Spatial resolution and velocity field improvement of 4D-flow MRI.

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Title: Spatial resolution and velocity field improvement of 4D-flow MRI.
Authors: Callaghan, Fraser M.1,2, Grieve, Stuart M.1,2,3 stuart.grieve@sydney.edu.au
Source: Magnetic Resonance in Medicine. Nov2017, Vol. 78 Issue 5, p1959-1968. 10p.
Abstract: Purpose 4D-flow MRI obtains a time-dependent 3D velocity field; however, its use for the calculation of higher-order parameters is limited by noise. We present an algorithm for denoising 4D-flow data. Theory and Methods By integrating a velocity field and eliminating streamlines in noisy flow, depicted by high curvature, a denoised dataset may be extracted. This method, defined as the velocity field improvement (VFIT) algorithm, was validated in an analytical dataset and using in vivo data in comparison with a computation fluid dynamics (CFD) simulation. As a proof of principal, wall shear stress (WSS) measurements in the descending aorta were compared with those defined by CFD. Results The VFIT algorithm achieved a >100% noise reduction of a corrupted analytical dataset. In addition, 4D-flow data were cleaned to show improved spatial resolution and near wall velocity representation. WSS measures compared well with CFD data and bulk flow dynamics were retained (<2% difference in flow measurements). Conclusion This study presents a method for denoising 4D-flow datasets with improved spatial resolution. Bulk flow dynamics are accurately conserved while velocity and velocity gradient fields are improved; this is important in the calculation of higher-order parameters such as WSS, which are shown to be more comparable to CFD measures. Magn Reson Med 78:1959-1968, 2017. © 2016 International Society for Magnetic Resonance in Medicine. [ABSTRACT FROM AUTHOR]
Copyright of Magnetic Resonance in Medicine is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Spatial resolution and velocity field improvement of 4D-flow MRI.
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  Data: &lt;searchLink fieldCode=&quot;AR&quot; term=&quot;%22Callaghan%2C+Fraser+M%2E%22&quot;&gt;Callaghan, Fraser M.&lt;/searchLink&gt;&lt;relatesTo&gt;1,2&lt;/relatesTo&gt;&lt;br /&gt;&lt;searchLink fieldCode=&quot;AR&quot; term=&quot;%22Grieve%2C+Stuart+M%2E%22&quot;&gt;Grieve, Stuart M.&lt;/searchLink&gt;&lt;relatesTo&gt;1,2,3&lt;/relatesTo&gt;&lt;i&gt; stuart.grieve@sydney.edu.au&lt;/i&gt;
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  Data: &lt;searchLink fieldCode=&quot;JN&quot; term=&quot;%22Magnetic+Resonance+in+Medicine%22&quot;&gt;Magnetic Resonance in Medicine&lt;/searchLink&gt;. Nov2017, Vol. 78 Issue 5, p1959-1968. 10p.
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Purpose 4D-flow MRI obtains a time-dependent 3D velocity field; however, its use for the calculation of higher-order parameters is limited by noise. We present an algorithm for denoising 4D-flow data. Theory and Methods By integrating a velocity field and eliminating streamlines in noisy flow, depicted by high curvature, a denoised dataset may be extracted. This method, defined as the velocity field improvement (VFIT) algorithm, was validated in an analytical dataset and using in vivo data in comparison with a computation fluid dynamics (CFD) simulation. As a proof of principal, wall shear stress (WSS) measurements in the descending aorta were compared with those defined by CFD. Results The VFIT algorithm achieved a &gt;100% noise reduction of a corrupted analytical dataset. In addition, 4D-flow data were cleaned to show improved spatial resolution and near wall velocity representation. WSS measures compared well with CFD data and bulk flow dynamics were retained (&lt;2% difference in flow measurements). Conclusion This study presents a method for denoising 4D-flow datasets with improved spatial resolution. Bulk flow dynamics are accurately conserved while velocity and velocity gradient fields are improved; this is important in the calculation of higher-order parameters such as WSS, which are shown to be more comparable to CFD measures. Magn Reson Med 78:1959-1968, 2017. &#169; 2016 International Society for Magnetic Resonance in Medicine. [ABSTRACT FROM AUTHOR]
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  Data: &lt;i&gt;Copyright of Magnetic Resonance in Medicine is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder&#39;s express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.&lt;/i&gt; (Copyright applies to all Abstracts.)
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