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Merton R, Bosshardt D, Strijkers GJ, Nederveen AJ, Schrauben EM, van Ooij P. Reproducibility of 3D thoracic aortic displacement from 3D cine balanced SSFP at 3 T without contrast enhancement. Magn Reson Med 2024; 91:466-480. [PMID: 37831612 DOI: 10.1002/mrm.29856] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Revised: 08/02/2023] [Accepted: 08/16/2023] [Indexed: 10/15/2023]
Abstract
PURPOSE Aortic motion has direct impact on the mechanical stresses acting on the aorta. In aortic disease, increased stiffness of the aorta may lead to decreased aortic motion over time, which could be a predictor for aortic dissection or rupture. This study investigates the reproducibility of obtaining 3D displacement and diameter maps quantified using accelerated 3D cine MRI at 3 T. METHODS A noncontrast-enhanced, free-breathing 3D cine sequence based on balanced SSFP and pseudo-spiral undersampling with high spatial isotropic resolution was developed (spatial/temporal resolution [1.6 mm]3 /67 ms). The thoracic aorta of 14 healthy volunteers was prospectively scanned three times at 3 T: twice on the same day and a third time 2 weeks later. Aortic displacement was calculated using iterative closest point nonrigid registration of manual segmentations of the 3D aorta at end-systole and mid-diastole. Interexamination and interobserver regional analysis of mean displacement for five regions of interest was performed using Bland-Altman analysis. Additionally, a complementary voxel-by-voxel analysis was done, allowing a more local inspection of the method. RESULTS No significant differences were found in mean and maximum displacement for any of the regions of interest for the interexamination and interobserver analysis. The maximum displacement measured in the lower half of the ascending aorta was 11.0 ± 3.4 mm (range: 3.0-17.5 mm) for the first scan. The smallest detectable change in mean displacement in the lower half of the ascending aorta was 3 mm. CONCLUSION Detailed 3D cine balanced SSFP at 3 T allows for reproducible quantification of systolic-diastolic mean aortic displacement within acceptable limits.
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Affiliation(s)
- Renske Merton
- Radiology and Nuclear Medicine, Amsterdam UMC location University of Amsterdam, Amsterdam, the Netherlands
- Amsterdam Cardiovascular Sciences, Amsterdam, the Netherlands
| | - Daan Bosshardt
- Radiology and Nuclear Medicine, Amsterdam UMC location University of Amsterdam, Amsterdam, the Netherlands
- Amsterdam Cardiovascular Sciences, Amsterdam, the Netherlands
| | - Gustav J Strijkers
- Amsterdam Cardiovascular Sciences, Amsterdam, the Netherlands
- Biomedical Physics and Engineering, Amsterdam UMC location University of Amsterdam, Amsterdam, the Netherlands
- Amsterdam Movement Sciences, Amsterdam, the Netherlands
| | - Aart J Nederveen
- Radiology and Nuclear Medicine, Amsterdam UMC location University of Amsterdam, Amsterdam, the Netherlands
- Amsterdam Cardiovascular Sciences, Amsterdam, the Netherlands
- Amsterdam Movement Sciences, Amsterdam, the Netherlands
| | - Eric M Schrauben
- Radiology and Nuclear Medicine, Amsterdam UMC location University of Amsterdam, Amsterdam, the Netherlands
- Amsterdam Cardiovascular Sciences, Amsterdam, the Netherlands
| | - Pim van Ooij
- Radiology and Nuclear Medicine, Amsterdam UMC location University of Amsterdam, Amsterdam, the Netherlands
- Amsterdam Cardiovascular Sciences, Amsterdam, the Netherlands
- Amsterdam Movement Sciences, Amsterdam, the Netherlands
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Rossi GMC, Mackowiak ALC, Açikgöz BC, Pierzchała K, Kober T, Hilbert T, Bastiaansen JAM. SPARCQ: A new approach for fat fraction mapping using asymmetries in the phase-cycled balanced SSFP signal profile. Magn Reson Med 2023; 90:2348-2361. [PMID: 37496187 DOI: 10.1002/mrm.29813] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Revised: 06/19/2023] [Accepted: 07/12/2023] [Indexed: 07/28/2023]
Abstract
PURPOSE To develop SPARCQ (Signal Profile Asymmetries for Rapid Compartment Quantification), a novel approach to quantify fat fraction (FF) using asymmetries in the phase-cycled balanced SSFP (bSSFP) profile. METHODS SPARCQ uses phase-cycling to obtain bSSFP frequency profiles, which display asymmetries in the presence of fat and water at certain TRs. For each voxel, the measured signal profile is decomposed into a weighted sum of simulated profiles via multi-compartment dictionary matching. Each dictionary entry represents a single-compartment bSSFP profile with a specific off-resonance frequency and relaxation time ratio. Using the results of dictionary matching, the fractions of the different off-resonance components are extracted for each voxel, generating quantitative maps of water and FF and banding-artifact-free images for the entire image volume. SPARCQ was validated using simulations, experiments in a water-fat phantom and in knees of healthy volunteers. Experimental results were compared with reference proton density FFs obtained with 1 H-MRS (phantoms) and with multiecho gradient-echo MRI (phantoms and volunteers). SPARCQ repeatability was evaluated in six scan-rescan experiments. RESULTS Simulations showed that FF quantification is accurate and robust for SNRs greater than 20. Phantom experiments demonstrated good agreement between SPARCQ and gold standard FFs. In volunteers, banding-artifact-free quantitative maps and water-fat-separated images obtained with SPARCQ and ME-GRE demonstrated the expected contrast between fatty and non-fatty tissues. The coefficient of repeatability of SPARCQ FF was 0.0512. CONCLUSION SPARCQ demonstrates potential for fat quantification using asymmetries in bSSFP profiles and may be a promising alternative to conventional FF quantification techniques.
