | - Jessica A.M. Bastiaansen
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- Center for Biomedical Imaging (CIBM), Lausanne, Switzerland
- Department of Diagnostic, Interventional and Pediatric Radiology (DIPR), Inselspital Bern University Hospital, University of Bern, 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
| | - Hajime Sakuma
- Department of Radiology, Mie University Hospital, Tsu, Mie, Japan
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Chaban YV, Vosshenrich J, McKee H, Gunasekaran S, Brown MJ, Atalay MK, Heye T, Markl M, Woolen SA, Simonetti OP, Hanneman K. Environmental Sustainability and MRI: Challenges, Opportunities, and a Call for Action. J Magn Reson Imaging 2024; 59:1149-1167. [PMID: 37694980 DOI: 10.1002/jmri.28994] [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: 07/14/2023] [Revised: 08/18/2023] [Accepted: 08/21/2023] [Indexed: 09/12/2023] Open
Abstract
The environmental impact of magnetic resonance imaging (MRI) has recently come into focus. This includes its enormous demand for electricity compared to other imaging modalities and contamination of water bodies with anthropogenic gadolinium related to contrast administration. Given the pressing threat of climate change, addressing these challenges to improve the environmental sustainability of MRI is imperative. The purpose of this review is to discuss the challenges, opportunities, and the need for action to reduce the environmental impact of MRI and prepare for the effects of climate change. The approaches outlined are categorized as strategies to reduce greenhouse gas (GHG) emissions from MRI during production and use phases, approaches to reduce the environmental impact of MRI including the preservation of finite resources, and development of adaption plans to prepare for the impact of climate change. Co-benefits of these strategies are emphasized including lower GHG emission and reduced cost along with improved heath and patient satisfaction. Although MRI is energy-intensive, there are many steps that can be taken now to improve the environmental sustainability of MRI and prepare for the effects of climate change. On-going research, technical development, and collaboration with industry partners are needed to achieve further reductions in MRI-related GHG emissions and to decrease the reliance on finite resources. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY: Stage 6.
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Affiliation(s)
- Yuri V Chaban
- Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Jan Vosshenrich
- Department of Radiology, University Hospital Basel, Basel, Switzerland
| | - Hayley McKee
- Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Suvai Gunasekaran
- Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Maura J Brown
- Department of Radiology, University of British Columbia, Vancouver, British Columbia, Canada
| | - Michael K Atalay
- Department of Diagnostic Imaging, Alpert Medical School of Brown University, Providence, Rhode Island, USA
| | - Tobias Heye
- Department of Radiology, University Hospital Basel, Basel, Switzerland
| | - Michael Markl
- Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
- Department of Biomedical Engineering, Northwestern University, Evanston, Illinois, USA
| | - Sean A Woolen
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
| | | | - Kate Hanneman
- Department of Medical Imaging, University Medical Imaging Toronto, University of Toronto, Toronto, Ontario, Canada
- Toronto General Hospital Research Institute, University Health Network, University of Toronto, Toronto, Ontario, Canada
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7
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Ming Z, Pogosyan A, Gao C, Colbert CM, Wu HH, Finn JP, Ruan D, Hu P, Christodoulou AG, Nguyen KL. ECG-free cine MRI with data-driven clustering of cardiac motion for quantification of ventricular function. NMR IN BIOMEDICINE 2024; 37:e5091. [PMID: 38196195 PMCID: PMC10947936 DOI: 10.1002/nbm.5091] [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: 05/08/2023] [Revised: 11/14/2023] [Accepted: 11/22/2023] [Indexed: 01/11/2024]
Abstract
BACKGROUND Despite the widespread use of cine MRI for evaluation of cardiac function, existing real-time methods do not easily enable quantification of ventricular function. Moreover, segmented cine MRI assumes periodicity of cardiac motion. We aim to develop a self-gated, cine MRI acquisition scheme with data-driven cluster-based binning of cardiac motion. METHODS A Cartesian golden-step balanced steady-state free precession sequence with sorted k-space ordering was designed. Image data were acquired with breath-holding. Principal component analysis and k-means clustering were used for binning of cardiac phases. Cluster compactness in the time dimension was assessed using temporal variability, and dispersion in the spatial dimension was assessed using the Caliński-Harabasz index. The proposed and the reference electrocardiogram (ECG)-gated cine methods were compared using a four-point image quality score, SNR and CNR values, and Bland-Altman analyses of ventricular function. RESULTS A total of 10 subjects with sinus rhythm and 8 subjects with arrhythmias underwent cardiac MRI at 3.0 T. The temporal variability was 45.6 ms (cluster) versus 24.6 ms (ECG-based) (p < 0.001), and the Caliński-Harabasz index was 59.1 ± 9.1 (cluster) versus 22.0 ± 7.1 (ECG based) (p < 0.001). In subjects with sinus rhythm, 100% of the end-systolic and end-diastolic images from both the cluster and reference approach received the highest image quality score of 4. Relative to the reference cine images, the cluster-based multiphase (cine) image quality consistently received a one-point lower score (p < 0.05), whereas the SNR and CNR values were not significantly different (p = 0.20). In cases with arrhythmias, 97.9% of the end-systolic and end-diastolic images from the cluster approach received an image quality score of 3 or more. The mean bias values for biventricular ejection fraction and volumes derived from the cluster approach versus reference cine were negligible. CONCLUSION ECG-free cine cardiac MRI with data-driven clustering for binning of cardiac motion is feasible and enables quantification of cardiac function.
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Affiliation(s)
- Zhengyang Ming
- Physics and Biology in Medicine Graduate Program, University of California, Los Angeles, CA, USA
- Department of Radiological Sciences, David Geffen School of Medicine at UCLA, CA, USA
| | - Arutyun Pogosyan
- Division of Cardiology, David Geffen School of Medicine at UCLA and VA Greater Los Angeles Healthcare System, CA, USA
| | - Chang Gao
- Physics and Biology in Medicine Graduate Program, University of California, Los Angeles, CA, USA
- Department of Radiological Sciences, David Geffen School of Medicine at UCLA, CA, USA
| | - Caroline M. Colbert
- Physics and Biology in Medicine Graduate Program, University of California, Los Angeles, CA, USA
- Department of Radiological Sciences, David Geffen School of Medicine at UCLA, CA, USA
- Division of Cardiology, David Geffen School of Medicine at UCLA and VA Greater Los Angeles Healthcare System, CA, USA
| | - Holden H. Wu
- Physics and Biology in Medicine Graduate Program, University of California, Los Angeles, CA, USA
- Department of Radiological Sciences, David Geffen School of Medicine at UCLA, CA, USA
- Department of Bioengineering, University of California, Los Angeles, CA, USA
| | - J. Paul Finn
- Physics and Biology in Medicine Graduate Program, University of California, Los Angeles, CA, USA
- Department of Radiological Sciences, David Geffen School of Medicine at UCLA, CA, USA
| | - Dan Ruan
- Physics and Biology in Medicine Graduate Program, University of California, Los Angeles, CA, USA
- Department of Bioengineering, University of California, Los Angeles, CA, USA
- Department of Radiation Oncology, David Geffen School of Medicine at UCLA, CA, USA
| | - Peng Hu
- Physics and Biology in Medicine Graduate Program, University of California, Los Angeles, CA, USA
- Department of Radiological Sciences, David Geffen School of Medicine at UCLA, CA, USA
- Department of Bioengineering, University of California, Los Angeles, CA, USA
| | - Anthony G. Christodoulou
- Department of Bioengineering, University of California, Los Angeles, CA, USA
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA
| | - Kim-Lien Nguyen
- Physics and Biology in Medicine Graduate Program, University of California, Los Angeles, CA, USA
- Department of Radiological Sciences, David Geffen School of Medicine at UCLA, CA, USA
- Division of Cardiology, David Geffen School of Medicine at UCLA and VA Greater Los Angeles Healthcare System, CA, USA
- Department of Bioengineering, University of California, Los Angeles, CA, USA
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8
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Roy CW, Milani B, Yerly J, Si-Mohamed S, Romanin L, Bustin A, Tenisch E, Rutz T, Prsa M, Stuber M. Intra-bin correction and inter-bin compensation of respiratory motion in free-running five-dimensional whole-heart magnetic resonance imaging. J Cardiovasc Magn Reson 2024; 26:101037. [PMID: 38499269 PMCID: PMC10987330 DOI: 10.1016/j.jocmr.2024.101037] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2024] [Revised: 03/09/2024] [Accepted: 03/11/2024] [Indexed: 03/20/2024] Open
Abstract
BACKGROUND Free-running cardiac and respiratory motion-resolved whole-heart five-dimensional (5D) cardiovascular magnetic resonance (CMR) can reduce scan planning and provide a means of evaluating respiratory-driven changes in clinical parameters of interest. However, respiratory-resolved imaging can be limited by user-defined parameters which create trade-offs between residual artifact and motion blur. In this work, we develop and validate strategies for both correction of intra-bin and compensation of inter-bin respiratory motion to improve the quality of 5D CMR. METHODS Each component of the reconstruction framework was systematically validated and compared to the previously established 5D approach using simulated free-running data (N = 50) and a cohort of 32 patients with congenital heart disease. The impact of intra-bin respiratory motion correction was evaluated in terms of image sharpness while inter-bin respiratory motion compensation was evaluated in terms of reconstruction error, compression of respiratory motion, and image sharpness. The full reconstruction framework (intra-acquisition correction and inter-acquisition compensation of respiratory motion [IIMC] 5D) was evaluated in terms of image sharpness and scoring of image quality by expert reviewers. RESULTS Intra-bin motion correction provides significantly (p < 0.001) sharper images for both simulated and patient data. Inter-bin motion compensation results in significant (p < 0.001) lower reconstruction error, lower motion compression, and higher sharpness in both simulated (10/11) and patient (9/11) data. The combined framework resulted in significantly (p < 0.001) sharper IIMC 5D reconstructions (End-expiration (End-Exp): 0.45 ± 0.09, End-inspiration (End-Ins): 0.46 ± 0.10) relative to the previously established 5D implementation (End-Exp: 0.43 ± 0.08, End-Ins: 0.39 ± 0.09). Similarly, image scoring by three expert reviewers was significantly (p < 0.001) higher using IIMC 5D (End-Exp: 3.39 ± 0.44, End-Ins: 3.32 ± 0.45) relative to 5D images (End-Exp: 3.02 ± 0.54, End-Ins: 2.45 ± 0.52). CONCLUSION The proposed IIMC reconstruction significantly improves the quality of 5D whole-heart MRI. This may be exploited for higher resolution or abbreviated scanning. Further investigation of the diagnostic impact of this framework and comparison to gold standards is needed to understand its full clinical utility, including exploration of respiratory-driven changes in physiological measurements of interest.
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Affiliation(s)
- Christopher W Roy
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.
| | - Bastien Milani
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Jérôme Yerly
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland; Center for Biomedical Imaging (CIBM), Lausanne, Switzerland
| | - Salim Si-Mohamed
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland; University Lyon, INSA-Lyon, University Claude Bernard Lyon 1, UJM-Saint Etienne, CNRS, Inserm, CREATIS UMR 5220, U1206, F-69621, 7 Avenue Jean Capelle O, 69100 Villeurbanne, France; Department of Radiology, Louis Pradel Hospital, Hospices Civils de Lyon, 59 Boulevard Pinel, 69500 Bron, France
| | - Ludovica Romanin
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland; Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland
| | - Aurélien Bustin
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland; IHU LIRYC, Electrophysiology and Heart Modeling Institute, Université de Bordeaux - INSERM U1045, Avenue du Haut Lévêque, 33604 Pessac, France; Department of Cardiovascular Imaging, Hôpital Cardiologique du Haut-Lévêque, CHU de Bordeaux, Avenue de Magellan, 33604 Pessac, France
| | - Estelle Tenisch
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Tobias Rutz
- Service of Cardiology, Heart and Vessel Department, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Milan Prsa
- Division of Pediatric Cardiology, Woman-Mother-Child Department, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Matthias Stuber
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland; Center for Biomedical Imaging (CIBM), Lausanne, Switzerland
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9
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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 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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Giacchi G, Milani B, Franceschiello B. On the Determination of Lagrange Multipliers for a Weighted LASSO Problem Using Geometric and Convex Analysis Techniques. APPLIED MATHEMATICS AND OPTIMIZATION 2024; 89:31. [PMID: 38261892 PMCID: PMC10794441 DOI: 10.1007/s00245-023-10096-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Accepted: 12/12/2023] [Indexed: 01/25/2024]
Abstract
Compressed Sensing (CS) encompasses a broad array of theoretical and applied techniques for recovering signals, given partial knowledge of their coefficients, cf. Candés (C. R. Acad. Sci. Paris, Ser. I 346, 589-592 (2008)), Candés et al. (IEEE Trans. Inf. Theo (2006)), Donoho (IEEE Trans. Inf. Theo. 52(4), (2006)), Donoho et al. (IEEE Trans. Inf. Theo. 52(1), (2006)). Its applications span various fields, including mathematics, physics, engineering, and several medical sciences, cf. Adcock and Hansen (Compressive Imaging: Structure, Sampling, Learning, p. 2021), Berk et al. (2019 13th International conference on Sampling Theory and Applications (SampTA) pp. 1-5. IEEE (2019)), Brady et al. (Opt. Express 17(15), 13040-13049 (2009)), Chan (Terahertz imaging with compressive sensing. Rice University, USA (2010)), Correa et al. (2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) pp. 7789-7793 (2014, May) IEEE), Gao et al. (Nature 516(7529), 74-77 (2014)), Liu and Kang (Opt. Express 18(21), 22010-22019 (2010)), McEwen and Wiaux (Mon. Notices Royal Astron. Soc. 413(2), 1318-1332 (2011)), Marim et al. (Opt. Lett. 35(6), 871-873 (2010)), Yu and Wang (Phys. Med. Biol. 54(9), 2791 (2009)), Yu and Wang (Phys. Med. Biol. 54(9), 2791 (2009)). Motivated by our interest in the mathematics behind Magnetic Resonance Imaging (MRI) and CS, we employ convex analysis techniques to analytically determine equivalents of Lagrange multipliers for optimization problems with inequality constraints, specifically a weighted LASSO with voxel-wise weighting. We investigate this problem under assumptions on the fidelity term A x - b 2 2 , either concerning the sign of its gradient or orthogonality-like conditions of its matrix. To be more precise, we either require the sign of each coordinate of 2 ( A x - b ) T A to be fixed within a rectangular neighborhood of the origin, with the side lengths of the rectangle dependent on the constraints, or we assume A T A to be diagonal. The objective of this work is to explore the relationship between Lagrange multipliers and the constraints of a weighted variant of LASSO, specifically in the mentioned cases where this relationship can be computed explicitly. As they scale the regularization terms of the weighted LASSO, Lagrange multipliers serve as tuning parameters for the weighted LASSO, prompting the question of their potential effective use as tuning parameters in applications like MR image reconstruction and denoising. This work represents an initial step in this direction.
