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Davies-Jenkins CW, Döring A, Fasano F, Kleban E, Mueller L, Evans CJ, Afzali M, Jones DK, Ronen I, Branzoli F, Tax CMW. Practical considerations of diffusion-weighted MRS with ultra-strong diffusion gradients. Front Neurosci 2023; 17:1258408. [PMID: 38144210 PMCID: PMC10740196 DOI: 10.3389/fnins.2023.1258408] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Accepted: 11/03/2023] [Indexed: 12/26/2023] Open
Abstract
Introduction Diffusion-weighted magnetic resonance spectroscopy (DW-MRS) offers improved cellular specificity to microstructure-compared to water-based methods alone-but spatial resolution and SNR is severely reduced and slow-diffusing metabolites necessitate higher b-values to accurately characterize their diffusion properties. Ultra-strong gradients allow access to higher b-values per-unit time, higher SNR for a given b-value, and shorter diffusion times, but introduce additional challenges such as eddy-current artefacts, gradient non-uniformity, and mechanical vibrations. Methods In this work, we present initial DW-MRS data acquired on a 3T Siemens Connectom scanner equipped with ultra-strong (300 mT/m) gradients. We explore the practical issues associated with this manner of acquisition, the steps that may be taken to mitigate their impact on the data, and the potential benefits of ultra-strong gradients for DW-MRS. An in-house DW-PRESS sequence and data processing pipeline were developed to mitigate the impact of these confounds. The interaction of TE, b-value, and maximum gradient amplitude was investigated using simulations and pilot data, whereby maximum gradient amplitude was restricted. Furthermore, two DW-MRS voxels in grey and white matter were acquired using ultra-strong gradients and high b-values. Results Simulations suggest T2-based SNR gains that are experimentally confirmed. Ultra-strong gradient acquisitions exhibit similar artefact profiles to those of lower gradient amplitude, suggesting adequate performance of artefact mitigation strategies. Gradient field non-uniformity influenced ADC estimates by up to 4% when left uncorrected. ADC and Kurtosis estimates for tNAA, tCho, and tCr align with previously published literature. Discussion In conclusion, we successfully implemented acquisition and data processing strategies for ultra-strong gradient DW-MRS and results indicate that confounding effects of the strong gradient system can be ameliorated, while achieving shorter diffusion times and improved metabolite SNR.
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Affiliation(s)
- Christopher W. Davies-Jenkins
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States
- Cardiff University Brain Research Imaging Centre, Cardiff University, Cardiff, United Kingdom
| | - André Döring
- Cardiff University Brain Research Imaging Centre, Cardiff University, Cardiff, United Kingdom
- CIBM Center for Biomedical Imaging, EPFL CIBM-AIT, EPFL Lausanne, Lausanne, Switzerland
| | - Fabrizio Fasano
- Cardiff University Brain Research Imaging Centre, Cardiff University, Cardiff, United Kingdom
- Siemens Healthcare Ltd., Camberly, United Kingdom
| | - Elena Kleban
- Cardiff University Brain Research Imaging Centre, Cardiff University, Cardiff, United Kingdom
- Department of Radiology, Universität Bern, Bern, Switzerland
| | - Lars Mueller
- Cardiff University Brain Research Imaging Centre, Cardiff University, Cardiff, United Kingdom
- Leeds Institute of Cardiovascular & Metabolic Medicine, University of Leeds, Leeds, United Kingdom
| | - C. John Evans
- Cardiff University Brain Research Imaging Centre, Cardiff University, Cardiff, United Kingdom
| | - Maryam Afzali
- Cardiff University Brain Research Imaging Centre, Cardiff University, Cardiff, United Kingdom
- Leeds Institute of Cardiovascular & Metabolic Medicine, University of Leeds, Leeds, United Kingdom
| | - Derek K. Jones
- Cardiff University Brain Research Imaging Centre, Cardiff University, Cardiff, United Kingdom
| | - Itamar Ronen
- Clinical Sciences Institue, Brighton and Sussex Medical School, Brighton, United Kingdom
| | - Francesca Branzoli
- Center for NeuroImaging Research (CENIR), Paris Brain Institute (ICM), Pitié-Salpêtrière Hospital, Paris, France
- Inserm U1127, CNRS U7225, Sorbonne Universités, Paris, France
| | - Chantal M. W. Tax
- Brain Research Imaging Centre, School Physics and Astronomy, Cardiff University, Cardiff, United Kingdom
- Image Sciences Institute, University Medical Center Utrecht, Utrecht, Netherlands
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2
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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: 2] [Impact Index Per Article: 1.0] [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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3
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Stimm J, Guenthner C, Kozerke S, Stoeck CT. Comparison of interpolation methods of predominant cardiomyocyte orientation from in vivo and ex vivo cardiac diffusion tensor imaging data. NMR IN BIOMEDICINE 2022; 35:e4667. [PMID: 34964179 PMCID: PMC9285076 DOI: 10.1002/nbm.4667] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/03/2021] [Revised: 11/25/2021] [Accepted: 11/26/2021] [Indexed: 06/14/2023]
Abstract
Cardiac electrophysiology and cardiac mechanics both depend on the average cardiomyocyte long-axis orientation. In the realm of personalized medicine, knowledge of the patient-specific changes in cardiac microstructure plays a crucial role. Patient-specific computational modelling has emerged as a tool to better understand disease progression. In vivo cardiac diffusion tensor imaging (cDTI) is a vital tool to non-destructively measure the average cardiomyocyte long-axis orientation in the heart. However, cDTI suffers from long scan times, rendering volumetric, high-resolution acquisitions challenging. Consequently, interpolation techniques are needed to populate bio-mechanical models with patient-specific average cardiomyocyte long-axis orientations. In this work, we compare five interpolation techniques applied to in vivo and ex vivo porcine input data. We compare two tensor interpolation approaches, one rule-based approximation, and two data-driven, low-rank models. We demonstrate the advantage of tensor interpolation techniques, resulting in lower interpolation errors than do low-rank models and rule-based methods adapted to cDTI data. In an ex vivo comparison, we study the influence of three imaging parameters that can be traded off against acquisition time: in-plane resolution, signal to noise ratio, and number of acquired short-axis imaging slices.
