Characterization of cardiac-related noise in fMRI of the cervical spinal cord

Magnetic resonance imaging (MRI) has recently been applied to study spinal cord function in humans. However, spinal functional MRI (fMRI) encounters major technical challenges with cardiac noise being considered a major source of noise. The present study relied on echo-planar imaging of the cervical cord at short TR (TR=250 ms; TE=40 ms; flip=45 degrees), combined with plethysmographic recordings to characterize the spatiotemporal properties of cardiac-induced signal changes in spinal fMRI. Frequency-based analyses examining signal change at the cardiac frequency confirmed mean fluctuations of about 10% (relative to the mean signal) in the spinal cord and surrounding cerebrospinal fluid (CSF), with maximal responses reaching up to 66% in some voxels. A spatial independent component analysis (sICA) confirmed that cardiac noise is an important source of variance in spinal fMRI with several components showing a response coherent with the cardiac frequency spectrum. The time course of the main cardiac components approximated a sinusoidal function tightly coupled to the cardiac systole with at least one component showing a comparable temporal profile across runs and subjects. Spatially, both the frequency-domain analysis and the sICA demonstrated cardiac noise distributed irregularly along the full rostrocaudal extent of the segments scanned with peaks concentrated in the ventral part of the lateral slices in all scans and subjects, consistent with the major channels of CSF flow. These results confirm that cardiac-induced changes are a significant source of noise likely to affect the detection of spinal Blood Oxygen Level Dependent (BOLD) responses. Most importantly, the complex spatiotemporal structure of cardiac noise is unlikely to be accounted for adequately by ad hoc linear methods, especially in data acquired using long TR (i.e. aliasing the cardiac frequency). However, the reliable spatiotemporal distribution of cardiac noise across scanning runs and within subjects may provide a valid means to identify and extract cardiac noise based on sICA methods.     

Images-based suppression of unwanted global signals in resting-state functional connectivity studies

Correlated fluctuations of low-frequency fMRI signal have been suggested to reflect functional connectivity among the involved regions. However, large-scale correlations are especially prone to spurious global modulations induced by coherent physiological noise. Cardiac and respiratory rhythms are the most offending component, and a tailored preprocessing is needed in order to reduce their impact. Several approaches have been proposed in the literature, generally based on the use of physiological recordings acquired during the functional scans, or on the extraction of the relevant information directly from the images. In this paper, the performances of the denoising approach based on general linear fitting of global signals of noninterest extracted from the functional scans were assessed. Results suggested that this approach is sufficiently accurate for the preprocessing of functional connectivity data.     

Improved functional mapping of the human amygdala using a standard functional magnetic resonance imaging sequence with simple modifications

As the amygdala is involved in various aspects of emotional processing, its characterization using neuroimaging modalities, such as functional magnetic resonance imaging (fMRI), is of great interest. However, in fMRI, the amygdala region suffers from susceptibility artifacts that are composed of signal dropouts and image distortions. Various technically demanding approaches to reduce these artifacts have been proposed, and most require alterations beyond a mere change of the acquisition parameters and cannot be easily implemented by the user without changing the MR sequence code. In the present study, we therefore evaluated the impact of simple alterations of the acquisition parameters of a standard gradient-echo echo-planar imaging technique at 3 T composed of echo times (TEs) of 27 and 36 ms as well as section thicknesses of 2 and 4 mm while retaining a section orientation parallel to the intercommissural plane and an in-plane resolution of 2x2 mm(2). In contrast to previous studies, we based our evaluation on the resulting activation maps using an emotional stimulation paradigm rather than on MR raw image quality only. Furthermore, we tested the effects of spatial smoothing of the functional raw data in the course of postprocessing using spatial filters of 4 and 8 mm. Regarding MR raw image quality, a TE of 27 ms and 2-mm sections resulted in the least susceptibility artifacts in the anteromedial aspect of the temporal lobe. The emotional stimulation paradigm resulted in robust bilateral amygdala activation for the approaches with 2-mm sections only -- but with larger activation volumes for a TE of 36 ms as compared with that of 27 ms. Moderate smoothing with a 4-mm spatial filter represented a good compromise between increased sensitivity and preserved specificity. In summary, we showed that rather than applying advanced modifications of the MR sequence, a simple increase in spatial resolution (i.e., the reduction of section thickness) is sufficient to improve the detectability of amygdala activation.     

A two-compartment gel phantom for optimization and quality assurance in clinical BOLD fMRI

Clinical applications of blood oxygen level-dependent (BOLD) functional magnetic resonance imaging (fMRI) depend heavily on robust paradigms, imaging methods and analysis procedures. In this work, as a means to optimize and perform quality assurance of the entire imaging and analysis chain, a phantom that provides a well known and reproducible signal change similar to a block type fMRI experiment is presented. It consists of two gel compartments with slightly different T2 that dynamically enter and leave the imaged volume. The homogeneous gel in combination with a cylindrical geometry results in a well-defined T*2 difference causing a signal difference between the two compartments in T*2-weighted MR images. From time series data obtained with the phantom, maps of percent signal change (PSC) and t-values are calculated. As an example of image parameter optimisation, the phantom is demonstrated to be useful for accurate determination of the influence of echo time (TE) on BOLD fMRI results, taking the t-value as a measure of sensitivity. In addition, the phantom is proposed as a tool for quality assurance (QA) since reproducible time series and t-maps are obtained in a series of independent repeat experiments. The phantom is relatively simple to build and can therefore be used by any clinical fMRI center.     

