Parallel MRI at microtesla fields

Parallel imaging techniques have been widely used in high-field magnetic resonance imaging (MRI). Multiple receiver coils have been shown to improve image quality and allow accelerated image acquisition. Magnetic resonance imaging at ultra-low fields (ULF MRI) is a new imaging approach that uses SQUID (superconducting quantum interference device) sensors to measure the spatially encoded precession of pre-polarized nuclear spin populations at microtesla-range measurement fields. In this work, parallel imaging at microtesla fields is systematically studied for the first time. A seven-channel SQUID system, designed for both ULF MRI and magnetoencephalography (MEG), is used to acquire 3D images of a human hand, as well as 2D images of a large water phantom. The imaging is performed at 46 mu T measurement field with pre-polarization at 40 mT. It is shown how the use of seven channels increases imaging field of view and improves signal-to-noise ratio for the hand images. A simple procedure for approximate correction of concomitant gradient artifacts is described. Noise propagation is analyzed experimentally, and the main source of correlated noise is identified. Accelerated imaging based on one-dimensional undersampling and 1D SENSE (sensitivity encoding) image reconstruction is studied in the case of the 2D phantom. Actual threefold imaging acceleration in comparison to single-average fully encoded Fourier imaging is demonstrated. These results show that parallel imaging methods are efficient in ULF MRI, and that imaging performance of SQUID-based instruments improves substantially as the number of channels is increased.     

Magnetic resonance imaging at frequencies below 1 kHz

Within the magnetic resonance imaging (MRI) community the trend is going to higher and higher magnetic fields, ranging from 1.5 T to 7 T, corresponding to Larmor frequencies of 63.8–298 MHz. Since for high-field MRI the magnetization increases with the applied magnetic field, the signal-to-noise-ratio increases as well, thus enabling higher image resolutions. On the other hand, MRI is possible also at ultra-low magnetic fields, as was shown by different groups. The goal of our development was to reach a Larmor frequency range of the low-field MRI system corresponding to the frequency range of human brain activities ranging from near zero-frequency (near-DC) to over 1 kHz. Here, first 2D MRI images of phantoms taken at Larmor frequencies of 100 Hz and 731 Hz will be shown and discussed. These frequencies are examples of brain activity triggered by electrostimulation of the median nerve. The method will allow the magnetic fields of the brain currents to influence the magnetic resonance image, and thus lead to a direct functional imaging modality of neuronal currents.     

On the nature of the BOLD fMRI contrast mechanism

Since its development about 15 years ago, functional magnetic resonance imaging (fMRI) has become the leading research tool for mapping brain activity. The technique works by detecting the levels of oxygen in the blood, point by point, throughout the brain. In other words, it relies on a surrogate signal, resulting from changes in oxygenation, blood volume and flow, and does not directly measure neural activity. Although a relationship between changes in brain activity and blood flow has long been speculated, indirectly examined and suggested and surely anticipated and expected, the neural basis of the fMRI signal was only recently demonstrated directly in experiments using combined imaging and intracortical recordings. In the present paper, we discuss the results obtained from such combined experiments. We also discuss our current knowledge of the extracellularly measured signals of the neural processes that they represent and of the structural and functional neurovascular coupling, which links such processes with the hemodynamic changes that offer the surrogate signal that we use to map brain activity. We conclude by considering applications of invasive MRI, including injections of paramagnetic tracers for the study of connectivity in the living animal and simultaneous imaging and electrical microstimulation.     

Multimodal integration of EEG, MEG and fMRI data for the solution of the neuroimage puzzle

In this paper, advanced methods for the modeling of human cortical activity from combined high-resolution electroencephalography (EEG), magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI) data are presented. These methods include a subject's multicompartment head model (scalp, skull, dura mater, cortex) constructed from magnetic resonance images, multidipole source model and regularized linear inverse source estimates of cortical current density. Determination of the priors in the resolution of the linear inverse problem was performed with the use of information from the hemodynamic responses of the cortical areas as revealed by block-designed (strength of activated voxels) fMRI. Examples of the application of these methods to the estimation of the time varying cortical current density activity in selected region of interest (ROI) are presented for movement-related high-resolution EEG data.     

