Generalized total variation-based MRI Rician denoising model with spatially adaptive regularization parameters

Magnetic resonance imaging (MRI) is an outstanding medical imaging modality but the quality often suffers from noise pollution during image acquisition and transmission. The purpose of this study is to enhance image quality using feature-preserving denoising method. In current literature, most existing MRI denoising methods did not simultaneously take the global image prior and local image features into account. The denoising method proposed in this paper is implemented based on an assumption of spatially varying Rician noise map. A two-step wavelet-domain estimation method is developed to extract the noise map. Following a Bayesian modeling approach, a generalized total variation-based MRI denoising model is proposed based on global hyper-Laplacian prior and Rician noise assumption. The proposed model has the properties of backward diffusion in local normal directions and forward diffusion in local tangent directions. To further improve the denoising performance, a local variance estimator-based method is introduced to calculate the spatially adaptive regularization parameters related to local image features and spatially varying noise map. The main benefit of the proposed method is that it takes full advantage of the global MR image prior and local image features. Numerous experiments have been conducted on both synthetic and real MR data sets to compare our proposed model with some state-of-the-art denoising methods. The experimental results have demonstrated the superior performance of our proposed model in terms of quantitative and qualitative image quality evaluations.     

Investigation of laminar appearance of articular cartilage by means of magnetic resonance microscopy

Magnetic resonance (MR) images and relaxation and diffusion maps of articular cartilage were obtained to explain discrepancies in its MR appearance. Porcine specimens were studied only by MR microscopy. For human specimens a combination of MR microscopy and large-scale MR imaging was used. Common features in the laminar structures of human and porcine samples are described. It was found that the decay of transverse magnetization was nonexponential with a rapidly decaying component which prevented construction of reliable proton-density maps. Dependence of T₂ values on the orientation of specimens in the magnetic field as well as magnetization transfer experiments supported the previous suggestions about a significant role of dipolar interaction with protons of collagen in the laminar appearance of articular cartilage. The loss of the laminar structure induced by rotation of the human cartilage specimen around the axis normal to its surface demonstrated nonuniform angular distribution of the collagen fibers within the layer.     

Investigating tumor perfusion and metabolism using multiple hyperpolarized (13)C compounds: HP001, pyruvate and urea

The metabolically inactive hyperpolarized agents HP001 (bis-1,1-(hydroxymethyl)-[1-(13)C]cyclopropane-d(8)) and urea enable a new type of perfusion magnetic resonance imaging based on a direct signal source that is background-free. The addition of perfusion information to metabolic information obtained by spectroscopic imaging of hyperpolarized [1-(13)C]pyruvate would be of great value in exploring the relationship between perfusion and metabolism in cancer. In preclinical normal murine and cancer model studies, we performed both dynamic multislice imaging of the specialized hyperpolarized perfusion compound HP001 (T(1)=95 s ex vivo, 32 s in vivo at 3 T) using a pulse sequence with balanced steady-state free precession and ramped flip angle over time for efficient utilization of the hyperpolarized magnetization and three-dimensional echo-planar spectroscopic imaging of urea copolarized with [1-(13)C]pyruvate, with compressed sensing for resolution enhancement. For the dynamic data, peak signal maps and blood flow maps derived from perfusion modeling were generated. The spatial heterogeneity of perfusion was increased 2.9-fold in tumor tissues (P=.05), and slower washout was observed in the dynamic data. The results of separate dynamic HP001 imaging and copolarized pyruvate/urea imaging were compared. A strong and significant correlation (R=0.73, P=.02) detected between the urea and HP001 data confirmed the value of copolarizing urea with pyruvate for simultaneous assessment of perfusion and metabolism.     

A statistical fMRI model for differential T2* contrast incorporating T1 and T2* of gray matter

Relaxation parameter estimation and brain activation detection are two main areas of study in magnetic resonance imaging (MRI) and functional magnetic resonance imaging (fMRI). Relaxation parameters can be used to distinguish voxels containing different types of tissue whereas activation determines voxels that are associated with neuronal activity. In fMRI, the standard practice has been to discard the first scans to avoid magnetic saturation effects. However, these first images have important information on the MR relaxivities for the type of tissue contained in voxels, which could provide pathological tissue discrimination. It is also well-known that the voxels located in gray matter (GM) contain neurons that are to be active while the subject is performing a task. As such, GM MR relaxivities can be incorporated into a statistical model in order to better detect brain activation. Moreover, although the MR magnetization physically depends on tissue and imaging parameters in a nonlinear fashion, a linear model is what is conventionally used in fMRI activation studies. In this study, we develop a statistical fMRI model for Differential T₂^? ConTrast Incorporating T₁ and T₂^? of GM, so-called DeTeCT-ING Model, that considers the physical magnetization equation to model MR magnetization; uses complex-valued time courses to estimate T₁ and T₂^? for each voxel; then incorporates gray matter MR relaxivities into the statistical model in order to better detect brain activation, all from a single pulse sequence by utilizing the first scans.     