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Affiliation(s)
- Johanna Stimm
- Institute for Biomedical EngineeringUniversity and ETH ZurichZurichSwitzerland
| | - Christian Guenthner
- Institute for Biomedical EngineeringUniversity and ETH ZurichZurichSwitzerland
| | - Sebastian Kozerke
- Institute for Biomedical EngineeringUniversity and ETH ZurichZurichSwitzerland
| | - Christian T. Stoeck
- Institute for Biomedical EngineeringUniversity and ETH ZurichZurichSwitzerland
- Division of Surgical ResearchUniversity Hospital ZurichUniversity ZurichSwitzerland
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4
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Valsamis JJ, Dubovan PI, Baron CA. Characterization and correction of time-varying eddy currents for diffusion MRI. Magn Reson Med 2021; 87:2209-2223. [PMID: 34894640 DOI: 10.1002/mrm.29124] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2021] [Revised: 11/26/2021] [Accepted: 11/29/2021] [Indexed: 12/16/2022]
Abstract
PURPOSE To develop and test a method for reducing artifacts due to time-varying eddy currents in oscillating gradient spin-echo (OGSE) diffusion images. METHODS An in-house algorithm (TVEDDY), that for the first time retrospectively models eddy current decay, was tested on pulsed gradient spin echo and OGSE brain images acquired at 7 T. Image pairs were acquired using opposite polarity diffusion gradients. A three-parameter exponential decay model (two amplitudes and a time constant) was used to characterize and correct eddy current distortions by minimizing the intensity difference between image pairs. Correction performance was compared with conventional correction methods by evaluating the mean squared error (MSE) between diffusion-weighted images acquired with opposite polarity diffusion gradients. As a ground-truth comparison, images were corrected using field dynamics up to third order in space, measured using a field monitoring system. RESULTS Time-varying eddy currents were observed for OGSE, which introduced blurring that was not reduced using the traditional approach but was diminished considerably with TVEDDY and field monitoring-informed model-based reconstruction. No MSE difference was observed between the conventional approach and TVEDDY for pulsed gradient spin echo, but for OGSE TVEDDY resulted in significantly lower MSE than the conventional approach. The field-monitoring reconstruction had the lowest MSE for both pulsed gradient spin echo and OGSE. CONCLUSION This work establishes that it is possible to estimate time-varying eddy currents from the actual diffusion data, which provides substantial image-quality improvements for gradient-intensive diffusion MRI acquisitions like OGSE.
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Affiliation(s)
- Jake J Valsamis
- Department of Medical Biophysics, Schulich School of Medicine & Dentistry, Western University, London, Ontario, Canada.,Center for Functional and Metabolic Mapping, Robarts Research Institute, London, Ontario, Canada
| | - Paul I Dubovan
- Department of Medical Biophysics, Schulich School of Medicine & Dentistry, Western University, London, Ontario, Canada.,Center for Functional and Metabolic Mapping, Robarts Research Institute, London, Ontario, Canada
| | - Corey A Baron
- Department of Medical Biophysics, Schulich School of Medicine & Dentistry, Western University, London, Ontario, Canada.,Center for Functional and Metabolic Mapping, Robarts Research Institute, London, Ontario, Canada
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5
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Koirala N, Kleinman D, Perdue MV, Su X, Villa M, Grigorenko EL, Landi N. Widespread effects of dMRI data quality on diffusion measures in children. Hum Brain Mapp 2021; 43:1326-1341. [PMID: 34799957 PMCID: PMC8837592 DOI: 10.1002/hbm.25724] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2021] [Revised: 11/02/2021] [Accepted: 11/11/2021] [Indexed: 12/12/2022] Open
Abstract
Diffusion magnetic resonance imaging (dMRI) datasets are susceptible to several confounding factors related to data quality, which is especially true in studies involving young children. With the recent trend of large‐scale multicenter studies, it is more critical to be aware of the varied impacts of data quality on measures of interest. Here, we investigated data quality and its effect on different diffusion measures using a multicenter dataset. dMRI data were obtained from 691 participants (5–17 years of age) from six different centers. Six data quality metrics—contrast to noise ratio, outlier slices, and motion (absolute, relative, translation, and rotational)—and four diffusion measures—fractional anisotropy, mean diffusivity, tract density, and length—were computed for each of 36 major fiber tracts for all participants. The results indicated that four out of six data quality metrics (all except absolute and translation motion) differed significantly between centers. Associations between these data quality metrics and the diffusion measures differed significantly across the tracts and centers. Moreover, these effects remained significant after applying recently proposed harmonization algorithms that purport to remove unwanted between‐site variation in diffusion data. These results demonstrate the widespread impact of dMRI data quality on diffusion measures. These tracts and measures have been routinely associated with individual differences as well as group‐wide differences between neurotypical populations and individuals with neurological or developmental disorders. Accordingly, for analyses of individual differences or group effects (particularly in multisite dataset), we encourage the inclusion of data quality metrics in dMRI analysis.