The phase shift index for marking functional asynchrony in Alzheimer's disease patients using fMRI

Our previous study suggested that the functional magnetic resonance imaging MRI (fMRI) COSLOF Index (CI) could be used as a quantitative biomarker for Alzheimer's disease (AD). The fMRI CI was lowest in the AD group (0.13+/-0.10), followed by the mild cognitive impairment (MCI) group (0.20+/-0.05) and the control group (0.34+/-0.09). The current study continues an investigation into which of the following two factors has a dominant role in determining the CI: the signal-to-noise ratio (SNR) or the phase shift of spontaneous low-frequency (SLF) components. By using a theoretical model for SLF components, we demonstrated that the normalized CI does not depend on the SNR of the SLF components. Further analysis shows that by taking the ratio of the cross-correlation coefficient to the maximum-shifted cross-correlation coefficient, the SNR factor can be canceled. Therefore, the determination of the phase shift index (PSI) method is independent of the SNR, and the PSI provides an accurate measure of the phase shift between SLF components. By applying this PSI method to the control, MCI and AD groups of subjects, experimental results demonstrated that the PSI was highest in the AD group (72.6+/-11.3 degrees ), followed by the MCI group (58.6+/-5.7 degrees ) and, finally, the control group (40.6+/-8.4 degrees ). These results suggest that the larger is the PSI value, the more asynchrony exists between SLF components.     

Drug-anaesthetic interaction in phMRI: the case of the psychotomimetic agent phencyclidine

Pharmacological magnetic resonance imaging (phMRI) provides a powerful means to map the effects of drugs on brain activity, with important applications in pharmacological research. However, phMRI studies in preclinical species are often conducted under general anaesthesia as a means to avoid head motion and to minimise the stress induced by the procedure. Under these conditions, the phMRI response to the drug of interest may be affected by interactions with the anaesthetic agent, with consequences for the interpretation of the data. Here, we have investigated the phMRI response to phencyclidine (PCP), an NMDA receptor blocker, in the halothane-anaesthetised rat for varying levels of anaesthesia and different PCP challenge doses. PCP induces psychotic-like symptoms in humans and laboratory animals and is widely applied as a pharmacological model of schizophrenia. However, PCP possesses anaesthetic properties per se, and its interactions with halothane might result in significant effects on the phMRI activation patterns. We observed two qualitatively different patterns of phMRI response. At 0.5 mg/kg iv PCP and 0.8% halothane maintenance anaesthesia, the lowest doses explored, an activation of discrete cortico-limbo-thalamic structures was observed, consistent with neuroimaging studies in humans and 2-deoxyglucose functional mapping in conscious animal models. However, higher anaesthetic concentrations or higher PCP challenge doses resulted in complete abolition of the positive response and in a widespread cortical deactivation (negative response). In the intermediate regime, we observed a dichotomic behaviour, with individual subjects showing one pattern or the other. These findings indicate a dose-dependent drug-anaesthetic interaction, with a complete reversal of the effects of PCP at higher challenge doses or HT concentrations.     

The effect of physiological noise in phase functional magnetic resonance imaging: from blood oxygen level-dependent effects to direct detection of neuronal currents

Recently, the possibility to use both magnitude and phase image sets for the statistical evaluation of fMRI has been proposed, with the prospective of increasing both statistical power and the spatial specificity. In the present work, several issues that affect the spatial and temporal stability in fMRI phase time series in the presence of physiologic noise processes are reviewed, discussed and illustrated by experiments performed at 3 T. The observed phase value is a fingerprint of the underlying voxel averaged magnetic field variations. Those related to physiological processes can be considered static or dynamic in relation to the temporal scale of a 2D acquisition and will play out on different spatial scales as well: globally across the entire images slice, and locally depending on the constituents and their relative fractions inside the MRI voxel. The 'static' respiration-induced effects lead to magneto-mechanic scan-to-scan variations in the global magnetic field but may also contribute to local BOLD fluctuations due to respiration-related variations in arterial carbon dioxide. Likewise, the 'dynamic' cardiac-related effects will lead to global susceptibility effects caused by pulsatile motion of the brain as well as local blood pressure-related changes in BOLD and changes in blood flow velocity. Finally, subject motion may lead to variations in both local and global tissue susceptibility that will be especially pronounced close to air cavities. Since dissimilar manifestations of physiological processes can be expected in phase and in magnitude images, a direct relationship between phase and magnitude scan-to-scan fluctuations cannot be assumed a priori. Therefore three different models were defined for the phase stability, each dependent on the relation between phase and magnitude variations and the best will depend on the underlying noise processes. By experiments on healthy volunteers at rest, we showed that phase stability depends on the type of post-processing and can be improved by reducing the low-frequency respiration-induced mechano-magnetic effects. Although the manifestations of physiological noise were in general more pronounced in phase than in magnitude images, due to phase wraps and global Bo effects, we suggest that a phase stability similar to that found in magnitude could theoretically be achieved by adequate correction methods. Moreover, as suggested by our experimental data regarding BOLD-related phase effects, phase stability could even supersede magnitude stability in voxels covering dense microvascular networks with BOLD-related fluctuations as the dominant noise contributor. In the interest of the quality of both BOLD-based and nc-MRI methods, future studies are required to find alternative methods that can improve phase stability, designed to match the temporal and spatial scale of the underlying neuronal activity.     

