1
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Dillinger H, Peereboom SM, Kozerke S. Beat phenomena of oscillating readouts. Magn Reson Med 2024; 91:1498-1511. [PMID: 38173292 DOI: 10.1002/mrm.29957] [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: 06/08/2023] [Revised: 11/15/2023] [Accepted: 11/17/2023] [Indexed: 01/05/2024]
Abstract
PURPOSE To demonstrate slowly varying, erroneous magnetic field gradients for oscillating readouts due to the mechanically resonant behavior of gradient systems. METHODS Projections of a static phantom were acquired using a one-dimensional (1D) EPI sequence with varying EPI frequencies ranging from 1121 to 1580 Hz on clinical 3T systems (30 mT/m, 200 T/m/s). Phase due to static B0 inhomogeneities was eliminated by a complex division of two separate scans with different polarities of the EPI readout. The temporal evolution of phase was evaluated and related to the mechanical resonances of the gradient systems derived from the gradient modulation transfer function. Additionally, the impact of temporally varying mechanical resonance effects on EPI was evaluated using an echo-planar spectroscopic imaging sequence. RESULTS A beat phenomenon resulting in a slowly varying phase was observed. Its temporal frequency was given by the difference between the EPI frequency and the mechanical resonance frequency of the activated gradient axis. The maximum erroneous, oscillating phase during phase encoding was ±0.5 rad for an EPI frequency of 1281 Hz. Echo-planar spectroscopic imaging images showed the resulting time-dependent stretching/compression of the FOV. CONCLUSION Oscillating readouts such as those used in EPI can result in low-frequency, erroneous phase contributions, which are explained by the beat phenomenon. Therefore, EPI phase-correction approaches may need to include beat effects for accurate image reconstruction.
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Affiliation(s)
- Hannes Dillinger
- Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland
| | - Sophie M Peereboom
- Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland
| | - Sebastian Kozerke
- Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland
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2
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Kim S, Kim D, Oh S. Straightforward Magnetic Resonance Temperature Measurements Combined with High Frame Rate and Magnetic Susceptibility Correction. Bioengineering (Basel) 2023; 10:1299. [PMID: 38002423 PMCID: PMC10669085 DOI: 10.3390/bioengineering10111299] [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: 09/05/2023] [Revised: 10/10/2023] [Accepted: 11/03/2023] [Indexed: 11/26/2023] Open
Abstract
Proton resonance frequency shift (PRFS) is an MRI-based simple temperature mapping method that exhibits higher spatial and temporal resolution than temperature mapping methods based on T1 relaxation time and diffusion. PRFS temperature measurements are validated against fiber-optic thermal sensors (FOSs). However, the use of FOSs may introduce temperature errors, leading to both underestimation and overestimation of PRFS measurements, primarily due to material susceptibility changes caused by the thermal sensors. In this study, we demonstrated susceptibility-corrected PRFS (scPRFS) with a high frame rate and accuracy for suitably distributed temperatures. A single-echo-based background removal technique was employed for phase variation correction, primarily owing to magnetic susceptibility, which enabled fast temperature mapping. The scPRFS was used to validate the temperature fidelity by comparing the temperatures of fiber-optic sensors and conventional PRFS through phantom-mimicked human and ex vivo experiments. This study demonstrates that scPRFS measurements in agar-gel are in good agreement with the thermal sensor readings, with a root mean square error (RMSE) of 0.33-0.36 °C in the phantom model and 0.12-0.16 °C in the ex vivo experiment. These results highlight the potential of scPRFS for precise thermal monitoring and ablation in both low- and high-temperature non-invasive therapies.
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Affiliation(s)
- Sangwoo Kim
- Department of Radiological Science, Daewon University College, Jecheon 27135, Republic of Korea
| | - Donghyuk Kim
- Neuroscience Research Institute, Gachon University, Incheon 21988, Republic of Korea
| | - Sukhoon Oh
- Center for Research Equipment, Korea Basic Science Institute, Cheongju 28119, Republic of Korea
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3
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Çavuşoğlu M. Arterial spin labeling MRI using spiral acquisitions and concurrent field monitoring. JOURNAL OF MAGNETIC RESONANCE (SAN DIEGO, CALIF. : 1997) 2023; 356:107572. [PMID: 37847985 DOI: 10.1016/j.jmr.2023.107572] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/05/2023] [Revised: 09/25/2023] [Accepted: 10/09/2023] [Indexed: 10/19/2023]
Abstract
Perfusion MRI based on arterial spin labeling (ASL) has intrinsically very low signal-to-noise ratio (SNR). Signal acquisition at shorter echo times (TE) is necessary to boost the SNR of the ASL images. Spiral trajectories provide substantially shorter TE yielding increased SNR and are among the fastest k-space sampling schemes to encode a given field of view and resolution. Moreover, they provide approximately isotropic point-spread functions and inherent refocusing of motion- and flow-induced phase errors. However, the efficiency of the spiral acquisitions in ASL-MRI has been limited because these advantages are counterbalanced by practical technical challenges. This is because spiral acquisitions are highly sensitive to encoding deficiencies such as static off-resonance in the main magnetic field manifested as blurring artifacts in the image. Moreover, deviation of the gradient fields from the nominal waveforms due to the imperfection of the employed hardware critically limits the practical utilization of spiral trajectories. In this work, I provide single- and multiple-shot spiral ASL images that are robust against typical spiral encoding drawbacks enabled by deploying a comprehensive signal model involving static off-resonance and coil sensitivity maps and actual B0 and gradient field dynamics up to third order in space. The spiral ASL signal acquisition was concurrently monitored using a 3rd order dynamic field camera based on NMR field probes. The reconstructed ASL images at 3 mm and 2 mm in-plane resolution associating with the monitored field dynamics and the static off-resonances exhibited strongly reduced blurring- and aliasing artifacts and distortion. Concurrent field monitoring also enables to account for quasi-static B0 drifts by encompassing the parametric input data with consistent encoding geometry and physiological field fluctuations. In conclusion, concurrent field monitoring in spiral ASL acquisition largely overcomes traditional vulnerability of spiral trajectories in practice providing high quality ASL images with increased SNR, speed and motion robustness.
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Affiliation(s)
- Mustafa Çavuşoğlu
- Institute for Biomedical Engineering, University and ETH Zürich, Zürich, Switzerland; Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, University of Zurich, Switzerland.
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4
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Srinivas S, Masutani E, Norbash A, Hsiao A. Deep learning phase error correction for cerebrovascular 4D flow MRI. Sci Rep 2023; 13:9095. [PMID: 37277401 DOI: 10.1038/s41598-023-36061-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2022] [Accepted: 05/29/2023] [Indexed: 06/07/2023] Open
Abstract
Background phase errors in 4D Flow MRI may negatively impact blood flow quantification. In this study, we assessed their impact on cerebrovascular flow volume measurements, evaluated the benefit of manual image-based correction, and assessed the potential of a convolutional neural network (CNN), a form of deep learning, to directly infer the correction vector field. With IRB waiver of informed consent, we retrospectively identified 96 MRI exams from 48 patients who underwent cerebrovascular 4D Flow MRI from October 2015 to 2020. Flow measurements of the anterior, posterior, and venous circulation were performed to assess inflow-outflow error and the benefit of manual image-based phase error correction. A CNN was then trained to directly infer the phase-error correction field, without segmentation, from 4D Flow volumes to automate correction, reserving from 23 exams for testing. Statistical analyses included Spearman correlation, Bland-Altman, Wilcoxon-signed rank (WSR) and F-tests. Prior to correction, there was strong correlation between inflow and outflow (ρ = 0.833-0.947) measurements with the largest discrepancy in the venous circulation. Manual phase error correction improved inflow-outflow correlation (ρ = 0.945-0.981) and decreased variance (p < 0.001, F-test). Fully automated CNN correction was non-inferior to manual correction with no significant differences in correlation (ρ = 0.971 vs ρ = 0.982) or bias (p = 0.82, Wilcoxon-Signed Rank test) of inflow and outflow measurements. Residual background phase error can impair inflow-outflow consistency of cerebrovascular flow volume measurements. A CNN can be used to directly infer the phase-error vector field to fully automate phase error correction.
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Affiliation(s)
- Shanmukha Srinivas
- Department of Radiology, University of California San Diego, 200 West Arbor Drive, San Diego, CA, 92103, USA
- Department of Radiology, University of California Los Angeles, 757 Westwood Plaza, Los Angeles, CA, 90095, USA
| | - Evan Masutani
- Department of Radiology, University of California San Diego, 200 West Arbor Drive, San Diego, CA, 92103, USA
| | - Alexander Norbash
- Department of Radiology, University of California San Diego, 200 West Arbor Drive, San Diego, CA, 92103, USA
| | - Albert Hsiao
- Department of Radiology, University of California San Diego, 200 West Arbor Drive, San Diego, CA, 92103, USA.
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5
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van Gorkum RJH, Guenthner C, Koethe A, Stoeck CT, Kozerke S. Characterization and correction of diffusion gradient-induced eddy currents in second-order motion-compensated echo-planar and spiral cardiac DTI. Magn Reson Med 2022; 88:2378-2394. [PMID: 35916545 PMCID: PMC9804234 DOI: 10.1002/mrm.29378] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2021] [Revised: 06/09/2022] [Accepted: 06/13/2022] [Indexed: 01/05/2023]
Abstract
PURPOSE Very high gradient amplitudes played out over extended time intervals as required for second-order motion-compensated cardiac DTI may violate the assumption of a linear time-invariant gradient system model. The aim of this work was to characterize diffusion gradient-related system nonlinearity and propose a correction approach for echo-planar and spiral spin-echo motion-compensated cardiac DTI. METHODS Diffusion gradient-induced eddy currents of 9 diffusion directions were characterized at b values of 150 s/mm2 and 450 s/mm2 for a 1.5 Tesla system and used to correct phantom, ex vivo, and in vivo motion-compensated cardiac DTI data acquired with echo-planar and spiral trajectories. Predicted trajectories were calculated using gradient impulse response function and diffusion gradient strength- and direction-dependent zeroth- and first-order eddy current responses. A reconstruction method was implemented using the predicted <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:semantics><mml:mrow><mml:mi>k</mml:mi></mml:mrow> <mml:annotation>$$ k $$</mml:annotation></mml:semantics> </mml:math> -space trajectories to additionally include off-resonances and concomitant fields. Resulting images were compared to a reference reconstruction omitting diffusion gradient-induced eddy current correction. RESULTS Diffusion gradient-induced eddy currents exhibited nonlinear effects when scaling up the gradient amplitude and could not be described by a 3D basis alone. This indicates that a gradient impulse response function does not suffice to describe diffusion gradient-induced eddy currents. Zeroth- and first-order diffusion gradient-induced eddy current effects of up to -1.7 rad and -16 to +12 rad/m, respectively, were identified. Zeroth- and first-order diffusion gradient-induced eddy current correction yielded improved image quality upon image reconstruction. CONCLUSION The proposed approach offers correction of diffusion gradient-induced zeroth- and first-order eddy currents, reducing image distortions to promote improvements of second-order motion-compensated spin-echo cardiac DTI.
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Affiliation(s)
| | - Christian Guenthner
- Institute for Biomedical Engineering, University and ETH Zurich
ZurichSwitzerland
| | - Andreas Koethe
- Institute for Biomedical Engineering, University and ETH Zurich
ZurichSwitzerland,Center for Proton Therapy, Paul Scherrer InstituteVilligenSwitzerland
| | - Christian T. Stoeck
- Institute for Biomedical Engineering, University and ETH Zurich
ZurichSwitzerland,Division of Surgical ResearchUniversity Hospital Zurich, University ZurichZurichSwitzerland
| | - Sebastian Kozerke
- Institute for Biomedical Engineering, University and ETH Zurich
ZurichSwitzerland
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6
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Fischer C, Wetzl J, Schaeffter T, Giese D. Fully automated background phase correction using M-estimate SAmple consensus (MSAC)-Application to 2D and 4D flow. Magn Reson Med 2022; 88:2709-2717. [PMID: 35916368 DOI: 10.1002/mrm.29363] [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: 02/11/2022] [Revised: 05/11/2022] [Accepted: 05/25/2022] [Indexed: 11/07/2022]
Abstract
PURPOSE Flow quantification by phase-contrast MRI is hampered by spatially varying background phase offsets. Correction performance by polynomial regression on stationary tissue may be affected by outliers such as wrap-around or constant flow. Therefore, we propose an alternative, M-estimate SAmple Consensus (MSAC) to reject outliers, and improve and fully automate background phase correction. METHODS The MSAC technique fits polynomials to randomly drawn small samples from the image. Over several trials, it aims to find the best consensus set of valid pixels by rejecting outliers to the fit and minimizing the residuals of the remaining pixels. The robustness of MSAC to its few parameters was investigated and verified using third-order polynomial correction fits on a total of 118 2D flow (97 with wrap-around) and 18 4D flow data sets (14 with wrap-around), acquired at 1.5 T and 3 T. Background phase was compared with standard stationary correction and phantom correction. Pulmonary/systemic flow ratios in 2D flow were derived, and exemplary 4D flow analysis was performed. RESULTS The MSAC technique is robust over a range of parameter choices, and a unique set of parameters is suitable for both 2D and 4D flow. In 2D flow, phase errors were significantly reduced by MSAC compared with stationary correction (p = 0.005), and stationary correction shows larger errors in pulmonary/systemic flow ratios compared with MSAC. In 4D flow, MSAC shows similar performance as stationary correction. CONCLUSIONS The MSAC method provides fully automated background phase correction to 2D and 4D flow data and shows improved robustness over stationary correction, especially with outliers present.
