High-resolution, multiple gradient-echo functional MRI at 1.5 T

Single-shot echo planar time-resolved imaging for multi-echo functional MRI and distortion-free diffusion imaging

PURPOSE

To develop a single-shot SNR-efficient distortion-free multi-echo imaging technique for dynamic imaging applications.

METHODS

Echo planar time-resolved imaging (EPTI) was first introduced as a multi-shot technique for distortion-free multi-echo imaging. This work aims to develop single-shot EPTI (ss-EPTI) to achieve improved robustness to motion/physiological noise, increased temporal resolution, and higher SNR efficiency. A new spatiotemporal encoding that enables reduced phase-encoding blips and minimized echo spacing under the single-shot regime was developed, which improves sampling efficiency and enhances spatiotemporal correlation in the k-TE space for improved reconstruction. A continuous readout with minimized deadtime was employed to optimize SNR efficiency. Moreover, k-TE partial Fourier and simultaneous multi-slice acquisition were integrated for further acceleration.

RESULTS

ss-EPTI provided distortion-free imaging with densely sampled multi-echo images at standard resolutions (e.g., ˜1.25 to 3 mm) in a single-shot. Improved SNR efficiency was observed in ss-EPTI due to improved motion/physiological-noise robustness and efficient continuous readout. Its ability to eliminate dynamic distortions-geometric changes across dynamics due to field changes induced by physiological variations or eddy currents-further improved the data's temporal stability. For multi-echo fMRI, ss-EPTI's multi-echo images recovered signal dropout in short-T 2 * $$ {\mathrm{T}}_2^{\ast } $$ regions and provided TE-dependent functional information to distinguish non-BOLD noise for further tSNR improvement. For diffusion MRI, it achieved shortened TEs for improved SNR and provided images free from both B0-induced and diffusion-encoding-dependent eddy-current-induced distortions with multi-TE diffusion metrics.

CONCLUSION

ss-EPTI provides SNR-efficient distortion-free multi-echo imaging with comparable temporal resolutions to ss-EPI, offering a new acquisition tool for dynamic imaging.

Single-shot Echo Planar Time-resolved Imaging for multi-echo functional MRI and distortion-free diffusion imaging

Purpose

To develop EPTI, a multi-shot distortion-free multi-echo imaging technique, into a single-shot acquisition to achieve improved robustness to motion and physiological noise, increased temporal resolution, and high SNR efficiency for dynamic imaging applications.

Methods

A new spatiotemporal encoding was developed to achieve single-shot EPTI by enhancing spatiotemporal correlation in k-t space. The proposed single-shot encoding improves reconstruction conditioning and sampling efficiency, with additional optimization under various accelerations to achieve optimized performance. To achieve high SNR efficiency, continuous readout with minimized deadtime was employed that begins immediately after excitation and extends for an SNR-optimized length. Moreover, k-t partial Fourier and simultaneous multi-slice acquisition were integrated to further accelerate the acquisition and achieve high spatial and temporal resolution.

Results

We demonstrated that ss-EPTI achieves higher tSNR efficiency than multi-shot EPTI, and provides distortion-free imaging with densely-sampled multi-echo images at resolutions ~1.25-3 mm at 3T and 7T-with high SNR efficiency and with comparable temporal resolutions to ss-EPI. The ability of ss-EPTI to eliminate dynamic distortions common in EPI also further improves temporal stability. For fMRI, ss-EPTI also provides early-TE images (e.g., 2.9ms) to recover signal-intensity and functional-sensitivity dropout in challenging regions. The multi-echo images provide TE-dependent information about functional fluctuations, successfully distinguishing noise-components from BOLD signals and further improving tSNR. For diffusion MRI, ss-EPTI provides high-quality distortion-free diffusion images and multi-echo diffusion metrics.

Conclusion

ss-EPTI provides distortion-free imaging with high image quality, rich multi-echo information, and enhanced efficiency within comparable temporal resolution to ss-EPI, offering a robust and efficient acquisition for dynamic imaging.

Sexually divergent development of depression-related brain networks during healthy human adolescence

Sexual differences in human brain development could be relevant to sex differences in the incidence of depression during adolescence. We tested for sex differences in parameters of normative brain network development using fMRI data on N = 298 healthy adolescents, aged 14 to 26 years, each scanned one to three times. Sexually divergent development of functional connectivity was located in the default mode network, limbic cortex, and subcortical nuclei. Females had a more "disruptive" pattern of development, where weak functional connectivity at age 14 became stronger during adolescence. This fMRI-derived map of sexually divergent brain network development was robustly colocated with i prior loci of reward-related brain activation ii a map of functional dysconnectivity in major depressive disorder (MDD), and iii an adult brain gene transcriptional pattern enriched for genes on the X chromosome, neurodevelopmental genes, and risk genes for MDD. We found normative sexual divergence in adolescent development of a cortico-subcortical brain functional network that is relevant to depression.

Compulsivity is linked to reduced adolescent development of goal-directed control and frontostriatal functional connectivity

A characteristic of adaptive behavior is its goal-directed nature. An ability to act in a goal-directed manner is progressively refined during development, but this refinement can be impacted by the emergence of psychiatric disorders. Disorders of compulsivity have been framed computationally as a deficit in model-based control, and have been linked also to abnormal frontostriatal connectivity. However, the developmental trajectory of model-based control, including an interplay between its maturation and an emergence of compulsivity, has not been characterized. Availing of a large sample of healthy adolescents (n = 569) aged 14 to 24 y, we show behaviorally that over the course of adolescence there is a within-person increase in model-based control, and this is more pronounced in younger participants. Using a bivariate latent change score model, we provide evidence that the presence of higher compulsivity traits is associated with an atypical profile of this developmental maturation in model-based control. Resting-state fMRI data from a subset of the behaviorally assessed subjects (n = 230) revealed that compulsivity is associated with a less pronounced change of within-subject developmental remodeling of functional connectivity, specifically between the striatum and a frontoparietal network. Thus, in an otherwise clinically healthy population sample, in early development, individual differences in compulsivity are linked to the developmental trajectory of model-based control and a remodeling of frontostriatal connectivity.