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Affiliation(s)
| | | | - Meaghan V Perdue
- Haskins Laboratories, New Haven, Connecticut, USA.,Department of Psychological Sciences, University of Connecticut, Connecticut, USA
| | - Xing Su
- Haskins Laboratories, New Haven, Connecticut, USA
| | - Martina Villa
- Haskins Laboratories, New Haven, Connecticut, USA.,Department of Psychological Sciences, University of Connecticut, Connecticut, USA
| | - Elena L Grigorenko
- Haskins Laboratories, New Haven, Connecticut, USA.,Department of Psychology, University of Houston, Houston, Texas, USA
| | - Nicole Landi
- Haskins Laboratories, New Haven, Connecticut, USA.,Department of Psychological Sciences, University of Connecticut, Connecticut, USA
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Correcting Susceptibility Artifacts of MRI Sensors in Brain Scanning: A 3D Anatomy-Guided Deep Learning Approach. SENSORS 2021; 21:s21072314. [PMID: 33810289 PMCID: PMC8037307 DOI: 10.3390/s21072314] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/08/2021] [Revised: 03/22/2021] [Accepted: 03/23/2021] [Indexed: 01/02/2023]
Abstract
Echo planar imaging (EPI), a fast magnetic resonance imaging technique, is a powerful tool in functional neuroimaging studies. However, susceptibility artifacts, which cause misinterpretations of brain functions, are unavoidable distortions in EPI. This paper proposes an end-to-end deep learning framework, named TS-Net, for susceptibility artifact correction (SAC) in a pair of 3D EPI images with reversed phase-encoding directions. The proposed TS-Net comprises a deep convolutional network to predict a displacement field in three dimensions to overcome the limitation of existing methods, which only estimate the displacement field along the dominant-distortion direction. In the training phase, anatomical T1-weighted images are leveraged to regularize the correction, but they are not required during the inference phase to make TS-Net more flexible for general use. The experimental results show that TS-Net achieves favorable accuracy and speed trade-off when compared with the state-of-the-art SAC methods, i.e., TOPUP, TISAC, and S-Net. The fast inference speed (less than a second) of TS-Net makes real-time SAC during EPI image acquisition feasible and accelerates the medical image-processing pipelines.
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7
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Fair MJ, Liao C, Manhard MK, Setsompop K. Diffusion-PEPTIDE: Distortion- and blurring-free diffusion imaging with self-navigated motion-correction and relaxometry capabilities. Magn Reson Med 2020; 85:2417-2433. [PMID: 33314281 DOI: 10.1002/mrm.28579] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2020] [Revised: 10/11/2020] [Accepted: 10/12/2020] [Indexed: 12/13/2022]
Abstract
PURPOSE To implement the time-resolved relaxometry PEPTIDE technique into a diffusion acquisition to provide self-navigated, distortion- and blurring-free diffusion imaging that is robust to motion, while simultaneously providing T2 and T 2 ∗ mapping. THEORY AND METHODS The PEPTIDE readout was implemented into a spin-echo diffusion acquisition, enabling reconstruction of a time-series of T2 - and T 2 ∗ -weighted images, free from conventional echo planar imaging (EPI) distortion and blurring, for each diffusion-encoding. Robustness of PEPTIDE to motion and shot-to-shot phase variation was examined through a deliberate motion-corrupted diffusion experiment. Two diffusion-relaxometry in vivo brain protocols were also examined: (1)1 × 1 × 3 mm3 across 32 diffusion directions in 20 min, (2)1.5 × 1.5 × 3.0 mm3 across 6 diffusion-weighted images in 3.4 min. T2 , T 2 ∗ , and diffusion parameter maps were calculated from these data. As initial exploration of the rich diffusion-relaxometry data content for use in multi-compartment modeling, PEPTIDE data were acquired of a gadolinium-doped asparagus phantom. These datasets contained two compartments with different relaxation parameters and different diffusion orientation properties, and T2 relaxation variations across these diffusion directions were explored. RESULTS Diffusion-PEPTIDE showed the capability to provide high quality diffusion images and T2 and T 2 ∗ maps from both protocols. The reconstructions were distortion-free, avoided potential resolution losses exceeding 100% in equivalent EPI acquisitions, and showed tolerance to nearly 30° of rotational motion. Expected variation in T2 values as a function of diffusion direction was observed in the two-compartment asparagus phantom (P < .01), demonstrating potential to explore diffusion-PEPTIDE data for multi-compartment modeling. CONCLUSIONS Diffusion-PEPTIDE provides highly robust diffusion and relaxometry data and offers potential for future applications in diffusion-relaxometry multi-compartment modeling.
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Affiliation(s)
- Merlin J Fair
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA.,Department of Radiology, Harvard Medical School, Boston, Massachusetts, USA
| | - Congyu Liao
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA.,Department of Radiology, Harvard Medical School, Boston, Massachusetts, USA
| | - Mary Kate Manhard
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA.,Department of Radiology, Harvard Medical School, Boston, Massachusetts, USA
| | - Kawin Setsompop
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA.,Department of Radiology, Harvard Medical School, Boston, Massachusetts, USA.,Harvard-MIT Health Sciences and Technology, MIT, Cambridge, Massachusetts, USA
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Kooreman ES, van Houdt PJ, Keesman R, Pos FJ, van Pelt VWJ, Nowee ME, Wetscherek A, Tijssen RHN, Philippens MEP, Thorwarth D, Wang J, Shukla-Dave A, Hall WA, Paulson ES, van der Heide UA. ADC measurements on the Unity MR-linac - A recommendation on behalf of the Elekta Unity MR-linac consortium. Radiother Oncol 2020; 153:106-113. [PMID: 33017604 PMCID: PMC8327388 DOI: 10.1016/j.radonc.2020.09.046] [Citation(s) in RCA: 50] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2020] [Revised: 09/23/2020] [Accepted: 09/23/2020] [Indexed: 01/23/2023]
Abstract
BACKGROUND AND PURPOSE Diffusion-weighted imaging (DWI) for treatment response monitoring is feasible on hybrid magnetic resonance linear accelerator (MR-linac) systems. The MRI scanner of the Elekta Unity system has an adjusted design compared to diagnostic scanners. We investigated its impact on measuring the DWI-derived apparent diffusion coefficient (ADC) regarding three aspects: the choice of b-values, the spatial variation of the ADC, and scanning during radiation treatment. The aim of this study is to give recommendations for accurate ADC measurements on Unity systems. MATERIALS AND METHODS Signal-to-noise ratio (SNR) measurements with increasing b-values were done to determine the highest bvalue that can be measured reliably. The spatial variation of the ADC was assessed on six Unity systems with a cylindrical phantom of 40 cm diameter. The influence of gantry rotation and irradiation was investigated by acquiring DWI images before and during treatment of 11 prostate cancer patients. RESULTS On the Unity system, a maximum b-value of 500 s/mm2 should be used for ADC quantification, as a trade-off between SNR and diffusion weighting. Accurate ADC values were obtained within 7 cm from the iso-center, while outside this region ADC values deviated more than 5%. The ADC was not influenced by the rotating linac or irradiation during treatment. CONCLUSION We provide Unity system specific recommendations for measuring the ADC. This will increase the consistency of ADC values acquired in different centers on the Unity system, enabling large cohort studies for biomarker discovery and treatment response monitoring.