Theory of MRI in the presence of zero to low magnetic fields and tensor imaging field gradients

Today, all commonly practiced magnetic resonance imaging (MRI) reconstruction methods assume that the magnetic field created by the gradient coils is everywhere truncated by a dominant static uniform magnetic field. However, with the advent of SQUID detected MRI at microtesla fields, the opposite limit attracts attention, i.e., image formation in the unperturbed tensor field of the gradient coils. Here, we show by numerical simulations that, in principle, it is possible to reconstruct the image of an object in the absence of a uniform static field, working with the same gradient field setup as used in conventional MRI. Our calculations show that this approach could increase the image resolution limit attainable at low fields with a minimal incorporation of additional hardware and pulse sequences.     

Complementary aspects of diffusion imaging and fMRI; I: structure and function

Studying the intersection of brain structure and function is an important aspect of modern neuroscience. The development of magnetic resonance imaging (MRI) over the last 25 years has provided new and powerful tools for the study of brain structure and function. Two tools in particular, diffusion imaging and functional MRI (fMRI), are playing increasingly important roles in elucidating the complementary aspects of brain structure and function. In this work, we review basic technical features of diffusion imaging and fMRI for studying the integrity of white matter structural components and for determining the location and extent of cortical activation in gray matter, respectively. We then review a growing body of literature in which the complementary aspects of diffusion imaging and fMRI, applied as separate examinations but analyzed in tandem, have been exploited to enhance our knowledge of brain structure and function.     

采用超导量子干涉组件在微特斯拉磁场下获取超极化~3He的核磁共振波谱和影像(英文)

该文以超导量子干涉元件研究光激发氦三极化气体的低磁场磁共振与造影术.使用圆偏极化雷色光将氦三气体极化,超导量子干涉元件磁共振与造影之测量是以磁通耦合方式来进行,超导量子干涉元件是用铋锶钙铜氧高溫超导罐来隔离环境噪音.此方法测得的磁共振信号与影像相较于直接将样品置于杜瓦瓶下方有较高的信噪比,当样品无法靠近感测元件时,此装置具高信噪比特色.磁通耦合方式的超导量子干涉元件低磁场磁共振与造影术及其氦三极化气体的肺部造影在学术与应用上是相当有趣.     

Dynamics of the brain: Mathematical models and non-invasive experimental studies

Dynamics is an essential aspect of the brain function. In this article we review theoretical models of neural and haemodynamic processes in the human brain and experimental non-invasive techniques developed to study brain functions and to measure dynamic characteristics, such as neurodynamics, neurovascular coupling, haemodynamic changes due to brain activity and autoregulation, and cerebral metabolic rate of oxygen. We focus on emerging theoretical biophysical models and experimental functional neuroimaging results, obtained mostly by functional magnetic resonance imaging (fMRI) and near-infrared spectroscopy (NIRS). We also included our current results on the effects of blood pressure variations on cerebral haemodynamics and simultaneous measurements of fast processes in the brain by near-infrared spectroscopy and a very novel functional MRI technique called magnetic resonance encephalography. Based on a rapid progress in theoretical and experimental techniques and due to the growing computational capacities and combined use of rapidly improving and emerging neuroimaging techniques we anticipate during next decade great achievements in the overall knowledge of the human brain.     