Conservative and disruptive modes of adolescent change in human brain functional connectivity

Adolescent changes in human brain function are not entirely understood. Here, we used multiecho functional MRI (fMRI) to measure developmental change in functional connectivity (FC) of resting-state oscillations between pairs of 330 cortical regions and 16 subcortical regions in 298 healthy adolescents scanned 520 times. Participants were aged 14 to 26 y and were scanned on 1 to 3 occasions at least 6 mo apart. We found 2 distinct modes of age-related change in FC: "conservative" and "disruptive." Conservative development was characteristic of primary cortex, which was strongly connected at 14 y and became even more connected in the period from 14 to 26 y. Disruptive development was characteristic of association cortex and subcortical regions, where connectivity was remodeled: connections that were weak at 14 y became stronger during adolescence, and connections that were strong at 14 y became weaker. These modes of development were quantified using the maturational index (MI), estimated as Spearman's correlation between edgewise baseline FC (at 14 y, [Formula: see text]) and adolescent change in FC ([Formula: see text]), at each region. Disruptive systems (with negative MI) were activated by social cognition and autobiographical memory tasks in prior fMRI data and significantly colocated with prior maps of aerobic glycolysis (AG), AG-related gene expression, postnatal cortical surface expansion, and adolescent shrinkage of cortical thickness. The presence of these 2 modes of development was robust to numerous sensitivity analyses. We conclude that human brain organization is disrupted during adolescence by remodeling of FC between association cortical and subcortical areas.

The effect of echo time and post-processing procedure on blood oxygenation level-dependent (BOLD) functional connectivity analysis

While spontaneous BOLD fMRI signal is a common tool to map functional connectivity, unexplained inter- and intra-subject variability frequently complicates interpretation. Similar to evoked BOLD fMRI responses, spontaneous BOLD signal is expected to vary with echo time (TE) and corresponding intra/extravascular sensitivity. This may contribute to discrepant conclusions even following identical post-processing pipelines. Here we applied commonly-utilized independent component analysis (ICA) as well as seed-based correlation analysis and investigated default mode network (DMN) and visual network (VN) detection from BOLD data acquired at three TEs (3T; TR=2500ms; TE=15ms, 35ms, and 55ms) and from quantitative R2* maps. Explained variance in ICA analysis was significantly higher (P<0.05) when R2*-derived maps were considered relative to single-TE data with no post-processing. While explained variance in the BOLD data increased with motion correction, R2* derived DMN and VN were minimally affected by motion correction. Explained variance increased in all data when physiological noise confounds were removed using CompCor. Notably, the R2*-derived connectivity patterns were least affected by motion and physiological noise confounds in a seed-based correlation analysis. Intermediate (35ms) and long (55ms) TE data provided similar spatial and temporal characteristics only after reducing motion and physiological noise contamination. Results provide an exemplar for how 3T spontaneous BOLD network detection varies with TE and post-processing procedure over the range of commonly acquired TE values.

The role of susceptibility weighted imaging in functional MRI

The development of functional brain magnetic resonance imaging (fMRI) has been a boon for neuroscientists and radiologists alike. It provides for fundamental information on brain function and better diagnostic tools to study disease. In this paper, we will review some of the early concepts in high resolution gradient echo imaging with a particular emphasis on susceptibility weighted imaging (SWI) and MR angiography (MRA). We begin with the history of our own experience in this area, followed by a discussion of the role of high resolution in studying the vasculature of the brain and how this relates to the BOLD (blood oxygenation level dependent) signal. We introduce the role of SWI and susceptibility mapping (SWIM) in fMRI and close with recommendations for future high resolution experiments.

Differentiating BOLD and non-BOLD signals in fMRI time series using multi-echo EPI

A central challenge in the fMRI based study of functional connectivity is distinguishing neuronally related signal fluctuations from the effects of motion, physiology, and other nuisance sources. Conventional techniques for removing nuisance effects include modeling of noise time courses based on external measurements followed by temporal filtering. These techniques have limited effectiveness. Previous studies have shown using multi-echo fMRI that neuronally related fluctuations are Blood Oxygen Level Dependent (BOLD) signals that can be characterized in terms of changes in R(2)* and initial signal intensity (S(0)) based on the analysis of echo-time (TE) dependence. We hypothesized that if TE-dependence could be used to differentiate BOLD and non-BOLD signals, non-BOLD signal could be removed to denoise data without conventional noise modeling. To test this hypothesis, whole brain multi-echo data were acquired at 3 TEs and decomposed with Independent Components Analysis (ICA) after spatially concatenating data across space and TE. Components were analyzed for the degree to which their signal changes fit models for R(2)* and S(0) change, and summary scores were developed to characterize each component as BOLD-like or not BOLD-like. These scores clearly differentiated BOLD-like "functional network" components from non BOLD-like components related to motion, pulsatility, and other nuisance effects. Using non BOLD-like component time courses as noise regressors dramatically improved seed-based correlation mapping by reducing the effects of high and low frequency non-BOLD fluctuations. A comparison with seed-based correlation mapping using conventional noise regressors demonstrated the superiority of the proposed technique for both individual and group level seed-based connectivity analysis, especially in mapping subcortical-cortical connectivity. The differentiation of BOLD and non-BOLD components based on TE-dependence was highly robust, which allowed for the identification of BOLD-like components and the removal of non BOLD-like components to be implemented as a fully automated procedure.

