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Recent Technical Developments in ASL: A Review of the State of the Art.

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Title: Recent Technical Developments in ASL: A Review of the State of the Art.
Authors: Hernandez‐Garcia, Luis1 (AUTHOR) hernan@umich.edu, Aramendía‐Vidaurreta, Verónica2 (AUTHOR), Bolar, Divya S.3 (AUTHOR), Dai, Weiying4 (AUTHOR), Fernández‐Seara, Maria A.2 (AUTHOR), Guo, Jia5 (AUTHOR), Madhuranthakam, Ananth J.6 (AUTHOR), Mutsaerts, Henk7 (AUTHOR), Petr, Jan8 (AUTHOR), Qin, Qin9 (AUTHOR), Schollenberger, Jonas1 (AUTHOR), Suzuki, Yuriko10 (AUTHOR), Taso, Manuel11 (AUTHOR), Thomas, David L.12 (AUTHOR), van Osch, Matthias J. P.13 (AUTHOR), Woods, Joseph10,14 (AUTHOR), Zhao, Moss Y.15 (AUTHOR), Yan, Lirong16 (AUTHOR), Wang, Ze17 (AUTHOR), Zhao, Li18 (AUTHOR)
Source: Magnetic Resonance in Medicine. Nov2022, Vol. 88 Issue 5, p2021-2042. 22p.
Subjects: Spin labels, Image reconstruction, Noise control, Deep learning, Magnetic resonance
Abstract: This review article provides an overview of a range of recent technical developments in advanced arterial spin labeling (ASL) methods that have been developed or adopted by the community since the publication of a previous ASL consensus paper by Alsop et al. It is part of a series of review/recommendation papers from the International Society for Magnetic Resonance in Medicine Perfusion Study Group. Here, we focus on advancements in readouts and trajectories, image reconstruction, noise reduction, partial volume correction, quantification of nonperfusion parameters, fMRI, fingerprinting, vessel selective ASL, angiography, deep learning, and ultrahigh field ASL. We aim to provide a high level of understanding of these new approaches and some guidance for their implementation, with the goal of facilitating the adoption of such advances by research groups and by MRI vendors. Topics outside the scope of this article that are reviewed at length in separate articles include velocity selective ASL, multiple‐timepoint ASL, body ASL, and clinical ASL recommendations. [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.)
Database: Engineering Source
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  Data: <searchLink fieldCode="AR" term="%22Hernandez‐Garcia%2C+Luis%22">Hernandez‐Garcia, Luis</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> hernan@umich.edu</i><br /><searchLink fieldCode="AR" term="%22Aramendía‐Vidaurreta%2C+Verónica%22">Aramendía‐Vidaurreta, Verónica</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Bolar%2C+Divya+S%2E%22">Bolar, Divya S.</searchLink><relatesTo>3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Dai%2C+Weiying%22">Dai, Weiying</searchLink><relatesTo>4</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Fernández‐Seara%2C+Maria+A%2E%22">Fernández‐Seara, Maria A.</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Guo%2C+Jia%22">Guo, Jia</searchLink><relatesTo>5</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Madhuranthakam%2C+Ananth+J%2E%22">Madhuranthakam, Ananth J.</searchLink><relatesTo>6</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Mutsaerts%2C+Henk%22">Mutsaerts, Henk</searchLink><relatesTo>7</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Petr%2C+Jan%22">Petr, Jan</searchLink><relatesTo>8</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Qin%2C+Qin%22">Qin, Qin</searchLink><relatesTo>9</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Schollenberger%2C+Jonas%22">Schollenberger, Jonas</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Suzuki%2C+Yuriko%22">Suzuki, Yuriko</searchLink><relatesTo>10</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Taso%2C+Manuel%22">Taso, Manuel</searchLink><relatesTo>11</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Thomas%2C+David+L%2E%22">Thomas, David L.</searchLink><relatesTo>12</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22van+Osch%2C+Matthias+J%2E+P%2E%22">van Osch, Matthias J. P.</searchLink><relatesTo>13</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Woods%2C+Joseph%22">Woods, Joseph</searchLink><relatesTo>10,14</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Zhao%2C+Moss+Y%2E%22">Zhao, Moss Y.</searchLink><relatesTo>15</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Yan%2C+Lirong%22">Yan, Lirong</searchLink><relatesTo>16</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Wang%2C+Ze%22">Wang, Ze</searchLink><relatesTo>17</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Zhao%2C+Li%22">Zhao, Li</searchLink><relatesTo>18</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Magnetic+Resonance+in+Medicine%22">Magnetic Resonance in Medicine</searchLink>. Nov2022, Vol. 88 Issue 5, p2021-2042. 22p.
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  Data: <searchLink fieldCode="DE" term="%22Spin+labels%22">Spin labels</searchLink><br /><searchLink fieldCode="DE" term="%22Image+reconstruction%22">Image reconstruction</searchLink><br /><searchLink fieldCode="DE" term="%22Noise+control%22">Noise control</searchLink><br /><searchLink fieldCode="DE" term="%22Deep+learning%22">Deep learning</searchLink><br /><searchLink fieldCode="DE" term="%22Magnetic+resonance%22">Magnetic resonance</searchLink>
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  Data: This review article provides an overview of a range of recent technical developments in advanced arterial spin labeling (ASL) methods that have been developed or adopted by the community since the publication of a previous ASL consensus paper by Alsop et al. It is part of a series of review/recommendation papers from the International Society for Magnetic Resonance in Medicine Perfusion Study Group. Here, we focus on advancements in readouts and trajectories, image reconstruction, noise reduction, partial volume correction, quantification of nonperfusion parameters, fMRI, fingerprinting, vessel selective ASL, angiography, deep learning, and ultrahigh field ASL. We aim to provide a high level of understanding of these new approaches and some guidance for their implementation, with the goal of facilitating the adoption of such advances by research groups and by MRI vendors. Topics outside the scope of this article that are reviewed at length in separate articles include velocity selective ASL, multiple‐timepoint ASL, body ASL, and clinical ASL recommendations. [ABSTRACT FROM AUTHOR]
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  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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