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Affiliation(s)
- Carola Fischer
- Department of Medical Imaging, Technical University of Berlin, Berlin, Germany.,Magnetic Resonance, Siemens Healthcare, Erlangen, Germany
| | - Jens Wetzl
- Magnetic Resonance, Siemens Healthcare, Erlangen, Germany
| | - Tobias Schaeffter
- Department of Medical Imaging, Technical University of Berlin, Berlin, Germany.,Biomedical Imaging, Physikalisch-Technische Bundesanstalt, Braunschweig and Berlin, Berlin, Germany.,School of Imaging Sciences and Biomedical Engineering, King's College London, London, UK
| | - Daniel Giese
- Magnetic Resonance, Siemens Healthcare, Erlangen, Germany.,Institute of Radiology, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), University Hospital Erlangen, Erlangen, Germany
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7
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Dillinger H, Kozerke S, Guenthner C. Direct comparison of gradient Fidelity and acoustic noise of the same MRI system at 3 T and 0.75 T. Magn Reson Med 2022; 88:1937-1947. [PMID: 35649198 DOI: 10.1002/mrm.29312] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2022] [Revised: 05/03/2022] [Accepted: 05/03/2022] [Indexed: 11/11/2022]
Abstract
PURPOSE To analyze the difference between gradient fidelity and acoustic noise of the same MRI scanner operated at product field strength (3 T) and lower field strength (0.75 T). METHODS Gradient modulation transfer functions (GMTFs) were measured using a four-slice 2D phase-encoded chirp-based sequence on the same scanner operated at 3 T and, following ramp-down, at 0.75 T with identical gradient specifications (40 mT/m, 200 T/m/s). Calibrated audio measurements were performed at both field strengths to correlate audio spectra with GMTFs. RESULTS While eddy currents were independent of field strength, mechanical resonances were substantially decreased at lower field, resulting in a reduction of GMTF distortions by up to 95% (88% on average) at the mechanical resonances of the gradient system. Audio spectra amplitudes were reduced by up to 87% when comparing 0.75 T versus 3 T. CONCLUSION Lower static fields lead to reduced Lorentz forces on the gradient coil and, in turn, to reduced mechanical resonances, thereby improving gradient fidelity. Simultaneously, the reduction of acoustic noise may help to improve patient comfort.
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Affiliation(s)
- Hannes Dillinger
- Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland
| | - Sebastian Kozerke
- Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland
| | - Christian Guenthner
- Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland
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8
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Arvidsson PM, Nelsson A, Magnusson M, Smith JG, Carlsson M, Arheden H. Hemodynamic force analysis is not ready for clinical trials on HFpEF. Sci Rep 2022; 12:4017. [PMID: 35256713 PMCID: PMC8901629 DOI: 10.1038/s41598-022-08023-4] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2021] [Accepted: 02/22/2022] [Indexed: 01/11/2023] Open
Abstract
Hemodynamic force analysis has been proposed as a novel tool for early detection of subclinical systolic dysfunction in heart failure with preserved ejection fraction (HFpEF). Here we investigated the ability of hemodynamic forces to discriminate between healthy subjects and heart failure patients with varying degrees of systolic dysfunction. We studied 34 controls, 16 HFpEF patients, and 25 heart failure patients with mid-range (HFmrEF) or reduced ejection fraction (HFrEF) using cardiac magnetic resonance with acquisition of cine images and 4D flow at 1.5 T. The Navier-Stokes equation was used to compute global left ventricular hemodynamic forces over the entire cardiac cycle. Forces were analyzed for systole, diastole, and the entire heartbeat, with and without normalization to left ventricular volume. Volume-normalized hemodynamic forces demonstrated significant positive correlation with EF (r2 = 0.47, p < 0.0001) and were found significantly lower in heart failure with reduced ejection fraction compared to controls (p < 0.0001 for systole and diastole). No difference was seen between controls and HFpEF (p > 0.34). Non-normalized forces displayed no differences between controls and HFpEF (p > 0.24 for all analyses) and did not correlate with EF (p = 0.36). Left ventricular hemodynamic force analysis, whether indexed to LV volumes or not, is not ready for clinical trials on HFpEF assessment.
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Affiliation(s)
- Per M Arvidsson
- Clinical Physiology, Department of Clinical Sciences Lund, Skåne University Hospital, Lund University, 22185, Lund, Sweden
| | - Anders Nelsson
- Clinical Physiology, Department of Clinical Sciences Lund, Skåne University Hospital, Lund University, 22185, Lund, Sweden
| | - Martin Magnusson
- Department of Cardiology, Clinical Sciences, Skåne University Hospital, Lund University, Malmö, Sweden.,Department of Clinical Sciences Malmö, Lund University, Malmö, Sweden.,Wallenberg Center for Molecular Medicine, Lund University, Lund, Sweden
| | - J Gustav Smith
- Department of Cardiology, Clinical Sciences, Skåne University Hospital, Lund University, Lund, Sweden
| | - Marcus Carlsson
- Clinical Physiology, Department of Clinical Sciences Lund, Skåne University Hospital, Lund University, 22185, Lund, Sweden
| | - Håkan Arheden
- Clinical Physiology, Department of Clinical Sciences Lund, Skåne University Hospital, Lund University, 22185, Lund, Sweden.
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9
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Yavuz Ilik S, Otani T, Yamada S, Watanabe Y, Wada S. A subject-specific assessment of measurement errors and their correction in cerebrospinal fluid velocity maps using 4D flow MRI. Magn Reson Med 2021; 87:2412-2423. [PMID: 34866235 DOI: 10.1002/mrm.29111] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2021] [Revised: 11/17/2021] [Accepted: 11/17/2021] [Indexed: 11/05/2022]
Abstract
PURPOSE Phase-contrast MRI (PC-MRI) of cerebrospinal fluid (CSF) velocity is used to evaluate the characteristics of intracranial diseases, such as normal-pressure hydrocephalus (NPH). Nevertheless, PC-MRI has several potential error sources, with eddy-current-based phase offset error being non-negligible in CSF measurement. In this study, we assess the measurement error of CSF velocity maps obtained using 4D flow MRI and evaluate correction methods. METHODS CSF velocity maps of 10 patients with NPH were acquired using 4D flow MRI (velocity-encoding = 5 cm/s). Distributed phase offset error was estimated for a whole 3D background field by polynomial fitting using robust regression analysis. This estimated phase offset error was then used to correct the CSF velocity maps. The estimated error profiles were compared with those obtained using an existing 2D correction approach involving local background information near the region of interest. RESULTS The residual standard error of the polynomial fitting against the phase offset error extracted from the measured velocities was within 0.2 cm/s. The spatial dependencies of the phase offset errors showed similar tendencies in all cases, but sufficient differences in these values were found to indicate requirement of velocity correction. Differences of the estimated errors among other correction approaches were in the order of 10-2 cm/s, and the estimated errors were in good agreement with those obtained using existing approaches. CONCLUSION Our method is capable of estimating the measurement error of CSF velocity maps obtained from 4D flow MRI and provides quantitatively reasonable characteristics for the main CSF profile in the cerebral aqueduct in patients with NPH.
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Affiliation(s)
- Selin Yavuz Ilik
- Department of Mechanical Science and Bioengineering, Graduate School of Engineering Science, Osaka University, Toyonaka, Osaka, Japan
| | - Tomohiro Otani
- Department of Mechanical Science and Bioengineering, Graduate School of Engineering Science, Osaka University, Toyonaka, Osaka, Japan
| | - Shigeki Yamada
- Department of Neurosurgery, Shiga University of Medical Science, Otsu, Shiga, Japan
| | - Yoshiyuki Watanabe
- Department of Radiology, Shiga University of Medical Science, Otsu, Shiga, Japan
| | - Shigeo Wada
- Department of Mechanical Science and Bioengineering, Graduate School of Engineering Science, Osaka University, Toyonaka, Osaka, Japan
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10
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Huang SY, Witzel T, Keil B, Scholz A, Davids M, Dietz P, Rummert E, Ramb R, Kirsch JE, Yendiki A, Fan Q, Tian Q, Ramos-Llordén G, Lee HH, Nummenmaa A, Bilgic B, Setsompop K, Wang F, Avram AV, Komlosh M, Benjamini D, Magdoom KN, Pathak S, Schneider W, Novikov DS, Fieremans E, Tounekti S, Mekkaoui C, Augustinack J, Berger D, Shapson-Coe A, Lichtman J, Basser PJ, Wald LL, Rosen BR. Connectome 2.0: Developing the next-generation ultra-high gradient strength human MRI scanner for bridging studies of the micro-, meso- and macro-connectome. Neuroimage 2021; 243:118530. [PMID: 34464739 PMCID: PMC8863543 DOI: 10.1016/j.neuroimage.2021.118530] [Citation(s) in RCA: 59] [Impact Index Per Article: 19.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Revised: 08/10/2021] [Accepted: 08/27/2021] [Indexed: 11/26/2022] Open
Abstract
The first phase of the Human Connectome Project pioneered advances in MRI technology for mapping the macroscopic structural connections of the living human brain through the engineering of a whole-body human MRI scanner equipped with maximum gradient strength of 300 mT/m, the highest ever achieved for human imaging. While this instrument has made important contributions to the understanding of macroscale connectional topology, it has also demonstrated the potential of dedicated high-gradient performance scanners to provide unparalleled in vivo assessment of neural tissue microstructure. Building on the initial groundwork laid by the original Connectome scanner, we have now embarked on an international, multi-site effort to build the next-generation human 3T Connectome scanner (Connectome 2.0) optimized for the study of neural tissue microstructure and connectional anatomy across multiple length scales. In order to maximize the resolution of this in vivo microscope for studies of the living human brain, we will push the diffusion resolution limit to unprecedented levels by (1) nearly doubling the current maximum gradient strength from 300 mT/m to 500 mT/m and tripling the maximum slew rate from 200 T/m/s to 600 T/m/s through the design of a one-of-a-kind head gradient coil optimized to minimize peripheral nerve stimulation; (2) developing high-sensitivity multi-channel radiofrequency receive coils for in vivo and ex vivo human brain imaging; (3) incorporating dynamic field monitoring to minimize image distortions and artifacts; (4) developing new pulse sequences to integrate the strongest diffusion encoding and highest spatial resolution ever achieved in the living human brain; and (5) calibrating the measurements obtained from this next-generation instrument through systematic validation of diffusion microstructural metrics in high-fidelity phantoms and ex vivo brain tissue at progressively finer scales with accompanying diffusion simulations in histology-based micro-geometries. We envision creating the ultimate diffusion MRI instrument capable of capturing the complex multi-scale organization of the living human brain - from the microscopic scale needed to probe cellular geometry, heterogeneity and plasticity, to the mesoscopic scale for quantifying the distinctions in cortical structure and connectivity that define cyto- and myeloarchitectonic boundaries, to improvements in estimates of macroscopic connectivity.
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Affiliation(s)
- Susie Y Huang
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
| | | | - Boris Keil
- Institute of Medical Physics and Radiation Protection (IMPS), TH-Mittelhessen University of Applied Sciences (THM), Giessen, Germany
| | - Alina Scholz
- Institute of Medical Physics and Radiation Protection (IMPS), TH-Mittelhessen University of Applied Sciences (THM), Giessen, Germany
| | - Mathias Davids
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | | | | | | | - John E Kirsch
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Anastasia Yendiki
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Qiuyun Fan
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Qiyuan Tian
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Gabriel Ramos-Llordén
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Hong-Hsi Lee
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Aapo Nummenmaa
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Berkin Bilgic
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Kawin Setsompop
- Radiological Sciences Laboratory, Department of Radiology, Stanford University, Stanford, CA, USA
| | - Fuyixue Wang
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Alexandru V Avram
- Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA
| | - Michal Komlosh
- Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA
| | - Dan Benjamini
- Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA
| | - Kulam Najmudeen Magdoom
- Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA
| | - Sudhir Pathak
- Learning Research and Development Center, University of Pittsburgh, Pittsburgh, PA, USA
| | - Walter Schneider
- Learning Research and Development Center, University of Pittsburgh, Pittsburgh, PA, USA
| | - Dmitry S Novikov
- Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, NY, USA; Center for Advanced Imaging Innovation and Research (CAI2R), New York University School of Medicine, New York, NY, USA
| | - Els Fieremans
- Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, NY, USA; Center for Advanced Imaging Innovation and Research (CAI2R), New York University School of Medicine, New York, NY, USA
| | - Slimane Tounekti
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Choukri Mekkaoui
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Jean Augustinack
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Daniel Berger
- Department of Molecular and Cell Biology and Center for Brain Science, Harvard University, Cambridge, MA, USA
| | - Alexander Shapson-Coe
- Department of Molecular and Cell Biology and Center for Brain Science, Harvard University, Cambridge, MA, USA
| | - Jeff Lichtman
- Department of Molecular and Cell Biology and Center for Brain Science, Harvard University, Cambridge, MA, USA
| | - Peter J Basser
- Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA
| | - Lawrence L Wald
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Bruce R Rosen
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
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11
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Wymer DT, Patel KP, Burke WF, Bhatia VK. Phase-Contrast MRI: Physics, Techniques, and Clinical Applications. Radiographics 2021; 40:122-140. [PMID: 31917664 DOI: 10.1148/rg.2020190039] [Citation(s) in RCA: 81] [Impact Index Per Article: 27.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
With phase-contrast imaging, the MRI signal is used to visualize and quantify velocity. This imaging modality relies on phase data, which are intrinsic to all MRI signals. With use of bipolar gradients, degrees of phase shift are encoded and in turn correlated directly with the velocity of protons. The acquisition of diagnostic-quality images requires selection of the correct imaging plane to ensure accurate measurement and selection of the encoding velocity and thus prevent aliasing and achieve the highest signal-to-noise ratio. Multiple applications of phase-contrast imaging are actively used in clinical practice. One of the most common clinical uses is in cardiac valvular flow imaging, at which the data are used to assess the severity of valvular disease and quantify the shunt fraction. In neurologic imaging, phase-contrast imaging can be used to measure the flow of cerebrospinal fluid. This measurement can aid in the diagnosis and direct management of normal pressure hydrocephalus or be used to evaluate the severity of stenosis, such as that in Chiari I malformations. At vascular analysis, phase-contrast imaging can be used to visualize arterial and venous flow, and this application is used most commonly in the brain. Three-dimensional imaging can yield highly detailed flow data in a technique referred to as four-dimensional flow. A more recently identified application is in MR elastography. Shear waves created by using an impulse device can be velocity encoded, and this velocity is directly proportional to the stiffness of the organ, or the shear modulus. This imaging modality is most commonly used in the liver for evaluation of cirrhosis and steatosis, although research on the assessment of other organs is being performed. Phase-contrast imaging is an important tool in the arsenal of MRI examinations and has many applications. Proper use of phase-contrast imaging requires an understanding of the many practical and technical factors and unique physics principles underlying the technique.©RSNA, 2020.