Absolute oxygenation metabolism measurements using magnetic resonance imaging

Cerebral oxygen metabolism plays a critical role in maintaining normal function of the brain. It is the primary energy source to sustain neuronal functions. Abnormalities in oxygen metabolism occur in various neuro-pathologic conditions such as ischemic stroke, cerebral trauma, cancer, Alzheimer’s disease and shock. Therefore, the ability to quantitatively measure tissue oxygenation and oxygen metabolism is essential to the understanding of pathophysiology and treatment of various diseases. The focus of this review is to provide an introduction of various blood oxygenation level dependent (BOLD) contrast methods for absolute measurements of tissue oxygenation, including both magnitude and phase image based approaches. The advantages and disadvantages of each method are discussed.

Advances in High-Field BOLD fMRI

This review article examines the current state of BOLD fMRI at a high magnetic field strength of 7 Tesla. The following aspects are covered: a short description of the BOLD contrast, spatial and temporal resolution, BOLD sensitivity, localization and spatial specificity, technical challenges as well as an outlook on future developments are given. It is shown that the main technical challenges of performing BOLD fMRI at high magnetic field strengths-namely development of array coils, imaging sequences and parallel imaging reconstruction-have been solved successfully. The combination of these developments has lead to the availability of high-resolution BOLD fMRI protocols that are able to cover the whole brain with a repetition time (TR) shorter than 3 s. The structural information available from these high-resolution fMRI images itself is already very detailed, which helps to co-localize structure and function. Potential future applications include whole-brain connectivity analysis on a laminar resolution and single subject examinations.

Multi-echo acquisition

The rapid development of fMRI was paralleled early on by the adaptation of MR spectroscopic imaging (MRSI) methods to quantify water relaxation changes during brain activation. This review describes the evolution of multi-echo acquisition from high-speed MRSI to multi-echo EPI and beyond. It highlights milestones in the development of multi-echo acquisition methods, such as the discovery of considerable gains in fMRI sensitivity when combining echo images, advances in quantification of the BOLD effect using analytical biophysical modeling and interleaved multi-region shimming. The review conveys the insight gained from combining fMRI and MRSI methods and concludes with recent trends in ultra-fast fMRI, which will significantly increase temporal resolution of multi-echo acquisition.

A dual echo approach to removing motion artefacts in fMRI time series

In fMRI, subject motion can severely affect data quality. This is a particular problem when movement is correlated with the experimental paradigm as this potentially causes artefactual activation. A method is presented that uses linear regression, to utilise the time course of an image acquired at very short echo time (TE) as a voxel-wise regressor for a second image in the same echo train, that is acquired with high BOLD sensitivity. The value of this approach is demonstrated using task-locked motion combined with visual stimulation. Results obtained at both 1.5 and 3 T show improvements in functional activation maps for individual subjects. The method is straightforward to implement, does not require extra scan time and can easily be embedded in a multi-echo acquisition framework.

MR relaxation in multiple sclerosis

This article provides an overview of relaxation times and their application to normal brain and brain and cord affected by multiple sclerosis. The goal is to provide readers with an intuitive understanding of what influences relaxation times, how relaxation times can be accurately measured, and how they provide specific information about the pathology of MS. The article summarizes significant results from relaxation time studies in the normal human brain and cord and from people who have multiple sclerosis. It also reports on studies that have compared relaxation time results with results from other MR techniques.

Three-dimensional spiral technique for high-resolution functional MRI

For high-resolution functional MRI (fMRI) studies, signal-to-noise ratio (SNR) plays an important role. Any method that results in an improvement in SNR will be able to improve the quality of activation maps. Three-dimensional (3D) acquisition methods in general can provide higher SNR than that of 2D methods due to volume excitation. To demonstrate the superiority of 3D methods for high-resolution fMRI scans, a comparison study between 3D and 2D spiral methods was performed using a contrast-reversing checkerboard visual stimulus. A 3-inch surface coil was used to limit the in-plane FOV to 14 cm x 14 cm so that 32 1-mm slices with an in-plane voxel size of 1.1 mm x 1.1 mm could be acquired within 5.76 seconds. Results showed that average numbers of activated voxels were 407 and 841 for 2D and 3D methods, respectively (P < 0.01). Therefore, the 3D technique may be a useful alternative to the conventional 2D method for high resolution fMRI studies.

Obtaining blood oxygenation levels from MR signal behavior in the presence of single venous vessels

The MR signal decay in gradient echo sequences includes signal loss due to spin dephasing caused by static magnetic field inhomogeneities. This decay can be calculated for different geometries of the susceptibility distribution, such as spheres, cylinders, or cylinder networks. In particular, the model of an infinitely long cylinder is a good approximation for single straight blood vessels. Blood oxygenation and blood volume fraction are important parameters, which influence the signal in a characteristic way. In this work the signal decays for a single cylindrical vessel were investigated and evaluated in simulations, phantom measurements as well as in vivo measurements of small single veins in the human brain by using a 3D multiecho gradient echo sequence. Good agreement between simulations and phantom experiments was obtained for different experimental settings. Based on the simulations, physiologically consistent values of venous blood oxygenation level, Y, were extracted from the in vivo measurements of different veins and volunteers (Y = 0.55 +/- 0.02). The methods ability to measure changes in venous blood oxygenation induced by carbogen breathing was demonstrated in one volunteer, where an increase from Y approximately 0.5 to Y approximately 0.7 was observed.

