High-Speed Real-Time Resting State fMRI using Multi-Slab Echo-Volumar Imaging
We recently demonstrated that ultra-high-speed real-time fMRI using multi-slab echo-volumar imaging (MEVI) significantly increases sensitivity for mapping task-related activation and resting state networks (RSNs) compared to echo-planar imaging (Posse et al. 2012). In the present study we characteri...
| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2013-08-01
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| Series: | Frontiers in Human Neuroscience |
| Subjects: | |
| Online Access: | http://journal.frontiersin.org/Journal/10.3389/fnhum.2013.00479/full |
| _version_ | 1819179440836444160 |
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| author | Stefan ePosse Stefan ePosse Stefan ePosse Elena eAckley Radu eMutihac Radu eMutihac Tongsheng eZhang Ruslan eHummatov Massoud eAkhtari Muhammad Omar Chohan Bruce eFisch Howard eYonas |
| author_facet | Stefan ePosse Stefan ePosse Stefan ePosse Elena eAckley Radu eMutihac Radu eMutihac Tongsheng eZhang Ruslan eHummatov Massoud eAkhtari Muhammad Omar Chohan Bruce eFisch Howard eYonas |
| author_sort | Stefan ePosse |
| collection | DOAJ |
| description | We recently demonstrated that ultra-high-speed real-time fMRI using multi-slab echo-volumar imaging (MEVI) significantly increases sensitivity for mapping task-related activation and resting state networks (RSNs) compared to echo-planar imaging (Posse et al. 2012). In the present study we characterize the sensitivity of MEVI for mapping RSN connectivity dynamics, comparing independent component analysis (ICA) and a novel seed-based connectivity analysis (SBCA) that combines sliding-window correlation analysis with meta-statistics. This SBCA approach is shown to minimize the effects of confounds, such as movement, and CSF and white matter signal changes, and enables real-time monitoring of RSN dynamics at time scales of tens of seconds. We demonstrate highly sensitive mapping of eloquent cortex in the vicinity of brain tumors and arteriovenous malformations, and detection of abnormal resting state connectivity in epilepsy. In patients with motor impairment, resting state fMRI provided focal localization of sensorimotor cortex compared with more diffuse activation in task-based fMRI. The fast acquisition speed of MEVI enabled segregation of cardiac-related signal pulsation using ICA, which revealed distinct regional differences in pulsation amplitude and waveform, elevated signal pulsation in patients with arteriovenous malformations and a trend towards reduced pulsatility in gray matter of patients compared with healthy controls. Mapping cardiac pulsation in cortical gray matter may carry important functional information that distinguishes healthy from diseased tissue vasculature. This novel fMRI methodology is particularly promising for mapping eloquent cortex in patients with neurological disease, having variable degree of cooperation in task-based fMRI. In conclusion, ultra-high-real-time speed fMRI enhances the sensitivity of mapping the dynamics of resting state connectivity and cerebrovascular pulsatility for clinical and neuroscience research applications. |
| first_indexed | 2024-12-22T21:58:29Z |
| format | Article |
| id | doaj.art-234d87fe6dc84cd5a0def02b9542d75c |
| institution | Directory Open Access Journal |
| issn | 1662-5161 |
| language | English |
| last_indexed | 2024-12-22T21:58:29Z |
| publishDate | 2013-08-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Human Neuroscience |
| spelling | doaj.art-234d87fe6dc84cd5a0def02b9542d75c2022-12-21T18:11:10ZengFrontiers Media S.A.Frontiers in Human Neuroscience1662-51612013-08-01710.3389/fnhum.2013.0047947074High-Speed Real-Time Resting State fMRI using Multi-Slab Echo-Volumar ImagingStefan ePosse0Stefan ePosse1Stefan ePosse2Elena eAckley3Radu eMutihac4Radu eMutihac5Tongsheng eZhang6Ruslan eHummatov7Massoud eAkhtari8Muhammad Omar Chohan9Bruce eFisch10Howard eYonas11University of New Mexico School of MedicineUniversity of New Mexico School of EngineeringUniversity of New Mexico School of ScienceUniversity of New Mexico School of MedicineUniversity of BucharestWalter Reed Army Institute of ResearchUniversity of New Mexico School of MedicineUniversity of New Mexico School of ScienceUCLAUniversity of New Mexico School of MedicineUniversity of New Mexico School of MedicineUniversity of New Mexico School of MedicineWe recently demonstrated that ultra-high-speed real-time fMRI using multi-slab echo-volumar imaging (MEVI) significantly increases sensitivity for mapping task-related activation and resting state networks (RSNs) compared to echo-planar imaging (Posse et al. 2012). In the present study we characterize the sensitivity of MEVI for mapping RSN connectivity dynamics, comparing independent component analysis (ICA) and a novel seed-based connectivity analysis (SBCA) that combines sliding-window correlation analysis with meta-statistics. This SBCA approach is shown to minimize the effects of confounds, such as movement, and CSF and white matter signal changes, and enables real-time monitoring of RSN dynamics at time scales of tens of seconds. We demonstrate highly sensitive mapping of eloquent cortex in the vicinity of brain tumors and arteriovenous malformations, and detection of abnormal resting state connectivity in epilepsy. In patients with motor impairment, resting state fMRI provided focal localization of sensorimotor cortex compared with more diffuse activation in task-based fMRI. The fast acquisition speed of MEVI enabled segregation of cardiac-related signal pulsation using ICA, which revealed distinct regional differences in pulsation amplitude and waveform, elevated signal pulsation in patients with arteriovenous malformations and a trend towards reduced pulsatility in gray matter of patients compared with healthy controls. Mapping cardiac pulsation in cortical gray matter may carry important functional information that distinguishes healthy from diseased tissue vasculature. This novel fMRI methodology is particularly promising for mapping eloquent cortex in patients with neurological disease, having variable degree of cooperation in task-based fMRI. In conclusion, ultra-high-real-time speed fMRI enhances the sensitivity of mapping the dynamics of resting state connectivity and cerebrovascular pulsatility for clinical and neuroscience research applications.http://journal.frontiersin.org/Journal/10.3389/fnhum.2013.00479/fullEpilepsyICAbrain tumorarteriovenous malformationreal-time fMRIresting state fMRI |
| spellingShingle | Stefan ePosse Stefan ePosse Stefan ePosse Elena eAckley Radu eMutihac Radu eMutihac Tongsheng eZhang Ruslan eHummatov Massoud eAkhtari Muhammad Omar Chohan Bruce eFisch Howard eYonas High-Speed Real-Time Resting State fMRI using Multi-Slab Echo-Volumar Imaging Frontiers in Human Neuroscience Epilepsy ICA brain tumor arteriovenous malformation real-time fMRI resting state fMRI |
| title | High-Speed Real-Time Resting State fMRI using Multi-Slab Echo-Volumar Imaging |
| title_full | High-Speed Real-Time Resting State fMRI using Multi-Slab Echo-Volumar Imaging |
| title_fullStr | High-Speed Real-Time Resting State fMRI using Multi-Slab Echo-Volumar Imaging |
| title_full_unstemmed | High-Speed Real-Time Resting State fMRI using Multi-Slab Echo-Volumar Imaging |
| title_short | High-Speed Real-Time Resting State fMRI using Multi-Slab Echo-Volumar Imaging |
| title_sort | high speed real time resting state fmri using multi slab echo volumar imaging |
| topic | Epilepsy ICA brain tumor arteriovenous malformation real-time fMRI resting state fMRI |
| url | http://journal.frontiersin.org/Journal/10.3389/fnhum.2013.00479/full |
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