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Affiliation(s)
- David T Wymer
- From the Department of Diagnostic Radiology, Mount Sinai Medical Center, 4300 Alton Rd, Miami Beach, FL 33140
| | - Kunal P Patel
- From the Department of Diagnostic Radiology, Mount Sinai Medical Center, 4300 Alton Rd, Miami Beach, FL 33140
| | - William F Burke
- From the Department of Diagnostic Radiology, Mount Sinai Medical Center, 4300 Alton Rd, Miami Beach, FL 33140
| | - Vinay K Bhatia
- From the Department of Diagnostic Radiology, Mount Sinai Medical Center, 4300 Alton Rd, Miami Beach, FL 33140
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Lagerstrand KM, Svensson F, Polte CL, Bech-Hanssen O, Starck G, Chadorowski A, Johnsson ÅA. Reliable phase-contrast flow volume magnetic resonance measurements are feasible without adjustment of the velocity encoding parameter. J Med Imaging (Bellingham) 2020; 7:063502. [PMID: 33313339 DOI: 10.1117/1.jmi.7.6.063502] [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: 04/14/2020] [Accepted: 11/23/2020] [Indexed: 11/14/2022] Open
Abstract
Purpose: To show that adjustment of velocity encoding (VENC) for phase-contrast (PC) flow volume measurements is not necessary in modern MR scanners with effective background velocity offset corrections. Approach: The independence on VENC was demonstrated theoretically, but also experimentally on dedicated phantoms and on patients with chronic aortic regurgitation ( n = 17 ) and one healthy volunteer. All PC measurements were performed using a modern MR scanner, where the pre-emphasis circuit but also a subsequent post-processing filter were used for effective correction of background velocity offset errors. Results: The VENC level strongly affected the velocity noise level in the PC images and, hence, the estimated peak flow velocity. However, neither the regurgitant blood flow volume nor the mean flow velocity displayed any clinically relevant dependency on the VENC level. Also, the background velocity offset was shown to be close to zero ( < 0.6 cm / s ) for a VENC range of 150 to 500 cm / s , adding no significant errors to the PC flow volume measurement. Conclusions: Our study shows that reliable PC flow volume measurements are feasible without adjustment of the VENC parameter. Without the need for VENC adjustments, the scan time can be reduced for the benefit of the patient.
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Affiliation(s)
- Kerstin M Lagerstrand
- The Sahlgrenska Academy, University of Gothenburg, Institute of Clinical Sciences, Sweden.,Sahlgrenska University Hospital, Department of Medical Physics and Biomedical Engineering, Gothenburg, Sweden
| | - Frida Svensson
- The Sahlgrenska Academy, University of Gothenburg, Institute of Clinical Sciences, Sweden.,Sahlgrenska University Hospital, Department of Medical Physics and Biomedical Engineering, Gothenburg, Sweden
| | - Christian L Polte
- The Sahlgrenska Academy, University of Gothenburg, Institute of Medicine, Sweden.,Sahlgrenska University Hospital, Department of Clinical Physiology, Gothenburg, Sweden
| | - Odd Bech-Hanssen
- The Sahlgrenska Academy, University of Gothenburg, Institute of Medicine, Sweden.,Sahlgrenska University Hospital, Department of Clinical Physiology, Gothenburg, Sweden
| | - Göran Starck
- The Sahlgrenska Academy, University of Gothenburg, Institute of Clinical Sciences, Sweden.,Sahlgrenska University Hospital, Department of Medical Physics and Biomedical Engineering, Gothenburg, Sweden
| | - Artur Chadorowski
- Chalmers University of Technology, Department of Electrical Engineering, Gothenburg, Sweden
| | - Åse A Johnsson
- The Sahlgrenska Academy, University of Gothenburg, Institute of Clinical Sciences, Sweden.,Sahlgrenska University Hospital, Department of Radiology, Gothenburg, Sweden
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13
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Minderhoud SCS, van der Velde N, Wentzel JJ, van der Geest RJ, Attrach M, Wielopolski PA, Budde RPJ, Helbing WA, Roos-Hesselink JW, Hirsch A. The clinical impact of phase offset errors and different correction methods in cardiovascular magnetic resonance phase contrast imaging: a multi-scanner study. J Cardiovasc Magn Reson 2020; 22:68. [PMID: 32938483 PMCID: PMC7495876 DOI: 10.1186/s12968-020-00659-3] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2020] [Accepted: 08/06/2020] [Indexed: 01/04/2023] Open
Abstract
BACKGROUND Cardiovascular magnetic resonance (CMR) phase contrast (PC) flow measurements suffer from phase offset errors. Background subtraction based on stationary phantom measurements can most reliably be used to overcome this inaccuracy. Stationary tissue correction is an alternative and does not require additional phantom scanning. The aim of this study was 1) to compare measurements with and without stationary tissue correction to phantom corrected measurements on different GE Healthcare CMR scanners using different software packages and 2) to evaluate the clinical implications of these methods. METHODS CMR PC imaging of both the aortic and pulmonary artery flow was performed in patients on three different 1.5 T CMR scanners (GE Healthcare) using identical scan parameters. Uncorrected, first, second and third order stationary tissue corrected flow measurement were compared to phantom corrected flow measurements, our reference method, using Medis QFlow, Circle cvi42 and MASS software. The optimal (optimized) stationary tissue order was determined per scanner and software program. Velocity offsets, net flow, clinically significant difference (deviation > 10% net flow), and regurgitation severity were assessed. RESULTS Data from 175 patients (28 (17-38) years) were included, of which 84% had congenital heart disease. First, second and third order and optimized stationary tissue correction did not improve the velocity offsets and net flow measurements. Uncorrected measurements resulted in the least clinically significant differences in net flow compared to phantom corrected data. Optimized stationary tissue correction per scanner and software program resulted in net flow differences (> 10%) in 19% (MASS) and 30% (Circle cvi42) of all measurements compared to 18% (MASS) and 23% (Circle cvi42) with no correction. Compared to phantom correction, regurgitation reclassification was the least common using uncorrected data. One CMR scanner performed worse and significant net flow differences of > 10% were present both with and without stationary tissue correction in more than 30% of all measurements. CONCLUSION Phase offset errors had a significant impact on net flow quantification, regurgitation assessment and varied greatly between CMR scanners. Background phase correction using stationary tissue correction worsened accuracy compared to no correction on three GE Healthcare CMR scanners. Therefore, careful assessment of phase offset errors at each individual scanner is essential to determine whether routine use of phantom correction is necessary. TRIAL REGISTRATION Observational Study.
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Affiliation(s)
- Savine C. S. Minderhoud
- Department of Cardiology, Erasmus Medical Center, University Medical Center Rotterdam, P.O. Box 2040, Room Rg-419, Rotterdam, 3000 CA the Netherlands
- Department of Radiology and Nuclear Medicine, Erasmus Medical Center, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Nikki van der Velde
- Department of Cardiology, Erasmus Medical Center, University Medical Center Rotterdam, P.O. Box 2040, Room Rg-419, Rotterdam, 3000 CA the Netherlands
- Department of Radiology and Nuclear Medicine, Erasmus Medical Center, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Jolanda J. Wentzel
- Department of Cardiology, Erasmus Medical Center, University Medical Center Rotterdam, P.O. Box 2040, Room Rg-419, Rotterdam, 3000 CA the Netherlands
| | - Rob J. van der Geest
- Department of Radiology, Division of Image Processing, Leiden University Medical Center, Leiden, The Netherlands
| | - Mohammed Attrach
- Department of Radiology and Nuclear Medicine, Erasmus Medical Center, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Piotr A. Wielopolski
- Department of Radiology and Nuclear Medicine, Erasmus Medical Center, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Ricardo P. J. Budde
- Department of Cardiology, Erasmus Medical Center, University Medical Center Rotterdam, P.O. Box 2040, Room Rg-419, Rotterdam, 3000 CA the Netherlands
- Department of Radiology and Nuclear Medicine, Erasmus Medical Center, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Willem A. Helbing
- Department of Radiology and Nuclear Medicine, Erasmus Medical Center, University Medical Center Rotterdam, Rotterdam, The Netherlands
- Division of Pediatric Cardiology, Department of Pediatrics, Erasmus Medical Center, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Jolien W. Roos-Hesselink
- Department of Cardiology, Erasmus Medical Center, University Medical Center Rotterdam, P.O. Box 2040, Room Rg-419, Rotterdam, 3000 CA the Netherlands
| | - Alexander Hirsch
- Department of Cardiology, Erasmus Medical Center, University Medical Center Rotterdam, P.O. Box 2040, Room Rg-419, Rotterdam, 3000 CA the Netherlands
- Department of Radiology and Nuclear Medicine, Erasmus Medical Center, University Medical Center Rotterdam, Rotterdam, The Netherlands
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14
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Williamson NH, Komlosh ME, Benjamini D, Basser PJ. Limits to flow detection in phase contrast MRI. JOURNAL OF MAGNETIC RESONANCE OPEN 2020; 2-3:100004. [PMID: 33345200 PMCID: PMC7745993 DOI: 10.1016/j.jmro.2020.100004] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/21/2023]
Abstract
Pulsed gradient spin echo (PGSE) complex signal behavior becomes dominated by attenuation rather than oscillation when displacements due to flow are similar or less than diffusive displacements. In this "slow-flow" regime, the optimal displacement encoding parameter q for phase contrast velocimetry depends on the diffusive length scale q s l o w = 1 / l D = 1 / 2 D Δ rather than the velocity encoding parameter v enc = π/(qΔ). The minimum detectable mean velocity using the difference between the phase at +q slow and -q slow is 〈 v m i n 〉 = 1 / SNR D / Δ . These theories are then validated and applied to MRI by performing PGSE echo planar imaging experiments on water flowing through a column with a bulk region and a beadpack region at controlled flow rates. Velocities as slow as 6 μm/s are detected with velocimetry. Theories, MRI experimental protocols, and validation on a controlled phantom help to bridge the gap between porous media NMR and pre-clinical phase contrast and diffusion MRI.
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Affiliation(s)
- Nathan H. Williamson
- National Institute of General Medical Sciences, National Institutes of Health, Bethesda, MD, USA
- Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA
- Corresponding author: Nathan H. Williamson,
| | - Michal E. Komlosh
- Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA
- The Center for Neuroscience and Regenerative Medicine, Uniformed Service University of the Health Sciences, Bethesda, MD, USA
| | - Dan Benjamini
- Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA
- The Center for Neuroscience and Regenerative Medicine, Uniformed Service University of the Health Sciences, Bethesda, MD, USA
| | - Peter J. Basser
- Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA
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15
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Magdoom KN, Sarntinoranont M, Mareci TH. An MRI-based switched gradient impulse response characterization method with uniform eigenmode excitation. JOURNAL OF MAGNETIC RESONANCE (SAN DIEGO, CALIF. : 1997) 2020; 313:106720. [PMID: 32217424 PMCID: PMC7245110 DOI: 10.1016/j.jmr.2020.106720] [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: 01/06/2020] [Revised: 03/14/2020] [Accepted: 03/16/2020] [Indexed: 06/10/2023]
Abstract
Switching gradients generate eddy currents and mechanical vibrations of the gradient assembly causing errors in the gradient time integrals. This results in image distortions in k-space and inaccuracies in q-space imaging. The purpose of this work is to develop an MRI based unbiased measurement of the switched gradient impulse response function (sGIRF). A new gradient pattern, called the Tukey windowed Shifted Sine-Integral (Tw-SSI) pulse, is introduced to excite the gradient eigenmodes uniformly over a user-defined bandwidth. A 3D MRI-based method with Hadamard encoding was developed to map the spatiotemporal magnetic field generated after the excitation pulse to obtain the sGIRF for all the three gradient axes simultaneously. Compared to an energy-equivalent traditional trapezoidal pulse, the Tw-SSI pulse is able to excite the weak bandlimited cross-terms of the sGIRF by uniformly distributing the energy across eigenmodes. The developed field mapping method is sensitive enough to capture both the direct and cross-terms in the sGIRF. The various mechanical resonant modes of the gradient coils are also revealed, which were found to last longer than eddy currents in the shielded gradient coil studied. Tunable Tw-SSI pulse offers the flexibility to perform unbiased sGIRF measurements over a bandwidth of interest. Rapid MRI field mapping can be easily implemented in any MRI system. The method may be used to perform gradient pre-emphasis, to evaluate new gradient coil designs, and to characterize higher order shims.