Very high-resolution three-dimensional functional MRI of the human visual cortex with elimination of large venous vessels

We propose a very high-resolution, three-dimensional (3D) gradient-echo technique with a twofold parallel imaging acceleration using a specialized occipital receiver coil at 3 T to perform functional MRI (fMRI) of the visual cortex. This configuration makes it possible to acquire 3D fMRI data within a timescale compatible with a block design. Without further processing, the functional maps at an isotropic 3D resolution of 0.42 microL (0.75 mm voxel size) and near-isotropic resolution of 1.2 microL (1 mm voxel size) show very robust activation in visual areas, but with clear contamination from larger veins. As this technique allows direct identification of veins in the functional scan, it permits removal of their effect from the activation maps. In our study, elimination of veins qualitatively improves the spatial specificity of activation maps, while reducing the activated volume by about 25%. The proposed technique provides functional information at the resolution of anatomical scans, is localized to gray matter, and facilitates functional to anatomical co-registration because of minimal distortions.

BOLD signal and vessel dynamics: a hierarchical cluster analysis

The aim of the present study was to analyze blood oxygenation level-dependent (BOLD) signal variation during an apnea-based task in order to assess the capability of a functional magnetic resonance imaging (fMRI) procedure to estimate cerebral vascular dynamic effects. We measured BOLD contrast by hierarchical cluster analysis in healthy subjects undergoing an fMRI experiment, in which the task paradigm was one phase of inspirational apnea (IA). By processing the time courses of the fMRI experiment, analysis was performed only on a subclass of all the possible signal patterns; basically, root mean square and absolute variation differences have been calculated. Considering the baseline value obtained by computing the mean value of the initial rest period as reference, particular voxels showed relative important variations during the IA task and during the recovery phase following the IA. We focused our interest on the signal response of voxels that would correspond mainly to white and gray matter regions and that also may be affected by the proximity of large venous vessels. The results are presented as maps of space-temporal distribution of time series variations with two levels of hierarchical clustering among voxels with low to high initial response. Furthermore, we have presented a clustering of the signal response delay, conducting to a partition and identification of specified brain sites.

High-resolution FMRI at 1.5T using balanced SSFP

The resolution in conventional BOLD FMRI is considerably lower than can be achieved with other MRI methods, and is insufficient for many important applications. One major difficulty in robustly improving spatial resolution is the poor image quality in BOLD FMRI, which suffers from distortions, blurring, and signal dropout. This work considers the potential for increased resolution with a new FMRI method based on balanced SSFP. This method establishes a blood oxygenation sensitive steady-state (BOSS) signal, in which the frequency sensitivity of balanced SSFP is used to detect the frequency shift of deoxyhemoglobin. BOSS FMRI is highly SNR efficient and does not suffer from image distortions or signal dropout, making this method an excellent candidate for high-resolution FMRI. This study presents the first demonstration of high-resolution BOSS FMRI, using an efficient 3D stack-of-segmented EPI readout and combined acquisition at multiple center frequencies. BOSS FMRI is shown to enable high-resolution FMRI data (1 x 1 x 2 mm(3)) in both visual and motor systems using standard hardware at 1.5 T. Currently, the major limitation of BOSS FMRI is its sensitivity to temporal and spatial field drift.

Susceptibility Weighted Imaging: Data Acquisition, Image Reconstruction and Clinical Applications

Susceptibility-weighted imaging (SWI) is a novel method, that combines magnitude and phase information from a high-resolution, fully velocity compensated 3D T2-weighted gradient echo sequence. Phase images are unwrapped and high pass filtered to highlight phase changes associated with venous vessels and converted into a mask that is multiplied with the corresponding phase image. This technique has been applied thus far to the imaging of tumors, vascular malformations, trauma, stroke, micro-hemorrhages, and as a functional imaging method. The purpose of this paper is to present an overview of the current status of the technique and to illustrate its potential.

Anatomical and functional brain imaging using high-resolution echo-planar spectroscopic imaging at 1.5 Tesla

High-resolution echo-planar spectroscopic imaging (EPSI) of water resonance (i.e. without water suppression) is proposed for anatomic and functional imaging of the human brain at 1.5 T. Water spectra with a resolution of 2.6 Hz and a bandwidth of 333 Hz were obtained in small voxels (1.7 x 1.7 x 3 mm3) across a single slice. Although water spectra appeared Lorentzian in most of the voxels in the brain, non-Lorentzian broadening of the water resonance was observed in voxels containing blood vessels. In functional experiments with a motor task, robust activation in motor cortices was observed in high-resolution T2* maps generated from the EPSI data. Shift of the water resonance frequency occurred during neuronal activation in motor cortices. The activation areas appeared to be more localized after excluding the voxels in which the lineshape of the water resonance had elevated T2* and became more non-Lorentzian during the motor task. These preliminary results suggest that high-resolution EPSI is a promising tool to study susceptibility-related effects, such as BOLD contrast, for improved anatomical and functional imaging of the brain.