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Affiliation(s)
- Gianluca Giacchi
- Università di Bologna, Dipartimento di Matematica, Piazza di Porta San Donato 5, 40126 Bologna, Italy
- Institute of Systems Engineering, School of Engineering, HES-SO Valais-Wallis, Rue de l’Industrie 23, 1950 Sion, Switzerland
- Lausanne University Hospital and University of Lausanne, Lausanne, Department of Diagnostic and Interventional Radiology, Rue du Bugnon 46, Lausanne, 1011 Switzerland
- The Sense Innovation and Research Center, Avenue de Provence 82 1007, Lausanne and Ch. de l’Agasse 5, 1950 Sion, Switzerland
| | - Bastien Milani
- Lausanne University Hospital and University of Lausanne, Lausanne, Department of Diagnostic and Interventional Radiology, Rue du Bugnon 46, Lausanne, 1011 Switzerland
| | - Benedetta Franceschiello
- Institute of Systems Engineering, School of Engineering, HES-SO Valais-Wallis, Rue de l’Industrie 23, 1950 Sion, Switzerland
- The Sense Innovation and Research Center, Avenue de Provence 82 1007, Lausanne and Ch. de l’Agasse 5, 1950 Sion, Switzerland
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11
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Vitouš J, Jiřík R, Stračina T, Hendrych M, Nádeníček J, Macíček O, Tian Y, Krátká L, Dražanová E, Nováková M, Babula P, Panovský R, DiBella E, Starčuk Z. T1 mapping of myocardium in rats using self-gated golden-angle acquisition. Magn Reson Med 2024; 91:368-380. [PMID: 37811699 DOI: 10.1002/mrm.29846] [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: 03/14/2023] [Revised: 07/19/2023] [Accepted: 08/10/2023] [Indexed: 10/10/2023]
Abstract
PURPOSE The aim of this study is to design a method of myocardial T1 quantification in small laboratory animals and to investigate the effects of spatiotemporal regularization and the needed acquisition duration. METHODS We propose a compressed-sensing approach to T1 quantification based on self-gated inversion-recovery radial two/three-dimensional (2D/3D) golden-angle stack-of-stars acquisition with image reconstruction performed using total-variation spatiotemporal regularization. The method was tested on a phantom and on a healthy rat, as well as on rats in a small myocardium-remodeling study. RESULTS The results showed a good match of the T1 estimates with the results obtained using the ground-truth method on a phantom and with the literature values for rats myocardium. The proposed 2D and 3D methods showed significant differences between normal and remodeling myocardium groups for acquisition lengths down to approximately 5 and 15 min, respectively. CONCLUSIONS A new 2D and 3D method for quantification of myocardial T1 in rats was proposed. We have shown the capability of both techniques to distinguish between normal and remodeling myocardial tissue. We have shown the effects of image-reconstruction regularization weights and acquisition length on the T1 estimates.
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Affiliation(s)
- Jiří Vitouš
- Institute of Scientific Instruments, Czech Academy of Sciences, Brno, Czechia
- Faculty of Electrical Engineering and Communication, Brno University of Technology, Brno, Czechia
| | - Radovan Jiřík
- Institute of Scientific Instruments, Czech Academy of Sciences, Brno, Czechia
| | - Tibor Stračina
- Department of Physiology, Masaryk University, Faculty of Medicine, Brno, Czechia
| | - Michal Hendrych
- First Department of Pathology, St. Anne's University Hospital and Faculty of Medicine Masaryk University, Brno, Czechia
| | - Jaroslav Nádeníček
- Department of Physiology, Masaryk University, Faculty of Medicine, Brno, Czechia
| | - Ondřej Macíček
- Institute of Scientific Instruments, Czech Academy of Sciences, Brno, Czechia
| | - Ye Tian
- Viterbi School of Engineering, University of Southern California, Los Angeles, California, USA
| | - Lucie Krátká
- Institute of Scientific Instruments, Czech Academy of Sciences, Brno, Czechia
| | - Eva Dražanová
- Institute of Scientific Instruments, Czech Academy of Sciences, Brno, Czechia
- Department of Pharmacology, Faculty of Medicine, Masaryk University, Brno, Czechia
| | - Marie Nováková
- Department of Physiology, Masaryk University, Faculty of Medicine, Brno, Czechia
| | - Petr Babula
- Department of Physiology, Masaryk University, Faculty of Medicine, Brno, Czechia
| | - Roman Panovský
- International Clinical Research Center, St. Anne's Faculty Hospital, Faculty of Medicine, Masaryk University, Brno, Czechia
- 1st Department of Internal Medicine/Cardioangiology, St. Anne's Faculty Hospital, Faculty of Medicine, Masaryk University, Brno, Czechia
| | - Edward DiBella
- School of Medicine, University of Utah, Salt Lake City, Utah, USA
| | - Zenon Starčuk
- Institute of Scientific Instruments, Czech Academy of Sciences, Brno, Czechia
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12
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Raynaud Q, Di Domenicantonio G, Yerly J, Dardano T, van Heeswijk RB, Lutti A. A characterization of cardiac-induced noise in R 2 * maps of the brain. Magn Reson Med 2024; 91:237-251. [PMID: 37708206 DOI: 10.1002/mrm.29853] [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: 07/13/2023] [Revised: 08/11/2023] [Accepted: 08/15/2023] [Indexed: 09/16/2023]
Abstract
PURPOSE Cardiac pulsation increases the noise level in brain maps of the transverse relaxation rate R2 *. Cardiac-induced noise is challenging to mitigate during the acquisition of R2 * mapping data because its characteristics are unknown. In this work, we aim to characterize cardiac-induced noise in brain maps of the MRI parameter R2 *. METHODS We designed a sampling strategy to acquire multi-echo 3D data in 12 intervals of the cardiac cycle, monitored with a fingertip pulse-oximeter. We measured the amplitude of cardiac-induced noise in this data and assessed the effect of cardiac pulsation on R2 * maps computed across echoes. The area of k-space that contains most of the cardiac-induced noise in R2 * maps was then identified. Based on these characteristics, we introduced a tentative sampling strategy that aims to mitigate cardiac-induced noise in R2 * maps of the brain. RESULTS In inferior brain regions, cardiac pulsation accounts for R2 * variations of up to 3 s-1 across the cardiac cycle (i.e., ∼35% of the overall variability). Cardiac-induced fluctuations occur throughout the cardiac cycle, with a reduced intensity during the first quarter of the cycle. A total of 50% to 60% of the overall cardiac-induced noise is localized near the k-space center (k < 0.074 mm-1 ). The tentative cardiac noise mitigation strategy reduced the variability of R2 * maps across repetitions by 11% in the brainstem and 6% across the whole brain. CONCLUSION We provide a characterization of cardiac-induced noise in brain R2 * maps that can be used as a basis for the design of mitigation strategies during data acquisition.
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Affiliation(s)
- Quentin Raynaud
- Laboratory for Research in Neuroimaging, Department for Clinical Neuroscience, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Giulia Di Domenicantonio
- Laboratory for Research in Neuroimaging, Department for Clinical Neuroscience, 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 (CIBM), Lausanne, Switzerland
| | - Thomas Dardano
- Laboratory for Research in Neuroimaging, Department for Clinical Neuroscience, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Ruud B van Heeswijk
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Antoine Lutti
- Laboratory for Research in Neuroimaging, Department for Clinical Neuroscience, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
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13
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Liu W, Mossel P, Schwach V, Slart RHJA, Luurtsema G. Cardiac PET Imaging of ATP Binding Cassette (ABC) Transporters: Opportunities and Challenges. Pharmaceuticals (Basel) 2023; 16:1715. [PMID: 38139840 PMCID: PMC10748140 DOI: 10.3390/ph16121715] [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: 10/06/2023] [Revised: 12/01/2023] [Accepted: 12/04/2023] [Indexed: 12/24/2023] Open
Abstract
Adenosine triphosphate binding cassette (ABC) transporters are a broad family of membrane protein complexes that use energy to transport molecules across cells and/or intracellular organelle lipid membranes. Many drugs used to treat cardiac diseases have an affinity for these transporters. Among others, P-glycoprotein (P-gp) plays an essential role in regulating drug concentrations that reach cardiac tissue and therefore contribute to cardiotoxicity. As a molecular imaging modality, positron emission tomography (PET) has emerged as a viable technique to investigate the function of P-gp in organs and tissues. Using PET imaging to evaluate cardiac P-gp function provides new insights for drug development and improves the precise use of medications. Nevertheless, information in this field is limited. In this review, we aim to examine the current applications of ABC transporter PET imaging and its tracers in the heart, with a specific emphasis on P-gp. Furthermore, the opportunities and challenges in this novel field will be discussed.
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Affiliation(s)
- Wanling Liu
- Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, University of Groningen, Hanzeplein 1, 9713 GZ Groningen, The Netherlands; (W.L.); (P.M.)
| | - Pascalle Mossel
- Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, University of Groningen, Hanzeplein 1, 9713 GZ Groningen, The Netherlands; (W.L.); (P.M.)
| | - Verena Schwach
- Department of Applied Stem Cell Technologies, TechMed Centre, University of Twente, 7500 AE Enschede, The Netherlands;
| | - Riemer H. J. A. Slart
- Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, University of Groningen, Hanzeplein 1, 9713 GZ Groningen, The Netherlands; (W.L.); (P.M.)
- Department of Biomedical Photonic Imaging, University of Twente, 7500 AE Enschede, The Netherlands
| | - Gert Luurtsema
- Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, University of Groningen, Hanzeplein 1, 9713 GZ Groningen, The Netherlands; (W.L.); (P.M.)
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14
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Wood G, Pedersen AU, Kunze KP, Neji R, Hajhosseiny R, Wetzl J, Yoon SS, Schmidt M, Nørgaard BL, Prieto C, Botnar RM, Kim WY. Automated detection of cardiac rest period for trigger delay calculation for image-based navigator coronary magnetic resonance angiography. J Cardiovasc Magn Reson 2023; 25:52. [PMID: 37779192 PMCID: PMC10544388 DOI: 10.1186/s12968-023-00962-9] [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: 06/28/2023] [Accepted: 09/12/2023] [Indexed: 10/03/2023] Open
Abstract
BACKGROUND Coronary magnetic resonance angiography (coronary MRA) is increasingly being considered as a clinically viable method to investigate coronary artery disease (CAD). Accurate determination of the trigger delay to place the acquisition window within the quiescent part of the cardiac cycle is critical for coronary MRA in order to reduce cardiac motion. This is currently reliant on operator-led decision making, which can negatively affect consistency of scan acquisition. Recently developed deep learning (DL) derived software may overcome these issues by automation of cardiac rest period detection. METHODS Thirty individuals (female, n = 10) were investigated using a 0.9 mm isotropic image-navigator (iNAV)-based motion-corrected coronary MRA sequence. Each individual was scanned three times utilising different strategies for determination of the optimal trigger delay: (1) the DL software, (2) an experienced operator decision, and (3) a previously utilised formula for determining the trigger delay. Methodologies were compared using custom-made analysis software to assess visible coronary vessel length and coronary vessel sharpness for the entire vessel length and the first 4 cm of each vessel. RESULTS There was no difference in image quality between any of the methodologies for determination of the optimal trigger delay, as assessed by visible coronary vessel length, coronary vessel sharpness for each entire vessel and vessel sharpness for the first 4 cm of the left mainstem, left anterior descending or right coronary arteries. However, vessel length of the left circumflex was slightly greater using the formula method. The time taken to calculate the trigger delay was significantly lower for the DL-method as compared to the operator-led approach (106 ± 38.0 s vs 168 ± 39.2 s, p < 0.01, 95% CI of difference 25.5-98.1 s). CONCLUSIONS Deep learning-derived automated software can effectively and efficiently determine the optimal trigger delay for acquisition of coronary MRA and thus may simplify workflow and improve reproducibility.
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Affiliation(s)
- Gregory Wood
- Department of Cardiology, Aarhus University Hospital, Palle Juul Jensens Boulevard 99, 8200, Aarhus N, Denmark.
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark.
| | - Alexandra Uglebjerg Pedersen
- Department of Cardiology, Aarhus University Hospital, Palle Juul Jensens Boulevard 99, 8200, Aarhus N, Denmark
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Karl P Kunze
- MR Research Collaborations, Siemens Healthcare Limited, Camberley, UK
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Radhouene Neji
- MR Research Collaborations, Siemens Healthcare Limited, Camberley, UK
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Reza Hajhosseiny
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
- National Heart and Lung Institute, Imperial College London, London, UK
| | - Jens Wetzl
- Cardiovascular MR Predevelopment, Siemens Healthcare GmbH, Erlangen, Germany
| | - Seung Su Yoon
- Cardiovascular MR Predevelopment, Siemens Healthcare GmbH, Erlangen, Germany
| | - Michaela Schmidt
- Cardiovascular MR Predevelopment, Siemens Healthcare GmbH, Erlangen, Germany
| | - Bjarne Linde Nørgaard
- Department of Cardiology, Aarhus University Hospital, Palle Juul Jensens Boulevard 99, 8200, Aarhus N, Denmark
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - 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, Santiago, Chile
| | - 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
- Instituto de Ingeniería Biológica y Médica, Pontificia Universidad Católica de Chile, Santiago, Chile
- Institute for Advanced Study, Technical University of Munich, Garching, Germany
- Millenium Institute for Intelligent Healthcare Engineering, Santiago, Chile
| | - Won Yong Kim
- Department of Cardiology, Aarhus University Hospital, Palle Juul Jensens Boulevard 99, 8200, Aarhus N, Denmark
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
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15
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Kettelkamp J, Romanin L, Piccini D, Priya S, Jacob M. Motion Compensated Unsupervised Deep Learning for 5D MRI. MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION : MICCAI ... INTERNATIONAL CONFERENCE ON MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION 2023; 14229:419-427. [PMID: 38737212 PMCID: PMC11087022 DOI: 10.1007/978-3-031-43999-5_40] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/14/2024]
Abstract
We propose an unsupervised deep learning algorithm for the motion-compensated reconstruction of 5D cardiac MRI data from 3D radial acquisitions. Ungated free-breathing 5D MRI simplifies the scan planning, improves patient comfort, and offers several clinical benefits over breath-held 2D exams, including isotropic spatial resolution and the ability to reslice the data to arbitrary views. However, the current reconstruction algorithms for 5D MRI take very long computational time, and their outcome is greatly dependent on the uniformity of the binning of the acquired data into different physiological phases. The proposed algorithm is a more data-efficient alternative to current motion-resolved reconstructions. This motion-compensated approach models the data in each cardiac/respiratory bin as Fourier samples of the deformed version of a 3D image template. The deformation maps are modeled by a convolutional neural network driven by the physiological phase information. The deformation maps and the template are then jointly estimated from the measured data. The cardiac and respiratory phases are estimated from 1D navigators using an auto-encoder. The proposed algorithm is validated on 5D bSSFP datasets acquired from two subjects.
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Affiliation(s)
| | - Ludovica Romanin
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland
| | - Davide Piccini
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland
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Fyrdahl A, Ullvin A, Ramos JG, Seiberlich N, Ugander M, Sigfridsson A. Three-dimensional sector-wise golden angle-improved k-space uniformity after electrocardiogram binning. Magn Reson Med 2023; 90:1041-1052. [PMID: 37183485 DOI: 10.1002/mrm.29698] [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: 11/14/2022] [Revised: 04/17/2023] [Accepted: 04/21/2023] [Indexed: 05/16/2023]
Abstract
PURPOSE To develop and evaluate a 3D sector-wise golden-angle (3D-SWIG) profile ordering scheme for cardiovascular MR cine imaging that maintains high k-space uniformity after electrocardiogram (ECG) binning. METHOD Cardiovascular MR (CMR) was performed at 1.5 T. A balanced SSFP pulse sequence was implemented with a novel 3D-SWIG radial ordering, where k-space was divided into wedges, and each wedge was acquired in a separate heartbeat. The high uniformity of k-space coverage after physiological binning can be used to perform functional imaging using a very short acquisition. The 3D-SWIG was compared with two commonly used 3D radial trajectories for CMR (i.e., double golden angle and spiral phyllotaxis) in numerical simulations. Free-breathing 3D-SWIG and conventional breath-held 2D cine were compared in patients (n = 17) referred clinically for CMR. Quantitative comparison was performed based on left ventricular segmentation. RESULTS Numerical simulations showed that 3D-SWIG both required smaller steps between successive readouts and achieved better k-space sampling uniformity after binning than either the double golden angle or spiral phyllotaxis trajectories. In vivo evaluation showed that measurements of left ventricular ejection fraction calculated from a 48 heart-beat free-breathing 3D-SWIG acquisition were highly reproducible and agreed with breath-held 2D-Cartesian cine (mean ± SD difference of -3.1 ± 3.5% points). CONCLUSIONS The 3D-SWIG acquisition offers a simple solution for highly improved k-space uniformity after physiological binning. The feasibility of the 3D-SWIG method is demonstrated in this study through whole-heart cine imaging during free breathing with an acquisition time of less than 1 min.