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Affiliation(s)
- Kulam Najmudeen Magdoom
- Department of Mechanical and Aerospace Engineering, University of Florida, Gainesville, FL, United States.
| | - Malisa Sarntinoranont
- Department of Mechanical and Aerospace Engineering, University of Florida, Gainesville, FL, United States; J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, FL, United States
| | - Thomas H Mareci
- J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, FL, United States; Department of Biochemistry and Molecular Biology, University of Florida, Gainesville, FL, United States
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16
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Wilm BJ, Dietrich BE, Reber J, Vannesjo SJ, Pruessmann KP. Gradient Response Harvesting for Continuous System Characterization During MR Sequences. IEEE TRANSACTIONS ON MEDICAL IMAGING 2020; 39:806-815. [PMID: 31425067 DOI: 10.1109/tmi.2019.2936107] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
MRI gradient systems are required to generate magnetic field gradient waveforms with very high fidelity. This is commonly implemented by gradient system calibration and pre-emphasis. However, a number of mechanisms, particularly thermal changes, cause variation in the gradient response over time, which cannot be addressed by calibration approaches. To overcome this limitation, we present a novel method termed gradient response harvesting, where the gradient response is continuously characterized during the course of a normal MR sequence. Snippets of field measurements are repeatedly acquired during an MR sequence, and from these multiple field measurements and the known nominal MR sequence gradients, the gradient response and gradient/field offsets are calculated. The calculation is implemented in a model-based and a model-free variant. The method is demonstrated for EPI with high gradient duty-cycle, where the continuous gradient characterization is used to obtain k-space trajectory estimates that are employed in the subsequent image reconstruction. During the course of the MR sequence, changes in both the envelope and the phase of the gradient response functions were observed, including shifts of mechanical resonances. The gradient response changes were also reflected in the calculated uninterrupted gradient waveforms and thus in the k-space trajectories. Using the updated encoding information in the image reconstruction removed ghosting artifacts, that otherwise impaired the image quality. We introduced the concept of gradient response harvesting and demonstrated its feasibility. The obtained gradient response functions may be used for quality assurance/preventive maintenance, real-time adaptation of gradient pre-emphasis or to calculate uninterrupted gradient field evolutions.
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17
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Stich M, Pfaff C, Wech T, Slawig A, Ruyters G, Dewdney A, Ringler R, Köstler H. The temperature dependence of gradient system response characteristics. Magn Reson Med 2019; 83:1519-1527. [PMID: 31592559 DOI: 10.1002/mrm.28013] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2019] [Revised: 08/29/2019] [Accepted: 09/04/2019] [Indexed: 02/03/2023]
Abstract
PURPOSE The gradient system transfer function (GSTF) characterizes the frequency transfer behavior of a dynamic gradient system and can be used to correct non-Cartesian k-space trajectories. This study analyzes the impact of the gradient coil temperature of a 3T scanner on the GSTF. METHODS GSTF self- and B0 -cross-terms were acquired for a 3T Siemens scanner (Siemens Healthcare, Erlangen, Germany) using a phantom-based measurement technique. The GSTF terms were measured for various temperature states up to 45°C. The gradient coil temperatures were measured continuously utilizing 12 temperature sensors which are integrated by the vendor. Different modeling approaches were applied and compared. RESULTS The self-terms depend linearly on temperature, whereas the B0 -cross-term does not. Effects induced by thermal variation are negligible for the phase response. The self-terms are best represented by a linear model including the three gradient coil sensors that showed the maximum temperature dependence for the three axes. The use of time derivatives of the temperature did not lead to an improvement of the model. The B0 -cross-terms can be modeled by a convolution model which considers coil-specific heat transportation. CONCLUSION The temperature dependency of the GSTF was analyzed for a 3T Siemens scanner. The self- and B0 -cross-terms can be modeled using a linear and convolution modeling approach based on the three main temperature sensor elements.
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Affiliation(s)
- Manuel Stich
- Department of Diagnostic and Interventional Radiology, University Hospital Würzburg, Würzburg, Germany.,X-Ray & Molecular Imaging Lab, Technical University Amberg-Weiden, Weiden, Germany.,Siemens Healthcare, Erlangen, Germany
| | - Christiane Pfaff
- Department of Diagnostic and Interventional Radiology, University Hospital Würzburg, Würzburg, Germany.,X-Ray & Molecular Imaging Lab, Technical University Amberg-Weiden, Weiden, Germany
| | - Tobias Wech
- Department of Diagnostic and Interventional Radiology, University Hospital Würzburg, Würzburg, Germany
| | - Anne Slawig
- Department of Diagnostic and Interventional Radiology, University Hospital Würzburg, Würzburg, Germany.,Comprehensive Heart Failure Center Würzburg, Würzburg, Germany
| | | | | | - Ralf Ringler
- X-Ray & Molecular Imaging Lab, Technical University Amberg-Weiden, Weiden, Germany
| | - Herbert Köstler
- Department of Diagnostic and Interventional Radiology, University Hospital Würzburg, Würzburg, Germany
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18
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Moersdorf R, Treutlein M, Kroeger JR, Ruijsink B, Wong J, Maintz D, Weiss K, Bunck AC, Baeßler B, Giese D. Precision, reproducibility and applicability of an undersampled multi-venc 4D flow MRI sequence for the assessment of cardiac hemodynamics. Magn Reson Imaging 2019; 61:73-82. [PMID: 31100318 DOI: 10.1016/j.mri.2019.05.015] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2018] [Revised: 03/05/2019] [Accepted: 05/06/2019] [Indexed: 11/25/2022]
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19
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Aigner CS, Rund A, Abo Seada S, Price AN, Hajnal JV, Malik SJ, Kunisch K, Stollberger R. Time optimal control-based RF pulse design under gradient imperfections. Magn Reson Med 2019; 83:561-574. [PMID: 31441536 PMCID: PMC6899978 DOI: 10.1002/mrm.27955] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2019] [Revised: 07/25/2019] [Accepted: 07/29/2019] [Indexed: 12/15/2022]
Abstract
Purpose This study incorporates a gradient system imperfection model into an optimal control framework for radio frequency (RF) pulse design. Theory and Methods The joint design of minimum‐time RF and slice selective gradient shapes is posed as an optimal control problem. Hardware limitations such as maximal amplitudes for RF and slice selective gradient or its slew rate are included as hard constraints to assure practical applicability of the optimized waveforms. In order to guarantee the performance of the optimized waveform with possible gradient system disturbances such as limited system bandwidth and eddy currents, a measured gradient impulse response function (GIRF) for a specific system is integrated into the optimization. Results The method generates optimized RF and pre‐distorted slice selective gradient shapes for refocusing that are able to fully compensate the modeled imperfections of the gradient system under investigation. The results nearly regenerate the optimal results of an idealized gradient system. The numerical Bloch simulations are validated by phantom and in‐vivo experiments on 2 3T scanners. Conclusions The presented design approach demonstrates the successful correction of gradient system imperfections within an optimal control framework for RF pulse design.
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Affiliation(s)
- Christoph S Aigner
- Institute of Medical Engineering, Graz University of Technology, Graz, Austria
| | - Armin Rund
- Institute for Mathematics and Scientific Computing, University of Graz, Graz, Austria
| | - Samy Abo Seada
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Anthony N Price
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Joseph V Hajnal
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Shaihan J Malik
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Karl Kunisch
- Institute for Mathematics and Scientific Computing, University of Graz, Graz, Austria.,Johann Radon Institute for Computational and Applied Mathematics (RICAM), Austrian Academy of Sciences, Linz, Austria.,BioTechMed-Graz, Graz, Austria
| | - Rudolf Stollberger
- Institute of Medical Engineering, Graz University of Technology, Graz, Austria.,BioTechMed-Graz, Graz, Austria
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20
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Automatic correction of background phase offset in 4D-flow of great vessels and of the heart in MRI using a third-order surface model. MAGNETIC RESONANCE MATERIALS IN PHYSICS BIOLOGY AND MEDICINE 2019; 32:629-642. [DOI: 10.1007/s10334-019-00765-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/22/2019] [Revised: 06/03/2019] [Accepted: 06/13/2019] [Indexed: 10/26/2022]
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21
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Ebel S, Dufke J, Köhler B, Preim B, Rosemeier S, Jung B, Dähnert I, Lurz P, Borger M, Grothoff M, Gutberlet M. Comparison of two accelerated 4D-flow sequences for aortic flow quantification. Sci Rep 2019; 9:8643. [PMID: 31201339 PMCID: PMC6572772 DOI: 10.1038/s41598-019-45196-x] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2019] [Accepted: 05/30/2019] [Indexed: 01/26/2023] Open
Abstract
To compare two broadly used 4D-flow- with a 2D-flow-sequence in healthy volunteers, regarding absolute flow parameters, image quality (IQ), and eddy current correction (ECC). Forty volunteers (42 ± 11.8 years, 22 females) were examined with a 3T scanner. Thoracic aortic flow was assessed using a 3D-T2w-SPACE-STIR-sequence for morphology and two accelerated 4D-flow sequences for comparison, one with k-t undersampling and one with standard GRAPPA parallel-imaging. 2D-flow was used as reference standard. The custom-made software tool Bloodline enabled flow measurements for all analyses at the same location. Quantitative flow analyses were performed with and without ECC. One reader assessed pathline IQ (IQ-PATH) and occurrence of motion artefacts (IQ-ART) on a 3-point grading scale, the higher the better. k-t GRAPPA allowed a significant mean scan time reduction of 46% (17:56 ± 5:26 min vs. 10:40 ± 3:15 min) and provided significantly fewer motion artefacts than standard GRAPPA (IQ-ART 1.57 ± 0.55 vs. 0.84 ± 0.48; p < 0.001). Neither 4D-flow sequence significantly differed in flow volume nor peak velocity results with or without ECC. Nevertheless, the correlation between both 4D-flow sequences and 2D-flow was better with ECC; the k-t GRAPPA sequence performed best (R = 0.96 vs. 0.90). k-t GRAPPA 4D-flow was not inferior to a standard GRAPPA-sequence, showed fewer artefacts, comparable IQ and was almost two-fold faster.
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Affiliation(s)
- Sebastian Ebel
- Department of Diagnostic and Interventional Radiology, University of Leipzig - Heart Centre, Leipzig, Germany.
| | - Josefin Dufke
- Department of Diagnostic and Interventional Radiology, University of Leipzig - Heart Centre, Leipzig, Germany
| | - Benjamin Köhler
- Department of Simulation and Graphics, University of Magdeburg, Magdeburg, Germany
| | - Bernhard Preim
- Department of Simulation and Graphics, University of Magdeburg, Magdeburg, Germany
| | - Susan Rosemeier
- Department of Diagnostic and Interventional Radiology, University of Leipzig - Heart Centre, Leipzig, Germany
| | - Bernd Jung
- Department of Diagnostic, Interventional and Paediatric Radiology, University of Bern, Bern, Switzerland
| | - Ingo Dähnert
- Department of Paediatric Cardiology, University of Leipzig - Heart Centre, Leipzig, Germany
| | - Philipp Lurz
- Department of Cardiology, University of Leipzig - Heart Centre, Leipzig, Germany
| | - Michael Borger
- Department of Cardiac Surgery, University of Leipzig - Heart Centre, Leipzig, Germany
| | - Matthias Grothoff
- Department of Diagnostic and Interventional Radiology, University of Leipzig - Heart Centre, Leipzig, Germany
| | - Matthias Gutberlet
- Department of Diagnostic and Interventional Radiology, University of Leipzig - Heart Centre, Leipzig, Germany
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22
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Hofman MBM, Rodenburg MJA, Markenroth Bloch K, Werner B, Westenberg JJM, Valsangiacomo Buechel ER, Nijveldt R, Spruijt OA, Kilner PJ, van Rossum AC, Gatehouse PD. In-vivo validation of interpolation-based phase offset correction in cardiovascular magnetic resonance flow quantification: a multi-vendor, multi-center study. J Cardiovasc Magn Reson 2019; 21:30. [PMID: 31104632 PMCID: PMC6526620 DOI: 10.1186/s12968-019-0538-3] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2018] [Accepted: 04/03/2019] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND A velocity offset error in phase contrast cardiovascular magnetic resonance (CMR) imaging is a known problem in clinical assessment of flow volumes in vessels around the heart. Earlier studies have shown that this offset error is clinically relevant over different systems, and cannot be removed by protocol optimization. Correction methods using phantom measurements are time consuming, and assume reproducibility of the offsets which is not the case for all systems. An alternative previously published solution is to correct the in-vivo data in post-processing, interpolating the velocity offset from stationary tissue within the field-of-view. This study aims to validate this interpolation-based offset correction in-vivo in a multi-vendor, multi-center setup. METHODS Data from six 1.5 T CMR systems were evaluated, with two systems from each of the three main vendors. At each system aortic and main pulmonary artery 2D flow studies were acquired during routine clinical or research examinations, with an additional phantom measurement using identical acquisition parameters. To verify the phantom acquisition, a region-of-interest (ROI) at stationary tissue in the thorax wall was placed and compared between in-vivo and phantom measurements. Interpolation-based offset correction was performed on the in-vivo data, after manually excluding regions of spatial wraparound. Correction performance of different spatial orders of interpolation planes was evaluated. RESULTS A total of 126 flow measurements in 82 subjects were included. At the thorax wall the agreement between in-vivo and phantom was - 0.2 ± 0.6 cm/s. Twenty-eight studies were excluded because of a difference at the thorax wall exceeding 0.6 cm/s from the phantom scan, leaving 98. Before correction, the offset at the vessel as assessed in the phantom was - 0.4 ± 1.5 cm/s, which resulted in a - 5 ± 16% error in cardiac output. The optimal order of the interpolation correction plane was 1st order, except for one system at which a 2nd order plane was required. Application of the interpolation-based correction revealed a remaining offset velocity of 0.1 ± 0.5 cm/s and 0 ± 5% error in cardiac output. CONCLUSIONS This study shows that interpolation-based offset correction reduces the offset with comparable efficacy as phantom measurement phase offset correction, without the time penalty imposed by phantom scans. TRIAL REGISTRATION The study was registered in The Netherlands National Trial Register (NTR) under TC 4865 . Registered 19 September 2014. Retrospectively registered.