The value of high-field MRI (3T) in the assessment of sellar lesions

The aim of this study was the evaluation of the normal sellar anatomy in vitro and in vivo with high-field MRI and its application in the diagnosis of sellar pathologies in comparison to standard MRI. All high-field MR images were obtained using a 3T Bruker Medspec 30/80 Scanner with a head birdcage transmit/receive coil and an actively shielded gradient system with a maximum gradient strength of 45 mT/m. Firstly an in vitro study of the sella turcica was performed to depict normal pituitary and sellar anatomy at high field. After a pilot-study this sequence-protocol was established: A RARE sequence (TR/TE = 7790/19 ms; matrix size, 512 x 512; RARE factor = 8, FOV, 200 mm) was used for T2-weighted coronal, axial and sagittal images. A 3D gradient echo sequence with magnetization-preparation (MP-RAGE, TR/TE/TI = 33.5/7.6/800 ms, matrix size, 512 x 512; FOV, 200 mm, effective slice thickness, 1.88 mm; 3 averages) was used for acquisition of T1-weighted pre- and post-contrast images. Between January 2002 and March 200458 patients were enrolled in this study. Seven patients were examined for suspected microadenoma and in 51 patients 3T MRI was used to obtain additional information about the sellar lesion already known to be present from standard MRI. In 21 cases the accuracy of the imaging findings was assessed afterwards by comparison with intraoperative findings. The infiltration of the medial cavernous sinus wall was suspected on standard MRI on 15 sides (47%), on high-field MRI on 9 sides (28%) and could be verified by intraoperative findings on 6 sides (19%). Accordingly, sensitivity to infiltration was 83% for 3T and 67% for standard MRI. Specificity was 84% for 3T and 58% for standard MRI. Moreover, high-field MRI revealed microadenomas in 7 patients with a median diameter of 4mm (range 2-9 mm). The segments of the cranial nerves were seen as mean 4 hypointense spots (range 2-5 spots) on high-field MRI in contrast to 3 spots (range 0-4 spots) on standard MRI. This difference was considerably significant (P < 0.001, Wilcoxon rank sum test). The histopathological results revealed pituitary adenoma in 16 patients and non-adenomatous sellar pathologies such as Rathke's cleft cyst, sarcoidosis, meningeoma and metastasis in 5 patients. High-field MRI is superior to standard MRI for the prediction of invasion of adjacent structures in patients with pituitary adenomas and improves surgical planning of sellar lesion.

A quantitative comparison of functional MRI cluster analysis

The aim of this work is to compare the efficiency and power of several cluster analysis techniques on fully artificial (mathematical) and synthesized (hybrid) functional magnetic resonance imaging (fMRI) data sets. The clustering algorithms used are hierarchical, crisp (neural gas, self-organizing maps, hard competitive learning, k-means, maximin-distance, CLARA) and fuzzy (c-means, fuzzy competitive learning). To compare these methods we use two performance measures, namely the correlation coefficient and the weighted Jaccard coefficient (wJC). Both performance coefficients (PCs) clearly show that the neural gas and the k-means algorithm perform significantly better than all the other methods using our setup. For the hierarchical methods the ward linkage algorithm performs best under our simulation design. In conclusion, the neural gas method seems to be the best choice for fMRI cluster analysis, given its correct classification of activated pixels (true positives (TPs)) whilst minimizing the misclassification of inactivated pixels (false positives (FPs)), and in the stability of the results achieved.

Application of three-tesla magnetic resonance imaging for diagnosis and surgery of sellar lesions

OBJECT

The aim of this study was to determine the value of high-field magnetic resonance (MR) imaging for diagnosis and surgery of sellar lesions.

METHODS

High-field MR images were obtained using a 3-tesla unit with emphasis on sellar and parasellar structures in 21 patients preoperatively to delineate endo-, supra-, and parasellar anatomical structures. Special attention was given to the medial border of the cavernous sinus and possible invasion of a sellar tumor therein, and to assessing the application of high-resolution images during intraoperative neuronavigation. The 3-tesla MR images were compared with the standard MR images already obtained and with intraoperative findings. Anatomical structures were studied in all 42 cavernous sinuses; in 32 of them comparisons with intraoperative findings were possible. The medial cavernous sinus border was rated intact in 53% on standard MR images, in 72% on 3-tesla MR images, and in 81% intraoperatively. With a positive correlation to surgical findings on 84% of 3-tesla MR images compared with 59% of standard MR images, a sensitivity of 83% compared with 67%, and a specificity of 84% compared with 58% (p = 0.016, McNemar test), 3-tesla MR imaging was superior for predicting tumor invasion through the medial cavernous sinus border. Although no difference was noted in delineation of the medial, superior, and inferior compartments, there was a better delineation of the lateral cavernous sinus compartment with 3-tesla MR imaging. This compartment was clearly visible on 40 sides (95%) on 3-tesla MR images compared with 34 sides (81%) on standard MR images. Identification of the cavernous sinus segments of the third, fourth, fifth (V1 and V2), and sixth cranial nerves was improved using high-resolution 3-tesla imaging compared with standard MR imaging. A mean of four cranial nerves was found as hypointense spots (range two-five spots) on 3-tesla MR imaging compared with a mean of three (range zero-four spots) on standard MR imaging. After addition of contrast agents, the anterior pituitary gland was found to be highly intense on 78% of T1-weighted three-dimensional magnetization-prepared rapid acquisition gradient-echo (MPRAGE) 3-tesla MR images compared with 73% of standard T1-weighted MR images. The optochiasmatic system displayed increased intensity on pre-contrast T1-weighted MPRAGE 3-tesla compared with standard T1-weighted MR images; it was hyperintense on 76% of 3-tesla compared with 15% of standard MR images, which was helpful for its delineation from suprasellar pituitary and tumor structures. Intraoperative navigation guided by fusion of 3-tesla MR images and computerized tomography (CT) scans was performed in seven patients. Whereas CT scanning was used during the transsphenoidal approach to depict the nasal bone structures, 3-tesla MR imaging was particularly useful for the visualization of parasellar tumor extension during microsurgical and/or endoscopic resection.

CONCLUSIONS

Due to its higher resolution, 3-tesla MR imaging was found to be superior to standard MR imaging for the delineation of parasellar anatomy and tumor infiltration of the cavernous sinus, and this modality provided improved imaging for intraoperative navigation.

