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Velikina JV, Jung Y, Field AS, Samsonov AA. High-resolution dynamic susceptibility contrast perfusion imaging using higher-order temporal smoothness regularization. Magn Reson Med 2023; 89:112-127. [PMID: 36198002 PMCID: PMC9617779 DOI: 10.1002/mrm.29425] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2022] [Revised: 08/03/2022] [Accepted: 08/05/2022] [Indexed: 01/12/2023]
Abstract
PURPOSE To improve image quality and resolution of dynamic susceptibility contrast perfusion weighted imaging (DSC-PWI) by developing acquisition and reconstruction methods exploiting the temporal regularity property of DSC-PWI signal. THEORY AND METHODS A novel regularized reconstruction is proposed that recovers DSC-PWI series from interleaved segmented spiral k-space acquisition using higher order temporal smoothness (HOTS) properties of the DSC-PWI signal. The HOTS regularization is designed to tackle representational insufficiency of the standard first-order temporal regularizations for supporting higher accelerations. The higher accelerations allow for k-space coverage with shorter spiral interleaves resulting in improved acquisition point spread function, and acquisition of images at multiple TEs for more accurate DSC-PWI analysis. RESULTS The methods were evaluated in simulated and in-vivo studies. HOTS regularization provided increasingly more accurate models for DSC-PWI than the standard first-order methods with either quadratic or robust norms at the expense of increased noise. HOTS DSC-PWI optimized for noise and accuracy demonstrated significant advantages over both spiral DSC-PWI without temporal regularization and traditional echo-planar DSC-PWI, improving resolution and mitigating image artifacts associated with long readout, including blurring and geometric distortions. In context of multi-echo DSC-PWI, the novel methods allowed ∼4.3× decrease of voxel volume, providing 2× number of TEs compared to the previously published results. CONCLUSIONS Proposed HOTS reconstruction combined with dynamic spiral sampling represents a valid mechanism for improving image quality and resolution of DSC-PWI significantly beyond those available with established fast imaging techniques.
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Affiliation(s)
- Julia V. Velikina
- Department of RadiologyUniversity of Wisconsin‐Madison
MadisonWisconsinUSA
| | - Youngkyoo Jung
- Department of RadiologyUniversity of California‐DavisDavisCaliforniaUSA
| | - Aaron S. Field
- Department of RadiologyUniversity of Wisconsin‐Madison
MadisonWisconsinUSA
| | - Alexey A. Samsonov
- Department of RadiologyUniversity of Wisconsin‐Madison
MadisonWisconsinUSA
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2
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Nunez-Gonzalez L, Nagtegaal MA, Poot DHJ, de Bresser J, van Osch MJP, Hernandez-Tamames JA, Vos FM. Accuracy and repeatability of joint sparsity multi-component estimation in MR Fingerprinting. Neuroimage 2022; 263:119638. [PMID: 36122685 DOI: 10.1016/j.neuroimage.2022.119638] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2022] [Revised: 08/11/2022] [Accepted: 08/31/2022] [Indexed: 11/30/2022] Open
Abstract
MR fingerprinting (MRF) is a promising method for quantitative characterization of tissues. Often, voxel-wise measurements are made, assuming a single tissue-type per voxel. Alternatively, the Sparsity Promoting Iterative Joint Non-negative least squares Multi-Component MRF method (SPIJN-MRF) facilitates tissue parameter estimation for identified components as well as partial volume segmentations. The aim of this paper was to evaluate the accuracy and repeatability of the SPIJN-MRF parameter estimations and partial volume segmentations. This was done (1) through numerical simulations based on the BrainWeb phantoms and (2) using in vivo acquired MRF data from 5 subjects that were scanned on the same week-day for 8 consecutive weeks. The partial volume segmentations of the SPIJN-MRF method were compared to those obtained by two conventional methods: SPM12 and FSL. SPIJN-MRF showed higher accuracy in simulations in comparison to FSL- and SPM12-based segmentations: Fuzzy Tanimoto Coefficients (FTC) comparing these segmentations and Brainweb references were higher than 0.95 for SPIJN-MRF in all the tissues and between 0.6 and 0.7 for SPM12 and FSL in white and gray matter and between 0.5 and 0.6 in CSF. For the in vivo MRF data, the estimated relaxation times were in line with literature and minimal variation was observed. Furthermore, the coefficient of variation (CoV) for estimated tissue volumes with SPIJN-MRF were 10.5% for the myelin water, 6.0% for the white matter, 5.6% for the gray matter, 4.6% for the CSF and 1.1% for the total brain volume. CoVs for CSF and total brain volume measured on the scanned data for SPIJN-MRF were in line with those obtained with SPM12 and FSL. The CoVs for white and gray matter volumes were distinctively higher for SPIJN-MRF than those measured with SPM12 and FSL. In conclusion, the use of SPIJN-MRF provides accurate and precise tissue relaxation parameter estimations taking into account intrinsic partial volume effects. It facilitates obtaining tissue fraction maps of prevalent tissues including myelin water which can be relevant for evaluating diseases affecting the white matter.