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Affiliation(s)
- Ernst S Kooreman
- Department of Radiation Oncology, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Petra J van Houdt
- Department of Radiation Oncology, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Rick Keesman
- Department of Radiation Oncology, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Floris J Pos
- Department of Radiation Oncology, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Vivian W J van Pelt
- Department of Radiation Oncology, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Marlies E Nowee
- Department of Radiation Oncology, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Andreas Wetscherek
- Joint Department of Physics, The Institute of Cancer Research, and The Royal Marsden NHS Foundation Trust, London, United Kingdom
| | - Rob H N Tijssen
- Department of Radiotherapy, University Medical Center Utrecht, The Netherlands
| | | | - Daniela Thorwarth
- Section for Biomedical Physics, Department of Radiation Oncology, University of Tübingen, Germany
| | - Jihong Wang
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, United States
| | - Amita Shukla-Dave
- Departments of Medical Physics and Radiology, Memorial Sloan Kettering Cancer Center, New York, United States
| | - William A Hall
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, United States
| | - Eric S Paulson
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, United States
| | - Uulke A van der Heide
- Department of Radiation Oncology, The Netherlands Cancer Institute, Amsterdam, The Netherlands.
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Kleban E, Tax CMW, Rudrapatna US, Jones DK, Bowtell R. Strong diffusion gradients allow the separation of intra- and extra-axonal gradient-echo signals in the human brain. Neuroimage 2020; 217:116793. [PMID: 32335263 PMCID: PMC7613126 DOI: 10.1016/j.neuroimage.2020.116793] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2019] [Revised: 02/28/2020] [Accepted: 03/19/2020] [Indexed: 12/12/2022] Open
Abstract
The quantification of brain white matter properties is a key area of application of Magnetic Resonance Imaging (MRI), with much effort focused on using MR techniques to quantify tissue microstructure. While diffusion MRI probes white matter (WM) microstructure by characterising the sensitivity of Brownian motion of water molecules to anisotropic structures, susceptibility-based techniques probe the tissue microstructure by observing the effect of interaction between the tissue and the magnetic field. Here, we unify these two complementary approaches by combining ultra-strong (300 mT/m) gradients with a novel Diffusion-Filtered Asymmetric Spin Echo (D-FASE) technique. Using D-FASE we can separately assess the evolution of the intra- and extra-axonal signals under the action of susceptibility effects, revealing differences in the behaviour in different fibre tracts. We observed that the effective relaxation rate of the ASE signal in the corpus callosum decreases with increasing b-value in all subjects (from 17.1 ± 0.7 s−1 at b = 0 s/mm2 to 14.6 ± 0.7 s−1 at b = 4800 s/mm2), while this dependence on b in the corticospinal tract is less pronounced (from 12.0± 1.1 s−1 at b = 0s/mm2 to 10.7 ± 0.5 s−1 at b = 4800 s/mm2). Voxelwise analysis of the signal evolution with respect to b-factor and acquisition delay using a microscopic model demonstrated differences in gradient echo signal evolution between the intra- and extra-axonal pools.
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Affiliation(s)
- Elena Kleban
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Maindy Road, Cardiff, CF24 4HQ, UK.
| | - Chantal M W Tax
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Maindy Road, Cardiff, CF24 4HQ, UK
| | - Umesh S Rudrapatna
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Maindy Road, Cardiff, CF24 4HQ, UK
| | - Derek K Jones
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Maindy Road, Cardiff, CF24 4HQ, UK; Mary MacKillop Institute for Health Research, Faculty of Health Sciences, Australian Catholic University, Melbourne, Victoria, 3065, Australia
| | - Richard Bowtell
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, NG7 2RD, UK
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10
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Stoeck CT, von Deuster C, van Gorkum RJH, Kozerke S. Motion and eddy current-induced signal dephasing in in vivo cardiac DTI. Magn Reson Med 2019; 84:277-288. [PMID: 31868257 DOI: 10.1002/mrm.28132] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2019] [Revised: 11/11/2019] [Accepted: 11/25/2019] [Indexed: 12/14/2022]
Abstract
PURPOSE To address motion in cardiac DWI, stimulated-echo acquisition mode (STEAM) and second-order motion-compensated spin-echo (SE) sequences have been proposed. Despite applying motion-compensation strategies, residual motion can cause misleading signal attenuation. The purpose of this study is to estimate the motion-induced error in both sequences by analysis of image phase. METHODS Diffusion-weighted motion-compensated SE sequences and STEAM imaging was applied in vivo with diffusion encoding along 3 orthogonal directions. A b-value range of 100 to 600 s/mm2 and trigger delays of 25%, 50%, and 75% of end systole and middiastole were used. Eddy-current contributions were obtained from phantom measurements. After computation of motion-induced phase maps, the amount of signal dephasing was computed from phase gradients, and the resulting errors in diffusion tensor parameters were calculated. RESULTS Motion-induced dephasing from the STEAM sequence showed less dependency on the b-value and no dependency on the heart phase, whereas SE imaging performed best at 75% end systole followed by 50% end systole and middiastole. For a typical experimental setting, errors of 3.3%/3.0% mean diffusivity, 4.9%/4.8% fractional anisotropy, 2.9º/3.2º helix angulation, 0.8º/0.7º transverse angulation, and 9.9º/10.0º sheet angulation (SE/STEAM) were calculated. CONCLUSION Image phase contains valuable information regarding uncompensated motion and eddy currents in cardiac DTI. Although the trigger delay window for SE is narrower compared with the STEAM-based approach, imaging in both systole and diastole is feasible and both sequences perform similarly if the trigger delays are selected carefully with SE.