Quantitative NumART2* mapping in functional MRI studies at 1.5 T

Quantitative mapping of the effective transverse relaxation time, T2* and proton density was performed in a motor activation functional MRI (fMRI) study using multi-echo, echo planar imaging (EPI) and NumART2* (Numerical Algorithm for Real time T2*). Comparisons between NumART2* and conventional single echo EPI with an echo time of 64 ms were performed for five healthy participants examined twice. Simulations were also performed to address specific issues associated with the two techniques, such as echo time-dependent signal variation. While the single echo contrast varied with the baseline T2* value, relative changes in T2* remained unaffected. Statistical analysis of the T2* maps yielded fMRI activation patterns with an improved statistical detection relative to conventional EPI but with less activated voxels, suggesting that NumART2* has superior spatial specificity. Two effects, inflow and dephasing, that may explain this finding were investigated. Particularly, a statistically significant increase in proton density was found in a brain area that was detected as activated by conventional EPI but not by NumART2* while no such changes were observed in brain areas that showed stimulus correlated signal changes on T2* maps.

Fuzzy cluster analysis of high-field functional MRI data

Functional magnetic resonance imaging (fMRI) based on blood-oxygen level dependent (BOLD) contrast today is an established brain research method and quickly gains acceptance for complementary clinical diagnosis. However, neither the basic mechanisms like coupling between neuronal activation and haemodynamic response are known exactly, nor can the various artifacts be predicted or controlled. Thus, modeling functional signal changes is non-trivial and exploratory data analysis (EDA) may be rather useful. In particular, identification and separation of artifacts as well as quantification of expected, i.e. stimulus correlated, and novel information on brain activity is important for both, new insights in neuroscience and future developments in functional MRI of the human brain. After an introduction on fuzzy clustering and very high-field fMRI we present several examples where fuzzy cluster analysis (FCA) of fMRI time series helps to identify and locally separate various artifacts. We also present and discuss applications and limitations of fuzzy cluster analysis in very high-field functional MRI: differentiate temporal patterns in MRI using (a) a test object with static and dynamic parts, (b) artifacts due to gross head motion artifacts. Using a synthetic fMRI data set we quantitatively examine the influences of relevant FCA parameters on clustering results in terms of receiver-operator characteristics (ROC) and compare them with a commonly used model-based correlation analysis (CA) approach. The application of FCA in analyzing in vivo fMRI data is shown for (a) a motor paradigm, (b) data from multi-echo imaging, and (c) a fMRI study using mental rotation of three-dimensional cubes. We found that differentiation of true "neural" from false "vascular" activation is possible based on echo time dependence and specific activation levels, as well as based on their signal time-course. Exploratory data analysis methods in general and fuzzy cluster analysis in particular may help to identify artifacts and add novel and unexpected information valuable for interpretation, classification and characterization of functional MRI data which can be used to design new data acquisition schemes, stimulus presentations, neuro(physio)logical paradigms, as well as to improve quantitative biophysical models.

Reduction of spectral ghost artifacts in high-resolution echo-planar spectroscopic imaging of water and fat resonances

Echo-planar spectroscopic imaging (EPSI) can be used for fast spectroscopic imaging of water and fat resonances at high resolution to improve structural and functional imaging. Because of the use of oscillating gradients during the free induction decay (FID), spectra obtained with EPSI are often degraded by Nyquist ghost artifacts arising from the inconsistency between the odd and even echoes. The presence of the spectral ghost lines causes errors in the evaluation of the true spectral lines, and this degrades images derived from high-resolution EPSI data. A technique is described for reducing the spectral ghost artifacts in EPSI of water and fat resonances, using echo shift and zero-order phase corrections. These corrections are applied during the data postprocessing. This technique is demonstrated with EPSI data acquired from human brains and breasts at 1.5 Tesla and from a water phantom at 4.7 Tesla. Experimental results indicate that the present approach significantly reduces the intensities of spectral ghosts. This technique is most useful in conjunction with high-resolution EPSI of water and fat resonances, but is less applicable to EPSI of metabolites due to the complexity of the spectra.

Real-time quantification of T(2)(*) changes using multiecho planar imaging and numerical methods

Conventional approaches to quantify whole brain T(2)(*) maps use nonlinear regression with intensive computational requirements that therefore likely limit quantitative T(2)(*) mapping for real-time applications. To overcome these limitations an alternative method, NumART(2)(*) (NUMerical Algorithm for Real-time T(2)(*) mapping) that directly calculates T(2)(*) by a linear combination of images obtained at three or more different echo times was developed. NumART(2)(*), linear least-squares, and nonlinear regression techniques were applied to multiecho planar images of the human brain and to simulated data. Although NumART(2)(*) may overestimate T(2)(*), it yields comparable values to regression techniques in cortical and subcortical areas, with only moderate deviations for echo spacings between 18 and 40 ms. NumART(2)(*), like linear regression, requires 2% of the computational time needed for nonlinear regression and compares favorably with linear regression due to its higher precision. The use of NumART(2)(*) for continuous on-line T(2)(*) mapping in real time fMRI studies is shown.

MRI of the tumor microenvironment

The microenvironment within tumors is significantly different from that in normal tissues. A major difference is seen in the chaotic vasculature of tumors, which results in unbalanced blood supply and significant perfusion heterogeneities. As a consequence, many regions within tumors are transiently or chronically hypoxic. This exacerbates tumor cells' natural tendency to overproduce acids, resulting in very acidic pH values. The hypoxia and acidity of tumors have important consequences for antitumor therapy and can contribute to the progression of tumors to a more aggressive metastatic phenotype. Over the past decade, techniques have emerged that allow the interrogation of the tumor microenvironment with high resolution and molecularly specific probes. Techniques are available to interrogate perfusion, vascular distribution, pH, and pO(2) nondestructively in living tissues with relatively high precision. Studies employing these methods have provided new insights into the causes and consequences of the hostile tumor microenvironment. Furthermore, it is quite exciting that there are emerging techniques that generate tumor image contrast via ill-defined mechanisms. Elucidation of these mechanisms will yield further insights into the tumor microenvironment. This review attempts to identify techniques and their application to tumor biology, with an emphasis on nuclear magnetic resonance (NMR) approaches. Examples are also discussed using electron MR, optical, and radionuclear imaging techniques.