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Affiliation(s)
- Mark B. M. Hofman
- Radiology and Nuclear Medicine, ICaR-VU, VU University Medical Center, PO Box 7057, 1007 MB Amsterdam, the Netherlands
| | - Manouk J. A. Rodenburg
- Radiology and Nuclear Medicine, ICaR-VU, VU University Medical Center, PO Box 7057, 1007 MB Amsterdam, the Netherlands
| | - Karin Markenroth Bloch
- Lund University Bioimaging Center, Lund University, SE-221 85 Lund, Sweden
- Philips Healthcare, SE-164 85 Stockholm, Sweden
| | - Beat Werner
- Department Diagnostic Imaging, University Children’s Hospital, Steinwiesstrasse 75, 8032 Zürich, Switzerland
| | - Jos J. M. Westenberg
- Radiology, Leiden University Medical Center, Albinusdreef 2, 2333 ZA Leiden, the Netherlands
| | | | - Robin Nijveldt
- Cardiology, ICaR-VU, VU University Medical Center, PO Box 7057, 1007 MB Amsterdam, the Netherlands
| | - Onno A. Spruijt
- Pulmonology, ICaR-VU, VU University Medical Center, PO Box 7057, 1007 MB Amsterdam, the Netherlands
| | - Philip J. Kilner
- Cardiovascular Magnetic Resonance Unit, Royal Brompton Hospital, Sydney Street, London, SW3 6NP UK
| | - Albert C. van Rossum
- Cardiology, ICaR-VU, VU University Medical Center, PO Box 7057, 1007 MB Amsterdam, the Netherlands
| | - Peter D. Gatehouse
- Cardiovascular Magnetic Resonance Unit, Royal Brompton Hospital, Sydney Street, London, SW3 6NP UK
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23
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Visualizing and quantifying flow stasis in abdominal aortic aneurysms in men using 4D flow MRI. Magn Reson Imaging 2019; 57:103-110. [DOI: 10.1016/j.mri.2018.11.003] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2018] [Revised: 11/10/2018] [Accepted: 11/11/2018] [Indexed: 01/24/2023]
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24
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Magdoom KN, Zeinomar A, Lonser RR, Sarntinoranont M, Mareci TH. Phase contrast MRI of creeping flows using stimulated echo. JOURNAL OF MAGNETIC RESONANCE (SAN DIEGO, CALIF. : 1997) 2019; 299:49-58. [PMID: 30579226 PMCID: PMC6402592 DOI: 10.1016/j.jmr.2018.12.009] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/10/2018] [Revised: 12/10/2018] [Accepted: 12/13/2018] [Indexed: 05/30/2023]
Abstract
Creeping flows govern many important physiological phenomena such as elevated interstitial fluid flows in tumors, glymphatic flows in the brain, among other applications. However, few methods exist to measure such slow flows non-invasively in optically opaque biological tissues in vivo. Phase-contrast MRI is a velocimetry technique routinely used in the clinic to measure fast flows in biological tissues, such as blood and cerebrospinal fluid (CSF), in the order of cm/s. Use of this technique to encode slower flows is hampered by diffusion weighting and phase error introduced by gradient hardware imperfections. In this study, a new PC-MRI technique is developed using stimulated echo preparation to overcome these challenges. Flows as slow as 1 μm/s are measured and validated using controlled water flow through a pipe at 4.7 T. The error in measured flow rate obtained by integrating the measured velocity over the cross-sectional area of the pipe is less than 10%. The developed method was also able to capture slow natural convection flows appearing in liquids placed inside a horizontal bore magnet. Monitoring the 4D velocity vector field revealed that the natural convection flows decay exponentially with time. This method could be applied in future to study creeping flows, e.g. in tissue.
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Affiliation(s)
- Kulam Najmudeen Magdoom
- Department of Mechanical and Aerospace Engineering, University of Florida, Gainesville, FL, USA.
| | - Ahmad Zeinomar
- Department of Biochemistry and Molecular Biology, University of Florida, Gainesville, FL, USA
| | - Russell R Lonser
- Department of Neurological Surgery, Wexner Medical Center, The Ohio State University, Columbus, OH, USA
| | - Malisa Sarntinoranont
- Department of Mechanical and Aerospace Engineering, University of Florida, Gainesville, FL, USA; J. Crayton Pruitt Family Department of Biomedical Engineering, 1275 Center Drive, Biomedical Sciences Building, Gainesville, FL, USA
| | - Thomas H Mareci
- Department of Biochemistry and Molecular Biology, University of Florida, Gainesville, FL, USA; J. Crayton Pruitt Family Department of Biomedical Engineering, 1275 Center Drive, Biomedical Sciences Building, Gainesville, FL, USA
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25
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Engel M, Kasper L, Barmet C, Schmid T, Vionnet L, Wilm B, Pruessmann KP. Single‐shot spiral imaging at 7
T. Magn Reson Med 2018; 80:1836-1846. [DOI: 10.1002/mrm.27176] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2017] [Revised: 02/15/2018] [Accepted: 02/18/2018] [Indexed: 01/18/2023]
Affiliation(s)
- Maria Engel
- Institute for Biomedical EngineeringETH Zurich and University of ZurichZurich Switzerland
| | - Lars Kasper
- Institute for Biomedical EngineeringETH Zurich and University of ZurichZurich Switzerland
- Translational Neuromodeling Unit, Institute for Biomedical EngineeringUniversity of Zurich and ETH ZurichZurich Switzerland
| | - Christoph Barmet
- Institute for Biomedical EngineeringETH Zurich and University of ZurichZurich Switzerland
- Skope Magnetic Resonance Technologies AGZurich Switzerland
| | - Thomas Schmid
- Institute for Biomedical EngineeringETH Zurich and University of ZurichZurich Switzerland
| | - Laetitia Vionnet
- Institute for Biomedical EngineeringETH Zurich and University of ZurichZurich Switzerland
| | - Bertram Wilm
- Institute for Biomedical EngineeringETH Zurich and University of ZurichZurich Switzerland
- Skope Magnetic Resonance Technologies AGZurich Switzerland
| | - Klaas P. Pruessmann
- Institute for Biomedical EngineeringETH Zurich and University of ZurichZurich Switzerland
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26
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Frydrychowicz A, Roldan-Alzate A, Winslow E, Consigny D, Campo CA, Motosugi U, Johnson KM, Wieben O, Reeder SB. Comparison of radial 4D Flow-MRI with perivascular ultrasound to quantify blood flow in the abdomen and introduction of a porcine model of pre-hepatic portal hypertension. Eur Radiol 2017; 27:5316-5324. [PMID: 28656461 DOI: 10.1007/s00330-017-4862-4] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2016] [Revised: 03/22/2017] [Accepted: 04/20/2017] [Indexed: 02/07/2023]
Abstract
OBJECTIVES Objectives of this study were to compare radial time-resolved phase contrast magnetic resonance imaging (4D Flow-MRI) with perivascular ultrasound (pvUS) and to explore a porcine model of acute pre-hepatic portal hypertension (PHTN). METHODS Abdominal 4D Flow-MRI and pvUS in portal and splenic vein, hepatic and both renal arteries were performed in 13 pigs of approximately 60 kg. In six pigs, measurements were repeated after partial portal vein (PV) ligature. Inter- and intra-reader comparisons and statistical analysis including Bland-Altman (BA) comparison, paired Student's t tests and linear regression were performed. RESULTS PvUS and 4D Flow-MRI measurements agreed well; flow before partial PV ligature was 322 ± 30 ml/min in pvUS and 297 ± 27 ml/min in MRI (p = 0.294), and average BA difference was 25 ml/min [-322; 372]. Inter- and intra-reader results differed very little, revealed excellent correlation (R 2 = 0.98 and 0.99, respectively) and resulted in BA differences of -5 ml/min [-161; 150] and -2 ml/min [-28; 25], respectively. After PV ligature, PV flow decreased from 356 ± 50 to 298 ± 61 ml/min (p = 0.02), and hepatic arterial flow increased from 277 ± 36 to 331 ± 65 ml/min (p = n.s.). CONCLUSION The successful in vivo comparison of radial 4D Flow-MRI to perivascular ultrasound revealed good agreement of abdominal blood flow although with considerable spread of results. A model of pre-hepatic PHTN was successfully introduced and acute responses monitored. KEY POINTS • Radial 4D Flow-MRI in the abdomen was successfully compared to perivascular ultrasound. • Inter- and intra-reader testing demonstrated excellent reproducibility of upper abdominal 4D Flow-MRI. • A porcine model of acute pre-hepatic portal hypertension was successfully introduced. • 4D Flow-MRI successfully monitored acute changes in a model of portal hypertension.
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Affiliation(s)
- A Frydrychowicz
- Department of Radiology, School of Medicine and Public Health, E3/366 Clinical Science Center, University of Wisconsin - Madison, 600 Highland Avenue, Madison, WI, 53792-3252, USA.
- Clinic for Radiology and Nuclear Medicine, University Hospital Schleswig-Holstein, Campus Lübeck, Ratzeburger Allee 160, 23562, Lübeck, Germany.
- University of Lübeck, Lübeck, Germany.
| | - A Roldan-Alzate
- Department of Radiology, School of Medicine and Public Health, E3/366 Clinical Science Center, University of Wisconsin - Madison, 600 Highland Avenue, Madison, WI, 53792-3252, USA
- Department of Mechanical Engineering, University of Wisconsin, Madison, USA
| | - E Winslow
- Department of Surgery, University of Wisconsin, Madison, USA
| | - D Consigny
- Department of Radiology, School of Medicine and Public Health, E3/366 Clinical Science Center, University of Wisconsin - Madison, 600 Highland Avenue, Madison, WI, 53792-3252, USA
| | - C A Campo
- Department of Radiology, School of Medicine and Public Health, E3/366 Clinical Science Center, University of Wisconsin - Madison, 600 Highland Avenue, Madison, WI, 53792-3252, USA
| | - U Motosugi
- Department of Radiology, School of Medicine and Public Health, E3/366 Clinical Science Center, University of Wisconsin - Madison, 600 Highland Avenue, Madison, WI, 53792-3252, USA
| | - K M Johnson
- Department of Medical Physics, University of Wisconsin, Madison, USA
| | - O Wieben
- Department of Radiology, School of Medicine and Public Health, E3/366 Clinical Science Center, University of Wisconsin - Madison, 600 Highland Avenue, Madison, WI, 53792-3252, USA
- Department of Medical Physics, University of Wisconsin, Madison, USA
| | - S B Reeder
- Department of Radiology, School of Medicine and Public Health, E3/366 Clinical Science Center, University of Wisconsin - Madison, 600 Highland Avenue, Madison, WI, 53792-3252, USA
- Department of Medical Physics, University of Wisconsin, Madison, USA
- Department of Biomedical Engineering, University of Wisconsin, Madison, USA
- Department of Medicine, University of Wisconsin, Madison, USA
- Department of Emergency Medicine, University of Wisconsin, Madison, USA
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27
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Bollmann S, Kasper L, Vannesjo SJ, Diaconescu AO, Dietrich BE, Gross S, Stephan KE, Pruessmann KP. Analysis and correction of field fluctuations in fMRI data using field monitoring. Neuroimage 2017; 154:92-105. [PMID: 28077303 DOI: 10.1016/j.neuroimage.2017.01.014] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2016] [Revised: 01/06/2017] [Accepted: 01/06/2017] [Indexed: 10/20/2022] Open
Abstract
This work investigates the role of magnetic field fluctuations as a confound in fMRI. In standard fMRI experiments with single-shot EPI acquisition at 3 Tesla the uniform and gradient components of the magnetic field were recorded with NMR field sensors. By principal component analysis it is found that differences of field evolution between the EPI readouts are explainable by few components relating to slow and within-shot field dynamics of hardware and physiological origin. The impact of fluctuating field components is studied by selective data correction and assessment of its influence on image fluctuation and SFNR. Physiological field fluctuations, attributed to breathing, were found to be small relative to those of hardware origin. The dominant confounds were hardware-related and attributable to magnet drift and thermal changes. In raw image time series, field fluctuation caused significant SFNR loss, reflected by a 67% gain upon correction. Large part of this correction can be accomplished by traditional image realignment, which addresses slow and spatially uniform field changes. With realignment, explicit field correction increased the SFNR on the order of 6%. In conclusion, field fluctuations are a relevant confound in fMRI and can be addressed effectively by retrospective data correction. Based on the physics involved it is anticipated that the advantage of full field correction increases with field strength, with non-Cartesian readouts, and upon phase-sensitive BOLD analysis.
