15
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      High temporal resolution arterial spin labeling MRI with whole‐brain coverage by combining time‐encoding with Look‐Locker and simultaneous multi‐slice imaging

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Purpose

          The goal of this study was to achieve high temporal resolution, multi‐time point pseudo‐continuous arterial spin labeling (pCASL) MRI in a time‐efficient manner, while maintaining whole‐brain coverage.

          Methods

          A Hadamard 8‐matrix was used to dynamically encode the pCASL labeling train, thereby providing the first source of temporal information. The second method for obtaining dynamic arterial spin labeling (ASL) signal consisted of a Look‐Locker (LL) readout of 4 phases that are acquired with a flip‐angle sweep to maintain constant sensitivity over the phases. To obtain whole‐brain coverage in the short LL interval, 4 slices were excited simultaneously by multi‐banded radiofrequency pulses. After subtraction according to the Hadamard scheme, the ASL signal was corrected for the use of the flip‐angle sweep and background suppression pulses. The BASIL toolkit of the Oxford Centre for FMRIB was used to quantify the ASL signal.

          Results

          By combining a time‐encoded pCASL labeling scheme with an LL readout and simultaneous multi‐slice acquisition, 28 time points of 16 slices with a 75‐ or 150‐ms time resolution were acquired in a total scan time of 10 minutes 20 seconds, from which cerebral blood flow (CBF) maps, arterial transit time maps, and arterial blood volume could be determined.

          Conclusion

          Whole‐brain ASL images were acquired with a 75‐ms time resolution for the angiography and 150‐ms resolution for the perfusion phase by combining the proposed techniques. Reducing the total scan time to 1 minute 18 seconds still resulted in reasonable CBF maps, which demonstrates the feasibility of this approach for practical studies on brain hemodynamics.

          Related collections

          Most cited references17

          • Record: found
          • Abstract: not found
          • Article: not found

          Variational Bayesian Inference for a Nonlinear Forward Model

            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Separation of macrovascular signal in multi-inversion time arterial spin labelling MRI.

            Arterial spin labeling (ASL) provides a noninvasive method to measure brain perfusion and is becoming an increasingly viable alternative to more invasive MR methods due to improvements in acquisition, such as the use of a three-dimensional GRASE readout. A potential source of error in ASL measurements is signal arising from intravascular blood that is destined for more distal tissue. This is typically suppressed using diffusion gradients in many ASL sequences. However, several problems exist with this approach, such as the choice of cutoff velocity and gradient direction and incompatibility with certain readout modules. An alternative approach is to explicitly model the intravascular signal. This study exploits this approach by using multi-inversion time ASL data with a recently developed model-fitting method. The method employed permits the intravascular contribution to be discarded in voxels where there is no support in the data for its inclusion, thereby addressing the issue of overfitting. It is shown by comparing data with and without flow suppression, and by comparing the intravascular contribution in GRASE ASL data to MR angiographic images, that the model-fitting approach can provide a viable alternative to flow suppression in ASL where suppression is either not feasible or not desirable. (c) 2010 Wiley-Liss, Inc.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Combined spatial and non-spatial prior for inference on MRI time-series.

              When modelling FMRI and other MRI time-series data, a Bayesian approach based on adaptive spatial smoothness priors is a compelling alternative to using a standard generalized linear model (GLM) on presmoothed data. Another benefit of the Bayesian approach is that biophysical prior information can be incorporated in a principled manner; however, this requirement for a fixed non-spatial prior on a parameter would normally preclude using spatial regularization on that same parameter. We have developed a Gaussian-process-based prior to apply adaptive spatial regularization while still ensuring that the fixed biophysical prior is correctly applied on each voxel. A parameterized covariance matrix provides separate control over the variance (the diagonal elements) and the between-voxel correlation (due to off-diagonal elements). Analysis proceeds using evidence optimization (EO), with variational Bayes (VB) updates used for some parameters. The method can also be applied to non-linear forward models by using a linear Taylor expansion centred on the latest parameter estimates. Applying the method to FMRI with a constrained haemodynamic response function (HRF) shape model shows improved fits in simulations, compared to using either the non-spatial or spatial-smoothness prior alone. We also analyse multi-inversion arterial spin labelling data using a non-linear perfusion model to estimate cerebral blood flow and bolus arrival time. By combining both types of prior information, this new prior performs consistently well across a wider range of situations than either prior alone, and provides better estimates when both types of prior information are relevant.
                Bookmark

                Author and article information

                Contributors
                m.c.e.van_der_plas@lumc.nl
                Journal
                Magn Reson Med
                Magn Reson Med
                10.1002/(ISSN)1522-2594
                MRM
                Magnetic Resonance in Medicine
                John Wiley and Sons Inc. (Hoboken )
                0740-3194
                1522-2594
                03 March 2019
                June 2019
                : 81
                : 6 ( doiID: 10.1002/mrm.v81.6 )
                : 3734-3744
                Affiliations
                [ 1 ] C.J. Gorter Center for High Field MRI, Department of Radiology Leiden University Medical Center Leiden The Netherlands
                [ 2 ] Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences University of Oxford Oxford United Kingdom
                [ 3 ] Institute of Biomedical Engineering, Research Council UK (EP/P012361/1) University of Oxford Oxford United Kingdom
                Author notes
                [*] [* ] Correspondence

                Merlijn C.E. van der Plas, C.J. Gorter Center for High Field MRI, Department of Radiology, C3Q, Leiden University Medical Center, P.O. Box 9600, 2300 RC, Leiden, The Netherlands.

                Email: m.c.e.van_der_plas@ 123456lumc.nl

                Twitter: @mri_lumc

                Author information
                https://orcid.org/0000-0003-2240-8405
                https://orcid.org/0000-0003-0750-7798
                https://orcid.org/0000-0003-1802-4214
                https://orcid.org/0000-0001-7034-8959
                Article
                MRM27692
                10.1002/mrm.27692
                6593668
                30828873
                1930d3c0-540f-4e84-9c4e-124965ec21ed
                © 2019 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 http://creativecommons.org/licenses/by-nc/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.

                History
                : 02 August 2018
                : 23 January 2019
                : 24 January 2019
                Page count
                Figures: 9, Tables: 1, Pages: 11, Words: 9058
                Funding
                Funded by: Stichting voor de Technische Wetenschappen
                Award ID: 016.160.351
                Funded by: Netherlands Organisation for Scientific Research.
                Categories
                Full Paper
                Full Papers—Imaging Methodology
                Custom metadata
                2.0
                mrm27692
                June 2019
                Converter:WILEY_ML3GV2_TO_NLMPMC version:5.6.5 mode:remove_FC converted:26.06.2019

                Radiology & Imaging
                arterial spin labeling,cerebral blood flow,magnetic resonance imaging,perfusion mri,simultaneously multi‐slice

                Comments

                Comment on this article