2014
DOI: 10.1002/mrm.25479
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Myocardial perfusion assessment in humans using steady‐pulsed arterial spin labeling

Abstract: spASL was able to quantify MBF in healthy subjects under free breathing. Because quantification with ASL is more direct than with first-pass perfusion MRI, it appears particularly suited for pathologies with diffuse microvascular alterations, MBF reserve, and follow-up studies.

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Cited by 19 publications
(29 citation statements)
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References 30 publications
(40 reference statements)
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“…In addition, MT effects are known to be greater when the duration between the tag pulse and read-out acquisition is substantially short (Capron et al, 2014). In our method, the TI time between Time-SLIP tag pulse and the read-out acquisition, is relatively long ranging from 103 to 1400 ms.…”
Section: Discussionmentioning
confidence: 97%
“…In addition, MT effects are known to be greater when the duration between the tag pulse and read-out acquisition is substantially short (Capron et al, 2014). In our method, the TI time between Time-SLIP tag pulse and the read-out acquisition, is relatively long ranging from 103 to 1400 ms.…”
Section: Discussionmentioning
confidence: 97%
“…The time course of SPIL resembles the recently introduced steady‐pulsed ASL (spASL) approach to cardiac perfusion . However, SPIL and spASL differ in their geometry, specifically, in where labeling takes place.…”
Section: Discussionmentioning
confidence: 98%
“…It would be interesting in future work to compare results between this free breathing FAIR technique and spASL introduced by Capron et al, which was also applied during free breathing, since in their study the authors compared the spASL data with FAIR ASL data acquired during breath holding and therefore limited to six label‐control pairs.…”
Section: Discussionmentioning
confidence: 99%
“…However, scan efficiency was compromised because of a 50% navigator acceptance rate, and therefore scan time was prolonged. Capron et al have also described a free breathing steady pulsed ASL (spASL) technique together with a retrospective image exclusion criterion using a contour‐based cross correlation algorithm, that resulted in discarding approximately 20% of the acquired data . However, this was only applied to spASL and not to FAIR ASL.…”
Section: Introductionmentioning
confidence: 99%