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Affiliation(s)
- Alexander Fyrdahl
- Department of Clinical Physiology, Karolinska University Hospital, and Karolinska Institutet, Stockholm, Sweden
| | - Amanda Ullvin
- Department of Clinical Physiology, Karolinska University Hospital, and Karolinska Institutet, Stockholm, Sweden
| | - Joao G Ramos
- Department of Clinical Physiology, Karolinska University Hospital, and Karolinska Institutet, Stockholm, Sweden
| | - Nicole Seiberlich
- Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
| | - Martin Ugander
- Department of Clinical Physiology, Karolinska University Hospital, and Karolinska Institutet, Stockholm, Sweden
- The Kolling Institute, Royal North Shore Hospital, and University of Sydney, Sydney, Australia
| | - Andreas Sigfridsson
- Department of Clinical Physiology, Karolinska University Hospital, and Karolinska Institutet, Stockholm, Sweden
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17
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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: 26] [Impact Index Per Article: 26.0] [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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18
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Falcão MBL, Rossi GMC, Rutz T, Prša M, Tenisch E, Ma L, Weiss EK, Baraboo JJ, Yerly J, Markl M, Stuber M, Roy CW. Focused navigation for respiratory-motion-corrected free-running radial 4D flow MRI. Magn Reson Med 2023; 90:117-132. [PMID: 36877140 PMCID: PMC10149606 DOI: 10.1002/mrm.29634] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2022] [Revised: 02/21/2023] [Accepted: 02/21/2023] [Indexed: 03/07/2023]
Abstract
PURPOSE To validate a respiratory motion correction method called focused navigation (fNAV) for free-running radial whole-heart 4D flow MRI. METHODS Using fNAV, respiratory signals derived from radial readouts are converted into three orthogonal displacements, which are then used to correct respiratory motion in 4D flow datasets. Hundred 4D flow acquisitions were simulated with non-rigid respiratory motion and used for validation. The difference between generated and fNAV displacement coefficients was calculated. Vessel area and flow measurements from 4D flow reconstructions with (fNAV) and without (uncorrected) motion correction were compared to the motion-free ground-truth. In 25 patients, the same measurements were compared between fNAV 4D flow, 2D flow, navigator-gated Cartesian 4D flow, and uncorrected 4D flow datasets. RESULTS For simulated data, the average difference between generated and fNAV displacement coefficients was 0.04± $$ \pm $$ 0.32 mm and 0.31± $$ \pm $$ 0.35 mm in the x and y directions, respectively. In the z direction, this difference was region-dependent (0.02± $$ \pm $$ 0.51 mm up to 5.85± $$ \pm $$ 3.41 mm). For all measurements (vessel area, net volume, and peak flow), the average difference from ground truth was higher for uncorrected 4D flow datasets (0.32± $$ \pm $$ 0.11 cm2 , 11.1± $$ \pm $$ 3.5 mL, and 22.3± $$ \pm $$ 6.0 mL/s) than for fNAV 4D flow datasets (0.10± $$ \pm $$ 0.03 cm2 , 2.6± $$ \pm $$ 0.7 mL, and 5.1± 0 $$ \pm 0 $$ .9 mL/s, p < 0.05). In vivo, average vessel area measurements were 4.92± $$ \pm $$ 2.95 cm2 , 5.06± $$ \pm $$ 2.64 cm2 , 4.87± $$ \pm $$ 2.57 cm2 , 4.87± $$ \pm $$ 2.69 cm2 , for 2D flow and fNAV, navigator-gated and uncorrected 4D flow datasets, respectively. In the ascending aorta, all 4D flow datasets except for the fNAV reconstruction had significantly different vessel area measurements from 2D flow. Overall, 2D flow datasets demonstrated the strongest correlation to fNAV 4D flow for both net volume (r2 = 0.92) and peak flow (r2 = 0.94), followed by navigator-gated 4D flow (r2 = 0.83 and r2 = 0.86, respectively), and uncorrected 4D flow (r2 = 0.69 and r2 = 0.86, respectively). CONCLUSION fNAV corrected respiratory motion in vitro and in vivo, resulting in fNAV 4D flow measurements that are comparable to those derived from 2D flow and navigator-gated Cartesian 4D flow datasets, with improvements over those from uncorrected 4D flow.
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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
| | - Giulia M. C. Rossi
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Tobias Rutz
- Service of Cardiology, Centre de Resonance Magnétique Cardiaque (CRMC), Lausanne University Hospital and University of Lausanne, 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
| | - Liliana Ma
- Department of Radiology, Feinberg School of Medicine, Northwestern University, Chicago, Illinois USA
- Department of Biomedical Engineering, Northwestern University, Chicago, Illinois USA
| | - Elizabeth K. Weiss
- Department of Radiology, Feinberg School of Medicine, Northwestern University, Chicago, Illinois USA
- Department of Biomedical Engineering, Northwestern University, Chicago, Illinois USA
| | - Justin J. Baraboo
- Department of Radiology, Feinberg School of Medicine, Northwestern University, Chicago, Illinois USA
- Department of Biomedical Engineering, Northwestern University, Chicago, Illinois USA
| | - Jérôme Yerly
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- Center for Biomedical Imaging (CIBM), 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
| | - 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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19
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Yang Y, Shah Z, Jacob AJ, Hair J, Chitiboi T, Passerini T, Yerly J, Di Sopra L, Piccini D, Hosseini Z, Sharma P, Sahu A, Stuber M, Oshinski JN. Deep learning-based left ventricular segmentation demonstrates improved performance on respiratory motion-resolved whole-heart reconstructions. FRONTIERS IN RADIOLOGY 2023; 3:1144004. [PMID: 37492382 PMCID: PMC10365088 DOI: 10.3389/fradi.2023.1144004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/13/2023] [Accepted: 05/17/2023] [Indexed: 07/27/2023]
Abstract
Introduction Deep learning (DL)-based segmentation has gained popularity for routine cardiac magnetic resonance (CMR) image analysis and in particular, delineation of left ventricular (LV) borders for LV volume determination. Free-breathing, self-navigated, whole-heart CMR exams provide high-resolution, isotropic coverage of the heart for assessment of cardiac anatomy including LV volume. The combination of whole-heart free-breathing CMR and DL-based LV segmentation has the potential to streamline the acquisition and analysis of clinical CMR exams. The purpose of this study was to compare the performance of a DL-based automatic LV segmentation network trained primarily on computed tomography (CT) images in two whole-heart CMR reconstruction methods: (1) an in-line respiratory motion-corrected (Mcorr) reconstruction and (2) an off-line, compressed sensing-based, multi-volume respiratory motion-resolved (Mres) reconstruction. Given that Mres images were shown to have greater image quality in previous studies than Mcorr images, we hypothesized that the LV volumes segmented from Mres images are closer to the manual expert-traced left ventricular endocardial border than the Mcorr images. Method This retrospective study used 15 patients who underwent clinically indicated 1.5 T CMR exams with a prototype ECG-gated 3D radial phyllotaxis balanced steady state free precession (bSSFP) sequence. For each reconstruction method, the absolute volume difference (AVD) of the automatically and manually segmented LV volumes was used as the primary quantity to investigate whether 3D DL-based LV segmentation generalized better on Mcorr or Mres 3D whole-heart images. Additionally, we assessed the 3D Dice similarity coefficient between the manual and automatic LV masks of each reconstructed 3D whole-heart image and the sharpness of the LV myocardium-blood pool interface. A two-tail paired Student's t-test (alpha = 0.05) was used to test the significance in this study. Results & Discussion The AVD in the respiratory Mres reconstruction was lower than the AVD in the respiratory Mcorr reconstruction: 7.73 ± 6.54 ml vs. 20.0 ± 22.4 ml, respectively (n = 15, p-value = 0.03). The 3D Dice coefficient between the DL-segmented masks and the manually segmented masks was higher for Mres images than for Mcorr images: 0.90 ± 0.02 vs. 0.87 ± 0.03 respectively, with a p-value = 0.02. Sharpness on Mres images was higher than on Mcorr images: 0.15 ± 0.05 vs. 0.12 ± 0.04, respectively, with a p-value of 0.014 (n = 15). Conclusion We conclude that the DL-based 3D automatic LV segmentation network trained on CT images and fine-tuned on MR images generalized better on Mres images than on Mcorr images for quantifying LV volumes.
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Affiliation(s)
- Yitong Yang
- Wallace H. Coulter Department of Biomedical Engineering, Emory University and the Georgia Institute of Technology, Atlanta, GA, United States
| | - Zahraw Shah
- Wallace H. Coulter Department of Biomedical Engineering, Emory University and the Georgia Institute of Technology, Atlanta, GA, United States
| | - Athira J. Jacob
- Digital Technology and Innovation, Siemens Medical Solutions USA, Princeton, NJ, United States
| | - Jackson Hair
- Wallace H. Coulter Department of Biomedical Engineering, Emory University and the Georgia Institute of Technology, Atlanta, GA, United States
| | - Teodora Chitiboi
- Digital Technology and Innovation, Siemens Medical Solutions USA, Princeton, NJ, United States
| | - Tiziano Passerini
- Digital Technology and Innovation, Siemens Medical Solutions USA, Princeton, NJ, United States
| | - Jerome Yerly
- Diagnostic and Interventional Radiology, Lausanne University Hospital, Lausanne, Switzerland
| | - Lorenzo Di Sopra
- Diagnostic and Interventional Radiology, Lausanne University Hospital, Lausanne, Switzerland
| | - Davide Piccini
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland
| | - Zahra Hosseini
- MR R&D Collaboration, Siemens Medical Solutions USA, Atlanta, GA, United States
| | - Puneet Sharma
- Digital Technology and Innovation, Siemens Medical Solutions USA, Princeton, NJ, United States
| | - Anurag Sahu
- MR R&D Collaboration, Siemens Medical Solutions USA, Atlanta, GA, United States
| | - Matthias Stuber
- Diagnostic and Interventional Radiology, Lausanne University Hospital, Lausanne, Switzerland
| | - John N. Oshinski
- Wallace H. Coulter Department of Biomedical Engineering, Emory University and the Georgia Institute of Technology, Atlanta, GA, United States
- Department of Radiology & Imaging Science, Emory University School of Medicine, Atlanta, GA, United States
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20
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Franceschiello B, Rumac S, Hilbert T, Nau M, Dziadosz M, Degano G, Roy CW, Gaglianese A, Petri G, Yerly J, Stuber M, Kober T, van Heeswijk RB, Murray MM, Fornari E. Hi-Fi fMRI: High-resolution, fast-sampled and sub-second whole-brain functional MRI at 3T in humans. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.05.13.540663. [PMID: 37425913 PMCID: PMC10327135 DOI: 10.1101/2023.05.13.540663] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/11/2023]
Abstract
Functional magnetic resonance imaging (fMRI) is a methodological cornerstone of neuroscience. Most studies measure blood-oxygen-level-dependent (BOLD) signal using echo-planar imaging (EPI), Cartesian sampling, and image reconstruction with a one-to-one correspondence between the number of acquired volumes and reconstructed images. However, EPI schemes are subject to trade-offs between spatial and temporal resolutions. We overcome these limitations by measuring BOLD with a gradient recalled echo (GRE) with 3D radial-spiral phyllotaxis trajectory at a high sampling rate (28.24ms) on standard 3T field-strength. The framework enables the reconstruction of 3D signal time courses with whole-brain coverage at simultaneously higher spatial (1mm 3 ) and temporal (up to 250ms) resolutions, as compared to optimized EPI schemes. Additionally, artifacts are corrected before image reconstruction; the desired temporal resolution is chosen after scanning and without assumptions on the shape of the hemodynamic response. By showing activation in the calcarine sulcus of 20 participants performing an ON-OFF visual paradigm, we demonstrate the reliability of our method for cognitive neuroscience research.
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21
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Sun A, Zhao B, Zheng Y, Long Y, Wu P, Wang B, Li R, Wang H. Motion-resolved real-time 4D flow MRI with low-rank and subspace modeling. Magn Reson Med 2023; 89:1839-1852. [PMID: 36533875 DOI: 10.1002/mrm.29557] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2022] [Revised: 11/01/2022] [Accepted: 11/25/2022] [Indexed: 12/23/2022]
Abstract
PURPOSE To develop a new motion-resolved real-time four-dimensional (4D) flow MRI method, which enables the quantification and visualization of blood flow velocities with three-directional flow encodings and volumetric coverage without electrocardiogram (ECG) synchronization and respiration control. METHODS An integrated imaging method is presented for real-time 4D flow MRI, which encompasses data acquisition, image reconstruction, and postprocessing. The proposed method features a specialized continuous ( k , t ) $$ \left(\mathbf{k},t\right) $$ -space acquisition scheme, which collects two sets of data (i.e., training data and imaging data) in an interleaved manner. By exploiting strong spatiotemporal correlation of 4D flow data, it reconstructs time-series images from highly-undersampled ( k , t ) $$ \left(\mathbf{k},t\right) $$ -space measurements with a low-rank and subspace model. Through data-binning-based postprocessing, it constructs a five-dimensional dataset (i.e., x-y-z-cardiac-respiratory), from which respiration-dependent flow information is further analyzed. The proposed method was evaluated in aortic flow imaging experiments with ten healthy subjects and two patients with atrial fibrillation. RESULTS The proposed method achieves 2.4 mm isotropic spatial resolution and 34.4 ms temporal resolution for measuring the blood flow of the aorta. For the healthy subjects, it provides flow measurements in good agreement with those from the conventional 4D flow MRI technique. For the patients with atrial fibrillation, it is able to resolve beat-by-beat pathological flow variations, which cannot be obtained from the conventional technique. The postprocessing further provides respiration-dependent flow information. CONCLUSION The proposed method enables high-resolution motion-resolved real-time 4D flow imaging without ECG gating and respiration control. It is able to resolve beat-by-beat blood flow variations as well as respiration-dependent flow information.
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Affiliation(s)
- Aiqi Sun
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Bo Zhao
- Department of Biomedical Engineering, University of Texas at Austin, Austin, Texas, USA.,Oden Institute for Computational Engineering and Sciences, University of Texas at Austin, Austin, Texas, USA
| | | | - Yuliang Long
- Department of Cardiology, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Peng Wu
- Philips Healthcare, Shanghai, China
| | - Bei Wang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Rui Li
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China
| | - He Wang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.,Department of Neurology, Zhongshan Hospital, Fudan University, Shanghai, China
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22
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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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23
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Piek M, Ryd D, Töger J, Testud F, Hedström E, Aletras AH. Fetal 3D cardiovascular cine image acquisition using radial sampling and compressed sensing. Magn Reson Med 2023; 89:594-604. [PMID: 36156292 PMCID: PMC10087603 DOI: 10.1002/mrm.29467] [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: 03/25/2022] [Revised: 08/09/2022] [Accepted: 09/04/2022] [Indexed: 12/13/2022]
Abstract
PURPOSE To explore a fetal 3D cardiovascular cine acquisition using a radial image acquisition and compressed-sensing reconstruction and compare image quality and scan time with conventional multislice 2D imaging. METHODS Volumetric fetal cardiac data were acquired in 26 volunteers using a radial 3D balanced SSFP pulse sequence. Cardiac gating was performed using a Doppler ultrasound device. Images were reconstructed using a parallel-imaging and compressed-sensing algorithm. Multiplanar reformatting to standard cardiac views was performed before image analysis. Clinical 2D images were used for comparison. Qualitative and quantitative image evaluation were performed by two experienced observers (scale: 1-4). Volumes, mass, and function were assessed. RESULTS Average scan time for the 3D imaging was 6 min, including one localizer. A 2D imaging stack covering the entire heart including localizer sequences took at least 6.5 min, depending on planning complexity. The 3D acquisition was successful in 7 of 26 subjects (27%). Overall image contrast and perceived resolution were lower in the 3D images. Nonetheless, the 3D images had, on average, a moderate cardiac diagnostic quality (median [range]: 3 [1-4]). Standard clinical 2D acquisitions had a high cardiac diagnostic quality (median [range]: 4 [3, 4]). Cardiac measurements were not different between 2D and 3D images (all p > 0.16). CONCLUSION The presented free-breathing whole-heart fetal 3D radial cine MRI acquisition and reconstruction method enables retrospective visualization of all cardiac views while keeping examination times short. This proof-of-concept work produced images with diagnostic quality, while at the same time reducing the planning complexity to a single localizer.