Functional magnetic resonance imaging technology and traumatic brain injury rehabilitation: guidelines for methodological and conceptual pitfalls

OBJECTIVES

To illuminate the current methodological and conceptual pitfalls inherent in conducting functional magnetic resonance imaging (fMRI) research with individuals who have sustained traumatic brain injury (TBI) and to discuss appropriate remedies. The aim is describe fMRI research, its limitations, and how to best use this technology to examine TBI.

DISCUSSION

The topics discussed in this article include issues regarding signal detection, brain activation measurement, head movement, and sources of signal artifact. Issues surrounding data interpretation and the importance of analyzing the brain as a connected neural network is also discussed. Finally, problems with spatial normalization when examining individuals with TBI are reviewed.

CONCLUSIONS

To date, there is a scarcity of research applying fMRI technology to the study of TBI. However, because it is a noninvasive procedure with high availability in hospital settings across the country, the next decade of TBI research will likely include a proliferation of this form of investigation. At this time, much work is needed to better understand how to optimally use this technology to examine the effects of TBI on behavior. For fMRI to enhance TBI research it will be imperative to establish valid research protocols and reliable methods of data interpretation.

High-resolution BOLD venographic imaging: a window into brain function

This paper reviews the recent development of a new high-resolution magnetic resonance imaging approach to visualizing small veins in the human brain with diameters in the sub-millimeter range, which is smaller than a voxel. It briefly introduces the physical background of the underlying bulk magnetic susceptibility effects, on which this approach is based, and it demonstrates the successful application of the method for imaging different intracranial lesions, like venous anomalies, arteriovenous malformations and brain tumors. The susceptibility difference between venous blood and the surrounding tissue is used to generate contrast. Using this method it is possible to visualize draining veins in lesions better than conventional magnetic resonance imaging methods, which often require application of a contrast medium or even conventional catheter angiography. Limitations of the method are discussed. The ability to highlight deoxygenated blood with high spatial resolution yields important vascular parameters which may be helpful for improved modeling of MR signal changes during functional brain activation, it may lead to a better understanding of brain function in diseased states, or it may even offer the possibility of differentiating benign from malignant tumors non-invasively.

Motion correction of parametric fMRI data from multi-slice single-shot multi-echo acquisitions

Fast parametric imaging using multi-echo techniques has been proven to yield quantitative parameter maps with high stability for functional MRI (fMRI). Due to the different contrasts and signal-to-noise ratios (SNRs) in the various images, motion correction of the echo images or the resulting parameter maps is not a straightforward process. 3D motion correction of parametric imaging data has not yet been examined thoroughly. However, motion correction is an essential step in fMRI data processing. In this study several possible motion detection methods were tested and compared. Motion parameters can be estimated from the different echo images as well as from the parameter maps. The accuracy of the different methods was examined in simulations and in in vivo experiments. Motion parameters should be estimated from the I(0)-parameter maps and subsequently applied to the T(*)(2)-parameter maps.

Characterization of BOLD activation in multi-echo fMRI data using fuzzy cluster analysis and a comparison with quantitative modeling

A combination of multiple gradient-echo imaging and exploratory data analysis (EDA), i.e. fuzzy cluster analysis (FCA), is proposed for separation and characterization of BOLD activation in single-shot spiral functional magnetic resonance imaging (fMRI) experiments at 3 T. Differentiation of functional activation using FCA is performed by clustering pixel signal changes (DeltaS) as a function of echo time (TE). Further vascular classification is supported by the localization of activation and the comparison with a single-exponential decay model. In some subjects, an additional indication for large vessels within a voxel was found as oscillation of the fMRI signal difference vs echo time (TE). Such large vessels may be separated from small vessel activation and, therefore, our proposed procedure might prove useful if a more specific functional localization is desired in fMRI. In addition to the signal change DeltaS, DeltaT(2)*/T(2)* is significantly different between activated regions. Averaged over all eight subjects DeltaT(2)* is 1.7 +/- 0.2 ms in ROIs with the highest signal change characterized as containing large vessels, whereas in ROIs corresponding to microvascular environment average DeltaT(2)* values are 0.8 +/- 0.1 ms.

Effect of graded hypo- and hypercapnia on fMRI contrast in visual cortex: quantification of T(*)(2) changes by multiecho EPI

The sensitivity of functional magnetic resonance imaging (fMRI) in visual cortex to graded hypo- and hypercapnia was quantified in 10 normal subjects using single-shot multiecho echo-planar imaging (Turbo-PEPSI) with eight equidistant echo times (TEs) between 12 and 140 ms. Visual stimulation was combined with controlled hyperventilation and carbon dioxide inhalation to perform fMRI at six levels of end-expiratory pCO(2) (PETCO(2)) between 20 and 70 mm Hg. T(*)(2) in visual cortex during baseline conditions (light off) increased nonlinearly from 20 to 70 mm Hg, from 61.1 +/- 4.2 ms to 72.0 +/- 4.6 ms. Changes in T(*)(2) due to visual stimulation increased 2.1-fold, from 1.2 +/- 0.6 ms at 20 mm Hg to 2.5 +/- 0.7 ms at 50 mm Hg. An almost complete loss of functional contrast was measured at 70 mm Hg. The model of MR signal dephasing by Yablonskiy and Haacke (Mag Reson Med 1994;32:749-763) was used to predict changes in cerebral blood flow (CBF), which were found to be consistent with results from previous positron emission tomography (PET) studies. This study further emphasizes that global CBF changes (due to PETCO(2) changes even in the physiological range) strongly influence fMRI contrast and need to be controlled for.