Improving the resolution of functional brain imaging: analyzing functional data in anatomical space

The accurate mapping of functional magnetic resonance imaging (fMRI) activations to anatomical structures is critical for fMRI studies of brain organization. In the commonly used functional space analysis method, functional images are realigned to a functional reference image and processed in low-resolution functional space. The average functional activations are then projected into high-resolution anatomical space for visualization. Here, we describe a new technique, anatomical space analysis (ASA), whereby low-resolution functional images are first coregistered and resampled directly into high-resolution anatomical space with all subsequent data processing performed in high-resolution space. A major advantage of ASA is that minor scanner sampling instabilities and small head movements can increase spatial resolution by providing multiple samples of the relationship between functional and anatomical space. Both simulations and analyses of real fMRI data show that ASA improves the precision, objectivity and reproducibility of functional brain mapping.     

High-resolution near-infrared tomographic imaging simulations of the rat cranium by use of a priori magnetic resonance imaging structural information

Near-infrared (NIR) optical image reconstruction that incorporates magnetic resonance image (MRI) structural data was tested in a series of simulated reconstructions. NIR diffuse tomography generally suffers from comparatively low spatial resolution. By using the fine structural detail that is available with MRI, combined with the functional information of NIR spectroscopy, it is possible to design a new image-reconstruction methodology that provides high-resolution images that are correlated with hemoglobin concentration and oxygen saturation. To test this concept a MRI spin-echo image of a rat cranium was used to obtain an outline of the bone, brain, and muscle tissues, and this information was incorporated into an iterative-based diffuse tomography reconstruction. These simulations represent what is believed to be the first attempt at evaluating a spatially constrained iterative-reconstruction MRI-NIR imaging modality for brain tissue.     

Realignment strategies for awake-monkey fMRI data

Functional magnetic resonance imaging (fMRI) experiments with awake nonhuman primates (NHPs) have recently seen a surge of applications. However, the standard fMRI analysis tools designed for human experiments are not optimal for NHP data collected at high fields. One major difference is the experimental setup. Although real head movement is impossible for NHPs, MRI image series often contain visible motion artifacts. Animal body movement results in image position changes and geometric distortions. Since conventional realignment methods are not appropriate to address such differences, algorithms tailored specifically for animal scanning become essential. We have implemented a series of high-field NHP specific methods in a software toolbox, fMRI Sandbox (http://kyb.tuebingen.mpg.de/~stoewer/), which allows us to use different realignment strategies. Here we demonstrate the effect of different realignment strategies on the analysis of awake-monkey fMRI data acquired at high field (7 T). We show that the advantage of using a nonstandard realignment algorithm depends on the amount of distortion in the dataset. While the benefits for less distorted datasets are minor, the improvement of statistical maps for heavily distorted datasets is significant.     

增强低场下脑功能磁共振成像显著性的研究

实现了基于低场0.35 T磁共振成像系统的大脑功能磁共振成像（functional Magnetic Resonance Imaging,fMRI）的研究. 基于质子密度加权的快速自旋回波(Turbo Spin Echo,TSE)图像,重点研究增强低场fMRI显著性的方法,目的在于提高低场fMRI的可用性. 结果表明：健康受试者在执行手动任务期间,大脑运动区的信号强度变化可以由基于血管外质子信号增强 (Signal Enhancement by Extravascular water Protons,EEP)的对比机制探测. 优化TSE序列参数能提高图像SNR和扫描速度,并在统计分析中增加外在屏蔽图像,可以有效地提高低场下fMRI研究结果的显著性.     