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Affiliation(s)
- Marjolein Piek
- Clinical Physiology, Department of Clinical Sciences Lund, Lund University, Skåne University Hospital, Lund, Sweden
| | - Daniel Ryd
- Clinical Physiology, Department of Clinical Sciences Lund, Lund University, Skåne University Hospital, Lund, Sweden
| | - Johannes Töger
- Clinical Physiology, Department of Clinical Sciences Lund, Lund University, Skåne University Hospital, Lund, Sweden
| | | | - Erik Hedström
- Clinical Physiology, Department of Clinical Sciences Lund, Lund University, Skåne University Hospital, Lund, Sweden.,Diagnostic Radiology, Department of Clinical Sciences Lund, Lund University, Skåne University Hospital, Lund, Sweden
| | - Anthony H Aletras
- Clinical Physiology, Department of Clinical Sciences Lund, Lund University, Skåne University Hospital, Lund, Sweden.,Laboratory of Computing, Medical Informatics and Biomedical-Imaging Technologies, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, Thessaloniki, Greece
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24
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Eyre K, Lindsay K, Razzaq S, Chetrit M, Friedrich M. Simultaneous multi-parametric acquisition and reconstruction techniques in cardiac magnetic resonance imaging: Basic concepts and status of clinical development. Front Cardiovasc Med 2022; 9:953823. [PMID: 36277755 PMCID: PMC9582154 DOI: 10.3389/fcvm.2022.953823] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2022] [Accepted: 09/22/2022] [Indexed: 11/13/2022] Open
Abstract
Simultaneous multi-parametric acquisition and reconstruction techniques (SMART) are gaining attention for their potential to overcome some of cardiovascular magnetic resonance imaging's (CMR) clinical limitations. The major advantages of SMART lie within their ability to simultaneously capture multiple "features" such as cardiac motion, respiratory motion, T1/T2 relaxation. This review aims to summarize the overarching theory of SMART, describing key concepts that many of these techniques share to produce co-registered, high quality CMR images in less time and with less requirements for specialized personnel. Further, this review provides an overview of the recent developments in the field of SMART by describing how they work, the parameters they can acquire, their status of clinical testing and validation, and by providing examples for how their use can improve the current state of clinical CMR workflows. Many of the SMART are in early phases of development and testing, thus larger scale, controlled trials are needed to evaluate their use in clinical setting and with different cardiac pathologies.
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Affiliation(s)
- Katerina Eyre
- McGill University Health Centre, Montreal, QC, Canada,Department of Experimental Medicine, McGill University, Montreal, QC, Canada,*Correspondence: Katerina Eyre,
| | - Katherine Lindsay
- McGill University Health Centre, Montreal, QC, Canada,Department of Experimental Medicine, McGill University, Montreal, QC, Canada
| | - Saad Razzaq
- Department of Experimental Medicine, McGill University, Montreal, QC, Canada
| | - Michael Chetrit
- McGill University Health Centre, Montreal, QC, Canada,Department of Experimental Medicine, McGill University, Montreal, QC, Canada
| | - Matthias Friedrich
- McGill University Health Centre, Montreal, QC, Canada,Department of Experimental Medicine, McGill University, Montreal, QC, Canada
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25
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Roy CW, Di Sopra L, Whitehead KK, Piccini D, Yerly J, Heerfordt J, Ghosh RM, Fogel MA, Stuber M. Free-running cardiac and respiratory motion-resolved 5D whole-heart coronary cardiovascular magnetic resonance angiography in pediatric cardiac patients using ferumoxytol. J Cardiovasc Magn Reson 2022; 24:39. [PMID: 35754040 PMCID: PMC9235103 DOI: 10.1186/s12968-022-00871-3] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2022] [Accepted: 06/10/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Coronary cardiovascular magnetic resonance angiography (CCMRA) of congenital heart disease (CHD) in pediatric patients requires accurate planning, adequate sequence parameter adjustments, lengthy scanning sessions, and significant involvement from highly trained personnel. Anesthesia and intubation are commonplace to minimize movements and control respiration in younger subjects. To address the above concerns and provide a single-click imaging solution, we applied our free-running framework for fully self-gated (SG) free-breathing 5D whole-heart CCMRA to CHD patients after ferumoxytol injection. We tested the hypothesis that spatial and motion resolution suffice to visualize coronary artery ostia in a cohort of CHD subjects, both for intubated and free-breathing acquisitions. METHODS In 18 pediatric CHD patients, non-electrocardiogram (ECG) triggered 5D free-running gradient echo CCMRA with whole-heart 1 mm3 isotropic spatial resolution was performed in seven minutes on a 1.5T CMR scanner. Eleven patients were anesthetized and intubated, while seven were breathing freely without anesthesia. All patients were slowly injected with ferumoxytol (4 mg/kg) over 15 minutes. Cardiac and respiratory motion-resolved 5D images were reconstructed with a fully SG approach. To evaluate the performance of motion resolution, visibility of coronary artery origins was assessed. Intubated and free-breathing patient sub-groups were compared for image quality using coronary artery length and conspicuity as well as lung-liver interface sharpness. RESULTS Data collection using the free-running framework was successful in all patients in less than 8 min; scan planning was very simple without the need for parameter adjustments, while no ECG lead placement and triggering was required. From the resulting SG 5D motion-resolved reconstructed images, coronary artery origins could be retrospectively extracted in 90% of the cases. These general findings applied to both intubated and free-breathing pediatric patients (no difference in terms of lung-liver interface sharpness), while image quality and coronary conspicuity between both cohorts was very similar. CONCLUSIONS A simple-to-use push-button framework for 5D whole-heart CCMRA was successfully employed in pediatric CHD patients with ferumoxytol injection. This approach, working without any external gating and for a wide range of heart rates and body sizes provided excellent definition of cardiac anatomy for both intubated and free-breathing patients.
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Affiliation(s)
- Christopher W. Roy
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Rue de Bugnon 46, BH-8-84, 1011 Lausanne, Switzerland
| | - Lorenzo Di Sopra
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Rue de Bugnon 46, BH-8-84, 1011 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, USA
| | - Davide Piccini
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Rue de Bugnon 46, BH-8-84, 1011 Lausanne, Switzerland
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland
| | - Jérôme Yerly
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Rue de Bugnon 46, BH-8-84, 1011 Lausanne, Switzerland
- Center for Biomedical Imaging (CIBM), Lausanne, Switzerland
| | - John Heerfordt
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Rue de Bugnon 46, BH-8-84, 1011 Lausanne, Switzerland
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland
| | - Reena M. Ghosh
- Division of Cardiology, Department of Pediatrics, The Children’s Hospital of Philadelphia, University of Pennsylvania Perelman School of Medicine, Philadelphia, USA
| | - Mark A. Fogel
- Division of Cardiology, Department of Pediatrics, The Children’s Hospital of Philadelphia, University of Pennsylvania Perelman School of Medicine, Philadelphia, USA
| | - Matthias Stuber
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Rue de Bugnon 46, BH-8-84, 1011 Lausanne, Switzerland
- Center for Biomedical Imaging (CIBM), Lausanne, Switzerland
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26
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Androulakis E, Mohiaddin R, Bratis K. Magnetic resonance coronary angiography in the era of multimodality imaging. Clin Radiol 2022; 77:e489-e499. [DOI: 10.1016/j.crad.2022.03.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2021] [Accepted: 03/09/2022] [Indexed: 11/28/2022]
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27
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Darnell D, Truong TK, Song AW. Recent Advances in Radio-Frequency Coil Technologies: Flexible, Wireless, and Integrated Coil Arrays. J Magn Reson Imaging 2022; 55:1026-1042. [PMID: 34324753 PMCID: PMC10494287 DOI: 10.1002/jmri.27865] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2021] [Revised: 07/19/2021] [Accepted: 07/19/2021] [Indexed: 12/25/2022] Open
Abstract
Radio-frequency (RF) coils are to magnetic resonance imaging (MRI) scanners what eyes are to the human body. Because of their critical importance, there have been constant innovations driving the rapid development of RF coil technologies. Over the past four decades, the breadth and depth of the RF coil technology evolution have far exceeded the space allowed for this review article. However, these past developments have laid the very foundation on which some of the recent technical breakthroughs are built upon. Here, we narrow our focus on some of the most recent RF coil advances, specifically, on flexible, wireless, and integrated coil arrays. To provide a detailed review, we discuss the theoretical underpinnings, experimental implementations, promising results, as well as future outlooks covering these exciting topics. These recent innovations have greatly improved patient comfort and ease of scan, while also increasing the signal-to-noise ratio, image resolution, temporal throughput, and diagnostic and treatment accuracy. Together with advances in other MRI subfields, they will undoubtedly continue to drive the field forward and lead us to an ever more exciting future. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY: Stage 1.
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Affiliation(s)
- Dean Darnell
- Brain Imaging and Analysis Center, Duke University, Durham, North Carolina, USA
| | - Trong-Kha Truong
- Brain Imaging and Analysis Center, Duke University, Durham, North Carolina, USA
| | - Allen W. Song
- Brain Imaging and Analysis Center, Duke University, Durham, North Carolina, USA
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28
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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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29
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Javed A, Ramasawmy R, O'Brien K, Mancini C, Su P, Majeed W, Benkert T, Bhat H, Suffredini AF, Malayeri A, Campbell-Washburn AE. Self-gated 3D stack-of-spirals UTE pulmonary imaging at 0.55T. Magn Reson Med 2021; 87:1784-1798. [PMID: 34783391 DOI: 10.1002/mrm.29079] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2021] [Revised: 09/22/2021] [Accepted: 10/22/2021] [Indexed: 12/24/2022]
Abstract
PURPOSE To develop an isotropic high-resolution stack-of-spirals UTE sequence for pulmonary imaging at 0.55 Tesla by leveraging a combination of robust respiratory-binning, trajectory correction, and concomitant-field corrections. METHODS A stack-of-spirals golden-angle UTE sequence was used to continuously acquire data for 15.5 minutes. The data was binned to a stable respiratory phase based on superoinferior readout self-navigator signals. Corrections for trajectory errors and concomitant field artifacts, along with image reconstruction with conjugate gradient SENSE, were performed inline within the Gadgetron framework. Finally, data were retrospectively reconstructed to simulate scan times of 5, 8.5, and 12 minutes. Image quality was assessed using signal-to-noise, image sharpness, and qualitative reader scores. The technique was evaluated in healthy volunteers, patients with coronavirus disease 2019 infection, and patients with lung nodules. RESULTS The technique provided diagnostic quality images with parenchymal lung SNR of 3.18 ± 0.0.60, 4.57 ± 0.87, 5.45 ± 1.02, and 5.89 ± 1.28 for scan times of 5, 8.5, 12, and 15.5 minutes, respectively. The respiratory binning technique resulted in significantly sharper images (p < 0.001) as measured with relative maximum derivative at the diaphragm. Concomitant field corrections visibly improved sharpness of anatomical structures away from iso-center. The image quality was maintained with a slight loss in SNR for simulated scan times down to 8.5 minutes. Inline image reconstruction and artifact correction were achieved in <5 minutes. CONCLUSION The proposed pulmonary imaging technique combined efficient stack-of-spirals imaging with robust respiratory binning, concomitant field correction, and trajectory correction to generate diagnostic quality images with 1.75 mm isotropic resolution in 8.5 minutes on a high-performance 0.55 Tesla system.
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Affiliation(s)
- Ahsan Javed
- Cardiovascular Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Rajiv Ramasawmy
- Cardiovascular Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Kendall O'Brien
- Cardiovascular Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Christine Mancini
- Cardiovascular Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Pan Su
- Siemens Medical Solutions USA Inc., Malvern, Pennsylvania, USA
| | - Waqas Majeed
- Siemens Medical Solutions USA Inc., Malvern, Pennsylvania, USA
| | | | - Himanshu Bhat
- Siemens Medical Solutions USA Inc., Malvern, Pennsylvania, USA
| | - Anthony F Suffredini
- Critical Care Medicine Department, Clinical Center, National Institutes of Health, Bethesda, Maryland, USA
| | - Ashkan Malayeri
- Department of Radiology and Imaging Sciences, Clinical Center, Department of Health and Human Services, National Institutes of Health, Bethesda, Maryland, USA
| | - Adrienne E Campbell-Washburn
- Cardiovascular Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland, USA
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30
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Bonanno G, Weiss RG, Piccini D, Yerly J, Soleimani S, Pan L, Bi X, Hays AG, Stuber M, Schär M. Volumetric coronary endothelial function assessment: a feasibility study exploiting stack-of-stars 3D cine MRI and image-based respiratory self-gating. NMR IN BIOMEDICINE 2021; 34:e4589. [PMID: 34291517 PMCID: PMC8969584 DOI: 10.1002/nbm.4589] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/13/2020] [Accepted: 06/25/2021] [Indexed: 06/13/2023]
Abstract
Abnormal coronary endothelial function (CEF), manifesting as depressed vasoreactive responses to endothelial-specific stressors, occurs early in atherosclerosis, independently predicts cardiovascular events, and responds to cardioprotective interventions. CEF is spatially heterogeneous along a coronary artery in patients with atherosclerosis, and thus recently developed and tested non-invasive 2D MRI techniques to measure CEF may not capture the extent of changes in CEF in a given coronary artery. The purpose of this study was to develop and test the first volumetric coronary 3D MRI cine method for assessing CEF along the proximal and mid-coronary arteries with isotropic spatial resolution and in free-breathing. This approach, called 3D-Stars, combines a 6 min continuous, untriggered golden-angle stack-of-stars acquisition with a novel image-based respiratory self-gating method and cardiac and respiratory motion-resolved reconstruction. The proposed respiratory self-gating method agreed well with respiratory bellows and center-of-k-space methods. In healthy subjects, 3D-Stars vessel sharpness was non-significantly different from that by conventional 2D radial in proximal segments, albeit lower in mid-portions. Importantly, 3D-Stars detected normal vasodilatation of the right coronary artery in response to endothelial-dependent isometric handgrip stress in healthy subjects. Coronary artery cross-sectional areas measured using 3D-Stars were similar to those from 2D radial MRI when similar thresholding was used. In conclusion, 3D-Stars offers good image quality and shows feasibility for non-invasively studying vasoreactivity-related lumen area changes along the proximal coronary artery in 3D during free-breathing.
