Feasibility of spiral fMRI based on an LTI gradient model

Spiral imaging is very well suited for functional MRI, however its use has been limited by the fact that artifacts caused by gradient imperfections and B0 inhomogeneity are more difficult to correct compared to EPI. Effective correction requires accurate knowledge of the traversed k-space trajectory...

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Autores principales:	Nadine N. Graedel, Lars Kasper, Maria Engel, Jennifer Nussbaum, Bertram J. Wilm, Klaas P. Pruessmann, S. Johanna Vannesjo
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	Functional MRI High-resolution fMRI Spiral imaging Single-shot spiral Linear time-invariant GIRF Neurosciences. Biological psychiatry. Neuropsychiatry RC321-571
Acceso en línea:	https://doaj.org/article/a3ab65573f0d42e3b5a18dae775f83a9
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spelling	oai:doaj.org-article:a3ab65573f0d42e3b5a18dae775f83a92021-11-22T04:18:51ZFeasibility of spiral fMRI based on an LTI gradient model1095-957210.1016/j.neuroimage.2021.118674https://doaj.org/article/a3ab65573f0d42e3b5a18dae775f83a92021-12-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S1053811921009472https://doaj.org/toc/1095-9572Spiral imaging is very well suited for functional MRI, however its use has been limited by the fact that artifacts caused by gradient imperfections and B0 inhomogeneity are more difficult to correct compared to EPI. Effective correction requires accurate knowledge of the traversed k-space trajectory. With the goal of making spiral fMRI more accessible, we have evaluated image reconstruction using trajectories predicted by the gradient impulse response function (GIRF), which can be determined in a one-time calibration step.GIRF-predicted reconstruction was tested for high-resolution (0.8 mm) fMRI at 7T. Image quality and functional results of the reconstructions using GIRF-prediction were compared to reconstructions using the nominal trajectory and concurrent field monitoring.The reconstructions using nominal spiral trajectories contain substantial artifacts and the activation maps contain misplaced activation. Image artifacts are substantially reduced when using the GIRF-predicted reconstruction, and the activation maps for the GIRF-predicted and monitored reconstructions largely overlap. The GIRF reconstruction provides a large increase in the spatial specificity of the activation compared to the nominal reconstruction.The GIRF-reconstruction generates image quality and fMRI results similar to using a concurrently monitored trajectory. The presented approach does not prolong or complicate the fMRI acquisition. Using GIRF-predicted trajectories has the potential to enable high-quality spiral fMRI in situations where concurrent trajectory monitoring is not available.Nadine N. GraedelLars KasperMaria EngelJennifer NussbaumBertram J. WilmKlaas P. PruessmannS. Johanna VannesjoElsevierarticleFunctional MRIHigh-resolution fMRISpiral imagingSingle-shot spiralLinear time-invariantGIRFNeurosciences. Biological psychiatry. NeuropsychiatryRC321-571ENNeuroImage, Vol 245, Iss , Pp 118674- (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Functional MRI High-resolution fMRI Spiral imaging Single-shot spiral Linear time-invariant GIRF Neurosciences. Biological psychiatry. Neuropsychiatry RC321-571
spellingShingle	Functional MRI High-resolution fMRI Spiral imaging Single-shot spiral Linear time-invariant GIRF Neurosciences. Biological psychiatry. Neuropsychiatry RC321-571 Nadine N. Graedel Lars Kasper Maria Engel Jennifer Nussbaum Bertram J. Wilm Klaas P. Pruessmann S. Johanna Vannesjo Feasibility of spiral fMRI based on an LTI gradient model
description	Spiral imaging is very well suited for functional MRI, however its use has been limited by the fact that artifacts caused by gradient imperfections and B0 inhomogeneity are more difficult to correct compared to EPI. Effective correction requires accurate knowledge of the traversed k-space trajectory. With the goal of making spiral fMRI more accessible, we have evaluated image reconstruction using trajectories predicted by the gradient impulse response function (GIRF), which can be determined in a one-time calibration step.GIRF-predicted reconstruction was tested for high-resolution (0.8 mm) fMRI at 7T. Image quality and functional results of the reconstructions using GIRF-prediction were compared to reconstructions using the nominal trajectory and concurrent field monitoring.The reconstructions using nominal spiral trajectories contain substantial artifacts and the activation maps contain misplaced activation. Image artifacts are substantially reduced when using the GIRF-predicted reconstruction, and the activation maps for the GIRF-predicted and monitored reconstructions largely overlap. The GIRF reconstruction provides a large increase in the spatial specificity of the activation compared to the nominal reconstruction.The GIRF-reconstruction generates image quality and fMRI results similar to using a concurrently monitored trajectory. The presented approach does not prolong or complicate the fMRI acquisition. Using GIRF-predicted trajectories has the potential to enable high-quality spiral fMRI in situations where concurrent trajectory monitoring is not available.
format	article
author	Nadine N. Graedel Lars Kasper Maria Engel Jennifer Nussbaum Bertram J. Wilm Klaas P. Pruessmann S. Johanna Vannesjo
author_facet	Nadine N. Graedel Lars Kasper Maria Engel Jennifer Nussbaum Bertram J. Wilm Klaas P. Pruessmann S. Johanna Vannesjo
author_sort	Nadine N. Graedel
title	Feasibility of spiral fMRI based on an LTI gradient model
title_short	Feasibility of spiral fMRI based on an LTI gradient model
title_full	Feasibility of spiral fMRI based on an LTI gradient model
title_fullStr	Feasibility of spiral fMRI based on an LTI gradient model
title_full_unstemmed	Feasibility of spiral fMRI based on an LTI gradient model
title_sort	feasibility of spiral fmri based on an lti gradient model
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/a3ab65573f0d42e3b5a18dae775f83a9
work_keys_str_mv	AT nadinengraedel feasibilityofspiralfmribasedonanltigradientmodel AT larskasper feasibilityofspiralfmribasedonanltigradientmodel AT mariaengel feasibilityofspiralfmribasedonanltigradientmodel AT jennifernussbaum feasibilityofspiralfmribasedonanltigradientmodel AT bertramjwilm feasibilityofspiralfmribasedonanltigradientmodel AT klaasppruessmann feasibilityofspiralfmribasedonanltigradientmodel AT sjohannavannesjo feasibilityofspiralfmribasedonanltigradientmodel
_version_	1718418240593461248

Feasibility of spiral fMRI based on an LTI gradient model

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