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Affiliation(s)
- Saskia Bollmann
- Institute for Biomedical Engineering, ETH Zurich and University of Zurich, 8092 Zurich, Switzerland.
| | - Lars Kasper
- Institute for Biomedical Engineering, ETH Zurich and University of Zurich, 8092 Zurich, Switzerland; Translational Neuromodeling Unit (TNU), Institute for Biomedical Engineering, University of Zurich and ETH Zurich, 8032 Zurich, Switzerland
| | - S Johanna Vannesjo
- Institute for Biomedical Engineering, ETH Zurich and University of Zurich, 8092 Zurich, Switzerland
| | - Andreea O Diaconescu
- Translational Neuromodeling Unit (TNU), Institute for Biomedical Engineering, University of Zurich and ETH Zurich, 8032 Zurich, Switzerland
| | - Benjamin E Dietrich
- Institute for Biomedical Engineering, ETH Zurich and University of Zurich, 8092 Zurich, Switzerland
| | - Simon Gross
- Institute for Biomedical Engineering, ETH Zurich and University of Zurich, 8092 Zurich, Switzerland
| | - Klaas E Stephan
- Translational Neuromodeling Unit (TNU), Institute for Biomedical Engineering, University of Zurich and ETH Zurich, 8032 Zurich, Switzerland; Wellcome Trust Centre for Neuroimaging, University College London, London WC1N 3BG, UK; Max Planck Institute for Metabolism Research, 50931 Cologne, Germany
| | - Klaas P Pruessmann
- Institute for Biomedical Engineering, ETH Zurich and University of Zurich, 8092 Zurich, Switzerland
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28
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Pennell DJ, Baksi AJ, Prasad SK, Mohiaddin RH, Alpendurada F, Babu-Narayan SV, Schneider JE, Firmin DN. Review of Journal of Cardiovascular Magnetic Resonance 2015. J Cardiovasc Magn Reson 2016; 18:86. [PMID: 27846914 PMCID: PMC5111217 DOI: 10.1186/s12968-016-0305-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2016] [Accepted: 11/02/2016] [Indexed: 12/14/2022] Open
Abstract
There were 116 articles published in the Journal of Cardiovascular Magnetic Resonance (JCMR) in 2015, which is a 14 % increase on the 102 articles published in 2014. The quality of the submissions continues to increase. The 2015 JCMR Impact Factor (which is published in June 2016) rose to 5.75 from 4.72 for 2014 (as published in June 2015), which is the highest impact factor ever recorded for JCMR. The 2015 impact factor means that the JCMR papers that were published in 2013 and 2014 were cited on average 5.75 times in 2015. The impact factor undergoes natural variation according to citation rates of papers in the 2 years following publication, and is significantly influenced by highly cited papers such as official reports. However, the progress of the journal's impact over the last 5 years has been impressive. Our acceptance rate is <25 % and has been falling because the number of articles being submitted has been increasing. In accordance with Open-Access publishing, the JCMR articles go on-line as they are accepted with no collating of the articles into sections or special thematic issues. For this reason, the Editors have felt that it is useful once per calendar year to summarize the papers for the readership into broad areas of interest or theme, so that areas of interest can be reviewed in a single article in relation to each other and other recent JCMR articles. The papers are presented in broad themes and set in context with related literature and previously published JCMR papers to guide continuity of thought in the journal. We hope that you find the open-access system increases wider reading and citation of your papers, and that you will continue to send your quality papers to JCMR for publication.
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Affiliation(s)
- D. J. Pennell
- Cardiovascular Magnetic Resonance Unit, Royal Brompton & Harefield NHS Foundation Trust, Sydney Street, London, SW 3 6NP UK
| | - A. J. Baksi
- Cardiovascular Magnetic Resonance Unit, Royal Brompton & Harefield NHS Foundation Trust, Sydney Street, London, SW 3 6NP UK
| | - S. K. Prasad
- Cardiovascular Magnetic Resonance Unit, Royal Brompton & Harefield NHS Foundation Trust, Sydney Street, London, SW 3 6NP UK
| | - R. H. Mohiaddin
- Cardiovascular Magnetic Resonance Unit, Royal Brompton & Harefield NHS Foundation Trust, Sydney Street, London, SW 3 6NP UK
| | - F. Alpendurada
- Cardiovascular Magnetic Resonance Unit, Royal Brompton & Harefield NHS Foundation Trust, Sydney Street, London, SW 3 6NP UK
| | - S. V. Babu-Narayan
- Cardiovascular Magnetic Resonance Unit, Royal Brompton & Harefield NHS Foundation Trust, Sydney Street, London, SW 3 6NP UK
| | - J. E. Schneider
- Cardiovascular Magnetic Resonance Unit, Royal Brompton & Harefield NHS Foundation Trust, Sydney Street, London, SW 3 6NP UK
| | - D. N. Firmin
- Cardiovascular Magnetic Resonance Unit, Royal Brompton & Harefield NHS Foundation Trust, Sydney Street, London, SW 3 6NP UK
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29
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Vannesjo SJ, Duerst Y, Vionnet L, Dietrich BE, Pavan M, Gross S, Barmet C, Pruessmann KP. Gradient and shim pre-emphasis by inversion of a linear time-invariant system model. Magn Reson Med 2016; 78:1607-1622. [PMID: 27797105 DOI: 10.1002/mrm.26531] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2016] [Revised: 10/05/2016] [Accepted: 10/06/2016] [Indexed: 11/07/2022]
Abstract
PURPOSE The goal of this contribution is to enhance the fidelity and switching speed of gradient and shim fields by advancing pre-emphasis toward broadband and full cross-term correction. THEORY AND METHODS The proposed approach is based on viewing gradient and shim chains as linear, time-invariant (LTI) systems. Pre-emphasis is accomplished by inversion of a broadband digital system model. In the multiple-channel case, it amounts to a matrix of broadband filters that perform concerted self- and cross-term correction. This approach is demonstrated with gradients and shims up to the third order in a 7 Tesla whole-body MR system. RESULTS Pre-emphasis by LTI model inversion is first verified by studying settling speeds and response behavior without and with the correction. It is then demonstrated for rapid shim updating, achieving substantially enhanced fidelity of field dynamics and shim settling within approximately 1 ms. In single-shot echo-planar imaging (EPI) acquisitions in vivo, this benefit is shown to translate into enhanced geometric fidelity. CONCLUSIONS The fidelity of gradient and shim dynamics can be greatly enhanced by pre-emphasis based on inverting a general LTI system model. Permitting shim settling on the millisecond scale, broadband multiple-channel pre-emphasis promises to render higher-order shimming fully versatile at the level of MRI sequence design. Magn Reson Med 78:1607-1622, 2017. © 2016 International Society for Magnetic Resonance in Medicine.
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Affiliation(s)
- S Johanna Vannesjo
- Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Zurich, Switzerland
| | - Yolanda Duerst
- Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Zurich, Switzerland
| | - Laetitia Vionnet
- Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Zurich, Switzerland
| | - Benjamin E Dietrich
- Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Zurich, Switzerland
| | - Matteo Pavan
- Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Zurich, Switzerland
| | - Simon Gross
- Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Zurich, Switzerland
| | - Christoph Barmet
- Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Zurich, Switzerland.,Skope Magnetic Resonance Technologies, 8044, Zurich, Switzerland
| | - Klaas P Pruessmann
- Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Zurich, Switzerland
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30
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Valvano G, Martini N, Huber A, Santelli C, Binter C, Chiappino D, Landini L, Kozerke S. Accelerating 4D flow MRI by exploiting low-rank matrix structure and hadamard sparsity. Magn Reson Med 2016; 78:1330-1341. [PMID: 27787911 DOI: 10.1002/mrm.26508] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2016] [Revised: 09/23/2016] [Accepted: 09/23/2016] [Indexed: 11/11/2022]
Affiliation(s)
- Giuseppe Valvano
- Department of Information Engineering; University of Pisa; Pisa Italy
- Fondazione G. Monasterio CNR-Regione Toscana; Massa Italy
| | - Nicola Martini
- Fondazione G. Monasterio CNR-Regione Toscana; Massa Italy
| | - Adrian Huber
- Institute for Biomedical Engineering; University and ETH Zurich; Zurich Switzerland
| | - Claudio Santelli
- Institute for Biomedical Engineering; University and ETH Zurich; Zurich Switzerland
| | - Christian Binter
- Institute for Biomedical Engineering; University and ETH Zurich; Zurich Switzerland
| | | | - Luigi Landini
- Department of Information Engineering; University of Pisa; Pisa Italy
- Fondazione G. Monasterio CNR-Regione Toscana; Massa Italy
| | - Sebastian Kozerke
- Institute for Biomedical Engineering; University and ETH Zurich; Zurich Switzerland
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31
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Wilm BJ, Barmet C, Gross S, Kasper L, Vannesjo SJ, Haeberlin M, Dietrich BE, Brunner DO, Schmid T, Pruessmann KP. Single‐shot spiral imaging enabled by an expanded encoding model:
D
emonstration in diffusion
MRI. Magn Reson Med 2016; 77:83-91. [DOI: 10.1002/mrm.26493] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2016] [Revised: 08/29/2016] [Accepted: 09/14/2016] [Indexed: 11/08/2022]
Affiliation(s)
- Bertram J. Wilm
- Institute for Biomedical EngineeringUniversity of Zurich and ETH ZurichZurich Switzerland
| | - Christoph Barmet
- Institute for Biomedical EngineeringUniversity of Zurich and ETH ZurichZurich Switzerland
- Skope Magnetic Resonance Technologies IncZurich Switzerland
| | - Simon Gross
- Institute for Biomedical EngineeringUniversity of Zurich and ETH ZurichZurich Switzerland
| | - Lars Kasper
- Institute for Biomedical EngineeringUniversity of Zurich and ETH ZurichZurich Switzerland
- Translational Neuromodeling Unit, Institute for Biomedical EngineeringUniversity of Zurich and ETH ZurichZurich Switzerland
| | - S. Johanna Vannesjo
- Institute for Biomedical EngineeringUniversity of Zurich and ETH ZurichZurich Switzerland
| | - Max Haeberlin
- Institute for Biomedical EngineeringUniversity of Zurich and ETH ZurichZurich Switzerland
| | - Benjamin E. Dietrich
- Institute for Biomedical EngineeringUniversity of Zurich and ETH ZurichZurich Switzerland
| | - David O. Brunner
- Institute for Biomedical EngineeringUniversity of Zurich and ETH ZurichZurich Switzerland
| | - Thomas Schmid
- Institute for Biomedical EngineeringUniversity of Zurich and ETH ZurichZurich Switzerland
| | - Klaas P. Pruessmann
- Institute for Biomedical EngineeringUniversity of Zurich and ETH ZurichZurich Switzerland
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32
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Brunner DO, Dietrich BE, Çavuşoğlu M, Wilm BJ, Schmid T, Gross S, Barmet C, Pruessmann KP. Concurrent recording of RF pulses and gradient fields - comprehensive field monitoring for MRI. NMR IN BIOMEDICINE 2016; 29:1162-1172. [PMID: 26269210 DOI: 10.1002/nbm.3359] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/06/2014] [Revised: 05/26/2015] [Accepted: 06/18/2015] [Indexed: 06/04/2023]
Abstract
Reconstruction of MRI data is based on exact knowledge of all magnetic field dynamics, since the interplay of RF and gradient pulses generates the signal, defines the contrast and forms the basis of resolution in spatial and spectral dimensions. Deviations caused by various sources, such as system imperfections, delays, eddy currents, drifts or externally induced fields, can therefore critically limit the accuracy of MRI examinations. This is true especially at ultra-high fields, because many error terms scale with the main field strength, and higher available SNR renders even smaller errors relevant. Higher baseline field also often requires higher acquisition bandwidths and faster signal encoding, increasing hardware demands and the severity of many types of hardware imperfection. To address field imperfections comprehensively, in this work we propose to expand the concept of magnetic field monitoring to also encompass the recording of RF fields. In this way, all dynamic magnetic fields relevant for spin evolution are covered, including low- to audio-frequency magnetic fields as produced by main magnets, gradients and shim systems, as well as RF pulses generated with single- and multiple-channel transmission systems. The proposed approach permits field measurements concurrently with actual MRI procedures on a strict common time base. The combined measurement is achieved with an array of miniaturized field probes that measure low- to audio-frequency fields via (19) F NMR and simultaneously pick up RF pulses in the MRI system's (1) H transmit band. Field recordings can form the basis of system calibration, retrospective correction of imaging data or closed-loop feedback correction, all of which hold potential to render MRI more robust and relax hardware requirements. The proposed approach is demonstrated for a range of imaging methods performed on a 7 T human MRI system, including accelerated multiple-channel RF pulses. Copyright © 2015 John Wiley & Sons, Ltd.