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Affiliation(s)
- Gabriele Bonanno
- Division of Cardiology, Department of Medicine, Johns Hopkins University, Baltimore, MD, USA
- Russel H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University, Baltimore, MD, USA
| | - Robert G. Weiss
- Division of Cardiology, Department of Medicine, Johns Hopkins University, Baltimore, MD, USA
- Russel H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University, Baltimore, MD, USA
| | - Davide Piccini
- Advanced Clinical Imaging Technology, Siemens Healthcare, Lausanne, Switzerland
| | - Jérôme Yerly
- Department of Radiology, University Hospital of Lausanne, Lausanne, Switzerland
- Center for Biomedical Imaging (CIBM), University Hospital of Lausanne, Lausanne, Switzerland
| | - Sahar Soleimani
- Russel H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University, Baltimore, MD, USA
| | - Li Pan
- Siemens Medical Solutions USA, Inc, Baltimore, MD, USA
| | - Xiaoming Bi
- Siemens Medical Solutions USA, Inc, Los Angeles, CA, USA
| | - Allison G Hays
- Division of Cardiology, Department of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Matthias Stuber
- Department of Radiology, University Hospital of Lausanne, Lausanne, Switzerland
- Center for Biomedical Imaging (CIBM), University Hospital of Lausanne, Lausanne, Switzerland
| | - Michael Schär
- Russel H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University, Baltimore, MD, USA
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31
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Bustin A, Toupin S, Sridi S, Yerly J, Bernus O, Labrousse L, Quesson B, Rogier J, Haïssaguerre M, van Heeswijk R, Jaïs P, Cochet H, Stuber M. Endogenous assessment of myocardial injury with single-shot model-based non-rigid motion-corrected T1 rho mapping. J Cardiovasc Magn Reson 2021; 23:119. [PMID: 34670572 PMCID: PMC8529795 DOI: 10.1186/s12968-021-00781-w] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2020] [Accepted: 05/26/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Cardiovascular magnetic resonance T1ρ mapping may detect myocardial injuries without exogenous contrast agent. However, multiple co-registered acquisitions are required, and the lack of robust motion correction limits its clinical translation. We introduce a single breath-hold myocardial T1ρ mapping method that includes model-based non-rigid motion correction. METHODS A single-shot electrocardiogram (ECG)-triggered balanced steady state free precession (bSSFP) 2D adiabatic T1ρ mapping sequence that collects five T1ρ-weighted (T1ρw) images with different spin lock times within a single breath-hold is proposed. To address the problem of residual respiratory motion, a unified optimization framework consisting of a joint T1ρ fitting and model-based non-rigid motion correction algorithm, insensitive to contrast change, was implemented inline for fast (~ 30 s) and direct visualization of T1ρ maps. The proposed reconstruction was optimized on an ex vivo human heart placed on a motion-controlled platform. The technique was then tested in 8 healthy subjects and validated in 30 patients with suspected myocardial injury on a 1.5T CMR scanner. The Dice similarity coefficient (DSC) and maximum perpendicular distance (MPD) were used to quantify motion and evaluate motion correction. The quality of T1ρ maps was scored. In patients, T1ρ mapping was compared to cine imaging, T2 mapping and conventional post-contrast 2D late gadolinium enhancement (LGE). T1ρ values were assessed in remote and injured areas, using LGE as reference. RESULTS Despite breath holds, respiratory motion throughout T1ρw images was much larger in patients than in healthy subjects (5.1 ± 2.7 mm vs. 0.5 ± 0.4 mm, P < 0.01). In patients, the model-based non-rigid motion correction improved the alignment of T1ρw images, with higher DSC (87.7 ± 5.3% vs. 82.2 ± 7.5%, P < 0.01), and lower MPD (3.5 ± 1.9 mm vs. 5.1 ± 2.7 mm, P < 0.01). This resulted in significantly improved quality of the T1ρ maps (3.6 ± 0.6 vs. 2.1 ± 0.9, P < 0.01). Using this approach, T1ρ mapping could be used to identify LGE in patients with 93% sensitivity and 89% specificity. T1ρ values in injured (LGE positive) areas were significantly higher than in the remote myocardium (68.4 ± 7.9 ms vs. 48.8 ± 6.5 ms, P < 0.01). CONCLUSIONS The proposed motion-corrected T1ρ mapping framework enables a quantitative characterization of myocardial injuries with relatively low sensitivity to respiratory motion. This technique may be a robust and contrast-free adjunct to LGE for gaining new insight into myocardial structural disorders.
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Affiliation(s)
- Aurélien Bustin
- INSERM, Centre de Recherche Cardio-Thoracique de Bordeaux, U1045, IHU LIRYC, Electrophysiology and Heart Modeling Institute, Université de Bordeaux, Avenue du Haut Lévêque, 33604, Pessac, France.
- Department of Cardiovascular Imaging, Hôpital Cardiologique du Haut-Lévêque, CHU de Bordeaux, Avenue de Magellan, 33604, Pessac, France.
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.
| | - Solenn Toupin
- Siemens Healthcare France, 93210, Saint-Denis, France
| | - Soumaya Sridi
- Department of Cardiovascular Imaging, Hôpital Cardiologique du Haut-Lévêque, CHU de Bordeaux, Avenue de Magellan, 33604, Pessac, France
| | - Jérôme Yerly
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- Center for Biomedical Imaging (CIBM), Lausanne, Switzerland
| | - Olivier Bernus
- INSERM, Centre de Recherche Cardio-Thoracique de Bordeaux, U1045, IHU LIRYC, Electrophysiology and Heart Modeling Institute, Université de Bordeaux, Avenue du Haut Lévêque, 33604, Pessac, France
| | - Louis Labrousse
- INSERM, Centre de Recherche Cardio-Thoracique de Bordeaux, U1045, IHU LIRYC, Electrophysiology and Heart Modeling Institute, Université de Bordeaux, Avenue du Haut Lévêque, 33604, Pessac, France
- Department of Cardiac Surgery, Hôpital Cardiologique du Haut-Lévêque, CHU de Bordeaux, Avenue de Magellan, 33604, Pessac, France
| | - Bruno Quesson
- INSERM, Centre de Recherche Cardio-Thoracique de Bordeaux, U1045, IHU LIRYC, Electrophysiology and Heart Modeling Institute, Université de Bordeaux, Avenue du Haut Lévêque, 33604, Pessac, France
| | - Julien Rogier
- INSERM, Centre de Recherche Cardio-Thoracique de Bordeaux, U1045, IHU LIRYC, Electrophysiology and Heart Modeling Institute, Université de Bordeaux, Avenue du Haut Lévêque, 33604, Pessac, France
| | - Michel Haïssaguerre
- INSERM, Centre de Recherche Cardio-Thoracique de Bordeaux, U1045, IHU LIRYC, Electrophysiology and Heart Modeling Institute, Université de Bordeaux, Avenue du Haut Lévêque, 33604, Pessac, France
- Department of Cardiac Electrophysiology, Hôpital Cardiologique du Haut-Lévêque, CHU de Bordeaux,, Avenue de Magellan, 33604, Pessac, France
| | - Ruud van Heeswijk
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Pierre Jaïs
- INSERM, Centre de Recherche Cardio-Thoracique de Bordeaux, U1045, IHU LIRYC, Electrophysiology and Heart Modeling Institute, Université de Bordeaux, Avenue du Haut Lévêque, 33604, Pessac, France
- Department of Cardiac Electrophysiology, Hôpital Cardiologique du Haut-Lévêque, CHU de Bordeaux,, Avenue de Magellan, 33604, Pessac, France
| | - Hubert Cochet
- INSERM, Centre de Recherche Cardio-Thoracique de Bordeaux, U1045, IHU LIRYC, Electrophysiology and Heart Modeling Institute, Université de Bordeaux, Avenue du Haut Lévêque, 33604, Pessac, France
- Department of Cardiovascular Imaging, Hôpital Cardiologique du Haut-Lévêque, CHU de Bordeaux, Avenue de Magellan, 33604, Pessac, France
| | - Matthias Stuber
- INSERM, Centre de Recherche Cardio-Thoracique de Bordeaux, U1045, IHU LIRYC, Electrophysiology and Heart Modeling Institute, Université de Bordeaux, Avenue du Haut Lévêque, 33604, Pessac, France
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- Center for Biomedical Imaging (CIBM), Lausanne, Switzerland
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32
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Dorniak K, Di Sopra L, Sabisz A, Glinska A, Roy CW, Gorczewski K, Piccini D, Yerly J, Jankowska H, Fijałkowska J, Szurowska E, Stuber M, van Heeswijk RB. Respiratory Motion-Registered Isotropic Whole-Heart T 2 Mapping in Patients With Acute Non-ischemic Myocardial Injury. Front Cardiovasc Med 2021; 8:712383. [PMID: 34660714 PMCID: PMC8511642 DOI: 10.3389/fcvm.2021.712383] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2021] [Accepted: 09/06/2021] [Indexed: 11/13/2022] Open
Abstract
Background: T2 mapping is a magnetic resonance imaging technique that can be used to detect myocardial edema and inflammation. However, the focal nature of myocardial inflammation may render conventional 2D approaches suboptimal and make whole-heart isotropic 3D mapping desirable. While self-navigated 3D radial T2 mapping has been demonstrated to work well at a magnetic field strength of 3T, it results in too noisy maps at 1.5T. We therefore implemented a novel respiratory motion-resolved compressed-sensing reconstruction in order to improve the 3D T2 mapping precision and accuracy at 1.5T, and tested this in a heterogeneous patient cohort. Materials and Methods: Nine healthy volunteers and 25 consecutive patients with suspected acute non-ischemic myocardial injury (sarcoidosis, n = 19; systemic sclerosis, n = 2; acute graft rejection, n = 2, and myocarditis, n = 2) were included. The free-breathing T2 maps were acquired as three ECG-triggered T2-prepared 3D radial volumes. A respiratory motion-resolved reconstruction was followed by image registration of the respiratory states and pixel-wise T2 mapping. The resulting 3D maps were compared to routine 2D T2 maps. The T2 values of segments with and without late gadolinium enhancement (LGE) were compared in patients. Results: In the healthy volunteers, the myocardial T2 values obtained with the 2D and 3D techniques were similar (45.8 ± 1.8 vs. 46.8 ± 2.9 ms, respectively; P = 0.33). Conversely, in patients, T2 values did differ between 2D (46.7 ± 3.6 ms) and 3D techniques (50.1 ± 4.2 ms, P = 0.004). Moreover, with the 2D technique, T2 values of the LGE-positive segments were similar to those of the LGE-negative segments (T2LGE-= 46.2 ± 3.7 vs. T2LGE+ = 47.6 ± 4.1 ms; P = 0.49), whereas the 3D technique did show a significant difference (T2LGE- = 49.3 ± 6.7 vs. T2LGE+ = 52.6 ± 8.7 ms, P = 0.006). Conclusion: Respiratory motion-registered 3D radial imaging at 1.5T led to accurate isotropic 3D whole-heart T2 maps, both in the healthy volunteers and in a small patient cohort with suspected non-ischemic myocardial injury. Significantly higher T2 values were found in patients as compared to controls in 3D but not in 2D, suggestive of the technique's potential to increase the sensitivity of CMR at earlier stages of disease. Further study will be needed to demonstrate its accuracy.
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Affiliation(s)
- Karolina Dorniak
- Department of Noninvasive Cardiac Diagnostics, Medical University of Gdansk, Gdansk, Poland
| | - Lorenzo Di Sopra
- Department of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Agnieszka Sabisz
- Second Department of Radiology, Medical University of Gdansk, Gdansk, Poland
| | - Anna Glinska
- Second Department of Radiology, Medical University of Gdansk, Gdansk, Poland
| | - Christopher W Roy
- Department of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | | | - Davide Piccini
- Department of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland.,Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland
| | - Jérôme Yerly
- Department of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland.,Center for Biomedical Imaging (CIBM), Lausanne, Switzerland
| | - Hanna Jankowska
- Department of Noninvasive Cardiac Diagnostics, Medical University of Gdansk, Gdansk, Poland
| | - Jadwiga Fijałkowska
- Second Department of Radiology, Medical University of Gdansk, Gdansk, Poland
| | - Edyta Szurowska
- Second Department of Radiology, Medical University of Gdansk, Gdansk, Poland
| | - Matthias Stuber
- Department of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland.,Center for Biomedical Imaging (CIBM), Lausanne, Switzerland
| | - Ruud B van Heeswijk
- Department of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
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Falcão MBL, Di Sopra L, Ma L, Bacher M, Yerly J, Speier P, Rutz T, Prša M, Markl M, Stuber M, Roy CW. Pilot tone navigation for respiratory and cardiac motion-resolved free-running 5D flow MRI. Magn Reson Med 2021; 87:718-732. [PMID: 34611923 PMCID: PMC8627452 DOI: 10.1002/mrm.29023] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2021] [Revised: 08/17/2021] [Accepted: 09/03/2021] [Indexed: 11/07/2022]
Abstract
Purpose In this work, we integrated the pilot tone (PT) navigation system into a reconstruction framework for respiratory and cardiac motion‐resolved 5D flow. We tested the hypotheses that PT would provide equivalent respiratory curves, cardiac triggers, and corresponding flow measurements to a previously established self‐gating (SG) technique while being independent from changes to the acquisition parameters. Methods Fifteen volunteers and 9 patients were scanned with a free‐running 5D flow sequence, with PT integrated. Respiratory curves and cardiac triggers from PT and SG were compared across all subjects. Flow measurements from 5D flow reconstructions using both PT and SG were compared to each other and to a reference electrocardiogram‐gated and respiratory triggered 4D flow acquisition. Radial trajectories with variable readouts per interleave were also tested in 1 subject to compare cardiac trigger quality between PT and SG. Results The correlation between PT and SG respiratory curves were 0.95 ± 0.06 for volunteers and 0.95 ± 0.04 for patients. Heartbeat duration measurements in volunteers and patients showed a bias to electrocardiogram measurements of, respectively, 0.16 ± 64.94 ms and 0.01 ± 39.29 ms for PT versus electrocardiogram and of 0.24 ± 63.68 ms and 0.09 ± 32.79 ms for SG versus electrocardiogram. No significant differences were reported for the flow measurements between 5D flow PT and from 5D flow SG. A decrease in the cardiac triggering quality of SG was observed for increasing readouts per interleave, whereas PT quality remained constant. Conclusion PT has been successfully integrated in 5D flow MRI and has shown equivalent results to the previously described 5D flow SG technique, while being completely acquisition‐independent.
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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
| | - Lorenzo Di Sopra
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Liliana Ma
- Department of Radiology, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA.,Department of Biomedical Engineering, Northwestern University, Chicago, Illinois, USA
| | - Mario Bacher
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland.,Siemens Healthcare GmbH, Erlangen, Germany.,Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland
| | - Jérôme Yerly
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland.,Center for Biomedical Imaging (CIBM), Lausanne, Switzerland
| | | | - Tobias Rutz
- Service of Cardiology, Centre de Resonance Magnétique Cardiaque (CRMC), Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Milan Prša
- Woman-Mother-Child Department, Lausanne University Hospital and University of Lausanne, 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
| | - 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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Hajhosseiny R, Munoz C, Cruz G, Khamis R, Kim WY, Prieto C, Botnar RM. Coronary Magnetic Resonance Angiography in Chronic Coronary Syndromes. Front Cardiovasc Med 2021; 8:682924. [PMID: 34485397 PMCID: PMC8416045 DOI: 10.3389/fcvm.2021.682924] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2021] [Accepted: 07/23/2021] [Indexed: 01/14/2023] Open
Abstract
Cardiovascular disease is the leading cause of mortality worldwide, with atherosclerotic coronary artery disease (CAD) accounting for the majority of cases. X-ray coronary angiography and computed tomography coronary angiography (CCTA) are the imaging modalities of choice for the assessment of CAD. However, the use of ionising radiation and iodinated contrast agents remain drawbacks. There is therefore a clinical need for an alternative modality for the early identification and longitudinal monitoring of CAD without these associated drawbacks. Coronary magnetic resonance angiography (CMRA) could be a potential alternative for the detection and monitoring of coronary arterial stenosis, without exposing patients to ionising radiation or iodinated contrast agents. Further advantages include its versatility, excellent soft tissue characterisation and suitability for repeat imaging. Despite the early promise of CMRA, widespread clinical utilisation remains limited due to long and unpredictable scan times, onerous scan planning, lower spatial resolution, as well as motion related image quality degradation. The past decade has brought about a resurgence in CMRA technology, with significant leaps in image acceleration, respiratory and cardiac motion estimation and advanced motion corrected or motion-resolved image reconstruction. With the advent of artificial intelligence, great advances are also seen in deep learning-based motion estimation, undersampled and super-resolution reconstruction promising further improvements of CMRA. This has enabled high spatial resolution (1 mm isotropic), 3D whole heart CMRA in a clinically feasible and reliable acquisition time of under 10 min. Furthermore, latest super-resolution image reconstruction approaches which are currently under evaluation promise acquisitions as short as 1 min. In this review, we will explore the recent technological advances that are designed to bring CMRA closer to clinical reality.