The quantification of DeltaR2(*) under brain activation: dependence on relaxation rate at rest and significance threshold

Transverse relaxation rates R2(*) were measured in subjects performing a motor task using a segmented EPI double gradient echo sequence (TE = 23/70 ms) with five different voxel sizes between 1.8 mm(3) and 41.7 mm(3). An analysis of the errors involved in the calculation of the change of the transverse relaxation rate--DeltaR2(*) and of the consequences of defining an arbitrary threshold of statistical significance in the data analysis was performed. Correlations between the magnitude of the BOLD effect and the significance level on one hand and between the transverse relaxation time at rest and its change under activation on the other, both referenced in the literature, can be understood as a consequence of this procedure. Analysing histograms of parameter changes rather than average values alone allows for an estimate of the contribution of false positive voxels. Furthermore, while the averaged signal change increases in proportion to the selection threshold the histograms of activated voxels remain insensitive to the latter.

EvIdent: a functional magnetic resonance image analysis system

EvIdent (EVent IDENTification) is a user-friendly, algorithm-rich, exploratory data analysis software for quickly detecting, investigating, and visualizing novel events in a set of images as they evolve in time and/or frequency. For instance, in a series of functional magnetic resonance neuroimages, novelty may manifest itself as neural activations in a time course. The core of the system is an enhanced variant of the fuzzy c-means clustering algorithm. Fuzzy clustering obviates the need for models of the underlying requisite biological function, models that are often statistically suspect.

High-resolution segmented EPI in a motor task fMRI study

A high-resolution gradient echo, multi-slice segmented echo planar imaging method was used for functional MRI (fMRI) using a motor task at 1.5 Tesla. Functional images with an in-plane resolution of 1 mm and slice thickness of 4 mm were obtained with good white-gray matter contrast. The multi-shot approach, combined with a short total readout period of 82 ms, limits blurring effects for short T(2)(*) tissues (such as gray matter), assuring truly high-resolution images. In all subjects, motor functions were clearly depicted in the contralateral central sulcus over several slices and sometimes activation was detected in the supplementary motor area and/or ipsilateral central sulcus. The average signal change of 11+/-3% was much higher than in standard low-resolution fMRI EPI experiments, as a result of larger relative blood fractions.

Ultra high resolution imaging of the human head at 8 tesla: 2K x 2K for Y2K

PURPOSE

To acquire ultra high resolution MRI images of the human brain at 8 Tesla within a clinically acceptable time frame.

METHOD

Gradient echo images were acquired from the human head of normal subjects using a transverse electromagnetic resonator operating in quadrature and tuned to 340 MHz. In each study, a group of six images was obtained containing a total of 208 MB of unprocessed information. Typical acquisition parameters were as follows: matrix = 2,000 x 2,000, field of view = 20 cm, slice thickness = 2 mm, number of excitations (NEX) = 1, flip angle = 45 degrees, TR = 750 ms, TE = 17 ms, receiver bandwidth = 69.4 kHz. This resulted in a total scan time of 23 minutes, an in-plane resolution of 100 microm, and a pixel volume of 0.02 mm3.

RESULTS

The ultra high resolution images acquired in this study represent more than a 50-fold increase in in-plane resolution relative to conventional 256 x 256 images obtained with a 20 cm field of view and a 5 mm slice thickness. Nonetheless, the ultra high resolution images could be acquired both with adequate image quality and signal to noise. They revealed numerous small venous structures throughout the image plane and provided reasonable delineation between gray and white matter.

DISCUSSION

The elevated signal-to-noise ratio observed in ultra high field magnetic resonance imaging can be utilized to acquire images with a level of resolution approaching the histological level under in vivo conditions. However, brain motion is likely to degrade the useful resolution. This situation may be remedied in part with cardiac gating. Nonetheless, these images represent a significant advance in our ability to examine small anatomical features with noninvasive imaging methods.

Functional MRI of the human motor cortex using single-shot, multiple gradient-echo spiral imaging

In this study, we combined the advantages of a fast multi-slice spiral imaging approach with a multiple gradient-echo sampling scheme at high magnetic field strength to improve quantification of BOLD and inflow effects and to estimate T2* relaxation times in functional brain imaging. Eight echoes are collected with echo time (TE) ranging from 5 to 180 ms. Acquisition time per slice and echo time is 25 ms for a nominal resolution of 4 x 4 x 4 mm3. Evaluation of parameter images during rest and stimulation yields no significant activation on the inflow sensitive spin-density images (rho or I0-maps) whereas clear activation patterns in primary human motor cortex (M1) and supplementary motor area (SMA) are detected on BOLD sensitive T2*-maps. The calculation of relaxation times and rates of the activated areas over all subjects yields an average T2* +/- standard deviation (SD) of 46.1+/-4.5 ms (R2* of 21.8+/-2.2 s(-1)) and an average increase (deltaT2* +/- SD) of 0.93+/-0.47 ms (deltaR2* of -0.4+/-0.14 s(-1)). Our findings demonstrate the usefulness of a multiple gradient echo data acquisition approach in separating various vascular contributions to brain activation in fMRI.

A hierarchical clustering method for analyzing functional MR images

We introduce a novel method for detecting anatomic and functional structures in fMRI. The main idea is to divide the data hierarchically into smaller groups using k-means clustering. The separation is halted if the clusters contain no further structure that is verified by several independent tests. The resulting cluster centers are then used for computing the final results in one step. The procedure is flexible, fast to compute, and the numbers of clusters in the data are obtained in a data-driven manner. Applying the algorithm to synthetic fMRI data yields perfect separation of "anatomic," i.e., time-invariant, and "functional," i.e., time-varying, information for a standard off-on paradigm and a typical functional contrast-to-noise ratio of two and higher. In addition, an EPI-fMRI data set of the human motor cortex was analyzed to demonstrate the performance of this novel approach in vivo.