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Affiliation(s)
- Giulia M C Rossi
- Department of Diagnostic, Interventional and Pediatric Radiology (DIPR), Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
- Translational Imaging Center, Swiss Institute for Translational and Entrepreneurial Medicine, Bern, Switzerland
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Adèle L C Mackowiak
- Department of Diagnostic, Interventional and Pediatric Radiology (DIPR), Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
- Translational Imaging Center, Swiss Institute for Translational and Entrepreneurial Medicine, Bern, Switzerland
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Berk Can Açikgöz
- Department of Diagnostic, Interventional and Pediatric Radiology (DIPR), Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
- Translational Imaging Center, Swiss Institute for Translational and Entrepreneurial Medicine, Bern, Switzerland
| | - Katarzyna Pierzchała
- CIBM Center for Biomedical Imaging, Lausanne, Switzerland
- Animal Imaging and Technology, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Tobias Kober
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland
- LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Tom Hilbert
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland
- LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Jessica A M Bastiaansen
- Department of Diagnostic, Interventional and Pediatric Radiology (DIPR), Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
- Translational Imaging Center, Swiss Institute for Translational and Entrepreneurial Medicine, Bern, Switzerland
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Kato Y, Noda C, Ambale-Venkatesh B, Ortman JM, Kassai Y, Lima JAC, Liu CY. The mechanisms of arterial signal intensity profile in non-contrast coronary MRA (NC-MRCA): a 3D printed phantom investigation and clinical translations. Int J Cardiovasc Imaging 2023; 39:209-220. [PMID: 36598690 DOI: 10.1007/s10554-022-02700-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/09/2022] [Accepted: 07/22/2022] [Indexed: 01/12/2023]
Abstract
Signal intensity (SI) drop has been proposed as an indirect stenosis assessment in non-contrast coronary MRA (NC-MRCA) but it uses unproven assumptions. We aimed to clarify the mechanisms that govern the SI in vitro and develop a stenosis detection method in vivo. Flow phantom tubes with/without stenosis were scanned under two spatial resolutions (0.5/1.0 mm3) on a 3.0 T MRI. Thirty-two coronary arteries from 11 volunteers were prospectively scanned with an EKG- and respiratory-gated 3D NC-MRCA with a resolution of 1.0 mm3, with coronary computed tomography angiography (CTA) as reference. The normalized SI along the centerline of the tubes or the coronary arteries was assessed against the distance from the orifice using a linear regression model. Its coefficient (SI decay slope) and goodness-of-fit (R2) were extracted to assess the effect of flow velocity and stenosis on the SI profile curve. The R2 was utilized for the stenosis detection. Phantom study: A slow flow velocity caused a steep SI decay slope. The SI drop revealed only at the inlet and outlet of stenosis due to the flow turbulence/vortex and yielded low R2, in which shape changed by the resolution. Clinical study: The R2 cutoff to detect ≥ 50% stenosis for the left and right coronary arteries were 0.64 and 0.20 with a sensitivity/specificity of 71.5/71.5 and 66.7/100 (%), respectively. The SI drop did not reflect the actual stenosis position and not suitable for the stenosis localization. The R2 cutoff represents an alternative method to detect stenoses on NC-MRCA at vessel level.Trial registration: ClinicalTrials.gov; NCT03768999, registered on December 7, 2018.