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Affiliation(s)
- Reza Hajhosseiny
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
- National Heart and Lung Institute, Imperial College London, London, United Kingdom
| | - Camila Munoz
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Gastao Cruz
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Ramzi Khamis
- National Heart and Lung Institute, Imperial College London, London, United Kingdom
| | - Won Yong Kim
- Department of Cardiology and Institute of Clinical Medicine, Aarhus University Hospital, Skejby, Denmark
| | - Claudia Prieto
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
- Escuela de Ingeniería, Pontificia Universidad Catolica de Chile, Santiago, Chile
| | - René M. Botnar
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
- Escuela de Ingeniería, Pontificia Universidad Catolica de Chile, Santiago, Chile
- Instituto de Ingeniería Biologica y Medica, Pontificia Universidad Catolica de Chile, Santiago, Chile
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35
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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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36
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Balasch A, Büttner MS, Metze P, Stumpf K, Beer M, Rottbauer W, Rasche V. Tiny golden angle stack-of-stars (tygaSoS) free-breathing functional lung imaging. Magn Reson Imaging 2021; 82:24-30. [PMID: 34153438 DOI: 10.1016/j.mri.2021.06.016] [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: 02/19/2021] [Revised: 04/21/2021] [Accepted: 06/15/2021] [Indexed: 11/26/2022]
Abstract
PURPOSE MRI of the lung parenchyma is still challenging due to cardiac and respiratory motion, and the low proton density and short T2*. Clinical feasible MRI methods for functional lung assessment are of great interest. It was the objective of this study to evaluate the potential of combining the ultra-short echo-time stack-of-stars approach with tiny golden angle (tyGASoS) profile ordering for self-gated free-breathing lung imaging. METHODS Free-breathing tyGASoS data were acquired in 10 healthy volunteers (3 smoker (S), 7 non-smoker (NS)). Images in different respiratory phases were reconstructed applying an image-based self-gating technique. Resulting image quality and sharpness, and parenchyma visibility were qualitatively scored by three blinded independent reader, and the signal-to-noise ratio (SNR), proton fraction (fP) and fractional ventilation (FV) quantified. RESULT The imaging protocol was well tolerated by all volunteers. Image quality was sufficient for subsequent quantitative analysis in all cases with good to excellent inter-reader reliability. Between expiration (EX) and inspiration (IN) significant differences (p < 0.001) were observed in SNR (EX: 3.73 ± 0.89, IN: 3.14 ± 0.74) and fP (EX: 0.27 ± 0.09, IN: 0.25 ± 0.08). A significant (p < 0.05) higher fP (EX/IN: 0.22 ± 0.07/0.21 ± 0.07 (NS), 0.33 ± 0.07/0.30 ± 0.06 (S)) was observed in the smoker group. No significant FV differences resulted between S and NS. CONCLUSION The study proves the feasibility of free-breathing tyGASoS for multiphase lung imaging. Changes in fP may indicate an initial response in the smoker group and as such proves the sensitivity of the proposed technique. A major limitation in FV quantification rises from the large inter-subject variability of breathing patterns and amplitudes, requiring further consideration.
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Affiliation(s)
- A Balasch
- Department of Internal Medicine II, Ulm University Medical Centre, Ulm, Germany.
| | - M S Büttner
- Department of Radiology, Ulm University Medical Centre, Ulm, Germany.
| | - P Metze
- Department of Internal Medicine II, Ulm University Medical Centre, Ulm, Germany.
| | - K Stumpf
- Department of Internal Medicine II, Ulm University Medical Centre, Ulm, Germany.
| | - M Beer
- Department of Radiology, Ulm University Medical Centre, Ulm, Germany.
| | - W Rottbauer
- Department of Internal Medicine II, Ulm University Medical Centre, Ulm, Germany.
| | - V Rasche
- Department of Internal Medicine II, Ulm University Medical Centre, Ulm, Germany.
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37
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Ma L, Yerly J, Di Sopra L, Piccini D, Lee J, DiCarlo A, Passman R, Greenland P, Kim D, Stuber M, Markl M. Using 5D flow MRI to decode the effects of rhythm on left atrial 3D flow dynamics in patients with atrial fibrillation. Magn Reson Med 2021; 85:3125-3139. [PMID: 33400296 PMCID: PMC7904609 DOI: 10.1002/mrm.28642] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2020] [Revised: 11/20/2020] [Accepted: 11/23/2020] [Indexed: 01/05/2023]
Abstract
PURPOSE This study used a 5D flow framework to explore the influence of arrhythmia on thrombogenic hemodynamic parameters in patients with atrial fibrillation (AF). METHODS A fully self-gated, 3D radial, highly accelerated free-running 5D flow sequence with interleaved four-point velocity-encoding was acquired using an in vitro arrhythmic flow phantom and in 25 patients with a history of AF (68 ± 8 y, 6 female). Self-gating signals were used to calculate AF burden, bin data, and tag each k-space line with its RRLength . Data were binned as an RR-resolved dataset with four RR-interval bins (RR1-RR4, short-to-long) for compressed sensing reconstruction. AF burden was calculated as interquartile range of all intrascan RR-intervals divided by median RR-interval, and left atrial (LA) stasis as the percent of the cardiac cycle where the velocity was <0.1 m/s. RESULTS In vitro results demonstrated successful recovery of RR-binned flow curves using RR-resolved 5D flow compared to a real-time PC reference standard. In vivo, 5D flow was acquired in 8:48 minutes. AF burden was significantly correlated with 5D flow-derived peak (PV) and mean (MV) velocity and stasis (|ρ| = 0.54-0.75, P < .001). Sensitivity analyses determined a threshold for low versus high AF burden at 9.7%. High burden patients had increased LA mean stasis (up to +42%, P < .01), and lower MV and PV (-30%, -40.6%, respectively, P < .01). RR4 deviated furthest from respiratory-resolved reconstruction (end-expiration) with increased mean stasis (7.6% ± 14.0%, P = .10) and decreased PV (-12.7 ± 14.2%, P = .09). CONCLUSIONS RR-resolved 5D flow can capture temporal and RR-resolved 3D hemodynamics in <10 minutes and offers a novel approach to investigate arrhythmias.
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Affiliation(s)
- Liliana Ma
- Department of Radiology, Feinberg School of Medicine, Chicago, IL, USA
- Department of Biomedical Engineering, Northwestern University, Evanston, IL, USA
| | - Jérôme Yerly
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Switzerland
- Center for Biomedical Imaging (CIBM), Lausanne, Switzerland
| | - Lorenzo Di Sopra
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Switzerland
| | - Davide Piccini
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Switzerland
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland
| | - Jeesoo Lee
- Department of Radiology, Feinberg School of Medicine, Chicago, IL, USA
| | - Amanda DiCarlo
- Department of Radiology, Feinberg School of Medicine, Chicago, IL, USA
| | - Rod Passman
- Department of Medicine and Preventive Medicine, Feinberg School of Medicine, Chicago, IL, USA
| | - Philip Greenland
- Department of Medicine and Preventive Medicine, Feinberg School of Medicine, Chicago, IL, USA
| | - Daniel Kim
- Department of Radiology, Feinberg School of Medicine, Chicago, IL, USA
- Department of Biomedical Engineering, Northwestern University, Evanston, IL, USA
| | - Matthias Stuber
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Switzerland
- Center for Biomedical Imaging (CIBM), Lausanne, Switzerland
| | - Michael Markl
- Department of Radiology, Feinberg School of Medicine, Chicago, IL, USA
- Department of Biomedical Engineering, Northwestern University, Evanston, IL, USA
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Roy CW, Heerfordt J, Piccini D, Rossi G, Pavon AG, Schwitter J, Stuber M. Motion compensated whole-heart coronary cardiovascular magnetic resonance angiography using focused navigation (fNAV). J Cardiovasc Magn Reson 2021; 23:33. [PMID: 33775246 PMCID: PMC8006382 DOI: 10.1186/s12968-021-00717-4] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2020] [Accepted: 01/28/2021] [Indexed: 11/30/2022] Open
Abstract
BACKGROUND Radial self-navigated (RSN) whole-heart coronary cardiovascular magnetic resonance angiography (CCMRA) is a free-breathing technique that estimates and corrects for respiratory motion. However, RSN has been limited to a 1D rigid correction which is often insufficient for patients with complex respiratory patterns. The goal of this work is therefore to improve the robustness and quality of 3D radial CCMRA by incorporating both 3D motion information and nonrigid intra-acquisition correction of the data into a framework called focused navigation (fNAV). METHODS We applied fNAV to 500 data sets from a numerical simulation, 22 healthy subjects, and 549 cardiac patients. In each of these cohorts we compared fNAV to RSN and respiratory resolved extradimensional golden-angle radial sparse parallel (XD-GRASP) reconstructions of the same data. Reconstruction times for each method were recorded. Motion estimate accuracy was measured as the correlation between fNAV and ground truth for simulations, and fNAV and image registration for in vivo data. Percent vessel sharpness was measured in all simulated data sets and healthy subjects, and a subset of patients. Finally, subjective image quality analysis was performed by a blinded expert reviewer who chose the best image for each in vivo data set and scored on a Likert scale 0-4 in a subset of patients by two reviewers in consensus. RESULTS The reconstruction time for fNAV images was significantly higher than RSN (6.1 ± 2.1 min vs 1.4 ± 0.3, min, p < 0.025) but significantly lower than XD-GRASP (25.6 ± 7.1, min, p < 0.025). Overall, there is high correlation between the fNAV and reference displacement estimates across all data sets (0.73 ± 0.29). For simulated data, healthy subjects, and patients, fNAV lead to significantly sharper coronary arteries than all other reconstruction methods (p < 0.01). Finally, in a blinded evaluation by an expert reviewer fNAV was chosen as the best image in 444 out of 571 data sets (78%; p < 0.001) and consensus grades of fNAV images (2.6 ± 0.6) were significantly higher (p < 0.05) than uncorrected (1.7 ± 0.7), RSN (1.9 ± 0.6), and XD-GRASP (1.8 ± 0.8). CONCLUSION fNAV is a promising technique for improving the quality of RSN free-breathing 3D whole-heart CCMRA. This novel approach to respiratory self-navigation can derive 3D nonrigid motion estimations from an acquired 1D signal yielding statistically significant improvement in image sharpness relative to 1D translational correction as well as XD-GRASP reconstructions. Further study of the diagnostic impact of this technique is therefore warranted to evaluate its full clinical utility.
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Affiliation(s)
- Christopher W Roy
- Department of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Rue de Bugnon 46, BH-7-84, 1011, Lausanne, Switzerland.
| | - John Heerfordt
- Department of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Rue de Bugnon 46, BH-7-84, 1011, Lausanne, Switzerland
- Advanced Clinical Imaging Technology (ACIT), Siemens Healthcare AG, Lausanne, Switzerland
| | - Davide Piccini
- Department of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Rue de Bugnon 46, BH-7-84, 1011, Lausanne, Switzerland
- Advanced Clinical Imaging Technology (ACIT), Siemens Healthcare AG, Lausanne, Switzerland
| | - Giulia Rossi
- Department of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Rue de Bugnon 46, BH-7-84, 1011, Lausanne, Switzerland
| | - Anna Giulia Pavon
- Division of Cardiology, Lausanne University Hospital (CHUV), Lausanne, Switzerland
| | - Juerg Schwitter
- Division of Cardiology, Lausanne University Hospital (CHUV), Lausanne, Switzerland
- Director CMR-Center, Lausanne University Hospital (CHUV), Lausanne, Switzerland
- Faculty of Biology and Medicine, University of Lausanne (UNIL), Lausanne, Switzerland
| | - Matthias Stuber
- Department of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Rue de Bugnon 46, BH-7-84, 1011, Lausanne, Switzerland
- Center for Biomedical Imaging (CIBM), Lausanne, Switzerland
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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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Yacoub B, Stroud RE, Piccini D, Schoepf UJ, Heerfordt J, Yerly J, Di Sopra L, Rollins JD, Turner DA, Emrich T, Xiong F, Suranyi P, Varga-Szemes A. Measurement accuracy of prototype non-contrast, compressed sensing-based, respiratory motion-resolved whole heart cardiovascular magnetic resonance angiography for the assessment of thoracic aortic dilatation: comparison with computed tomography angiography. J Cardiovasc Magn Reson 2021; 23:7. [PMID: 33557887 PMCID: PMC7871614 DOI: 10.1186/s12968-020-00697-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2020] [Accepted: 12/09/2020] [Indexed: 01/16/2023] Open
Abstract
BACKGROUND Patients with thoracic aortic dilatation who undergo annual computed tomography angiography (CTA) are subject to repeated radiation and contrast exposure. The purpose of this study was to evaluate the feasibility of a non-contrast, respiratory motion-resolved whole-heart cardiovascular magnetic resonance angiography (CMRA) technique against reference standard CTA, for the quantitative assessment of cardiovascular anatomy and monitoring of disease progression in patients with thoracic aortic dilatation. METHODS: Twenty-four patients (68.6 ± 9.8 years) with thoracic aortic dilatation prospectively underwent clinical CTA and research 1.5T CMRA between July 2017 and November 2018. Scans were repeated in 15 patients 1 year later. A prototype free-breathing 3D radial balanced steady-state free-precession whole-heart CMRA sequence was used in combination with compressed sensing-based reconstruction. Area, circumference, and diameter measurements were obtained at seven aortic levels by two experienced and two inexperienced readers. In addition, area and diameter measurements of the cardiac chambers, pulmonary arteries and pulmonary veins were also obtained. Agreement between the two modalities was assessed with intraclass correlation coefficient (ICC) analysis, Bland-Altman plots and scatter plots. RESULTS Area, circumference and diameter measurements on a per-level analysis showed good or excellent agreement between CTA and CMRA (ICCs > 0.84). Means of differences on Bland-Altman plots were: area 0.0 cm2 [- 1.7; 1.6]; circumference 1.0 mm [- 10.0; 12.0], and diameter 0.6 mm [- 2.6; 3.6]. Area and diameter measurements of the left cardiac chambers showed good agreement (ICCs > 0.80), while moderate to good agreement was observed for the right chambers (all ICCs > 0.56). Similar good to excellent inter-modality agreement was shown for the pulmonary arteries and veins (ICC range 0.79-0.93), with the exception of the left lower pulmonary vein (ICC < 0.51). Inter-reader assessment demonstrated mostly good or excellent agreement for both CTA and CMRA measurements on a per-level analysis (ICCs > 0.64). Difference in maximum aortic diameter measurements at baseline vs follow up showed excellent agreement between CMRA and CTA (ICC = 0.91). CONCLUSIONS The radial whole-heart CMRA technique combined with respiratory motion-resolved reconstruction provides comparable anatomical measurements of the thoracic aorta and cardiac structures as the reference standard CTA. It could potentially be used to diagnose and monitor patients with thoracic aortic dilatation without exposing them to radiation or contrast media.
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Affiliation(s)
- Basel Yacoub
- Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Ashley River Tower, MSC 226, 25 Courtenay Dr, Charleston, SC, 29425, USA
| | - Robert E Stroud
- Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Ashley River Tower, MSC 226, 25 Courtenay Dr, Charleston, SC, 29425, USA
| | - 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
| | - U Joseph Schoepf
- Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Ashley River Tower, MSC 226, 25 Courtenay Dr, Charleston, SC, 29425, USA
| | - 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
| | - Jérôme Yerly
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- Center for Biomedical Imaging (CIBM), Lausanne, Switzerland
| | - Lorenzo Di Sopra
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Jonathan D Rollins
- Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Ashley River Tower, MSC 226, 25 Courtenay Dr, Charleston, SC, 29425, USA
| | - D Alan Turner
- College of Medicine, Medical University of South Carolina, Charleston, SC, USA
| | - Tilman Emrich
- Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Ashley River Tower, MSC 226, 25 Courtenay Dr, Charleston, SC, 29425, USA
- Department of Radiology, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
- German Center for Cardiovascular Research (DZHK), Partner Site Rhine Main, Mainz, Germany
| | - Fei Xiong
- Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Ashley River Tower, MSC 226, 25 Courtenay Dr, Charleston, SC, 29425, USA
- Cardiovascular MR R&D, Siemens Medical Solutions USA Inc, Charleston, SC, USA
| | - Pal Suranyi
- Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Ashley River Tower, MSC 226, 25 Courtenay Dr, Charleston, SC, 29425, USA
| | - Akos Varga-Szemes
- Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Ashley River Tower, MSC 226, 25 Courtenay Dr, Charleston, SC, 29425, USA.
