Phase stability in fMRI time series: effect of noise regression, off-resonance correction and spatial filtering techniques.

Although the majority of fMRI studies exploit magnitude changes only, there is an increasing interest regarding the potential additive information conveyed by the phase signal. This integrated part of the complex number furnished by the MR scanners can also be used for exploring direct detection of neuronal activity and for thermography. Few studies have explicitly addressed the issue of the available signal stability in the context of phase time-series, and therefore we explored the spatial pattern of frequency specific phase fluctuations, and evaluated the effect of physiological noise components (heart beat and respiration) on the phase signal. Three categories of retrospective noise reduction techniques were explored and the temporal signal stability was evaluated in terms of a physiologic noise model, for seven fMRI measurement protocols in eight healthy subjects at 3T, for segmented CSF, gray and white matter voxels. We confirmed that for most processing methods, an efficient use of the phase information is hampered by the fact that noise from physiological and instrumental sources contributes significantly more to the phase than to the magnitude instability. Noise regression based on the phase evolution of the central k-space point, RETROICOR, or an orthonormalized combination of these were able to reduce their impact, but without bringing phase stability down to levels expected from the magnitude signal. Similar results were obtained after targeted removal of scan-to-scan variations in the bulk magnetic field by the dynamic off-resonance in k-space (DORK) method and by the temporal off-resonance alignment of single-echo time series technique (TOAST). We found that spatial high-pass filtering was necessary, and in vivo a Gaussian filter width of 20mm was sufficient to suppress physiological noise and bring the phase fluctuations to magnitude levels. Stronger filters brought the fluctuations down to levels dictated by thermal noise contributions, and for 62.5mm(3) voxels the phase stability was as low as 5 mrad (0.27°). In conditions of low SNR(o) and high temporal sampling rate (short TR); we achieved an upper bound for the phase instabilities at 0.0017 ppm, which is close to the dHb contribution to the GM/WM phase contrast.

Advantages of using multiple-echo image combination and asymmetric triangular phase masking in magnetic resonance venography at 3 T.

The present work explores the possibility of localizing veins with magnetic resonance venography using susceptibility weighted imaging. It also seeks new approaches, directed by the spatial specificity of activated brain regions, that have sufficient precision for practical use in functional MRI studies. A 3D flow compensated multiple gradient echo sequence, featuring optimized T2* weighting within a reasonable time of acquisition (11 min) and a small voxel size (0.5x0.5x1 mm3), was used to acquire MR images at 3 T. Post-processing consisted of homodyne filtering, linear phase scaling and magnitude masking prior to minimum intensity projection (mIP). The multiple echo approach provided a satisfactory (48+/-7%) increase in signal-to-noise ratio with respect to conventional methods. Specific features of the blood oxygenation level-dependent phase effect were simulated and used for designing and exploring different phase masking methods in relation to vessel morphology and MRI voxel geometry. As with simulations, the best results were obtained with an asymmetric triangular phase masking, featuring an improved venographic contrast without any increase in the full-width at half-maximum. The multiple echo approach provided satisfactory vessel localization capacity by using asymmetric triangular phase masking and a 4-mm-thick mIP. The venographic contrast obtained enabled the detection of vessels with diameter down to approximately 500 microm, suggesting the applicability of the proposed method as an additional technique in fMRI studies.

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.

Voxel-based analysis of R2* maps in the healthy human brain.

PURPOSE: To develop a voxel-based analysis of an R2* map of healthy human brain that is automatic, reproducible, and realizable in a single examination on a 3T MR imager. Such a tool could be useful to measure iron accumulation in neurodegenerative diseases. MATERIALS AND METHODS: In all, 18 healthy subjects underwent MR imaging at a field strength of 3T: 1) six consecutive T2*-weighted gradient-echo volumes were acquired using a segmented echo-planar imaging sequence and 2) a conventional dual-echo turbo spin echo sequence was also applied to acquire T2-weighted images. Images were realigned and spatial correction was performed using a template brain dataset with SPM2. For each subject we performed a voxel-by-voxel nonlinear least-squares fitting of the data acquired at the six echo times to obtain a monoexponential signal decay curve. The reproducibility and sensitivity to age variation were assessed by voxel-based analysis. RESULTS: The reproducibility tests in whole brain analysis showed little R2* variation. Furthermore, the statistical analysis, performed on each brain voxel, revealed a significant positive correlation between age and MR values located in regions where a slow and constant age-related iron deposition is known. CONCLUSION: Our method, combining data acquisition and data processing, demonstrates the feasibility of voxel-based analysis on an R2* map and affords a high degree of sensitivity and good reproducibility while maintaining high spatial resolution.