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Affiliation(s)
- Christian T Stoeck
- 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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11
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Tournier JD. Diffusion MRI in the brain - Theory and concepts. PROGRESS IN NUCLEAR MAGNETIC RESONANCE SPECTROSCOPY 2019; 112-113:1-16. [PMID: 31481155 DOI: 10.1016/j.pnmrs.2019.03.001] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/18/2019] [Revised: 03/05/2019] [Accepted: 03/07/2019] [Indexed: 06/10/2023]
Abstract
Over the past two decades, diffusion MRI has become an essential tool in neuroimaging investigations. This is due to its sensitivity to the motion of water molecules as they diffuse through the microstructural environment, allowing diffusion MRI to be used as a 'probe' of tissue microstructure. Furthermore, this sensitivity is strongly direction-dependent, notably in brain white matter, due to the alignment of structures that restrict or hinder the motion of water molecules, notably axonal membranes. This provides a means of inferring the orientation of fibres in vivo, and by use of appropriate fibre-tracking algorithms, of delineating the path of white matter tracts in the brain. The ability to perform so-called tractography in humans in vivo non-invasively is unique to diffusion MRI, and is now used in applications such as neurosurgery planning and more broadly within investigations of brain connectomics. This review describes the theory and concepts of diffusion MRI and describes its most important areas of application in the brain, with a strong focus on tractography.
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Affiliation(s)
- J-Donald Tournier
- Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, King's Health Partners, St. Thomas' Hospital, London SE1 7EH, UK; Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, King's Health Partners, St. Thomas' Hospital, London SE1 7EH, UK.
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12
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Johnson EB, Gregory S. Huntington's disease: Brain imaging in Huntington's disease. PROGRESS IN MOLECULAR BIOLOGY AND TRANSLATIONAL SCIENCE 2019; 165:321-369. [PMID: 31481169 DOI: 10.1016/bs.pmbts.2019.04.004] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Huntington's disease (HD) gene-carriers show prominent neuronal loss by end-stage disease, and the use of magnetic resonance imaging (MRI) has been increasingly used to quantify brain changes during earlier stages of the disease. MRI offers an in vivo method of measuring structural and functional brain change. The images collected via MRI are processed to measure different anatomical features, such as brain volume, macro- and microstructural changes within white matter and functional brain activity. Structural imaging has demonstrated significant volume loss across multiple white and gray matter regions in HD, particularly within subcortical structures. There also appears to be increasing disorganization of white matter tracts and between-region connectivity with increasing disease progression. Finally, functional changes are thought to represent changes in brain activity underlying compensatory mechanisms in HD. This chapter will provide an overview of the principles of MRI and practicalities associated with using MRI in HD studies, and summarize findings from MRI studies investigating brain structure and function in HD.
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Affiliation(s)
- Eileanoir B Johnson
- Huntington's Disease Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Sarah Gregory
- Huntington's Disease Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom.
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13
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Holdsworth SJ, O'Halloran R, Setsompop K. The quest for high spatial resolution diffusion-weighted imaging of the human brain in vivo. NMR IN BIOMEDICINE 2019; 32:e4056. [PMID: 30730591 DOI: 10.1002/nbm.4056] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/09/2018] [Revised: 09/11/2018] [Accepted: 11/08/2018] [Indexed: 06/09/2023]
Abstract
Diffusion-weighted imaging, a contrast unique to MRI, is used for assessment of tissue microstructure in vivo. However, this exquisite sensitivity to finer scales far above imaging resolution comes at the cost of vulnerability to errors caused by sources of motion other than diffusion motion. Addressing the issue of motion has traditionally limited diffusion-weighted imaging to a few acquisition techniques and, as a consequence, to poorer spatial resolution than other MRI applications. Advances in MRI imaging methodology have allowed diffusion-weighted MRI to push to ever higher spatial resolution. In this review we focus on the pulse sequences and associated techniques under development that have pushed the limits of image quality and spatial resolution in diffusion-weighted MRI.
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Affiliation(s)
- Samantha J Holdsworth
- Department of Anatomy Medical Imaging & Centre for Brain Research, University of Auckland, Auckland, New Zealand
| | | | - Kawin Setsompop
- Harvard Medical School, Massachusetts General Hospital, Boston, MA, USA
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14
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Optimization of diffusion-weighted single-refocused spin-echo EPI by reducing eddy-current artifacts and shortening the echo time. MAGNETIC RESONANCE MATERIALS IN PHYSICS BIOLOGY AND MEDICINE 2018; 31:585-597. [DOI: 10.1007/s10334-018-0684-x] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/17/2017] [Revised: 03/05/2018] [Accepted: 03/19/2018] [Indexed: 12/24/2022]
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15
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Zhang Q, Coolen BF, Versluis MJ, Strijkers GJ, Nederveen AJ. Diffusion-prepared stimulated-echo turbo spin echo (DPsti-TSE): An eddy current-insensitive sequence for three-dimensional high-resolution and undistorted diffusion-weighted imaging. NMR IN BIOMEDICINE 2017; 30:e3719. [PMID: 28295736 DOI: 10.1002/nbm.3719] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/07/2016] [Revised: 01/10/2017] [Accepted: 02/04/2017] [Indexed: 06/06/2023]
Abstract
In this study, we present a new three-dimensional (3D), diffusion-prepared turbo spin echo sequence based on a stimulated-echo read-out (DPsti-TSE) enabling high-resolution and undistorted diffusion-weighted imaging (DWI). A dephasing gradient in the diffusion preparation module and rephasing gradients in the turbo spin echo module create stimulated echoes, which prevent signal loss caused by eddy currents. Near to perfect agreement of apparent diffusion coefficient (ADC) values between DPsti-TSE and diffusion-weighted echo planar imaging (DW-EPI) was demonstrated in both phantom transient signal experiments and phantom imaging experiments. High-resolution and undistorted DPsti-TSE was demonstrated in vivo in prostate and carotid vessel wall. 3D whole-prostate DWI was achieved with four b values in only 6 min. Undistorted ADC maps of the prostate peripheral zone were obtained at low and high imaging resolutions with no change in mean ADC values [(1.60 ± 0.10) × 10-3 versus (1.60 ± 0.02) × 10-3 mm2 /s]. High-resolution 3D DWI of the carotid vessel wall was achieved in 12 min, with consistent ADC values [(1.40 ± 0.23) × 10-3 mm2 /s] across different subjects, as well as slice locations through the imaging volume. This study shows that DPsti-TSE can serve as a robust 3D diffusion-weighted sequence and is an attractive alternative to the traditional two-dimensional DW-EPI approaches.
