Identifying Dysfunctional Cortex: Dissociable Effects of Stroke and Aging on Resting State Dynamics in MEG and fMRI.

Spontaneous signals in neuroimaging data may provide information on cortical health in disease and aging, but the relative sensitivity of different approaches is unknown. In the present study, we compared different but complementary indicators of neural dynamics in resting-state MEG and BOLD fMRI, and their relationship with blood flow. Participants included patients with post-stroke aphasia, age-matched controls, and young adults. The complexity of brain activity at rest was quantified in MEG using spectral analysis and multiscale entropy (MSE) measures, whereas BOLD variability was quantified as the standard deviation (SDBOLD), mean squared successive difference (MSSD), and sample entropy of the BOLD time series. We sought to assess the utility of signal variability and complexity measures as markers of age-related changes in healthy adults and perilesional dysfunction in chronic stroke. The results indicate that reduced BOLD variability is a robust finding in aging, whereas MEG measures are more sensitive to the cortical abnormalities associated with stroke. Furthermore, reduced complexity of MEG signals in perilesional tissue were correlated with hypoperfusion as assessed with arterial spin labeling (ASL), while no such relationship was apparent with BOLD variability. These findings suggest that MEG signal complexity offers a sensitive index of neural dysfunction in perilesional tissue in chronic stroke, and that these effects are clearly distinguishable from those associated with healthy aging.

Origins of the BOLD post-stimulus undershoot.

The interpretation of the blood-oxygenation level-dependent (BOLD) post-stimulus undershoot has been a topic of considerable interest, as the mechanisms behind this prominent BOLD transient may provide valuable clues on the neurovascular response process and energy supply routes of the brain. Biomechanical theories explain the origin of the BOLD undershoot through the passive ballooning of post-capillary vessels which leads to an increase in venous blood volume (CBV(v), comprising deoxygenated blood in capillary, venular and arteriolar compartments), resulting in susceptibility-induced signal decrease. While there has been substantial evidence supporting a role for venous ballooning, there have also been reports arguing for a prolonged post-stimulus elevation in cerebral oxygenation consumption (CMRo(2)) as the primary cause. Furthermore, a contribution of post-stimulus cerebral blood flow (CBF) undershoots has also been demonstrated. To clarify the role of the venous compartment in causing the BOLD undershoot, we performed in vivo fMRI measurements of the transient DeltaCBV(v), DeltaCBF and DeltaBOLD responses in healthy humans. We observed a slow post-stimulus return to baseline in venous CBV which supports the existence of a passive "balloon" effect, implying that previous observations of a quicker recovery of the total CBV response may be dominated by arterial CBV change. Our findings also support a significant contribution from the CBF undershoots, which, combined with a slow venous CBV response, would account for much of the BOLD undershoot.

Human whole blood T2 relaxometry at 3 Tesla.

A precise understanding of human blood spin-spin relaxation is of major importance for numerous applications, particularly functional magnetic resonance imaging (fMRI), which is increasingly performed at 3 Tesla. It is well known that T2 measured from partially deoxygenated blood depends on the Carr-Purcell Meiboom-Gill (CPMG) refocusing interval (tau180) and on blood oxygenation (Y), yet debate remains over the quantification of this phenomenon, primarily with respect to the accuracy of its characterization by the diffusion and fast two-site exchange models. In this study, a detailed characterization of the deoxygenation-induced T2 reduction in human whole blood, as well as a comprehensive assessment of the role of tau180, were performed at 3 T. The diffusion model was found to better fit the observed T2 behavior as compared with the exchange model. The estimated diffusion-model parameters suggest the T2 decay enhancement at 3 T is due to a linear increase in the magnitude of deoxygenation-induced field inhomogeneities with field strength. These findings also confirm the potential of tau180 manipulation in measuring changes in venous blood volume.

Cerebral blood flow measurement using fMRI and PET: a cross-validation study.

