Techniques for blood volume fMRI with VASO: From low-resolution mapping towards sub-millimeter layer-dependent applications

Abstract

Poser, B. A. (2018). Techniques for blood volume fMRI with VASO: From low-resolution mapping towards sub-millimeter layerdependent applications. Neuroimage, 164,[131][132][133][134][135][136][137][138][139][140][141][142][143] Document license: CC BY-NC-ND Please check the document version of this publication:• A submitted manuscript is the version of the article upon submission and before peer-review. There can be important differences between the submitted version and the official published version of record. People interested in the research are advised to contact the author for the final version of the publication, or visit the DOI to the publisher's website.• The final author version and the galley proof are versions of the publication after peer review.• The final published version features the final layout of the paper including the volume, issue and page numbers. Link to publication General rightsCopyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.• Users may download and print one copy of any publication from the public portal for the purpose of private study or research.• You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal.If the publication is distributed under the terms of Article 25fa of the Dutch Copyright Act, indicated by the "Taverne" license above, please follow below link for the End User Agreement:www.umlib.nl/taverne-license Take down policyIf you believe that this document breaches copyright please contact us at:repository@maastrichtuniversity.nl providing details and we will investigate your claim. applications at ultra-high magnetic fields (7 T and higher). Non-invasive CBV fMRI using

Ultra-high resolution blood volume fMRI and BOLD fMRI in humans at 9.4 T: Capabilities and challenges

“…The average tapping-induced CBV change of 2.6±0.7 ml per 100 ml of tissue (mean ± STD) is in very good agreement with previous studies using the same task at slightly lower resolutions (0.78 mm - 0.8 mm) (Guidi et al, 2016; Huber et al, 2018, 2017a, 2015a). However, the measured value of 2.6±0.7 ml per 100 ml of tissue (mean ± STD) is significantly higher compared to studies using the same task at resolutions of 1.5 – 3 mm (Donahue et al, 2009a).…”

“…However, the measured value of 2.6±0.7 ml per 100 ml of tissue (mean ± STD) is significantly higher compared to studies using the same task at resolutions of 1.5 – 3 mm (Donahue et al, 2009a). This resolution-dependence of the measured CBV change is presumably coming from differing partial volume effects at different voxel sizes as estimated earlier (Huber et al, 2018). …”

“…In addition to the SNR advantage of 3D over 2D readouts at high resolution (Huber et al, 2018), the slab-selective nature of 3D requires the use of much lower flip angles and hence results in a much lower SAR footprint than conventional 2D-EPI. As in our previous work (Huber et al, 2018, 2017a), we used a VASO sequence based on 3D-EPI implementations from (Poser et al, 2010) with support for CAIPIRINHA sampling (Poser et al, 2013).…”

“…As in our previous work (Huber et al, 2018, 2017a), we used a VASO sequence based on 3D-EPI implementations from (Poser et al, 2010) with support for CAIPIRINHA sampling (Poser et al, 2013). 3D slab fold-over along the second phase-encoding direction was minimized by using a sharp slab-selective excitation pulse, with a bandwidth-time- product of 25.…”

“…Here, we implemented the FLASH-ACS approach and our pilot experiments suggested that FLASH-GRAPPA ACS provide higher tSNR as opposed to previously used LIN→PAR acquisition schemes at 7 T (Huber et al, 2018). For the reconstruction, the vendor’s GRAPPA (Griswold et al, 2006) reconstruction algorithms were applied, using a 3×4 (read direction × phase direction) kernel.…”