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Affiliation(s)
- David O Brunner
- Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Zurich, Switzerland
| | - Benjamin E Dietrich
- Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Zurich, Switzerland
| | - Mustafa Çavuşoğlu
- Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Zurich, Switzerland
| | - Bertram J Wilm
- Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Zurich, Switzerland
- Skope Magnetic Resonance Technologies, Zurich, Switzerland
| | - Thomas Schmid
- Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Zurich, Switzerland
| | - Simon Gross
- Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Zurich, Switzerland
| | - Christoph Barmet
- Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Zurich, Switzerland
- Skope Magnetic Resonance Technologies, Zurich, Switzerland
| | - Klaas P Pruessmann
- Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Zurich, Switzerland
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Teh I, McClymont D, Burton RAB, Maguire ML, Whittington HJ, Lygate CA, Kohl P, Schneider JE. Resolving Fine Cardiac Structures in Rats with High-Resolution Diffusion Tensor Imaging. Sci Rep 2016; 6:30573. [PMID: 27466029 PMCID: PMC4964346 DOI: 10.1038/srep30573] [Citation(s) in RCA: 37] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2016] [Accepted: 07/04/2016] [Indexed: 02/03/2023] Open
Abstract
Cardiac architecture is fundamental to cardiac function and can be assessed non-invasively with diffusion tensor imaging (DTI). Here, we aimed to overcome technical challenges in ex vivo DTI in order to extract fine anatomical details and to provide novel insights in the 3D structure of the heart. An integrated set of methods was implemented in ex vivo rat hearts, including dynamic receiver gain adjustment, gradient system scaling calibration, prospective adjustment of diffusion gradients, and interleaving of diffusion-weighted and non-diffusion-weighted scans. Together, these methods enhanced SNR and spatial resolution, minimised orientation bias in diffusion-weighting, and reduced temperature variation, enabling detection of tissue structures such as cell alignment in atria, valves and vessels at an unprecedented level of detail. Improved confidence in eigenvector reproducibility enabled tracking of myolaminar structures as a basis for segmentation of functional groups of cardiomyocytes. Ex vivo DTI facilitates acquisition of high quality structural data that complements readily available in vivo cardiac functional and anatomical MRI. The improvements presented here will facilitate next generation virtual models integrating micro-structural and electro-mechanical properties of the heart.
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Affiliation(s)
- Irvin Teh
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, OX3 7BN, United Kingdom
| | - Darryl McClymont
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, OX3 7BN, United Kingdom
| | - Rebecca A. B. Burton
- Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, OX1 3PT, United Kingdom
| | - Mahon L. Maguire
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, OX3 7BN, United Kingdom
| | - Hannah J. Whittington
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, OX3 7BN, United Kingdom
| | - Craig A. Lygate
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, OX3 7BN, United Kingdom
| | - Peter Kohl
- National Heart and Lung Institute, Imperial College London, London, SW3 6NP, United Kingdom
- Institute for Experimental Cardiovascular Medicine, University Heart Centre Freiburg · Bad Krozingen, Medical School of the University of Freiburg, Freiburg, 79110, Germany
| | - Jürgen E. Schneider
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, OX3 7BN, United Kingdom
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34
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Advanced flow MRI: emerging techniques and applications. Clin Radiol 2016; 71:779-95. [PMID: 26944696 DOI: 10.1016/j.crad.2016.01.011] [Citation(s) in RCA: 92] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2015] [Revised: 12/10/2015] [Accepted: 01/10/2016] [Indexed: 12/12/2022]
Abstract
Magnetic resonance imaging (MRI) techniques provide non-invasive and non-ionising methods for the highly accurate anatomical depiction of the heart and vessels throughout the cardiac cycle. In addition, the intrinsic sensitivity of MRI to motion offers the unique ability to acquire spatially registered blood flow simultaneously with the morphological data, within a single measurement. In clinical routine, flow MRI is typically accomplished using methods that resolve two spatial dimensions in individual planes and encode the time-resolved velocity in one principal direction, typically oriented perpendicular to the two-dimensional (2D) section. This review describes recently developed advanced MRI flow techniques, which allow for more comprehensive evaluation of blood flow characteristics, such as real-time flow imaging, 2D multiple-venc phase contrast MRI, four-dimensional (4D) flow MRI, quantification of complex haemodynamic properties, and highly accelerated flow imaging. Emerging techniques and novel applications are explored. In addition, applications of these new techniques for the improved evaluation of cardiovascular (aorta, pulmonary arteries, congenital heart disease, atrial fibrillation, coronary arteries) as well as cerebrovascular disease (intra-cranial arteries and veins) are presented.
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Phase Error Correction in Time-Averaged 3D Phase Contrast Magnetic Resonance Imaging of the Cerebral Vasculature. PLoS One 2016; 11:e0149930. [PMID: 26910600 PMCID: PMC4765993 DOI: 10.1371/journal.pone.0149930] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2015] [Accepted: 02/05/2016] [Indexed: 11/19/2022] Open
Abstract
Purpose Volume flow rate (VFR) measurements based on phase contrast (PC)-magnetic resonance (MR) imaging datasets have spatially varying bias due to eddy current induced phase errors. The purpose of this study was to assess the impact of phase errors in time averaged PC-MR imaging of the cerebral vasculature and explore the effects of three common correction schemes (local bias correction (LBC), local polynomial correction (LPC), and whole brain polynomial correction (WBPC)). Methods Measurements of the eddy current induced phase error from a static phantom were first obtained. In thirty healthy human subjects, the methods were then assessed in background tissue to determine if local phase offsets could be removed. Finally, the techniques were used to correct VFR measurements in cerebral vessels and compared statistically. Results In the phantom, phase error was measured to be <2.1 ml/s per pixel and the bias was reduced with the correction schemes. In background tissue, the bias was significantly reduced, by 65.6% (LBC), 58.4% (LPC) and 47.7% (WBPC) (p < 0.001 across all schemes). Correction did not lead to significantly different VFR measurements in the vessels (p = 0.997). In the vessel measurements, the three correction schemes led to flow measurement differences of -0.04 ± 0.05 ml/s, 0.09 ± 0.16 ml/s, and -0.02 ± 0.06 ml/s. Although there was an improvement in background measurements with correction, there was no statistical difference between the three correction schemes (p = 0.242 in background and p = 0.738 in vessels). Conclusions While eddy current induced phase errors can vary between hardware and sequence configurations, our results showed that the impact is small in a typical brain PC-MR protocol and does not have a significant effect on VFR measurements in cerebral vessels.
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Töger J, Kanski M, Arvidsson PM, Carlsson M, Kovács SJ, Borgquist R, Revstedt J, Söderlind G, Arheden H, Heiberg E. Vortex-ring mixing as a measure of diastolic function of the human heart: Phantom validation and initial observations in healthy volunteers and patients with heart failure. J Magn Reson Imaging 2015; 43:1386-97. [PMID: 26663607 DOI: 10.1002/jmri.25111] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2015] [Accepted: 11/17/2015] [Indexed: 11/12/2022] Open
Abstract
PURPOSE To present and validate a new method for 4D flow quantification of vortex-ring mixing during early, rapid filling of the left ventricle (LV) as a potential index of diastolic dysfunction and heart failure. MATERIALS AND METHODS 4D flow mixing measurements were validated using planar laser-induced fluorescence (PLIF) in a phantom setup. Controls (n = 23) and heart failure patients (n = 23) were studied using 4D flow at 1.5T (26 subjects) or 3T (20 subjects) to determine vortex volume (VV) and inflowing volume (VVinflow ). The volume mixed into the vortex-ring was quantified as VVmix-in = VV-VVinflow . The mixing ratio was defined as MXR = VVmix-in /VV. Furthermore, we quantified the fraction of the end-systolic volume (ESV) mixed into the vortex-ring (VVmix-in /ESV) and the fraction of the LV volume at diastasis (DV) occupied by the vortex-ring (VV/DV). RESULTS PLIF validation of MXR showed fair agreement (R(2) = 0.45, mean ± SD 1 ± 6%). MXR was higher in patients compared to controls (28 ± 11% vs. 16 ± 10%, P < 0.001), while VVmix-in /ESV and VV/DV were lower in patients (10 ± 6% vs. 18 ± 12%, P < 0.01 and 25 ± 8% vs. 50 ± 6%, P < 0.0001). CONCLUSION Vortex-ring mixing can be quantified using 4D flow. The differences in mixing parameters observed between controls and patients motivate further investigation as indices of diastolic dysfunction. J. Magn. Reson. Imaging 2016;43:1386-1397.
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Affiliation(s)
- Johannes Töger
- Department of Clinical Physiology, Lund University Hospital, Lund University, Lund, Sweden.,Department of Numerical Analysis, Centre for Mathematical Sciences, Lund University, Lund, Sweden
| | - Mikael Kanski
- Department of Clinical Physiology, Lund University Hospital, Lund University, Lund, Sweden
| | - Per M Arvidsson
- Department of Clinical Physiology, Lund University Hospital, Lund University, Lund, Sweden
| | - Marcus Carlsson
- Department of Clinical Physiology, Lund University Hospital, Lund University, Lund, Sweden
| | - Sándor J Kovács
- Department of Internal Medicine, Cardiovascular Division, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Rasmus Borgquist
- Department of Arrhythmias, Lund University Hospital, Lund, Lund University, Lund, Sweden
| | - Johan Revstedt
- Department of Energy Sciences, Faculty of Engineering, Lund University, Sweden
| | - Gustaf Söderlind
- Department of Numerical Analysis, Centre for Mathematical Sciences, Lund University, Lund, Sweden
| | - Håkan Arheden
- Department of Clinical Physiology, Lund University Hospital, Lund University, Lund, Sweden
| | - Einar Heiberg
- Department of Clinical Physiology, Lund University Hospital, Lund University, Lund, Sweden.,Department of Numerical Analysis, Centre for Mathematical Sciences, Lund University, Lund, Sweden.,Department of Biomedical Engineering, Faculty of Engineering, Lund University, Lund, Sweden
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Pennell DJ, Baksi AJ, Prasad SK, Raphael CE, Kilner PJ, Mohiaddin RH, Alpendurada F, Babu-Narayan SV, Schneider J, Firmin DN. Review of Journal of Cardiovascular Magnetic Resonance 2014. J Cardiovasc Magn Reson 2015; 17:99. [PMID: 26589839 PMCID: PMC4654908 DOI: 10.1186/s12968-015-0203-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2015] [Accepted: 11/08/2015] [Indexed: 01/19/2023] Open
Abstract
There were 102 articles published in the Journal of Cardiovascular Magnetic Resonance (JCMR) in 2014, which is a 6% decrease on the 109 articles published in 2013. The quality of the submissions continues to increase. The 2013 JCMR Impact Factor (which is published in June 2014) fell to 4.72 from 5.11 for 2012 (as published in June 2013). The 2013 impact factor means that the JCMR papers that were published in 2011 and 2012 were cited on average 4.72 times in 2013. The impact factor undergoes natural variation according to citation rates of papers in the 2 years following publication, and is significantly influenced by highly cited papers such as official reports. However, the progress of the journal's impact over the last 5 years has been impressive. Our acceptance rate is <25% and has been falling because the number of articles being submitted has been increasing. In accordance with Open-Access publishing, the JCMR articles go on-line as they are accepted with no collating of the articles into sections or special thematic issues. For this reason, the Editors have felt that it is useful once per calendar year to summarize the papers for the readership into broad areas of interest or theme, so that areas of interest can be reviewed in a single article in relation to each other and other recent JCMR articles. The papers are presented in broad themes and set in context with related literature and previously published JCMR papers to guide continuity of thought in the journal. We hope that you find the open-access system increases wider reading and citation of your papers, and that you will continue to send your quality papers to JCMR for publication.
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Affiliation(s)
- D J Pennell
- Cardiovascular Biomedical Research Unit, Royal Brompton & Harefield NHS Foundation Trust & Imperial College, Sydney Street, London, SW 3 6NP, UK.
| | - A J Baksi
- Cardiovascular Biomedical Research Unit, Royal Brompton & Harefield NHS Foundation Trust & Imperial College, Sydney Street, London, SW 3 6NP, UK.
| | - S K Prasad
- Cardiovascular Biomedical Research Unit, Royal Brompton & Harefield NHS Foundation Trust & Imperial College, Sydney Street, London, SW 3 6NP, UK.
| | - C E Raphael
- Cardiovascular Biomedical Research Unit, Royal Brompton & Harefield NHS Foundation Trust & Imperial College, Sydney Street, London, SW 3 6NP, UK.
| | - P J Kilner
- Cardiovascular Biomedical Research Unit, Royal Brompton & Harefield NHS Foundation Trust & Imperial College, Sydney Street, London, SW 3 6NP, UK.
| | - R H Mohiaddin
- Cardiovascular Biomedical Research Unit, Royal Brompton & Harefield NHS Foundation Trust & Imperial College, Sydney Street, London, SW 3 6NP, UK.
| | - F Alpendurada
- Cardiovascular Biomedical Research Unit, Royal Brompton & Harefield NHS Foundation Trust & Imperial College, Sydney Street, London, SW 3 6NP, UK.
| | - S V Babu-Narayan
- Cardiovascular Biomedical Research Unit, Royal Brompton & Harefield NHS Foundation Trust & Imperial College, Sydney Street, London, SW 3 6NP, UK.
| | - J Schneider
- Cardiovascular Biomedical Research Unit, Royal Brompton & Harefield NHS Foundation Trust & Imperial College, Sydney Street, London, SW 3 6NP, UK.
| | - D N Firmin
- Cardiovascular Biomedical Research Unit, Royal Brompton & Harefield NHS Foundation Trust & Imperial College, Sydney Street, London, SW 3 6NP, UK.