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Affiliation(s)
- Qinwei Zhang
- Department of Radiology, Academic Medical Center, Amsterdam, the Netherlands
| | - Bram F Coolen
- Department of Biomedical Engineering and Physics, Academic Medical Center, Amsterdam, the Netherlands
| | | | - Gustav J Strijkers
- Department of Biomedical Engineering and Physics, Academic Medical Center, Amsterdam, the Netherlands
| | - Aart J Nederveen
- Department of Radiology, Academic Medical Center, Amsterdam, the Netherlands
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16
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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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17
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Hope TR, White NS, Kuperman J, Chao Y, Yamin G, Bartch H, Schenker-Ahmed NM, Rakow-Penner R, Bussell R, Nomura N, Kesari S, Bjørnerud A, Dale AM. Demonstration of Non-Gaussian Restricted Diffusion in Tumor Cells Using Diffusion Time-Dependent Diffusion-Weighted Magnetic Resonance Imaging Contrast. Front Oncol 2016; 6:179. [PMID: 27532028 PMCID: PMC4970563 DOI: 10.3389/fonc.2016.00179] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2015] [Accepted: 07/19/2016] [Indexed: 12/31/2022] Open
Abstract
The diffusion-weighted magnetic resonance imaging (DWI) technique enables quantification of water mobility for probing microstructural properties of biological tissue and has become an effective tool for collecting information about the underlying pathology of cancerous tissue. Measurements using multiple b-values have indicated biexponential signal attenuation, ascribed to “fast” (high ADC) and “slow” (low ADC) diffusion components. In this empirical study, we investigate the properties of the diffusion time (Δ)-dependent components of the diffusion-weighted (DW) signal in a constant b-value experiment. A xenograft gliobastoma mouse was imaged using Δ = 11 ms, 20 ms, 40 ms, 60 ms, and b = 500–4000 s/mm2 in intervals of 500 s/mm2. Data were corrected for EPI distortions, and the Δ-dependence on the DW-signal was measured within three regions of interest [intermediate- and high-density tumor regions and normal-appearing brain (NAB) tissue regions]. In this study, we verify the assumption that the slow decaying component of the DW-signal is non-Gaussian and dependent on Δ, consistent with restricted diffusion of the intracellular space. As the DW-signal is a function of Δ and is specific to restricted diffusion, manipulating Δ at constant b-value (cb) provides a complementary and direct approach for separating the restricted from the hindered diffusion component. We found that Δ-dependence is specific to the tumor tissue signal. Based on an extended biexponential model, we verified the interpretation of the diffusion time-dependent contrast and successfully estimated the intracellular restricted ADC, signal volume fraction, and cell size within each ROI.
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Affiliation(s)
- Tuva R Hope
- The Interventional Centre, Oslo University Hospital, Oslo, Norway; Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, Trondheim, Norway
| | - Nathan S White
- Department of Radiology, University of California San Diego , La Jolla, CA , USA
| | - Joshua Kuperman
- Department of Radiology, University of California San Diego , La Jolla, CA , USA
| | - Ying Chao
- Department of Neurosciences, University of California San Diego , La Jolla, CA , USA
| | - Ghiam Yamin
- Department of Radiology, University of California San Diego , La Jolla, CA , USA
| | - Hauke Bartch
- Department of Radiology, University of California San Diego , La Jolla, CA , USA
| | | | - Rebecca Rakow-Penner
- Department of Radiology, University of California San Diego , La Jolla, CA , USA
| | - Robert Bussell
- Department of Radiology, University of California San Diego , La Jolla, CA , USA
| | - Natsuko Nomura
- Department of Neurosciences, University of California San Diego , La Jolla, CA , USA
| | - Santosh Kesari
- Department of Neurosciences, University of California San Diego , La Jolla, CA , USA
| | - Atle Bjørnerud
- The Interventional Centre, Oslo University Hospital, Oslo, Norway; Department of Physics, University of Oslo, Oslo, Norway
| | - Anders M Dale
- Department of Radiology, University of California San Diego, La Jolla, CA, USA; Department of Neurosciences, University of California San Diego, La Jolla, CA, USA
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18
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Andersson JLR, Sotiropoulos SN. An integrated approach to correction for off-resonance effects and subject movement in diffusion MR imaging. Neuroimage 2016; 125:1063-1078. [PMID: 26481672 PMCID: PMC4692656 DOI: 10.1016/j.neuroimage.2015.10.019] [Citation(s) in RCA: 1997] [Impact Index Per Article: 249.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2015] [Revised: 09/23/2015] [Accepted: 10/09/2015] [Indexed: 01/02/2023] Open
Abstract
In this paper we describe a method for retrospective estimation and correction of eddy current (EC)-induced distortions and subject movement in diffusion imaging. In addition a susceptibility-induced field can be supplied and will be incorporated into the calculations in a way that accurately reflects that the two fields (susceptibility- and EC-induced) behave differently in the presence of subject movement. The method is based on registering the individual volumes to a model free prediction of what each volume should look like, thereby enabling its use on high b-value data where the contrast is vastly different in different volumes. In addition we show that the linear EC-model commonly used is insufficient for the data used in the present paper (high spatial and angular resolution data acquired with Stejskal-Tanner gradients on a 3T Siemens Verio, a 3T Siemens Connectome Skyra or a 7T Siemens Magnetome scanner) and that a higher order model performs significantly better. The method is already in extensive practical use and is used by four major projects (the WU-UMinn HCP, the MGH HCP, the UK Biobank and the Whitehall studies) to correct for distortions and subject movement.