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Affiliation(s)
- L Nunez-Gonzalez
- Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, the Netherlands.
| | - M A Nagtegaal
- Department of Imaging Physics, Delft University of Technology, Delft, the Netherlands
| | - D H J Poot
- Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, the Netherlands
| | - J de Bresser
- Department of Radiology, Leiden University Medical Center, Leiden, the Netherlands
| | - M J P van Osch
- C.J. Gorter Center for MRI, Radiology Department, Leiden University Medical Center, Leiden, the Netherlands
| | - J A Hernandez-Tamames
- Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, the Netherlands; Department of Imaging Physics, Delft University of Technology, Delft, the Netherlands
| | - F M Vos
- Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, the Netherlands; Department of Imaging Physics, Delft University of Technology, Delft, the Netherlands
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Mailhot N, Cheriton R, Vyas K, Cook J, Prawer S, Hinzer K, Spinello D. Eighty-Five Percent of Improved Optical Power Delivery to Epiretinal Prostheses Using Rigid Body Compensation Algorithm. J Biomech Eng 2021; 143:061009. [PMID: 33537711 DOI: 10.1115/1.4050026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2019] [Indexed: 11/08/2022]
Abstract
Vision impairment caused by degenerative retinal pathologies such as age-related macular degeneration can be treated using retinal implants. Such devices receive power and data using cables passing through a permanent surgical incision in the eye wall (sclera), which increases the risk to patients and surgical costs. A recently developed retinal implant design eliminates the necessity of the implant cable using a photonic power converter (PPC), which receives optical power and data through the pupil and is directed by an ellipsoidal reflector and micro-electromechanical mirror. We present a misalignment compensation algorithm model that accounts for rigid-body motions of the reflector relative to the eye and applies the correction to the mirror coordinates in the presence of angular misalignment of the reflector. We demonstrate that up to 85% of the nominal optical power can be delivered to the implant with axial reflector misalignments up to 30 deg using the compensation algorithm.