A 16-channel loop array for in vivo macaque whole-brain imaging at 3 T

Non-human primates (NHPs) are vital models for neuroscience research. These animals have been widely used in behavioral, electrophysiological, molecular, and more recently, multimodal neuroimaging and neuro-engineering studies. Several RF coil arrays have been designed for functional, high-resolution brain magnetic resonance imaging (MRI), but few have been designed to accommodate multimodal devices. In the present study, a 16-channel array coil was constructed for brain imaging of macaques at 3 Tesla (3 T). To construct this coil, a close-fitting helmet-shaped form was designed to host 16 coil loops for whole-brain coverage. This assembly is mountable onto stereotaxic head frame bars, and the coil functions while the monkey is in the sphinx position with a clear line of vision of stimuli presented from outside of the MRI system. In addition, 4 openings were allocated in the coil housing, allowing multimodal devices to directly access visual cortical regions such as V1-V4 and MT. Coil performance was evaluated in an anesthetized macaque by quantifying and comparing signal-to-noise ratios (SNRs), noise correlations, and g-factor maps to a vendor-supplied human pediatric coil frequently used for NHP MRI. The result from in vivo experiments showed that the NHP coil was well-decoupled, had higher SNRs in cortical regions, and improved data acquisition acceleration capability compared with a vendor-supplied human pediatric coil that has been frequently used in macaque MRI studies. Furthermore, whole-brain anatomic imaging, diffusion tensor imaging and functional brain imaging have also been conducted: the details of brain anatomical structure, such as cerebellum and brainstem, can be clearly visualized in T2-SPACE images; b0 SNR calculated from b0 maps was higher than the human pediatric coil in all regions of interest (ROIs); the time-course SNR (tSNR) map calculated for GRE-EPI images demonstrates that the presented coil can be used for high-resolution functional imaging at 3 T.     

Direct detection of neuronal activity with MRI: Fantasy, possibility, or reality?

Hemodynamic-based functional magnetic resonance imaging (fMRI) techniques have proven to be extremely robust and sensitive methods for noninvasive detection and mapping of human brain activation. Nevertheless, limitations in temporal and spatial resolution as well as interpretation remain because hemodynamic changes accompanying brain activation are relatively sluggish and variable and therefore imprecise measures of neuronal activity. A hope among brain imagers would be to possess a technique that would allow direct mapping of brain activity with spatial resolution on the order of a cortical column and temporal resolution on the order of an action potential or at least a postsynaptic potential. Recent efforts in understanding the direct effects of neuronal activity on MRI signal have provided some degree of hope for those who want a more precise noninvasive brain activation mapping technique than fMRI as we know it now. While the manner in which electrical currents influence MRI signal is well understood, the manner in which neuronal firing spatially and temporally integrates on the spatial scale of an MRI voxel to produce a magnetic field shift and subsequently an NMR phase and/or magnitude change is not well understood. It is also not established that this field shift would be large or long enough in duration to be detected. The objective of this paper is to provide a perspective of the work that has been performed towards the direction of achieving direct neuronal current imaging with MRI. A specific goal is to further clarify what is understood about the theoretical and practical possibilities of neuronal current imaging. Specifically discussed are modeling efforts, phantom studies, in vitro studies, and human studies.     

Solving the problem of concomitant gradients in ultra-low-field MRI

In ultra-low-field magnetic resonance imaging (ULF MRI), spin precession is detected typically in magnetic fields of the order of 10-100 μT. As in conventional high-field MRI, the spatial origin of the signals can be encoded by superposing gradient fields on a homogeneous main field. However, because the main field is weak, gradient field amplitudes become comparable to it. In this case, the concomitant gradients forced by Maxwell's equations cause the assumption of linearly varying field gradients to fail. Thus, image reconstruction with Fourier transformation would produce severe image artifacts. We propose a direct linear inversion (DLI) method to reconstruct images without limiting assumptions about the gradient fields. We compare the quality of the images obtained using the proposed reconstruction method and the Fourier reconstruction. With simulations, we show how the reconstruction errors of the methods depend on the strengths of the concomitant gradients. The proposed approach produces nearly distortion-free images even when the main field reaches zero.     