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19
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Mueller L, Wetscherek A, Kuder TA, Laun FB. Eddy current compensated double diffusion encoded (DDE) MRI. Magn Reson Med 2015; 77:328-335. [PMID: 26715361 DOI: 10.1002/mrm.26092] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2015] [Revised: 11/06/2015] [Accepted: 11/24/2015] [Indexed: 11/07/2022]
Abstract
PURPOSE Eddy currents might lead to image distortions in diffusion-weighted echo planar imaging. A method is proposed to reduce their effects on double diffusion encoding (DDE) MRI experiments and the thereby derived microscopic fractional anisotropy (μFA). METHODS The twice-refocused spin echo scheme was adapted for DDE measurements. To assess the effect of individual diffusion encodings on the image distortions, measurements of a grid of plastic rods in water were performed. The effect of eddy current compensation on μFA measurements was evaluated in the brains of six healthy volunteers. RESULTS The use of an eddy current compensation reduced the signal variation. As expected, the distortions caused by the second encoding were larger than those of the first encoding, entailing a stronger need to compensate for them. For an optimal result, however, both encodings had to be compensated. The artifact reduction strongly improved the measurement of the μFA in ventricles and gray matter by reducing the overestimation. An effect of the compensation on absolute μFA values in white matter was not observed. CONCLUSION It is advisable to compensate both encodings in DDE measurements for eddy currents. Magn Reson Med 77:328-335, 2017. © 2015 Wiley Periodicals, Inc.
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Affiliation(s)
- Lars Mueller
- Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Andreas Wetscherek
- Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Tristan Anselm Kuder
- Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Frederik Bernd Laun
- Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
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20
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Donati F, Figueroa CA, Smith NP, Lamata P, Nordsletten DA. Non-invasive pressure difference estimation from PC-MRI using the work-energy equation. Med Image Anal 2015; 26:159-72. [PMID: 26409245 PMCID: PMC4686008 DOI: 10.1016/j.media.2015.08.012] [Citation(s) in RCA: 38] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2015] [Revised: 08/21/2015] [Accepted: 08/31/2015] [Indexed: 01/15/2023]
Abstract
Pressure difference is an accepted clinical biomarker for cardiovascular disease conditions such as aortic coarctation. Currently, measurements of pressure differences in the clinic rely on invasive techniques (catheterization), prompting development of non-invasive estimates based on blood flow. In this work, we propose a non-invasive estimation procedure deriving pressure difference from the work-energy equation for a Newtonian fluid. Spatial and temporal convergence is demonstrated on in silico Phase Contrast Magnetic Resonance Image (PC-MRI) phantoms with steady and transient flow fields. The method is also tested on an image dataset generated in silico from a 3D patient-specific Computational Fluid Dynamics (CFD) simulation and finally evaluated on a cohort of 9 subjects. The performance is compared to existing approaches based on steady and unsteady Bernoulli formulations as well as the pressure Poisson equation. The new technique shows good accuracy, robustness to noise, and robustness to the image segmentation process, illustrating the potential of this approach for non-invasive pressure difference estimation.
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Affiliation(s)
- Fabrizio Donati
- King's College London, Department of Biomedical Engineering and Imaging Sciences, St. Thomas' Hospital, 4th floor Lambeth Wing, The Rayne Institute, London SE1 7EH, United Kingdom.
| | - C Alberto Figueroa
- University of Michigan, North Campus Research Complex, 2800 Plymouth Road, Ann Arbor, MI 48105, United States.
| | - Nicolas P Smith
- King's College London, Department of Biomedical Engineering and Imaging Sciences, St. Thomas' Hospital, 4th floor Lambeth Wing, The Rayne Institute, London SE1 7EH, United Kingdom; University of Auckland, Engineering School Block 1, Level 5, 20 Symonds St, Auckland 101, New Zealand.
| | - Pablo Lamata
- King's College London, Department of Biomedical Engineering and Imaging Sciences, St. Thomas' Hospital, 4th floor Lambeth Wing, The Rayne Institute, London SE1 7EH, United Kingdom; University of Oxford, Department of Computer Science, Wolfson Building, Parks Road, Oxford OX1 3QD, United Kingdom.
| | - David A Nordsletten
- King's College London, Department of Biomedical Engineering and Imaging Sciences, St. Thomas' Hospital, 4th floor Lambeth Wing, The Rayne Institute, London SE1 7EH, United Kingdom.
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21
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von Deuster C, Stoeck CT, Genet M, Atkinson D, Kozerke S. Spin echo versus stimulated echo diffusion tensor imaging of the in vivo human heart. Magn Reson Med 2015; 76:862-72. [PMID: 26445426 PMCID: PMC4989478 DOI: 10.1002/mrm.25998] [Citation(s) in RCA: 48] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2015] [Revised: 07/29/2015] [Accepted: 09/01/2015] [Indexed: 12/13/2022]
Abstract
Purpose To compare signal‐to‐noise ratio (SNR) efficiency and diffusion tensor metrics of cardiac diffusion tensor mapping using acceleration‐compensated spin‐echo (SE) and stimulated echo acquisition mode (STEAM) imaging. Methods Diffusion weighted SE and STEAM sequences were implemented on a clinical 1.5 Tesla MR system. The SNR efficiency of SE and STEAM was measured (b = 50–450 s/mm2) in isotropic agar, anisotropic diffusion phantoms and the in vivo human heart. Diffusion tensor analysis was performed on mean diffusivity, fractional anisotropy, helix and transverse angles. Results In the isotropic phantom, the ratio of SNR efficiency for SE versus STEAM, SNRt(SE/STEAM), was 2.84 ± 0.08 for all tested b‐values. In the anisotropic diffusion phantom the ratio decreased from 2.75 ± 0.05 to 2.20 ± 0.13 with increasing b‐value, similar to the in vivo decrease from 2.91 ± 0.43 to 2.30 ± 0.30. Diffusion tensor analysis revealed reduced deviation of helix angles from a linear transmural model and reduced transverse angle standard deviation for SE compared with STEAM. Mean diffusivity and fractional anisotropy were measured to be statistically different (P < 0.001) between SE and STEAM. Conclusion Cardiac DTI using motion‐compensated SE yields a 2.3–2.9× increase in SNR efficiency relative to STEAM and improved accuracy of tensor metrics. The SE method hence presents an attractive alternative to STEAM based approaches. Magn Reson Med 76:862–872, 2016. © 2015 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
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Affiliation(s)
- Constantin von Deuster
- Imaging Sciences and Biomedical Engineering, King's College London, London, United Kingdom.,Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland