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Affiliation(s)
- Nathaniel Mailhot
- Department of Mechanical Engineering, University of Ottawa, Ottawa, ON K1N 6M6, Canada
| | - Ross Cheriton
- National Research Council of Canada, Ottawa, ON K1N 6M6, Canada
| | - Kaustubh Vyas
- Electrical Engineering and Computer Science, University of Ottawa, Ottawa, ON K1N 6M6, Canada
| | - John Cook
- Electrical Engineering and Computer Science, University of Ottawa, Ottawa, ON K1N 6M6, Canada
| | - Steven Prawer
- Department of Physics, University of Melbourne, Melbourne VIC 3010, Australia
| | - Karin Hinzer
- Electrical Engineering and Computer Science, University of Ottawa, Ottawa, ON K1N 6M6, Canada
| | - Davide Spinello
- Department of Mechanical Engineering, University of Ottawa, Ottawa, ON K1N 6M6, Canada
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Cao X, Ye H, Liao C, Li Q, He H, Zhong J. Fast 3D brain MR fingerprinting based on multi-axis spiral projection trajectory. Magn Reson Med 2019; 82:289-301. [PMID: 30883867 DOI: 10.1002/mrm.27726] [Citation(s) in RCA: 43] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2018] [Revised: 02/09/2019] [Accepted: 02/12/2019] [Indexed: 01/12/2023]
Abstract
PURPOSE To develop a fast, sub-millimeter 3D magnetic resonance fingerprinting (MRF) technique for whole-brain quantitative scans. METHODS An acquisition trajectory based on multi-axis spiral projection imaging (maSPI) was implemented for 3D MRF with steady-state precession and slab excitation. By appropriately assigning the in-plane and through-plane rotations of spiral interleaves in a novel acquisition scheme, an maSPI-based acquisition was implemented, and the total acquisition time was reduced by up to a factor of 8 compared to stack-of-spiral (SOS)-based acquisition. A sliding-window method was also used to further reduce the required number of time points for a faster acquisition. The experiments were conducted both on a phantom and in vivo. RESULTS The results from the phantom measurements with the proposed and gold standard methods were consistent with a good linear correlation and an R2 value approaching 0.99. The in vivo experiments achieved whole-brain parametric maps with isotropic resolutions of 1 mm and 0.8 mm in 5.0 and 6.0 min, respectively, with potential for further acceleration. An in vivo experiment with intentionally moving subjects demonstrated that the maSPI scheme largely outperforms the SOS scheme in terms of robustness to head motion. CONCLUSION 3D MRF with an maSPI acquisition scheme enables fast and robust scans for high-resolution parametric mapping.
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Affiliation(s)
- Xiaozhi Cao
- Center for Brain Imaging Science and Technology, Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrumental Science, Zhejiang University, Hangzhou, Zhejiang, China
| | - Huihui Ye
- Center for Brain Imaging Science and Technology, Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrumental Science, Zhejiang University, Hangzhou, Zhejiang, China.,State Key Laboratory of Modern Optical Instrumentation, College of Optical Science and Engineering, Zhejiang University, Hangzhou, Zhejiang, China
| | - Congyu Liao
- Center for Brain Imaging Science and Technology, Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrumental Science, Zhejiang University, Hangzhou, Zhejiang, China
| | - Qing Li
- Center for Brain Imaging Science and Technology, Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrumental Science, Zhejiang University, Hangzhou, Zhejiang, China
| | - Hongjian He
- Center for Brain Imaging Science and Technology, Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrumental Science, Zhejiang University, Hangzhou, Zhejiang, China
| | - Jianhui Zhong
- Center for Brain Imaging Science and Technology, Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrumental Science, Zhejiang University, Hangzhou, Zhejiang, China.,Department of Imaging Sciences, University of Rochester, Rochester, New York
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Babayeva M, Kober T, Knowles B, Herbst M, Meuli R, Zaitsev M, Krueger G. Accuracy and Precision of Head Motion Information in Multi-Channel Free Induction Decay Navigators for Magnetic Resonance Imaging. IEEE TRANSACTIONS ON MEDICAL IMAGING 2015; 34:1879-1889. [PMID: 25781624 DOI: 10.1109/tmi.2015.2413211] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/04/2023]
Abstract
Free induction decay (FID) navigators were found to qualitatively detect rigid-body head movements, yet it is unknown to what extent they can provide quantitative motion estimates. Here, we acquired FID navigators at different sampling rates and simultaneously measured head movements using a highly accurate optical motion tracking system. This strategy allowed us to estimate the accuracy and precision of FID navigators for quantification of rigid-body head movements. Five subjects were scanned with a 32-channel head coil array on a clinical 3T MR scanner during several resting and guided head movement periods. For each subject we trained a linear regression model based on FID navigator and optical motion tracking signals. FID-based motion model accuracy and precision was evaluated using cross-validation. FID-based prediction of rigid-body head motion was found to be with a mean translational and rotational error of 0.14±0.21 mm and 0.08±0.13°, respectively. Robust model training with sub-millimeter and sub-degree accuracy could be achieved using 100 data points with motion magnitudes of ±2 mm and ±1° for translation and rotation. The obtained linear models appeared to be subject-specific as inter-subject application of a "universal" FID-based motion model resulted in poor prediction accuracy. The results show that substantial rigid-body motion information is encoded in FID navigator signal time courses. Although, the applied method currently requires the simultaneous acquisition of FID signals and optical tracking data, the findings suggest that multi-channel FID navigators have a potential to complement existing tracking technologies for accurate rigid-body motion detection and correction in MRI.