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Affiliation(s)
- Yoko Kato
- Division of Cardiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Chikara Noda
- Division of Cardiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | | | - Jason M Ortman
- Division of Cardiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Yoshimori Kassai
- Canon Medical Systems Corporation, 1385 Shimoishigami, Otawara-shi, Tochigi, 324-8550, Japan
| | - Joao A C Lima
- Division of Cardiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Chia-Ying Liu
- Canon Medical Systems Corporation, 1385 Shimoishigami, Otawara-shi, Tochigi, 324-8550, Japan.
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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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Feng L. Golden-Angle Radial MRI: Basics, Advances, and Applications. J Magn Reson Imaging 2022; 56:45-62. [PMID: 35396897 PMCID: PMC9189059 DOI: 10.1002/jmri.28187] [Citation(s) in RCA: 25] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Revised: 03/23/2022] [Accepted: 03/24/2022] [Indexed: 12/21/2022] Open
Abstract
In recent years, golden‐angle radial sampling has received substantial attention and interest in the magnetic resonance imaging (MRI) community, and it has become a popular sampling trajectory for both research and clinical use. However, although the number of relevant techniques and publications has grown rapidly, there is still a lack of a review paper that provides a comprehensive overview and summary of the basics of golden‐angle rotation, the advantages and challenges/limitations of golden‐angle radial sampling, and recommendations in using different types of golden‐angle radial trajectories for MRI applications. Such a review paper is expected to be helpful both for clinicians who are interested in learning the potential benefits of golden‐angle radial sampling and for MRI physicists who are interested in exploring this research direction. The main purpose of this review paper is thus to present an overview and summary about golden‐angle radial MRI sampling. The review consists of three sections. The first section aims to answer basic questions such as: what is a golden angle; how is the golden angle calculated; why is golden‐angle radial sampling useful, and what are its limitations. The second section aims to review more advanced trajectories of golden‐angle radial sampling, including tiny golden‐angle rotation, stack‐of‐stars golden‐angle radial sampling, and three‐dimensional (3D) kooshball golden‐angle radial sampling. Their respective advantages and limitations and potential solutions to address these limitations are also discussed. Finally, the third section reviews MRI applications that can benefit from golden‐angle radial sampling and provides recommendations to readers who are interested in implementing golden‐angle radial trajectories in their MRI studies.
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Affiliation(s)
- Li Feng
- BioMedical Engineering and Imaging Institute (BMEII) and Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
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6
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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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Bolat Gümüş E, Şatir S, Kuştarci A. Microleakage beneath orthodontic brackets in high field magnetic resonance imaging (MRI) AT 1.5 & 3 tesla. Dentomaxillofac Radiol 2022; 51:20210512. [PMID: 35113678 PMCID: PMC9499206 DOI: 10.1259/dmfr.20210512] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022] Open
Abstract
OBJECTIVES The aim of the present study was to evaluate the effects of 1.5 T and 3 T MRI on the adhesion between the orthodontic brackets and the teeth by evaluating the microleakage between theenamel, adhesive and brackets interfaces. METHODS Fifty-eight extracted human premolars which were received a standard bracket bonding procedure were randomly divided into three groups; control group (n = 20; no MRI), 1.5 T MRI group (n = 19; 20 min MRI exposure of 1.5 T) and 3 T MRI group (n = 19; 20 min MRI exposure of 3 T). The teeth were kept in distiled water for 2 weeks, and thereafter subjected to 500 thermal cycles. Then specimens were sealed with nail varnish, stained with 0.5% basic fuchsin for 24 h, sectioned and photographed under a stereomicroscope. Microleakage was scored with regard to the adhesive-enamel and bracket-adhesive interfaces at the occlusal and gingival levels. Statistical analysis was accomplished by Kruskal-Wallis and Bonferroni-Dunn tests. RESULTS All of the groups exhibited statistically similar microleakage scores in the adhesive-enamel interface along occlusal margins (p>0.05, p = 0.331). The mean microleakage scores along gingival margins in the 3 T MRI group was significantly higher compared to the control group both in the adhesiv-enamel and bracket-adhesive interfaces (p<0.05, p = 0.019 and p = 0.020 respectively). The microleakage scores along the gingival margins were also significantly higher than the occlusal margins in the 3 T MRI group (p<0.05, p = 0.029). CONCLUSIONS 3 T MRI may weaken the adhesion between the enamel and the stainless steel orthodontic brackets.
