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Improved visualization of intracranial distal arteries with multiple 2D slice dynamic ASL‐MRA and super‐resolution convolutional neural network.

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Title: Improved visualization of intracranial distal arteries with multiple 2D slice dynamic ASL‐MRA and super‐resolution convolutional neural network.
Authors: Suzuki, Yuriko1 (AUTHOR) yuriko.suzuki@ndcn.ox.ac.uk, Koktzoglou, Ioannis2,3 (AUTHOR), Li, Ziyu1 (AUTHOR), Jezzard, Peter1 (AUTHOR), Okell, Thomas1 (AUTHOR)
Source: Magnetic Resonance in Medicine. Dec2024, Vol. 92 Issue 6, p2491-2505. 15p.
Subjects: Convolutional neural networks, Spin labels, Cerebrovascular disease, Blood flow, Spatial resolution
Abstract: Purpose: To develop a novel framework to improve the visualization of distal arteries in arterial spin labeling (ASL) dynamic MRA. Methods: The attenuation of ASL blood signal due to the repetitive application of excitation RF pulses was minimized by splitting the acquisition volume into multiple thin 2D (M2D) slices, thereby reducing the exposure of the arterial blood magnetization to RF pulses while it flows within the brain. To improve the degraded vessel visualization in the slice direction due to the limited minimum achievable 2D slice thickness, a super‐resolution (SR) convolutional neural network (CNN) was trained by using 3D time‐of‐flight (TOF)‐MRA images from a large public dataset. And then, we applied domain transfer from 3D TOF‐MRA to M2D ASL‐MRA, while avoiding acquiring a large number of ASL‐MRA data required for CNN training. Results: Compared to the conventional 3D ASL‐MRA, far more distal arteries were visualized with higher signal intensity by using M2D ASL‐MRA. In general, however, the vessel visualization with a conventional interpolation was prone to be blurry and unclear due to the limited spatial resolution in the slice direction, particularly in small vessels. Application of CNN‐based SR transferred from 3D TOF‐MRA to M2D ASL‐MRA successfully addressed such a limitation and achieved clearer visualization of small vessels than conventional interpolation. Conclusion: This study demonstrated that the proposed framework provides improved visualization of distal arteries in later dynamic phases, which will particularly benefit the application of this approach in patients with cerebrovascular disease who have slow blood flow. [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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  Label: Title
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  Data: Improved visualization of intracranial distal arteries with multiple 2D slice dynamic ASL‐MRA and super‐resolution convolutional neural network.
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  Data: <searchLink fieldCode="AR" term="%22Suzuki%2C+Yuriko%22">Suzuki, Yuriko</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> yuriko.suzuki@ndcn.ox.ac.uk</i><br /><searchLink fieldCode="AR" term="%22Koktzoglou%2C+Ioannis%22">Koktzoglou, Ioannis</searchLink><relatesTo>2,3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Li%2C+Ziyu%22">Li, Ziyu</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Jezzard%2C+Peter%22">Jezzard, Peter</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Okell%2C+Thomas%22">Okell, Thomas</searchLink><relatesTo>1</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Magnetic+Resonance+in+Medicine%22">Magnetic Resonance in Medicine</searchLink>. Dec2024, Vol. 92 Issue 6, p2491-2505. 15p.
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  Data: <searchLink fieldCode="DE" term="%22Convolutional+neural+networks%22">Convolutional neural networks</searchLink><br /><searchLink fieldCode="DE" term="%22Spin+labels%22">Spin labels</searchLink><br /><searchLink fieldCode="DE" term="%22Cerebrovascular+disease%22">Cerebrovascular disease</searchLink><br /><searchLink fieldCode="DE" term="%22Blood+flow%22">Blood flow</searchLink><br /><searchLink fieldCode="DE" term="%22Spatial+resolution%22">Spatial resolution</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Purpose: To develop a novel framework to improve the visualization of distal arteries in arterial spin labeling (ASL) dynamic MRA. Methods: The attenuation of ASL blood signal due to the repetitive application of excitation RF pulses was minimized by splitting the acquisition volume into multiple thin 2D (M2D) slices, thereby reducing the exposure of the arterial blood magnetization to RF pulses while it flows within the brain. To improve the degraded vessel visualization in the slice direction due to the limited minimum achievable 2D slice thickness, a super‐resolution (SR) convolutional neural network (CNN) was trained by using 3D time‐of‐flight (TOF)‐MRA images from a large public dataset. And then, we applied domain transfer from 3D TOF‐MRA to M2D ASL‐MRA, while avoiding acquiring a large number of ASL‐MRA data required for CNN training. Results: Compared to the conventional 3D ASL‐MRA, far more distal arteries were visualized with higher signal intensity by using M2D ASL‐MRA. In general, however, the vessel visualization with a conventional interpolation was prone to be blurry and unclear due to the limited spatial resolution in the slice direction, particularly in small vessels. Application of CNN‐based SR transferred from 3D TOF‐MRA to M2D ASL‐MRA successfully addressed such a limitation and achieved clearer visualization of small vessels than conventional interpolation. Conclusion: This study demonstrated that the proposed framework provides improved visualization of distal arteries in later dynamic phases, which will particularly benefit the application of this approach in patients with cerebrovascular disease who have slow blood flow. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>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.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1002/mrm.30245
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        Text: English
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        Type: general
      – SubjectFull: Spin labels
        Type: general
      – SubjectFull: Cerebrovascular disease
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      – SubjectFull: Blood flow
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      – SubjectFull: Spatial resolution
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      – TitleFull: Improved visualization of intracranial distal arteries with multiple 2D slice dynamic ASL‐MRA and super‐resolution convolutional neural network.
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            NameFull: Suzuki, Yuriko
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              M: 12
              Text: Dec2024
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              Y: 2024
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