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Riemannian means on special euclidean group and unipotent matrices group. ScientificWorldJournal 2013; 2013:292787. [PMID: 24282378 PMCID: PMC3824837 DOI: 10.1155/2013/292787] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2013] [Accepted: 09/16/2013] [Indexed: 12/03/2022] Open
Abstract
Among the noncompact matrix Lie groups, the special Euclidean group and the unipotent matrix group play important roles in both theoretic and applied studies. The Riemannian means of a finite set of the given points on the two matrix groups are investigated, respectively. Based on the left invariant metric on the matrix Lie groups, the geodesic between any two points is gotten. And the sum of the geodesic distances is taken as the cost function, whose minimizer is the Riemannian mean. Moreover, a Riemannian gradient algorithm for computing the Riemannian mean on the special Euclidean group and an iterative formula for that on the unipotent matrix group are proposed, respectively. Finally, several numerical simulations in the 3-dimensional case are given to illustrate our results.
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Fang Z, Lee JH. High-throughput optogenetic functional magnetic resonance imaging with parallel computations. J Neurosci Methods 2013; 218:184-95. [PMID: 23747482 DOI: 10.1016/j.jneumeth.2013.04.015] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2012] [Revised: 02/13/2013] [Accepted: 04/20/2013] [Indexed: 11/30/2022]
Abstract
Optogenetic functional magnetic resonance imaging (of MRI) technology enables cell-type-specific, temporally precise neuronal control and the accurate, in vivo readout of the resulting activity across the entire brain. With the ability to precisely control excitation and inhibition parameters and accurately record the resulting activity, there is an increased need for a high-throughput method to bring the of MRI studies to their full potential. In this paper, an advanced system facilitating real-time fMRI with interactive control and analysis in a fraction of the MRI acquisition repetition time (TR) is proposed. With high-processing speed, sufficient time will be available for the integration of future developments that further enhance of MRI data or streamline the study. We designed and implemented a highly optimised, massively parallel system using graphics processing units (GPUs), which achieves the reconstruction, motion correction, and analysis of 3D volume data in approximately 12.80 ms. As a result, with a 750 ms TR and 4 interleaf fMRI acquisition, we can now conduct sliding window reconstruction, motion correction, analysis and display in approximately 1.7% of the TR. Therefore, a significant amount of time can now be allocated to integrating advanced but computationally intensive methods that improve image quality and enhance the analysis results within a TR. Utilising the proposed high-throughput imaging platform with sliding window reconstruction, we were also able to observe the much-debated initial dips in our of MRI data. Combined with methods to further improve SNR, the proposed system will enable efficient real-time, interactive, high-throughput of MRI studies.
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Affiliation(s)
- Zhongnan Fang
- Department of Electrical Engineering, Stanford University, CA 94305, USA
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Loktyushin A, Nickisch H, Pohmann R, Schölkopf B. Blind retrospective motion correction of MR images. Magn Reson Med 2013; 70:1608-18. [PMID: 23401078 DOI: 10.1002/mrm.24615] [Citation(s) in RCA: 53] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2012] [Revised: 11/30/2012] [Accepted: 12/02/2012] [Indexed: 11/12/2022]
Abstract
PURPOSE Subject motion can severely degrade MR images. A retrospective motion correction algorithm, Gradient-based motion correction, which significantly reduces ghosting and blurring artifacts due to subject motion was proposed. The technique uses the raw data of standard imaging sequences; no sequence modifications or additional equipment such as tracking devices are required. Rigid motion is assumed. METHODS The approach iteratively searches for the motion trajectory yielding the sharpest image as measured by the entropy of spatial gradients. The vast space of motion parameters is efficiently explored by gradient-based optimization with a convergence guarantee. RESULTS The method has been evaluated on both synthetic and real data in two and three dimensions using standard imaging techniques. MR images are consistently improved over different kinds of motion trajectories. Using a graphics processing unit implementation, computation times are in the order of a few minutes for a full three-dimensional volume. CONCLUSION The presented technique can be an alternative or a complement to prospective motion correction methods and is able to improve images with strong motion artifacts from standard imaging sequences without requiring additional data.
