High-Speed Real-Time Resting-State fMRI Using Multi-Slab Echo-Volumar Imaging

Abstract

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 arterio-venous 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 arterio-venous malformations and a trend toward 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 cerebro-vascular pulsatility for clinical and neuroscience research applications.

Ultra-fast magnetic resonance encephalography of physiological brain activity – Glymphatic pulsation mechanisms?

“…The negative change is strong in CSF and thus cannot be solely a classical BOLD susceptibility change. Moreover, in-flow effects would rather result in positive in signal changes 33 and would in any case not be expected given the 3D MREG excitation. The negative signal changes are more likely due to a disruption of steady-state precession caused by CSF impulses, which lead to incomplete T2 relaxation.…”

Advantages and disadvantages of a fast fMRI sequence in the context of EEG–fMRI investigation of epilepsy patients: A realistic simulation study

“…Multiple high temporal resolution fMRI sequences were developed (Posse et al, 2012;Asslander et al, 2013;Chang et al, 2013) to help shed some light on basic neuroscience questions as well as increased clinical impact in understanding some neurodegenerative disorders that rely on functional imaging (Posse et al, 2013). Functional connectivity and epilepsy studies using those high resolution sequences have been reported (Posse et al, 2012;Lee et al, 2013;Jacobs et al, 2014), but the need for a sub-second scale fMRI sequence is still uncertain given the sluggish and slow BOLD response.…”

“…A more recent sequence, echo-shifted InI, was able to perform fMRI at a TR of 30 ms and to show group-level hemodynamic responses timing differences as low as 50 ms in the visual system (Chang et al, 2013), suggesting that subtle neural activation timing are tractable with fMRI. Fast Multi-slab echo-volumar imaging (EVI) was shown to reveal resting state networks with high sensitivity in measurement times as short as 75 s (Posse et al, 2012;Posse et al, 2013), having clinical implications for patient populations with variable degrees of cooperation. Other connectivity studies relying on such fast sampling sequences have indeed shown increased statistical power and revealed interesting brain networks oscillating in the 0.5-0.8 Hz band, well beyond the very low frequency range (0.01-0.1 Hz) traditionally studied using the conventional EPI sequence .…”

ICA of fMRI studies: new approaches and cutting edge applications

“…The capacity of ICA to find common patterns of activation in huge cohorts of subjects is demonstrated by the parallel computing approach described by Kalcher et al (2012) and the use of ICA with cutting edge MR methods are presented by the groups of Stefan Posse [Echo Volume Imaging (Posse et al, 2013)], Markus Barth [EEG-fMRI (Meyer et al, 2013) and Ultra-Fast Generalized Inverse Imaging (Boyacioglu et al, 2013)], and Jorge Jovicich [realtime fMRI (Soldati et al, 2013a,b)]. …”