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Affiliation(s)
- Esra Bolat Gümüş
- Orthodontics Department, Faculty of Dentistry, Akdeniz University, Antalya, Turkey
| | - Samed Şatir
- Oral and Maxillofacial Radiology Department, Faculty of Dentistry, Alanya Alaaddin Keykubat University, Antalya, Turkey
| | - Alper Kuştarci
- Endodontics Department, Faculty of Dentistry, Akdeniz University, Antalya, Turkey
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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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9
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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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Nakamura S, Ishida M, Nakata K, Ichikawa Y, Takase S, Takafuji M, Ito H, Nakamori S, Kurita T, Dohi K, Sakuma H. Long-term prognostic value of whole-heart coronary magnetic resonance angiography. J Cardiovasc Magn Reson 2021; 23:56. [PMID: 33993891 PMCID: PMC8127259 DOI: 10.1186/s12968-021-00749-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2020] [Accepted: 03/18/2021] [Indexed: 11/23/2022] Open
Abstract
BACKGROUND Coronary magnetic resonance angiography (CMRA) allows non-ionizing visualization of luminal narrowing in coronary artery disease (CAD). Although a prior study showed the usefulness of CMRA for risk stratification in short-term follow-up, the long-term prognostic value of CMRA remains unclear. The purpose of this study was to evaluate the long-term prognostic value of CMRA. METHODS A total of 506 patients without history of myocardial infarction or prior coronary artery revascularization underwent free-breathing whole-heart CMRA between 2009 and 2015. Images were acquired using a 1.5 T or 3 T scanner and visually evaluated as the consensus decisions of two observers. Obstructive CAD on CMRA was defined as luminal narrowing of ≥ 50% in at least one coronary artery. Major adverse cardiac events (MACE) comprised cardiac death, nonfatal myocardial infarction, and unstable angina. RESULTS Obstructive CAD on CMRA was observed in 214 patients (42%). During follow-up (median, 5.6 years), 31 MACE occurred. Kaplan-Meier curve analysis revealed a significant difference in event-free survival between patients with and without obstructive CAD for MACE (log-rank, p = 0.003) and cardiac death (p = 0.012). Annualized event rates for MACE in patients with no obstructive CAD, 1-vessel disease, 2-vessel disease, and left-main or 3-vessel disease were 0.6%, 1.5%, 2.3%, and 3.6%, respectively (log-rank, p = 0.003). Cox proportional hazard regression analysis showed that, among obstructive CAD on CMRA and clinical risk factors (age, sex, hypertension, diabetes, dyslipidemia, smoking, and family history of CAD), obstructive CAD and diabetes were significant predictors of MACE (hazard ratios, 2.9 [p = 0.005] and 2.2 [p = 0.034], respectively). In multivariate analysis, obstructive CAD remained an independent predictor (adjusted hazard ratio, 2.6 [p = 0.010]) after adjusting for diabetes. Addition of obstructive CAD to clinical risk factors significantly increased the global chi-square result from 8.3 to 13.8 (p = 0.022). CONCLUSIONS In long-term follow-up, free breathing whole heart CMRA allows non-invasive risk stratification for MACE and cardiac death and provides incremental prognostic value over conventional risk factors in patients without a history of myocardial infarction or prior coronary artery revascularization. The presence and severity of obstructive CAD detected by CMRA were associated with worse prognosis. Importantly, patients without obstructive CAD on CMRA displayed favorable prognosis.
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Affiliation(s)
- Satoshi Nakamura
- Department of Radiology, Mie University Hospital, 2-174 Edobashi, Tsu, Mie, 514-8507, Japan
| | - Masaki Ishida
- Department of Radiology, Mie University Hospital, 2-174 Edobashi, Tsu, Mie, 514-8507, Japan.