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Friedrich MG. Steps and Leaps on the Path toward Simpler and Faster Cardiac MRI Scanning. Radiology 2021; 298:587-588. [PMID: 33475467 DOI: 10.1148/radiol.2021204084] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Affiliation(s)
- Matthias G Friedrich
- From the Departments of Medicine and Diagnostic Radiology, McGill University Health Centre, 1001 Decarie Blvd, Montreal, QC, Canada H4A 3J1
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Küstner T, Bustin A, Jaubert O, Hajhosseiny R, Masci PG, Neji R, Botnar R, Prieto C. Fully self-gated free-running 3D Cartesian cardiac CINE with isotropic whole-heart coverage in less than 2 min. NMR IN BIOMEDICINE 2021; 34:e4409. [PMID: 32974984 DOI: 10.1002/nbm.4409] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/24/2020] [Revised: 08/19/2020] [Accepted: 08/21/2020] [Indexed: 06/11/2023]
Abstract
PURPOSE To develop a novel fast water-selective free-breathing 3D Cartesian cardiac CINE scan with full self-navigation and isotropic whole-heart (WH) coverage. METHODS A free-breathing 3D Cartesian cardiac CINE scan with a water-selective balanced steady-state free precession and a continuous (non-ECG-gated) variable-density Cartesian sampling with spiral profile ordering, out-inward sampling and acquisition-adaptive alternating tiny golden and golden angle increment between spiral arms is proposed. Data is retrospectively binned based on respiratory and cardiac self-navigation signals. A translational respiratory-motion-corrected and cardiac-motion-resolved image is reconstructed with a multi-bin patch-based low-rank reconstruction (MB-PROST) within about 15 min. A respiratory-motion-resolved approach is also investigated. The proposed 3D Cartesian cardiac CINE is acquired in sagittal orientation in 1 min 50 s for 1.9 mm3 isotropic WH coverage. Left ventricular (LV) function parameters and image quality derived from a blinded reading of the proposed 3D CINE framework are compared against conventional multi-slice 2D CINE imaging in 10 healthy subjects and 10 patients with suspected cardiovascular disease. RESULTS The proposed framework provides free-breathing 3D cardiac CINE images with 1.9 mm3 spatial and about 45 ms temporal resolution in a short acquisition time (<2 min). LV function parameters derived from 3D CINE were in good agreement with 2D CINE (10 healthy subjects and 10 patients). Bias and confidence intervals were obtained for end-systolic volume, end-diastolic volume and ejection fraction of 0.1 ± 3.5 mL, -0.6 ± 8.2 mL and -0.1 ± 2.2%, respectively. CONCLUSION The proposed framework enables isotropic 3D Cartesian cardiac CINE under free breathing for fast assessment of cardiac anatomy and function.
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Affiliation(s)
- Thomas Küstner
- School of Biomedical Engineering and Imaging Sciences, King's College London, St. Thomas' Hospital, London, UK
| | - Aurelien Bustin
- School of Biomedical Engineering and Imaging Sciences, King's College London, St. Thomas' Hospital, London, UK
| | - Olivier Jaubert
- School of Biomedical Engineering and Imaging Sciences, King's College London, St. Thomas' Hospital, London, UK
| | - Reza Hajhosseiny
- School of Biomedical Engineering and Imaging Sciences, King's College London, St. Thomas' Hospital, London, UK
| | - Pier Giorgio Masci
- School of Biomedical Engineering and Imaging Sciences, King's College London, St. Thomas' Hospital, London, UK
| | - Radhouene Neji
- School of Biomedical Engineering and Imaging Sciences, King's College London, St. Thomas' Hospital, London, UK
- MR Research Collaborations, Siemens Healthcare Limited, Frimley, UK
| | - René Botnar
- School of Biomedical Engineering and Imaging Sciences, King's College London, St. Thomas' Hospital, London, UK
- Escuela de Ingeniería, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Claudia Prieto
- School of Biomedical Engineering and Imaging Sciences, King's College London, St. Thomas' Hospital, London, UK
- Escuela de Ingeniería, Pontificia Universidad Católica de Chile, Santiago, Chile
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Hajhosseiny R, Bustin A, Munoz C, Rashid I, Cruz G, Manning WJ, Prieto C, Botnar RM. Coronary Magnetic Resonance Angiography: Technical Innovations Leading Us to the Promised Land? JACC Cardiovasc Imaging 2020; 13:2653-2672. [PMID: 32199836 DOI: 10.1016/j.jcmg.2020.01.006] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/24/2019] [Revised: 01/03/2020] [Accepted: 01/08/2020] [Indexed: 02/07/2023]
Abstract
Coronary artery disease remains the leading cause of cardiovascular morbidity and mortality. Invasive X-ray angiography and coronary computed tomography angiography are established gold standards for coronary luminography. However, they expose patients to invasive complications, ionizing radiation, and iodinated contrast agents. Among a number of imaging modalities, coronary cardiovascular magnetic resonance (CMR) angiography may be used in some cases as an alternative for the detection and monitoring of coronary arterial stenosis, with advantages including its versatility, excellent soft tissue characterization, and avoidance of ionizing radiation and iodinated contrast agents. In this review, we explore the recent advances in motion correction, image acceleration, and reconstruction technologies that are bringing coronary CMR angiography closer to widespread clinical implementation.
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Affiliation(s)
- Reza Hajhosseiny
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom; National Heart and Lung Institute, Imperial College London, London, United Kingdom.
| | - Aurelien Bustin
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Camila Munoz
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Imran Rashid
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Gastao Cruz
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Warren J Manning
- Department of Medicine (Cardiovascular Division) and Radiology, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA
| | - Claudia Prieto
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom; Escuela de Ingeniería, Pontificia Universidad Catolica de Chile, Santiago, Chile
| | - René M Botnar
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom; Escuela de Ingeniería, Pontificia Universidad Catolica de Chile, Santiago, Chile
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Ma LE, Yerly J, Piccini D, Di Sopra L, Roy CW, Carr JC, Rigsby CK, Kim D, Stuber M, Markl M. 5D Flow MRI: A Fully Self-gated, Free-running Framework for Cardiac and Respiratory Motion-resolved 3D Hemodynamics. Radiol Cardiothorac Imaging 2020; 2:e200219. [PMID: 33385164 PMCID: PMC7755133 DOI: 10.1148/ryct.2020200219] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2020] [Revised: 08/19/2020] [Accepted: 08/20/2020] [Indexed: 02/07/2023]
Abstract
PURPOSE To implement, validate, and apply a self-gated free-running whole-heart five-dimensional (5D) flow MRI framework to evaluate respiration-driven effects on three-dimensional (3D) hemodynamics in a clinical setting. MATERIALS AND METHODS In this prospective study, a free-running five-dimensional (5D) flow sequence was implemented with 3D radial sampling, self-gating, and a compressed-sensing reconstruction. The 5D flow was evaluated in a pulsatile phantom and adult participants with aortic and/or valvular disease who were enrolled between May and August 2019. Conventional twofold-accelerated four-dimensional (4D) flow of the thoracic aorta with navigator gating was performed as a reference comparison. Continuous parameters were evaluated for parameter normality and were compared between conventional 4D flow and 5D flow using a signed-rank or two-tailed paired t test. Differences between respiratory states were evaluated using a repeated-measure analysis of variance or a nonparametric Friedman test. RESULTS A total of 20 adult participants (mean age, 49 years ± 17 [standard deviation]; 18 men and two women) were included. In vitro 5D flow results showed excellent agreement with conventional 4D flow-derived values (peak and net flow, <7% difference over all quantified planes). Whole-heart 5D flow data were collected in all participants in 7.65 minutes ± 0.35 (acceleration rate = 36.0-76.9) versus 9.88 minutes ± 3.17 for conventional aortic 4D flow. In vivo, 5D flow demonstrated moderate agreement with conventional 4D flow but demonstrated overestimation in net flow and peak velocity (up to 26% and 12%, respectively) in the ascending aorta and underestimation (<12%) in the arch and descending aorta. Respiratory-resolved analyses of caval veins showed significantly increased net and peak flow in the inferior vena cava in end inspiration compared with end expiration, and the opposite trend was shown in the superior vena cava. CONCLUSION A free-running 5D flow MRI framework consistently captured cardiac and respiratory motion-resolved 3D hemodynamics in less than 8 minutes. Supplemental material is available for this article. © RSNA, 2020.
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Affiliation(s)
- Liliana E. Ma
- From the Departments of Radiology, Feinberg School of Medicine (L.E.M., J.C.C., C.K.R., D.K., M.M.) and Biomedical Engineering (L.E.M., J.C.C., D.K., M.M.), Northwestern University, 737 N Michigan Ave, Suite 1600, Chicago, IL 60611; Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland (J.Y., D.P., L.D.S., C.W.R., M.S.); Center for Biomedical Imaging, Lausanne, Switzerland (J.Y., M.S.); Department of Advanced Clinical Imaging Technology, Siemens Healthineers, Lausanne, Switzerland (D.P.); and Department of Medical Imaging, Ann and Robert H. Lurie Children’s Hospital of Chicago, Chicago, Ill (C.K.R.)
| | - Jérôme Yerly
- From the Departments of Radiology, Feinberg School of Medicine (L.E.M., J.C.C., C.K.R., D.K., M.M.) and Biomedical Engineering (L.E.M., J.C.C., D.K., M.M.), Northwestern University, 737 N Michigan Ave, Suite 1600, Chicago, IL 60611; Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland (J.Y., D.P., L.D.S., C.W.R., M.S.); Center for Biomedical Imaging, Lausanne, Switzerland (J.Y., M.S.); Department of Advanced Clinical Imaging Technology, Siemens Healthineers, Lausanne, Switzerland (D.P.); and Department of Medical Imaging, Ann and Robert H. Lurie Children’s Hospital of Chicago, Chicago, Ill (C.K.R.)
| | - Davide Piccini
- From the Departments of Radiology, Feinberg School of Medicine (L.E.M., J.C.C., C.K.R., D.K., M.M.) and Biomedical Engineering (L.E.M., J.C.C., D.K., M.M.), Northwestern University, 737 N Michigan Ave, Suite 1600, Chicago, IL 60611; Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland (J.Y., D.P., L.D.S., C.W.R., M.S.); Center for Biomedical Imaging, Lausanne, Switzerland (J.Y., M.S.); Department of Advanced Clinical Imaging Technology, Siemens Healthineers, Lausanne, Switzerland (D.P.); and Department of Medical Imaging, Ann and Robert H. Lurie Children’s Hospital of Chicago, Chicago, Ill (C.K.R.)
| | - Lorenzo Di Sopra
- From the Departments of Radiology, Feinberg School of Medicine (L.E.M., J.C.C., C.K.R., D.K., M.M.) and Biomedical Engineering (L.E.M., J.C.C., D.K., M.M.), Northwestern University, 737 N Michigan Ave, Suite 1600, Chicago, IL 60611; Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland (J.Y., D.P., L.D.S., C.W.R., M.S.); Center for Biomedical Imaging, Lausanne, Switzerland (J.Y., M.S.); Department of Advanced Clinical Imaging Technology, Siemens Healthineers, Lausanne, Switzerland (D.P.); and Department of Medical Imaging, Ann and Robert H. Lurie Children’s Hospital of Chicago, Chicago, Ill (C.K.R.)
| | - Christopher W. Roy
- From the Departments of Radiology, Feinberg School of Medicine (L.E.M., J.C.C., C.K.R., D.K., M.M.) and Biomedical Engineering (L.E.M., J.C.C., D.K., M.M.), Northwestern University, 737 N Michigan Ave, Suite 1600, Chicago, IL 60611; Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland (J.Y., D.P., L.D.S., C.W.R., M.S.); Center for Biomedical Imaging, Lausanne, Switzerland (J.Y., M.S.); Department of Advanced Clinical Imaging Technology, Siemens Healthineers, Lausanne, Switzerland (D.P.); and Department of Medical Imaging, Ann and Robert H. Lurie Children’s Hospital of Chicago, Chicago, Ill (C.K.R.)
| | - James C. Carr
- From the Departments of Radiology, Feinberg School of Medicine (L.E.M., J.C.C., C.K.R., D.K., M.M.) and Biomedical Engineering (L.E.M., J.C.C., D.K., M.M.), Northwestern University, 737 N Michigan Ave, Suite 1600, Chicago, IL 60611; Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland (J.Y., D.P., L.D.S., C.W.R., M.S.); Center for Biomedical Imaging, Lausanne, Switzerland (J.Y., M.S.); Department of Advanced Clinical Imaging Technology, Siemens Healthineers, Lausanne, Switzerland (D.P.); and Department of Medical Imaging, Ann and Robert H. Lurie Children’s Hospital of Chicago, Chicago, Ill (C.K.R.)
| | - Cynthia K. Rigsby
- From the Departments of Radiology, Feinberg School of Medicine (L.E.M., J.C.C., C.K.R., D.K., M.M.) and Biomedical Engineering (L.E.M., J.C.C., D.K., M.M.), Northwestern University, 737 N Michigan Ave, Suite 1600, Chicago, IL 60611; Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland (J.Y., D.P., L.D.S., C.W.R., M.S.); Center for Biomedical Imaging, Lausanne, Switzerland (J.Y., M.S.); Department of Advanced Clinical Imaging Technology, Siemens Healthineers, Lausanne, Switzerland (D.P.); and Department of Medical Imaging, Ann and Robert H. Lurie Children’s Hospital of Chicago, Chicago, Ill (C.K.R.)
| | - Daniel Kim
- From the Departments of Radiology, Feinberg School of Medicine (L.E.M., J.C.C., C.K.R., D.K., M.M.) and Biomedical Engineering (L.E.M., J.C.C., D.K., M.M.), Northwestern University, 737 N Michigan Ave, Suite 1600, Chicago, IL 60611; Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland (J.Y., D.P., L.D.S., C.W.R., M.S.); Center for Biomedical Imaging, Lausanne, Switzerland (J.Y., M.S.); Department of Advanced Clinical Imaging Technology, Siemens Healthineers, Lausanne, Switzerland (D.P.); and Department of Medical Imaging, Ann and Robert H. Lurie Children’s Hospital of Chicago, Chicago, Ill (C.K.R.)
| | - Matthias Stuber
- From the Departments of Radiology, Feinberg School of Medicine (L.E.M., J.C.C., C.K.R., D.K., M.M.) and Biomedical Engineering (L.E.M., J.C.C., D.K., M.M.), Northwestern University, 737 N Michigan Ave, Suite 1600, Chicago, IL 60611; Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland (J.Y., D.P., L.D.S., C.W.R., M.S.); Center for Biomedical Imaging, Lausanne, Switzerland (J.Y., M.S.); Department of Advanced Clinical Imaging Technology, Siemens Healthineers, Lausanne, Switzerland (D.P.); and Department of Medical Imaging, Ann and Robert H. Lurie Children’s Hospital of Chicago, Chicago, Ill (C.K.R.)
| | - Michael Markl
- From the Departments of Radiology, Feinberg School of Medicine (L.E.M., J.C.C., C.K.R., D.K., M.M.) and Biomedical Engineering (L.E.M., J.C.C., D.K., M.M.), Northwestern University, 737 N Michigan Ave, Suite 1600, Chicago, IL 60611; Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland (J.Y., D.P., L.D.S., C.W.R., M.S.); Center for Biomedical Imaging, Lausanne, Switzerland (J.Y., M.S.); Department of Advanced Clinical Imaging Technology, Siemens Healthineers, Lausanne, Switzerland (D.P.); and Department of Medical Imaging, Ann and Robert H. Lurie Children’s Hospital of Chicago, Chicago, Ill (C.K.R.)
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Pruitt A, Rich A, Liu Y, Jin N, Potter L, Tong M, Rajpal S, Simonetti O, Ahmad R. Fully self-gated whole-heart 4D flow imaging from a 5-minute scan. Magn Reson Med 2020; 85:1222-1236. [PMID: 32996625 DOI: 10.1002/mrm.28491] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2020] [Revised: 07/20/2020] [Accepted: 08/01/2020] [Indexed: 11/07/2022]
Abstract
PURPOSE To develop and validate an acquisition and processing technique that enables fully self-gated 4D flow imaging with whole-heart coverage in a fixed 5-minute scan. THEORY AND METHODS The data are acquired continuously using Cartesian sampling and sorted into respiratory and cardiac bins using the self-gating signal. The reconstruction is performed using a recently proposed Bayesian method called ReVEAL4D. ReVEAL4D is validated using data from 8 healthy volunteers and 2 patients and compared with compressed sensing technique, L1-SENSE. RESULTS Healthy subjects-Compared with 2D phase-contrast MRI (2D-PC), flow quantification from ReVEAL4D shows no significant bias. In contrast, the peak velocity and peak flow rate for L1-SENSE are significantly underestimated. Compared with traditional parallel MRI-based 4D flow imaging, ReVEAL4D demonstrates small but significant biases in net flow and peak flow rate, with no significant bias in peak velocity. All 3 indices are significantly and more markedly underestimated by L1-SENSE. Patients-Flow quantification from ReVEAL4D agrees well with the 2D-PC reference. In contrast, L1-SENSE markedly underestimated peak velocity. CONCLUSIONS The combination of highly accelerated 5-minute Cartesian acquisition, self-gating, and ReVEAL4D enables whole-heart 4D flow imaging with accurate flow quantification.
