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Single Voxel Proton Spectroscopy for Neurofeedback at 7 Tesla

Echo-planar imaging (EPI) in fMRI is regularly used to reveal BOLD activation in presubscribed regions of interest (ROI). The response is mediated by relative changes in T2* which appear as changes in the image pixel intensities. We have proposed an application of functional single-voxel proton spec...

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Detalles Bibliográficos
Autores principales: Koush, Yury, Elliott, Mark A., Mathiak, Klaus
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3886242/
https://www.ncbi.nlm.nih.gov/pubmed/24416473
http://dx.doi.org/10.3390/ma4091548
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author Koush, Yury
Elliott, Mark A.
Mathiak, Klaus
author_facet Koush, Yury
Elliott, Mark A.
Mathiak, Klaus
author_sort Koush, Yury
collection PubMed
description Echo-planar imaging (EPI) in fMRI is regularly used to reveal BOLD activation in presubscribed regions of interest (ROI). The response is mediated by relative changes in T2* which appear as changes in the image pixel intensities. We have proposed an application of functional single-voxel proton spectroscopy (fSVPS) for real-time studies at ultra-high MR field which can be comparable to the EPI BOLD fMRI technique. A spin-echo SVPS protocol without water suppression was acquired with 310 repetitions on a 7T Siemens MR scanner (TE/TR = 20/1000 ms, flip angle α = 90°, voxel size 10 × 10 × 10 mm(3)). Transmitter reference voltage was optimized for the voxel location. Spectral processing of the water signal free induction decay (FID) using log-linear regression was used to estimate the T2* change between rest and activation of a functional task. The FID spectrum was filtered with a Gaussian window around the water peak, and log-linear regression was optimized for the particular ROI by adoption of the linearization length. The spectroscopic voxel was positioned on an ROI defined from a real-time fMRI EPI BOLD localizer. Additional online signal processing algorithms performed signal drift removal (exponential moving average), despiking and low-pass filtering (modified Kalman filter) and, finally, the dynamic feedback signal normalization. Two functional tasks were used to estimate the sensitivity of the SVPS method compared to BOLD signal changes, namely the primary motor cortex (PMC, left hand finger tapping) and visual cortex (VC, blinking checkerboard). Four healthy volunteers performed these tasks and an additional session using real-time signal feedback modulating their activation level of the PMC. Results show that single voxel spectroscopy is able to provide a good and reliable estimation of the ΒΟLD signal changes. Small data size and FID signal processing instead of processing entire brain volumes as well as more information revealed from the acquired total water spectrum, i.e., direct estimation of the T2* values and B0 changes, make SVPS proton spectroscopy suitable and advantageous for real-time neurofeedback studies. Particular challenges of ultra-high field spectroscopy due to the non-linearity in the spectral information, e.g., poor main magnetic field homogeneity and the absence of motion correction for the SVPS sequence may lead to the special artifacts in the control signal which still need to be addressed. The contrast to noise ratio (CNR), experimental statistic (t-values) and percent signal change were used as quality parameters to estimate the method performance. The potential and challenges of the spectroscopic approach for fMRI studies needs to be further investigated.
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spelling pubmed-38862422014-01-09 Single Voxel Proton Spectroscopy for Neurofeedback at 7 Tesla Koush, Yury Elliott, Mark A. Mathiak, Klaus Materials (Basel) Article Echo-planar imaging (EPI) in fMRI is regularly used to reveal BOLD activation in presubscribed regions of interest (ROI). The response is mediated by relative changes in T2* which appear as changes in the image pixel intensities. We have proposed an application of functional single-voxel proton spectroscopy (fSVPS) for real-time studies at ultra-high MR field which can be comparable to the EPI BOLD fMRI technique. A spin-echo SVPS protocol without water suppression was acquired with 310 repetitions on a 7T Siemens MR scanner (TE/TR = 20/1000 ms, flip angle α = 90°, voxel size 10 × 10 × 10 mm(3)). Transmitter reference voltage was optimized for the voxel location. Spectral processing of the water signal free induction decay (FID) using log-linear regression was used to estimate the T2* change between rest and activation of a functional task. The FID spectrum was filtered with a Gaussian window around the water peak, and log-linear regression was optimized for the particular ROI by adoption of the linearization length. The spectroscopic voxel was positioned on an ROI defined from a real-time fMRI EPI BOLD localizer. Additional online signal processing algorithms performed signal drift removal (exponential moving average), despiking and low-pass filtering (modified Kalman filter) and, finally, the dynamic feedback signal normalization. Two functional tasks were used to estimate the sensitivity of the SVPS method compared to BOLD signal changes, namely the primary motor cortex (PMC, left hand finger tapping) and visual cortex (VC, blinking checkerboard). Four healthy volunteers performed these tasks and an additional session using real-time signal feedback modulating their activation level of the PMC. Results show that single voxel spectroscopy is able to provide a good and reliable estimation of the ΒΟLD signal changes. Small data size and FID signal processing instead of processing entire brain volumes as well as more information revealed from the acquired total water spectrum, i.e., direct estimation of the T2* values and B0 changes, make SVPS proton spectroscopy suitable and advantageous for real-time neurofeedback studies. Particular challenges of ultra-high field spectroscopy due to the non-linearity in the spectral information, e.g., poor main magnetic field homogeneity and the absence of motion correction for the SVPS sequence may lead to the special artifacts in the control signal which still need to be addressed. The contrast to noise ratio (CNR), experimental statistic (t-values) and percent signal change were used as quality parameters to estimate the method performance. The potential and challenges of the spectroscopic approach for fMRI studies needs to be further investigated. MDPI 2011-09-15 /pmc/articles/PMC3886242/ /pubmed/24416473 http://dx.doi.org/10.3390/ma4091548 Text en © 2011 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/).
spellingShingle Article
Koush, Yury
Elliott, Mark A.
Mathiak, Klaus
Single Voxel Proton Spectroscopy for Neurofeedback at 7 Tesla
title Single Voxel Proton Spectroscopy for Neurofeedback at 7 Tesla
title_full Single Voxel Proton Spectroscopy for Neurofeedback at 7 Tesla
title_fullStr Single Voxel Proton Spectroscopy for Neurofeedback at 7 Tesla
title_full_unstemmed Single Voxel Proton Spectroscopy for Neurofeedback at 7 Tesla
title_short Single Voxel Proton Spectroscopy for Neurofeedback at 7 Tesla
title_sort single voxel proton spectroscopy for neurofeedback at 7 tesla
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3886242/
https://www.ncbi.nlm.nih.gov/pubmed/24416473
http://dx.doi.org/10.3390/ma4091548
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