Fine-scale functional connectivity in somatosensory cortex revealed by high-resolution fMRI

High-resolution functional magnetic resonance imaging (fMRI) at high field (9.4 T) has been used to measure functional connectivity between subregions within the primary somatosensory (SI) cortex of the squirrel monkey brain. The hand-face region within the SI cortex of the squirrel monkey has been previously well mapped with functional imaging and electrophysiological and anatomical methods, and the orderly topographic map of the hand region is characterized by a lateral to medial representation of individual digits in four subregions of areas 3a, 3b, 1 and 2. With submillimeter resolution, we are able to detect not only the separate islands of activation corresponding to vibrotactile stimulations of single digits but also, in subsequent acquisitions, the degree of correlation between voxels within the SI cortex in the resting state. The results suggest that connectivity patterns are very similar to stimulus-driven distributions of activity and that connectivity varies on the scale of millimeters within the same primary region. Connectivity strength is not a reflection of global larger-scale changes in blood flow and is not directly dependent on distance between regions. Preliminary electrophysiological recordings agree well with the fMRI data. In human studies at 7 T, high-resolution fMRI may also be used to identify the same subregions and assess responses to sensory as well as painful stimuli, and to measure connectivity dynamically before and after such stimulations.     

Synchronized detection of minute electrical currents with MRI using Lorentz effect imaging

The blood oxygenation level-dependent (BOLD) effect is the most commonly used contrast mechanism in functional magnetic resonance imaging (fMRI), due to its relatively high spatial resolution and sensitivity. However, the ability of BOLD fMRI to accurately localize neuronal activation in space and time is limited by the inherent hemodynamic modulation. There is hence a need to develop alternative MRI methods that can directly image neuroelectric activity, thereby achieving both a high temporal resolution and spatial specificity as compared to conventional BOLD fMRI. In this paper, we extend the Lorentz effect imaging technique, which can detect spatially incoherent yet temporally synchronized minute electrical activity in a strong magnetic field, and demonstrate its feasibility for imaging randomly oriented electrical currents on the order of microamperes with a temporal resolution on the order of milliseconds in gel phantoms. This constitutes a promising step towards its application to direct imaging of neuroelectric activity in vivo, which has the same order of current density and temporal synchrony.     

Respiratory noise correction using phase information

Respiratory noise is a confounding factor in functional magnetic resonance imaging (MRI) data analysis. A novel method called Respiratory noise Correction using Phase information is proposed to retrospectively correct for the respiratory noise in functional MRI (fMRI) time series. It is demonstrated that the respiratory movement and the phase of functional MRI images are highly correlated in time. The signal fluctuation due to respiratory movements can be effectively estimated from the phase variation and removed from the functional MRI time series using a Wiener filtering technique. In our experiments, this new method is compared with RETROICOR, which requires recording respiration signal simultaneously in an fMRI experiment. The two techniques show comparable performance with respect to the respiratory noise correction for fMRI time series. However, this technique is more advantageous because there is no need for monitoring the subjects’ respiration or changing functional MRI protocols. This technique is also potentially useful for correcting respiratory noise from abnormal breathing or when the respiration is not periodic.     

Registering and analyzing rat fMRI data in the stereotaxic framework by exploiting intrinsic anatomical features

The value of analyzing neuroimaging data on a group level has been well established in human studies. However, there is no standard procedure for registering and analyzing functional magnetic resonance imaging (fMRI) data into common space in rodent fMRI studies. An approach for performing rat imaging data analysis in the stereotaxic framework is presented. This method is rooted in the biological observation that the skull shape and size of rat brain are essentially the same as long as their weights are within certain range. Registration is performed using rigid-body transformations without scaling or shearing, preserving the unique properties of the stable shape and size inherent in rat brain structure. Also, it does not require brain tissue masking and is not biased towards surface coil sensitivity profile. A standard rat brain atlas is used to facilitate the identification of activated areas in common space, allowing accurate region of interest analysis. This technique is evaluated from a group of rats (n=11) undergoing routine MRI scans; the registration accuracy is estimated to be within 400 μm. The analysis of fMRI data acquired with an electrical forepaw stimulation model demonstrates the utility of this technique. The method is implemented within the Analysis of Functional NeuroImages (AFNI) framework and can be readily extended to other studies.