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Dyverfeldt P, Bissell M, Barker AJ, Bolger AF, Carlhäll CJ, Ebbers T, Francios CJ, Frydrychowicz A, Geiger J, Giese D, Hope MD, Kilner PJ, Kozerke S, Myerson S, Neubauer S, Wieben O, Markl M. 4D flow cardiovascular magnetic resonance consensus statement. J Cardiovasc Magn Reson 2015; 17:72. [PMID: 26257141 PMCID: PMC4530492 DOI: 10.1186/s12968-015-0174-5] [Citation(s) in RCA: 563] [Impact Index Per Article: 62.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2015] [Accepted: 07/17/2015] [Indexed: 02/07/2023] Open
Abstract
Pulsatile blood flow through the cavities of the heart and great vessels is time-varying and multidirectional. Access to all regions, phases and directions of cardiovascular flows has formerly been limited. Four-dimensional (4D) flow cardiovascular magnetic resonance (CMR) has enabled more comprehensive access to such flows, with typical spatial resolution of 1.5×1.5×1.5 - 3×3×3 mm(3), typical temporal resolution of 30-40 ms, and acquisition times in the order of 5 to 25 min. This consensus paper is the work of physicists, physicians and biomedical engineers, active in the development and implementation of 4D Flow CMR, who have repeatedly met to share experience and ideas. The paper aims to assist understanding of acquisition and analysis methods, and their potential clinical applications with a focus on the heart and greater vessels. We describe that 4D Flow CMR can be clinically advantageous because placement of a single acquisition volume is straightforward and enables flow through any plane across it to be calculated retrospectively and with good accuracy. We also specify research and development goals that have yet to be satisfactorily achieved. Derived flow parameters, generally needing further development or validation for clinical use, include measurements of wall shear stress, pressure difference, turbulent kinetic energy, and intracardiac flow components. The dependence of measurement accuracy on acquisition parameters is considered, as are the uses of different visualization strategies for appropriate representation of time-varying multidirectional flow fields. Finally, we offer suggestions for more consistent, user-friendly implementation of 4D Flow CMR acquisition and data handling with a view to multicenter studies and more widespread adoption of the approach in routine clinical investigations.
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Affiliation(s)
- Petter Dyverfeldt
- Division of Cardiovascular Medicine, Department of Medical and Health Sciences, Linköping University, Linköping, Sweden.
- Center for Medical Image Science and Visualization, Linköping University, Linköping, Sweden.
| | - Malenka Bissell
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford Centre for Clinical Magnetic Resonance Research, Oxford, UK.
| | - Alex J Barker
- Department of Radiology, Northwestern University, Chicago, USA.
| | - Ann F Bolger
- Division of Cardiovascular Medicine, Department of Medical and Health Sciences, Linköping University, Linköping, Sweden.
- Center for Medical Image Science and Visualization, Linköping University, Linköping, Sweden.
- Department of Medicine, University of California San Francisco, San Francisco, CA, United States.
| | - Carl-Johan Carlhäll
- Division of Cardiovascular Medicine, Department of Medical and Health Sciences, Linköping University, Linköping, Sweden.
- Center for Medical Image Science and Visualization, Linköping University, Linköping, Sweden.
- Department of Clinical Physiology, Department of Medical and Health Sciences, Linköping University, Linköping, Sweden.
| | - Tino Ebbers
- Division of Cardiovascular Medicine, Department of Medical and Health Sciences, Linköping University, Linköping, Sweden.
- Center for Medical Image Science and Visualization, Linköping University, Linköping, Sweden.
| | | | - Alex Frydrychowicz
- Klinik für Radiologie und Nuklearmedizin, University Hospital Schleswig-Holstein, Campus Lübeck, Lübeck, Germany.
| | - Julia Geiger
- Department of Radiology, University Children's Hospital Zurich, Zurich, Switzerland.
| | - Daniel Giese
- Department of Radiology, University Hospital of Cologne, Cologne, Germany.
| | - Michael D Hope
- Department of Radiology, University of California San Francisco, San Francisco, CA, United States.
| | - Philip J Kilner
- NIHR Cardiovascular Biomedical Research Unit, Royal Brompton and Harefield NHS Foundation Trust, National Heart and Lung Institute, Imperial College, London, UK.
| | - Sebastian Kozerke
- Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland.
| | - Saul Myerson
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford Centre for Clinical Magnetic Resonance Research, Oxford, UK.
| | - Stefan Neubauer
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford Centre for Clinical Magnetic Resonance Research, Oxford, UK.
| | - Oliver Wieben
- Department of Radiology, University of Wisconsin, Madison, Wisconsin, USA.
- Department of Medical Physics, University of Wisconsin, Madison, Wisconsin, USA.
| | - Michael Markl
- Department of Radiology, Northwestern University, Chicago, USA.
- Department of Biomedical Engineering, Northwestern University, Chicago, IL, USA.
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Nayak KS, Nielsen JF, Bernstein MA, Markl M, D Gatehouse P, M Botnar R, Saloner D, Lorenz C, Wen H, S Hu B, Epstein FH, N Oshinski J, Raman SV. Cardiovascular magnetic resonance phase contrast imaging. J Cardiovasc Magn Reson 2015; 17:71. [PMID: 26254979 PMCID: PMC4529988 DOI: 10.1186/s12968-015-0172-7] [Citation(s) in RCA: 154] [Impact Index Per Article: 17.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2015] [Accepted: 07/16/2015] [Indexed: 11/10/2022] Open
Abstract
Cardiovascular magnetic resonance (CMR) phase contrast imaging has undergone a wide range of changes with the development and availability of improved calibration procedures, visualization tools, and analysis methods. This article provides a comprehensive review of the current state-of-the-art in CMR phase contrast imaging methodology, clinical applications including summaries of past clinical performance, and emerging research and clinical applications that utilize today's latest technology.
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Affiliation(s)
- Krishna S Nayak
- Ming Hsieh Department of Electrical Engineering, University of Southern California, 3740 McClintock Ave, EEB 406, Los Angeles, California, 90089-2564, USA.
| | - Jon-Fredrik Nielsen
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA.
| | | | - Michael Markl
- Department of Radiology, Northwestern University, Chicago, IL, USA.
| | - Peter D Gatehouse
- Cardiovascular Biomedical Research Unit, Royal Brompton Hospital, London, UK.
| | - Rene M Botnar
- Cardiovascular Imaging, Imaging Sciences Division, Kings's College London, London, UK.
| | - David Saloner
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA.
| | - Christine Lorenz
- Center for Applied Medical Imaging, Siemens Corporation, Baltimore, MD, USA.
| | - Han Wen
- Imaging Physics Laboratory, National Heart Lung and Blood Institute, Bethesda, MD, USA.
| | - Bob S Hu
- Palo Alto Medical Foundation, Palo Alto, CA, USA.
| | - Frederick H Epstein
- Departments of Radiology and Biomedical Engineering, University of Virginia, Charlottesville, VA, USA.
| | - John N Oshinski
- Departments of Radiology and Biomedical Engineering, Emory University School of Medicine, Atlanta, GA, USA.
| | - Subha V Raman
- Division of Cardiovascular Medicine, The Ohio State University, Columbus, OH, USA.
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40
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Vannesjo SJ, Graedel NN, Kasper L, Gross S, Busch J, Haeberlin M, Barmet C, Pruessmann KP. Image reconstruction using a gradient impulse response model for trajectory prediction. Magn Reson Med 2015. [PMID: 26211410 DOI: 10.1002/mrm.25841] [Citation(s) in RCA: 51] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
PURPOSE Gradient imperfections remain a challenge in MRI, especially for sequences relying on long imaging readouts. This work aims to explore image reconstruction based on k-space trajectories predicted by an impulse response model of the gradient system. THEORY AND METHODS Gradient characterization was performed twice with 3 years interval on a commercial 3 Tesla (T) system. The measured gradient impulse response functions were used to predict actual k-space trajectories for single-shot echo-planar imaging (EPI), spiral and variable-speed EPI sequences. Image reconstruction based on the predicted trajectories was performed for phantom and in vivo data. Resulting images were compared with reconstructions based on concurrent field monitoring, separate trajectory measurements, and nominal trajectories. RESULTS Image reconstruction using model-based trajectories yielded high-quality images, comparable to using separate trajectory measurements. Compared with using nominal trajectories, it strongly reduced ghosting, blurring, and geometric distortion. Equivalent image quality was obtained with the recent characterization and that performed 3 years prior. CONCLUSION Model-based trajectory prediction enables high-quality image reconstruction for technically challenging sequences such as single-shot EPI and spiral imaging. It thus holds great promise for fast structural imaging and advanced neuroimaging techniques, including functional MRI, diffusion tensor imaging, and arterial spin labeling. The method can be based on a one-time system characterization as demonstrated by successful use of 3-year-old calibration data. Magn Reson Med 76:45-58, 2016. © 2015 Wiley Periodicals, Inc.
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Affiliation(s)
- S Johanna Vannesjo
- Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Zurich, Switzerland
| | - Nadine N Graedel
- Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Zurich, Switzerland
| | - Lars Kasper
- Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Zurich, Switzerland.,Translational Neuromodeling Unit, Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Zurich, Switzerland
| | - Simon Gross
- Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Zurich, Switzerland
| | - Julia Busch
- Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Zurich, Switzerland
| | - Maximilian Haeberlin
- Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Zurich, Switzerland
| | - Christoph Barmet
- Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Zurich, Switzerland.,Skope Magnetic Resonance Technologies, Zurich, Switzerland
| | - Klaas P Pruessmann
- Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Zurich, Switzerland
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41
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Wilm BJ, Nagy Z, Barmet C, Vannesjo SJ, Kasper L, Haeberlin M, Gross S, Dietrich BE, Brunner DO, Schmid T, Pruessmann KP. Diffusion MRI with concurrent magnetic field monitoring. Magn Reson Med 2015; 74:925-33. [DOI: 10.1002/mrm.25827] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2015] [Revised: 06/08/2015] [Accepted: 06/09/2015] [Indexed: 11/10/2022]
Affiliation(s)
- Bertram J. Wilm
- Institute for Biomedical Engineering; University of Zurich and ETH Zurich; Switzerland
| | - Zoltan Nagy
- Laboratory for Social and Neural Systems Research; University of Zurich; Switzerland
| | - Christoph Barmet
- Institute for Biomedical Engineering; University of Zurich and ETH Zurich; Switzerland
- Skope Magnetic Resonance Technologies LCC; Zurich Switzerland
| | - S. Johanna Vannesjo
- Institute for Biomedical Engineering; University of Zurich and ETH Zurich; Switzerland
| | - Lars Kasper
- Institute for Biomedical Engineering; University of Zurich and ETH Zurich; Switzerland
- Translational Neuromodeling Unit; Institute for Biomedical Engineering, University of Zurich and ETH Zurich; Switzerland
| | - Max Haeberlin
- Institute for Biomedical Engineering; University of Zurich and ETH Zurich; Switzerland
| | - Simon Gross
- Institute for Biomedical Engineering; University of Zurich and ETH Zurich; Switzerland
| | - Benjamin E. Dietrich
- Institute for Biomedical Engineering; University of Zurich and ETH Zurich; Switzerland
| | - David O. Brunner
- Institute for Biomedical Engineering; University of Zurich and ETH Zurich; Switzerland
| | - Thomas Schmid
- Institute for Biomedical Engineering; University of Zurich and ETH Zurich; Switzerland
| | - Klaas P. Pruessmann
- Institute for Biomedical Engineering; University of Zurich and ETH Zurich; Switzerland
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42
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Campbell-Washburn AE, Xue H, Lederman RJ, Faranesh AZ, Hansen MS. Real-time distortion correction of spiral and echo planar images using the gradient system impulse response function. Magn Reson Med 2015; 75:2278-85. [PMID: 26114951 DOI: 10.1002/mrm.25788] [Citation(s) in RCA: 49] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2015] [Revised: 04/08/2015] [Accepted: 04/30/2015] [Indexed: 11/08/2022]
Abstract
PURPOSE MRI-guided interventions demand high frame rate imaging, making fast imaging techniques such as spiral imaging and echo planar imaging (EPI) appealing. In this study, we implemented a real-time distortion correction framework to enable the use of these fast acquisitions for interventional MRI. METHODS Distortions caused by gradient waveform inaccuracies were corrected using the gradient impulse response function (GIRF), which was measured by standard equipment and saved as a calibration file on the host computer. This file was used at runtime to calculate the predicted k-space trajectories for image reconstruction. Additionally, the off-resonance reconstruction frequency was modified in real time to interactively deblur spiral images. RESULTS Real-time distortion correction for arbitrary image orientations was achieved in phantoms and healthy human volunteers. The GIRF-predicted k-space trajectories matched measured k-space trajectories closely for spiral imaging. Spiral and EPI image distortion was visibly improved using the GIRF-predicted trajectories. The GIRF calibration file showed no systematic drift in 4 months and was demonstrated to correct distortions after 30 min of continuous scanning despite gradient heating. Interactive off-resonance reconstruction was used to sharpen anatomical boundaries during continuous imaging. CONCLUSIONS This real-time distortion correction framework will enable the use of these high frame rate imaging methods for MRI-guided interventions. Magn Reson Med 75:2278-2285, 2016. © 2015 Wiley Periodicals, Inc.
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Affiliation(s)
- Adrienne E Campbell-Washburn
- Pulmonary and Cardiovascular Branch, Division of Intramural Research National Heart Lung and Blood Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Hui Xue
- Pulmonary and Cardiovascular Branch, Division of Intramural Research National Heart Lung and Blood Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Robert J Lederman
- Pulmonary and Cardiovascular Branch, Division of Intramural Research National Heart Lung and Blood Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Anthony Z Faranesh
- Pulmonary and Cardiovascular Branch, Division of Intramural Research National Heart Lung and Blood Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Michael S Hansen
- Pulmonary and Cardiovascular Branch, Division of Intramural Research National Heart Lung and Blood Institute, National Institutes of Health, Bethesda, Maryland, USA
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