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Affiliation(s)
- Aaron Pruitt
- Biomedical Engineering, The Ohio State University, Columbus, OH, USA
| | - Adam Rich
- Biomedical Engineering, The Ohio State University, Columbus, OH, USA.,Electrical and Computer Engineering, The Ohio State University, Columbus, OH, USA
| | - Yingmin Liu
- Davis Heart & Lung Research Institute, The Ohio State University, Columbus, OH, USA
| | - Ning Jin
- Cardiovascular MR R&D, Siemens Medical Solutions USA Inc., Columbus, OH, USA
| | - Lee Potter
- Electrical and Computer Engineering, The Ohio State University, Columbus, OH, USA.,Davis Heart & Lung Research Institute, The Ohio State University, Columbus, OH, USA
| | - Matthew Tong
- Internal Medicine, The Ohio State University, Columbus, OH, USA
| | - Saurabh Rajpal
- Internal Medicine, The Ohio State University, Columbus, OH, USA
| | - Orlando Simonetti
- Davis Heart & Lung Research Institute, The Ohio State University, Columbus, OH, USA.,Internal Medicine, The Ohio State University, Columbus, OH, USA.,Radiology, The Ohio State University, Columbus, OH, USA
| | - Rizwan Ahmad
- Biomedical Engineering, The Ohio State University, Columbus, OH, USA.,Electrical and Computer Engineering, The Ohio State University, Columbus, OH, USA.,Davis Heart & Lung Research Institute, The Ohio State University, Columbus, OH, USA
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Krishnamoorthy G, Smink J, Tourais J, Breeuwer M, Kouwenhoven M. Variable anisotropic FOV for 3D radial imaging with spiral phyllotaxis (VASP). Magn Reson Med 2020; 85:68-77. [PMID: 32851711 PMCID: PMC7692914 DOI: 10.1002/mrm.28449] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2019] [Revised: 05/30/2020] [Accepted: 07/08/2020] [Indexed: 12/16/2022]
Abstract
PURPOSE To develop a new 3D radial trajectory based on the natural spiral phyllotaxis (SP), with variable anisotropic FOV. THEORY & METHODS A 3D radial trajectory based on the SP with favorable interleaving properties for cardiac imaging has been proposed by Piccini et al (Magn Reson Med. 2011;66:1049-1056), which supports a FOV with a fixed anisotropy. However, a fixed anisotropy can be inefficient when sampling objects with different anisotropic dimensions. We extend Larson's 3D radial method to provide variable anisotropic FOV for spiral phyllotaxis (VASP). Simulations were performed to measure distance between successive projections, analyze point spread functions, and compare aliasing artifacts for both VASP and conventional SP. VASP was fully implemented on a whole-body clinical MR scanner. Phantom and in vivo cardiac images were acquired at 1.5 tesla. RESULTS Simulations, phantom, and in vivo experiments confirmed that VASP can achieve variable anisotropic FOV while maintaining the favorable interleaving properties of SP. For an anisotropic FOV with 100:100:35 ratio, VASP required ~65% fewer radial projections than the conventional SP to satisfy Nyquist criteria. Alternatively, when the same number of radial projections were used as in conventional SP, VASP produced fewer aliasing artifacts for anisotropic objects within the excited imaging volumes. CONCLUSION We have developed a new method (VASP), which enables variable anisotropic FOV for 3D radial trajectory with SP. For anisotropic objects within the excited imaging volumes, VASP can reduce scan times and/or reduce aliasing artifacts.
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Affiliation(s)
- Guruprasad Krishnamoorthy
- Department of MR R&D-Clinical Science, Philips, Best, The Netherlands.,Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
| | - Jouke Smink
- Department of MR R&D-Clinical Science, Philips, Best, The Netherlands
| | - Joao Tourais
- Department of MR R&D-Clinical Science, Philips, Best, The Netherlands.,Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
| | - Marcel Breeuwer
- Department of MR R&D-Clinical Science, Philips, Best, The Netherlands.,Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
| | - Marc Kouwenhoven
- Department of MR R&D-Clinical Science, Philips, Best, The Netherlands
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Franceschiello B, Di Sopra L, Minier A, Ionta S, Zeugin D, Notter MP, Bastiaansen JAM, Jorge J, Yerly J, Stuber M, Murray MM. 3-Dimensional magnetic resonance imaging of the freely moving human eye. Prog Neurobiol 2020; 194:101885. [PMID: 32653462 DOI: 10.1016/j.pneurobio.2020.101885] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2019] [Revised: 04/21/2020] [Accepted: 07/07/2020] [Indexed: 12/16/2022]
Abstract
Eye motion is a major confound for magnetic resonance imaging (MRI) in neuroscience or ophthalmology. Currently, solutions toward eye stabilisation include participants fixating or administration of paralytics/anaesthetics. We developed a novel MRI protocol for acquiring 3-dimensional images while the eye freely moves. Eye motion serves as the basis for image reconstruction, rather than an impediment. We fully reconstruct videos of the moving eye and head. We quantitatively validate data quality with millimetre resolution in two ways for individual participants. First, eye position based on reconstructed images correlated with simultaneous eye-tracking. Second, the reconstructed images preserve anatomical properties; the eye's axial length measured from MRI images matched that obtained with ocular biometry. The technique operates on a standard clinical setup, without necessitating specialized hardware, facilitating wide deployment. In clinical practice, we anticipate that this may help reduce burdens on both patients and infrastructure, by integrating multiple varieties of assessments into a single comprehensive session. More generally, our protocol is a harbinger for removing the necessity of fixation, thereby opening new opportunities for ethologically-valid, naturalistic paradigms, the inclusion of populations typically unable to stably fixate, and increased translational research such as in awake animals whose eye movements constitute an accessible behavioural readout.
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Affiliation(s)
- Benedetta Franceschiello
- The Laboratory for Investigative Neurophysiology (The LINE), Department of Radiology, University Hospital Center and University of Lausanne, Lausanne, Switzerland; Department of Ophthalmology, University of Lausanne, Jules Gonin Eye Hospital, Fondation Asile des aveugles, Lausanne, Switzerland.
| | - Lorenzo Di Sopra
- Department of Radiology, University Hospital Center and University of Lausanne, Lausanne, Switzerland
| | - Astrid Minier
- The Laboratory for Investigative Neurophysiology (The LINE), Department of Radiology, University Hospital Center and University of Lausanne, Lausanne, Switzerland; Department of Ophthalmology, University of Lausanne, Jules Gonin Eye Hospital, Fondation Asile des aveugles, Lausanne, Switzerland
| | - Silvio Ionta
- Department of Ophthalmology, University of Lausanne, Jules Gonin Eye Hospital, Fondation Asile des aveugles, Lausanne, Switzerland
| | - David Zeugin
- The Laboratory for Investigative Neurophysiology (The LINE), Department of Radiology, University Hospital Center and University of Lausanne, Lausanne, Switzerland; Department of Ophthalmology, University of Lausanne, Jules Gonin Eye Hospital, Fondation Asile des aveugles, Lausanne, Switzerland
| | - Michael P Notter
- The Laboratory for Investigative Neurophysiology (The LINE), Department of Radiology, University Hospital Center and University of Lausanne, Lausanne, Switzerland
| | - Jessica A M Bastiaansen
- Department of Radiology, University Hospital Center and University of Lausanne, Lausanne, Switzerland
| | - João Jorge
- École Polytechnique Fédérale de Lausanne (EPFL) Lausanne, Switzerland
| | - Jérôme Yerly
- Department of Radiology, University Hospital Center and University of Lausanne, Lausanne, Switzerland; Center for Biomedical Imaging (CIBM), Lausanne, Switzerland
| | - Matthias Stuber
- Department of Radiology, University Hospital Center and University of Lausanne, Lausanne, Switzerland; Center for Biomedical Imaging (CIBM), Lausanne, Switzerland
| | - Micah M Murray
- The Laboratory for Investigative Neurophysiology (The LINE), Department of Radiology, University Hospital Center and University of Lausanne, Lausanne, Switzerland; Department of Ophthalmology, University of Lausanne, Jules Gonin Eye Hospital, Fondation Asile des aveugles, Lausanne, Switzerland; Center for Biomedical Imaging (CIBM), Lausanne, Switzerland; Department of Hearing and Speech Sciences, Vanderbilt University Nashville, TN, USA.
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48
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Fyrdahl A, Holst K, Caidahl K, Ugander M, Sigfridsson A. Generalization of three-dimensional golden-angle radial acquisition to reduce eddy current artifacts in bSSFP CMR imaging. MAGNETIC RESONANCE MATERIALS IN PHYSICS BIOLOGY AND MEDICINE 2020; 34:109-118. [PMID: 32592094 PMCID: PMC7910232 DOI: 10.1007/s10334-020-00859-z] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/30/2020] [Revised: 06/10/2020] [Accepted: 06/18/2020] [Indexed: 12/28/2022]
Abstract
Purpose We propose a novel generalization of the three-dimensional double-golden-angle profile ordering, which allows for whole-heart volumetric imaging with retrospective binning and reduced eddy current artifacts. Methods A novel theory bridging the gap between the three-dimensional double golden-angle trajectory, and the two-dimensional tiny-golden-angle trajectory is presented. This enables a class of double golden-angle profile orderings with a smaller angular distance between successive k-space readouts. The novel profile orderings were evaluated through simulations, phantom experiments, and in vivo imaging. Comparisons were made to the original double-golden-angle trajectory. Image uniformity and off-resonance sensitivity were evaluated using phantom measurements, and qualitative image quality was assessed using in vivo images acquired in a healthy volunteer. Results The proposed theory successfully reduced the angular step while maintaining image uniformity after binning. Simulations revealed a slow degradation with decreasing angular steps and an increasing number of physiological bins. The phantom images showed a definite improvement in image uniformity and increased robustness to off-resonance, and in vivo imaging corroborated those findings. Conclusion Reducing the angular step in cardio-respiratory-binned golden-angle imaging shows potential for overcoming eddy current-induced image artifacts associated with 3D golden-angle radial imaging.
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Affiliation(s)
- Alexander Fyrdahl
- Department of Clinical Physiology, Karolinska University Hospital, and Karolinska Institutet, Stockholm, Sweden
| | - Karen Holst
- Department of Clinical Physiology, Karolinska University Hospital, and Karolinska Institutet, Stockholm, Sweden
| | - Kenneth Caidahl
- Department of Clinical Physiology, Karolinska University Hospital, and Karolinska Institutet, Stockholm, Sweden.,Sahlgrenska Academy, Gothenburg University, and Västra Götaland Region, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Martin Ugander
- Department of Clinical Physiology, Karolinska University Hospital, and Karolinska Institutet, Stockholm, Sweden.,The Kolling Institute, Royal North Shore Hospital, and Northern Clinical School, Sydney Medical School, University of Sydney, Sydney, Australia
| | - Andreas Sigfridsson
- Department of Clinical Physiology, Karolinska University Hospital, and Karolinska Institutet, Stockholm, Sweden.
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49
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Zeng DY, Baron CA, Malavé MO, Kerr AB, Yang PC, Hu BS, Nishimura DG. Combined T 2 -preparation and multidimensional outer volume suppression for coronary artery imaging with 3D cones trajectories. Magn Reson Med 2020; 83:2221-2231. [PMID: 31691350 PMCID: PMC7047567 DOI: 10.1002/mrm.28057] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2019] [Revised: 10/08/2019] [Accepted: 10/09/2019] [Indexed: 11/07/2022]
Abstract
PURPOSE To develop a modular magnetization preparation sequence for combined T2 -preparation and multidimensional outer volume suppression (OVS) for coronary artery imaging. METHODS A combined T2 -prepared 1D OVS sequence with fat saturation was defined to contain a 90°-60 180°60 composite nonselective tip-down pulse, two 180°Y hard pulses for refocusing, and a -90° spectral-spatial sinc tip-up pulse. For 2D OVS, 2 modules were concatenated, selective in X and then Y. Bloch simulations predicted robustness of the sequence to B0 and B1 inhomogeneities. The proposed sequence was compared with a T2 -prepared 2D OVS sequence proposed by Luo et al, which uses a spatially selective 2D spiral tip-up. The 2 sequences were compared in phantom studies and in vivo coronary artery imaging studies with a 3D cones trajectory. RESULTS Phantom results demonstrated superior OVS for the proposed sequence compared with the Luo sequence. In studies on 15 healthy volunteers, the proposed sequence had superior image edge profile acutance values compared with the Luo sequence for the right (P < .05) and left (P < .05) coronary arteries, suggesting superior vessel sharpness. The proposed sequence also had superior signal-to-noise ratio (P < .05) and passband-to-stopband ratio (P < .05). Reader scores and reader preference indicated superior coronary image quality of the proposed sequence for both the right (P < .05) and left (P < .05) coronary arteries. CONCLUSION The proposed sequence with concatenated 1D spatially selective tip-ups and integrated fat saturation has superior image quality and suppression compared with the Luo sequence with 2D spatially selective tip-up.
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Affiliation(s)
- David Y Zeng
- Department of Electrical Engineering, Stanford University, Stanford, California
| | - Corey A Baron
- Department of Electrical Engineering, Stanford University, Stanford, California
- Department of Medical Biophysics, Western University, London, Canada
| | - Mario O Malavé
- Department of Electrical Engineering, Stanford University, Stanford, California
| | - Adam B Kerr
- Department of Electrical Engineering, Stanford University, Stanford, California
| | - Phillip C Yang
- Division of Cardiovascular Medicine, Department of Medicine, Stanford University, Stanford, California
| | - Bob S Hu
- Department of Electrical Engineering, Stanford University, Stanford, California
- Department of Cardiology, Palo Alto Medical Foundation, Palo Alto, California
| | - Dwight G Nishimura
- Department of Electrical Engineering, Stanford University, Stanford, California
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50
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Masala N, Bastiaansen JAM, Di Sopra L, Roy CW, Piccini D, Yerly J, Colotti R, Stuber M. Free‐running 5D coronary MR angiography at 1.5T using LIBRE water excitation pulses. Magn Reson Med 2020; 84:1470-1485. [DOI: 10.1002/mrm.28221] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2019] [Revised: 12/31/2019] [Accepted: 01/30/2020] [Indexed: 12/12/2022]
Affiliation(s)
- Nemanja Masala
- Department of Diagnostic and Interventional Radiology Lausanne University Hospital (CHUV) and University of Lausanne (UNIL) Lausanne Switzerland
| | - Jessica A. M. Bastiaansen
- Department of Diagnostic and Interventional Radiology Lausanne University Hospital (CHUV) and University of Lausanne (UNIL) Lausanne Switzerland
| | - Lorenzo Di Sopra
- Department of Diagnostic and Interventional Radiology Lausanne University Hospital (CHUV) and University of Lausanne (UNIL) Lausanne Switzerland
| | - Christopher W. Roy
- Department of Diagnostic and Interventional Radiology Lausanne University Hospital (CHUV) and University of Lausanne (UNIL) Lausanne Switzerland
| | - Davide Piccini
- Department of Diagnostic and Interventional Radiology Lausanne University Hospital (CHUV) and University of Lausanne (UNIL) Lausanne Switzerland
- Advanced Clinical Imaging Technology Siemens Healthcare AG Lausanne Switzerland
| | - Jérôme Yerly
- Department of Diagnostic and Interventional Radiology Lausanne University Hospital (CHUV) and University of Lausanne (UNIL) Lausanne Switzerland
- Center for Biomedical Imaging (CIBM) Lausanne Switzerland
| | - Roberto Colotti
- Department of Diagnostic and Interventional Radiology Lausanne University Hospital (CHUV) and University of Lausanne (UNIL) Lausanne 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
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