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Maclaren J, Herbst M, Speck O, Zaitsev M. Prospective motion correction in brain imaging: a review. Magn Reson Med 2012; 69:621-36. [PMID: 22570274 DOI: 10.1002/mrm.24314] [Citation(s) in RCA: 258] [Impact Index Per Article: 21.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2012] [Revised: 03/30/2012] [Accepted: 04/04/2012] [Indexed: 11/11/2022]
Abstract
Motion correction in magnetic resonance imaging by real-time adjustment of the imaging pulse sequence was first proposed more than 20 years ago. Recent advances have resulted from combining real-time correction with new navigator and external tracking mechanisms capable of quantifying rigid-body motion in all 6 degrees of freedom. The technique is now often referred to as "prospective motion correction." This article describes the fundamentals of prospective motion correction and reviews the latest developments in its application to brain imaging and spectroscopy. Although emphasis is placed on the brain as the organ of interest, the same principles apply whenever the imaged object can be approximated as a rigid body. Prospective motion correction can be used with most MR sequences, so it has potential to make a large impact in clinical routine. To maximize the benefits obtained from the technique, there are, however, several challenges still to be met. These include practical implementation issues, such as obtaining tracking data with minimal delay, and more fundamental problems, such as the magnetic field distortions caused by a moving object. This review discusses these challenges and summarizes the state of the art. We hope that this work will motivate further developments in prospective motion correction and help the technique to reach its full potential.
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Affiliation(s)
- Julian Maclaren
- Medical Physics, Department of Radiology, University Medical Center Freiburg, Freiburg, Germany.
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Zwart NR, Johnson KO, Pipe JG. Efficient sample density estimation by combining gridding and an optimized kernel. Magn Reson Med 2011; 67:701-10. [PMID: 21688320 DOI: 10.1002/mrm.23041] [Citation(s) in RCA: 66] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2011] [Revised: 03/30/2011] [Accepted: 05/18/2011] [Indexed: 11/07/2022]
Abstract
The reconstruction of non-Cartesian k-space trajectories often requires the estimation of nonuniform sampling density. Particularly for 3D, this calculation can be computationally expensive. The method proposed in this work combines an iterative algorithm previously proposed by Pipe and Menon (Magn Reson Med 1999;41:179-186) with the optimal kernel design previously proposed by Johnson and Pipe (Magn Reson Med 2009;61:439-447). The proposed method shows substantial time reductions in estimating the densities of center-out trajectories, when compared with that of Johnson. It is demonstrated that, depending on the trajectory, the proposed method can provide reductions in execution time by factors of 12 to 85. The method is also shown to be robust in areas of high trajectory overlap, when compared with two analytical density estimation methods, producing a 10-fold increase in accuracy in one case. Initial conditions allow the proposed method to converge in fewer iterations and are shown to be flexible in terms of the accuracy of information supplied. The proposed method is not only one of the fastest and most accurate algorithms, it is also completely generic, allowing any arbitrary trajectory to be density compensated extemporaneously. The proposed method is also simple and can be implemented on parallel computing platforms in a straightforward manner.
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Affiliation(s)
- Nicholas R Zwart
- Keller Center for Imaging Innovation, Neuroimaging Research, Barrow Neurological Institute, Phoenix, Arizona 85013, USA.
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