| | - Kei Nakata
- Department of Radiology, Mie University Hospital, 2-174 Edobashi, Tsu, Mie, 514-8507, Japan
| | - Yasutaka Ichikawa
- Department of Radiology, Mie University Hospital, 2-174 Edobashi, Tsu, Mie, 514-8507, Japan
| | - Shinichi Takase
- Department of Radiology, Mie University Hospital, 2-174 Edobashi, Tsu, Mie, 514-8507, Japan
| | - Masafumi Takafuji
- Department of Radiology, Mie University Hospital, 2-174 Edobashi, Tsu, Mie, 514-8507, Japan
| | - Haruno Ito
- Department of Radiology, Mie University Hospital, 2-174 Edobashi, Tsu, Mie, 514-8507, Japan
| | - Shiro Nakamori
- Department of Cardiology and Nephrology, Mie University Hospital, Tsu, Mie, Japan
| | - Tairo Kurita
- Department of Cardiology and Nephrology, Mie University Hospital, Tsu, Mie, Japan
| | - Kaoru Dohi
- Department of Cardiology and Nephrology, Mie University Hospital, Tsu, Mie, Japan
| | - Hajime Sakuma
- Department of Radiology, Mie University Hospital, 2-174 Edobashi, Tsu, Mie, 514-8507, Japan
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11
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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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12
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Arn L, van Heeswijk RB, Stuber M, Bastiaansen JAM. A robust broadband fat-suppressing phaser T 2 -preparation module for cardiac magnetic resonance imaging at 3T. Magn Reson Med 2021; 86:1434-1444. [PMID: 33759208 DOI: 10.1002/mrm.28785] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2020] [Revised: 03/01/2021] [Accepted: 03/04/2021] [Indexed: 12/25/2022]
Abstract
PURPOSE Designing a new T2 -preparation (T2 -Prep) module to simultaneously provide robust fat suppression and efficient T2 preparation without requiring an additional fat-suppression module for T2 -weighted imaging at 3T. METHODS The tip-down radiofrequency (RF) pulse of an adiabatic T2 -Prep module was replaced by a custom-designed RF-excitation pulse that induces a phase difference between water and fat, resulting in a simultaneous T2 preparation of water signals and the suppression of fat signals at the end of the module (a phaser adiabatic T2 -Prep). Numerical simulations and in vitro and in vivo electrocardiogram (ECG)-triggered navigator-gated acquisitions of the human heart were performed. Blood, myocardium, and fat signal-to-noise ratios and right coronary artery vessel sharpness were compared against previously published adiabatic T2 -Prep approaches. RESULTS Numerical simulations predicted an increased fat-suppression bandwidth and decreased sensitivity to transmit magnetic field inhomogeneities using the proposed approach while preserving the water T2 -Prep capabilities. This was confirmed by the tissue signals acquired in the phantom and the in vivo images, which show similar blood and myocardium signal-to-noise ratio, contrast-to-noise ratio, and significantly reduced fat signal-to-noise ratio compared with the other methods. As a result, the right coronary artery conspicuity was significantly increased. CONCLUSION A novel fat-suppressing T2 -Prep method was developed and implemented that showed robust fat suppression and increased vessel sharpness compared with conventional techniques while preserving its T2 -Prep capabilities.
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Affiliation(s)
- Lionel Arn
- Department of Diagnostic and Interventional Radiology, 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
| | - Matthias Stuber
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.,Center for Biomedical Imaging, Lausanne, Switzerland
| | - Jessica A M Bastiaansen
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
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13
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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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14
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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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15
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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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Kato Y, Ambale-Venkatesh B, Kassai Y, Kasuboski L, Schuijf J, Kapoor K, Caruthers S, Lima JAC. Non-contrast coronary magnetic resonance angiography: current frontiers and future horizons. MAGMA (NEW YORK, N.Y.) 2020; 33:591-612. [PMID: 32242282 PMCID: PMC7502041 DOI: 10.1007/s10334-020-00834-8] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/04/2019] [Revised: 01/22/2020] [Accepted: 01/29/2020] [Indexed: 02/07/2023]
Abstract
Coronary magnetic resonance angiography (coronary MRA) is advantageous in its ability to assess coronary artery morphology and function without ionizing radiation or contrast media. However, technical limitations including reduced spatial resolution, long acquisition times, and low signal-to-noise ratios prevent it from clinical routine utilization. Nonetheless, each of these limitations can be specifically addressed by a combination of novel technologies including super-resolution imaging, compressed sensing, and deep-learning reconstruction. In this paper, we first review the current clinical use and motivations for non-contrast coronary MRA, discuss currently available coronary MRA techniques, and highlight current technical developments that hold unique potential to optimize coronary MRA image acquisition and post-processing. In the final section, we examine the various research-based coronary MRA methods and metrics that can be leveraged to assess coronary stenosis severity, physiological function, and atherosclerotic plaque characterization. We specifically discuss how such technologies may contribute to the clinical translation of coronary MRA into a robust modality for routine clinical use.
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Affiliation(s)
- Yoko Kato
- Division of Cardiology, Johns Hopkins University School of Medicine, 600 N Wolfe St, Blalock 524, Baltimore, MD, 21287-0409, USA
| | | | | | | | | | - Karan Kapoor
- Division of Cardiology, Johns Hopkins University School of Medicine, 600 N Wolfe St, Blalock 524, Baltimore, MD, 21287-0409, USA
| | | | - Joao A C Lima
- Division of Cardiology, Johns Hopkins University School of Medicine, 600 N Wolfe St, Blalock 524, Baltimore, MD, 21287-0409, USA.
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17
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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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