An important aspect of functional magnetic resonance imaging (fMRI) is the study of brain hemodynamics, and MR arterial spin labeling (ASL) perfusion imaging has gained wide acceptance as a robust and noninvasive technique. However, the cerebral blood flow (CBF) measurements obtained with ASL fMRI have not been fully validated, particularly during global CBF modulations. We present a comparison of cerebral blood flow changes (DeltaCBF) measured using a flow-sensitive alternating inversion recovery (FAIR) ASL perfusion method to those obtained using H(2) (15)O PET, which is the current gold standard for in vivo imaging of CBF. To study regional and global CBF changes, a group of 10 healthy volunteers were imaged under identical experimental conditions during presentation of 5 levels of visual stimulation and one level of hypercapnia. The CBF changes were compared using 3 types of region-of-interest (ROI) masks. FAIR measurements of CBF changes were found to be slightly lower than those measured with PET (average DeltaCBF of 21.5 +/- 8.2% for FAIR versus 28.2 +/- 12.8% for PET at maximum stimulation intensity). Nonetheless, there was a strong correlation between measurements of the two modalities. Finally, a t-test comparison of the slopes of the linear fits of PET versus ASL DeltaCBF for all 3 ROI types indicated no significant difference from unity (P > .05).

The impact of partial-volume effects in dynamic susceptibility contrast magnetic resonance perfusion imaging.

PURPOSE: To demonstrate the degree of the cerebral blood flow (CBF) estimation bias that could arise from distortion of the arterial input function (AIF) as a result of partial-volume effects (PVEs) in dynamic susceptibility contrast (DSC) magnetic resonance imaging (MRI). MATERIALS AND METHODS: A model of the volume fraction an artery occupies in a voxel was devised, and a mathematical relationship between the amount of PVE and the measured baseline MR signal intensity was derived. Based on this model, simulation studies were performed to assess the impact of PVE on CBF. Furthermore, the effectiveness of linear PVE compensation approaches on the concentration function was investigated. RESULTS: Simulation results showed a nonlinear relationship between PVE and the resulting CBF measurement error. In addition to AIF underestimation, PVE also causes distortions of AIF frequency characteristics, leading to CBF errors varying with mean transit time (MTT). An uncorrected AIF measured at a voxel with a partial-volume fraction of

Reassessing the clinical efficacy of two MR quantitative DSC PWI CBF algorithms following cross-calibration with PET images.

Clinical cerebral blood flow (CBF) maps generated through dynamic- susceptibility contrast (DSC) magnetic resonance (MR) perfusion imaging are currently cross-calibrated with PET studies. The cross-calibration is achieved by rescaling the MR CBF values so that normal white matter CBF corresponds to 22 ml/100 g/min. Examples are provided in this paper to show how this rescaling procedure changes both the clinical interpretation of CBF maps and the manner by which the performance of a given deconvolution algorithm should be assessed. (i) Singular-value decomposition-based (SVD) algorithms produce absolute CBF estimates that are inherently under-estimated for all tissue mean transit times (MTT) but, after rescaling, will generate CBF maps that are over-estimated for MTT >4.8 s. (ii) In principle, frequency-domain modelling techniques are expected to be inherently less sensitive to contrast recirculation biases than the time-domain SVD algorithms. However, it is shown that both CBF algorithms become greatly less sensitive to distortions from recirculation after clinical cross-calibration through rescaling has been performed. It is concluded that, when rescaling procedures are employed, it is relatively more important to develop deconvolution algorithms that produce CBF estimates with accuracies that vary little with MTT than to produce algorithms that provide inherently more accurate CBF estimates, but whose relative accuracy varies significantly with MTT.

Advantages of frequency-domain modeling in dynamic-susceptibility contrast magnetic resonance cerebral blood flow quantification.

In dynamic-susceptibility contrast magnetic resonance perfusion imaging, the cerebral blood flow (CBF) is estimated from the tissue residue function obtained through deconvolution of the contrast concentration functions. However, the reliability of CBF estimates obtained by deconvolution is sensitive to various distortions including high-frequency noise amplification. The frequency-domain Fourier transform-based and the time-domain singular-value decomposition-based (SVD) algorithms both have biases introduced into their CBF estimates when noise stability criteria are applied or when contrast recirculation is present. The recovery of the desired signal components from amid these distortions by modeling the residue function in the frequency domain is demonstrated. The basic advantages and applicability of the frequency-domain modeling concept are explored through a simple frequency-domain Lorentzian model (FDLM); with results compared to standard SVD-based approaches. The performance of the FDLM method is model dependent, well representing residue functions in the exponential family while less accurately representing other functions.