| | - Christian T Stoeck
- Imaging Sciences and Biomedical Engineering, King's College London, London, United Kingdom.,Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland
| | - Martin Genet
- Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland
| | - David Atkinson
- Centre for Medical Imaging, University College London, London, United Kingdom
| | - Sebastian Kozerke
- Imaging Sciences and Biomedical Engineering, King's College London, London, United Kingdom.,Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland
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22
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Frohwein LJ, Hoerr V, Faber C, Schäfers KP. Correction of MRI-induced geometric distortions in whole-body small animal PET-MRI. Med Phys 2015; 42:3848-58. [PMID: 26133586 DOI: 10.1118/1.4921418] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
Abstract
PURPOSE The fusion of positron emission tomography (PET) and magnetic resonance imaging (MRI) data can be a challenging task in whole-body PET-MRI. The quality of the registration between these two modalities in large field-of-views (FOV) is often degraded by geometric distortions of the MRI data. The distortions at the edges of large FOVs mainly originate from MRI gradient nonlinearities. This work describes a method to measure and correct for these kind of geometric distortions in small animal MRI scanners to improve the registration accuracy of PET and MRI data. METHODS The authors have developed a geometric phantom which allows the measurement of geometric distortions in all spatial axes via control points. These control points are detected semiautomatically in both PET and MRI data with a subpixel accuracy. The spatial transformation between PET and MRI data is determined with these control points via 3D thin-plate splines (3D TPS). The transformation derived from the 3D TPS is finally applied to real MRI mouse data, which were acquired with the same scan parameters used in the phantom data acquisitions. Additionally, the influence of the phantom material on the homogeneity of the magnetic field is determined via field mapping. RESULTS The spatial shift according to the magnetic field homogeneity caused by the phantom material was determined to a mean of 0.1 mm. The results of the correction show that distortion with a maximum error of 4 mm could be reduced to less than 1 mm with the proposed correction method. Furthermore, the control point-based registration of PET and MRI data showed improved congruence after correction. CONCLUSIONS The developed phantom has been shown to have no considerable negative effect on the homogeneity of the magnetic field. The proposed method yields an appropriate correction of the measured MRI distortion and is able to improve the PET and MRI registration. Furthermore, the method is applicable to whole-body small animal imaging routines including different standard MRI sequences.
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Affiliation(s)
- Lynn J Frohwein
- European Institute for Molecular Imaging, University of Münster, Münster 48149, Germany
| | - Verena Hoerr
- Department of Clinical Radiology, University Hospital of Münster, Münster 48149, Germany
| | - Cornelius Faber
- Department of Clinical Radiology, University Hospital of Münster, Münster 48149, Germany
| | - Klaus P Schäfers
- European Institute for Molecular Imaging, University of Münster, Münster 48149, Germany
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The Age-ility Project (Phase 1): Structural and functional imaging and electrophysiological data repository. Neuroimage 2015; 124:1137-1142. [PMID: 25936806 DOI: 10.1016/j.neuroimage.2015.04.047] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2015] [Revised: 04/20/2015] [Accepted: 04/21/2015] [Indexed: 11/22/2022] Open
Abstract
Our understanding of the complex interplay between structural and functional organisation of brain networks is being advanced by the development of novel multi-modal analyses approaches. The Age-ility Project (Phase 1) data repository offers open access to structural MRI, diffusion MRI, and resting-state fMRI scans, as well as resting-state EEG recorded from the same community participants (n=131, 15-35 y, 66 male). Raw imaging and electrophysiological data as well as essential demographics are made available via the NITRC website. All data have been reviewed for artifacts using a rigorous quality control protocol and detailed case notes are provided.
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24
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Miao HC, Wu MT, Kao EF, Chiu YH, Chou MC. Comparisons of Reproducibility and Mean Values of Diffusion Tensor Imaging-Derived Indices between Unipolar and Bipolar Diffusion Pulse Sequences. J Neuroimaging 2015; 25:892-9. [PMID: 25753738 DOI: 10.1111/jon.12231] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2014] [Accepted: 01/28/2015] [Indexed: 11/29/2022] Open
Abstract
Eddy current distortion is an important issue that may influence the quantitative measurements of diffusion tensor imaging (DTI). The corrections of eddy current artifacts could be performed using bipolar diffusion gradients or unipolar gradients with affine registration. Whether the diffusion pulse sequence affects the quantification of DTI indices and the technique that produces more reliable DTI indices in terms of reproducibility both remain unclear. Therefore, the purpose of this study was to compare the reproducibility and mean values of DTI-derived indices between unipolar and bipolar diffusion pulse sequences based on actual human brain data. Five repeated datasets of unipolar and bipolar DTI were acquired from 10 healthy subjects at different echo times (TEs). The reproducibility and mean values of DTI indices were assessed by calculating the coefficient of variation and mean values of the 5 repeated measurements. The results revealed that the reproducibility and mean values of DTI indices were significantly affected by the pulse sequence. Unipolar DTI exhibited significantly higher reproducibility than bipolar DTI even at the same TE, and the mean values of DTI indices were significantly different between them. Therefore, we concluded that the reproducibility and mean values of DTI indices were significantly influenced by diffusion pulse sequences.
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Affiliation(s)
- Hsiao-Chien Miao
- Department of Medical Imaging and Radiological Sciences, Kaohsiung Medical University, Kaohsiung, Taiwan
| | - Ming-Ting Wu
- Department of Radiology, Kaohsiung Veterans General Hospital, Kaohsiung, Taiwan
| | - E-Fong Kao
- Department of Medical Imaging and Radiological Sciences, Kaohsiung Medical University, Kaohsiung, Taiwan
| | - Yu-Hsien Chiu
- Department of Healthcare Administration and Medical Informatics, Kaohsiung Medical University, Kaohsiung, Taiwan
| | - Ming-Chung Chou
- Department of Medical Imaging and Radiological Sciences, Kaohsiung Medical University, Kaohsiung, Taiwan.,Department of Healthcare Administration and Medical Informatics, Kaohsiung Medical University, Kaohsiung, Taiwan
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