Optimizing the mapping of finger areas in primary somatosensory cortex using functional MRI

Functional magnetic resonance imaging mapping of the finger somatotopy in the primary somatosensory cortex requires a reproducible and precise stimulation. The highly detailed functional architecture in this region of the brain also requires careful consideration in choice of spatial resolution and postprocessing parameters. The purpose of this study is therefore to investigate the impact of spatial resolution and level of smoothing during tactile stimulation using a precise stimuli system. Twenty-one volunteers were scanned using 2³ mm³ and 3³ mm³ voxel volume and subsequently evaluated using three different smoothing kernel widths. The overall activation reproducibility was also evaluated. Using a high spatial resolution proved advantageous for all fingers. At 2³ mm³ voxel volume, activation of the thumb, middle finger and little finger areas was seen in 89%, 67% and 50% of the volunteers, compared to 78%, 61% and 33% at 3³ mm³, respectively. The sensitivity was comparable for nonsmoothed and slightly smoothed (4 mm kernel width) data; however, increasing the smoothing kernel width from 4 to 8 mm resulted in a critical decrease (50%) in sensitivity. In repeated measurements of the same subject at six different days, the localization reproducibility of all fingers was within 4 mm (1 S.D. of the mean). The precise computer-controlled stimulus, together with data acquisition at high spatial resolution and with only minor smoothing during evaluation, could be a very useful strategy in studies of brain plasticity and rehabilitation strategies in hand and finger disorders and injuries.     

Assessing functional connectivity in the human brain by fMRI

Functional magnetic resonance imaging (fMRI) is widely used to detect and delineate regions of the brain that change their level of activation in response to specific stimuli and tasks. Simple activation maps depict only the average level of engagement of different regions within distributed systems. FMRI potentially can reveal additional information about the degree to which components of large-scale neural systems are functionally coupled together to achieve specific tasks. In order to better understand how brain regions contribute to functionally connected circuits, it is necessary to record activation maps either as a function of different conditions, at different times or in different subjects. Data obtained under different conditions may then be analyzed by a variety of techniques to infer correlations and couplings between nodes in networks. Several multivariate statistical methods have been adapted and applied to analyze variations within such data. An approach of particular interest that is suited to studies of connectivity within single subjects makes use of acquisitions of runs of MRI images obtained while the brain is in a so-called steady state, either at rest (i.e., without any specific stimulus or task) or in a condition of continuous activation. Interregional correlations between fluctuations of MRI signal potentially reveal functional connectivity. Recent studies have established that interregional correlations between different components of circuits in each of the visual, language, motor and working memory systems can be detected in the resting state. Correlations at baseline are changed during the performance of a continuous task. In this review, various methods available for assessing connectivity are described and evaluated.     

Imaging treatment effects in Alzheimer's disease

Alzheimer's disease (AD) is the commonest form of degenerative dementia and is characterised by progressive cognitive decline. Despite extensive research, the cause of AD is unknown and there is no cure at present. Of the deficits found in AD, that affecting the cholinergic neurotransmitter system is the best established and the only one translated into symptomatic treatment. Cholinergic enhancement with cholinesterase inhibitor (ChEI) drugs has been achieved and their efficacy and safety ascertained by conventional clinical trials. The mechanism of action of these drugs, however, is not well understood. Imaging with SPECT, PET, MRI and fMRI after treatment has clarified what happens in the brains of those AD patients treated with ChEI drugs. Studies with these techniques have identified increases in brain blood flow and glucose metabolism, restoration of nicotinic receptor function and re-establishment of task-related regional brain activation in response to cognitive stimulation after treatment. Structural MRI studies have explained, to some degree, why only a proportion of patients benefits from ChEI treatment and there is some evidence that some ChEI drugs might be neuroprotective. There are, however, many unsolved problems. Timing of treatment intervention to obtain maximum response and the determinants of treatment response are mostly unknown. It is also unclear whether administration of treatment in those patients who have no potential for response accelerates disease progression. These issues cannot be solved by conventional clinical trials. Pharmacoimaging studies could assist the development and refinement of drugs to treat those diseases, such as AD, which affect the central nervous system.