Assessment of absolute blood volume in carcinoma by USPIO contrast-enhanced MRI

OBJECTIVES: The characterization of tumor vasculature is essential in studying tumor physiology. The aim of this study was to develop a new method - based on water proton MR density measurements, in combination with ultrasmall superparamagnetic iron oxide (USPIO) administration - to measure absolute blood volume (BV) in murine colon carcinoma. MATERIALS AND METHODS: MRI experiments were performed at 7 T. CPMG imaging was performed on subcutaneous murine colon carcinoma in six mice before and after administration of an USPIO blood-pool contrast agent. Density maps were obtained from the signal amplitude at TE=0 of the CPMG decay fit. Post-USPIO density maps were subtracted from pre-USPIO density maps to quantitatively yield absolute tumor BV maps. In a separate group of mice (n=6), the relative vascular area (RVA) of tumors was determined by immunohistochemistry. RESULTS: Ultrasmall superparamagnetic iron oxide administration resulted in a small decrease in the water proton MR density. The BV averaged over the six tumors was 4.6+/-1.6%. The value of the RVA measured by immunohistochemical staining was equal to 3.9+/-2.2%. CONCLUSIONS: After administration of an USPIO blood-pool agent (T(2) relaxivity > 100 mM(-1) s(-1)), the blood water protons become MRI invisible, and pixel-by-pixel BV map can be obtained by subtracting the calculated post-USPIO density map from the pre-USPIO density map. The value of absolute BV obtained with this novel MR approach is in good agreement with the value of the relative vascular measured by immunohistochemical staining.     

Magnetic resonance imaging and epilepsy: Neurosurgical decision making

Advances in magnetic resonance imaging (MRI) techniques have had an important impact on the decision-making process leading to surgical resection for chronic seizures. The MRI is now obtained relatively early in the work-up, and, when it shows abnormality, it assumes a crucial role in the detection of specific surgically remediable syndromes. These syndromes, when diagnosed by MR and other confirmatory studies such as electroencephalography (EEG), positron emission tomography (PET), magnetoencephalography (MEG), and neuropsychological testing, define the essential part of the surgical plan; that is, removal of the disease substrate. The availability of a host of MR techniques enable us to investigate epilepsy not only as a structural pathology but as physiological pathology reflected in abnormal blood flow, metabolism, and synaptic transmission. The mainstay of surgical treatment is the removal of the anatomic pathology, but other MR techniques may be helpful in the delineation of dual pathology in lesional cases, in appreciation of the full extent of microscopic pathology in developmental lesions, and in the imposition of restrictions on the resection based upon functional mapping. Finally, functional and anatomic maps obtained preoperatively can be related directly to the spatial coordinates of the exposed brain in the operating room using MRI-based frameless stereotactic methods. The final outcome, then, is the removal of the disease substrate without injury to adjacent, functionally salient cortical regions.     

Bilateral neurostimulation systems used for deep brain stimulation: in vitro study of MRI-related heating at 1.5 T and implications for clinical imaging of the brain

Deep brain stimulation (DBS) is used increasingly in the field of movement disorders. The implanted electrodes create not only a prior risk to patient safety during MRI, but also a unique opportunity in the collection of functional MRI data conditioned by direct neural stimulation. We evaluated MRI-related heating for bilateral neurostimulation systems used for DBS with an emphasis on assessing clinically relevant imaging parameters. Magnetic resonance imaging was performed using transmit body radiofrequency (RF) coil and receive-only head RF coil at various specific absorption rates (SARs) of RF power. In vitro testing was performed using a gel-filled phantom with temperatures recorded at the electrode tips. Each DBS electrode was positioned with a single extension loop around each pulse generator and a single loop at the "head" end of the phantom. Various pulse sequences were used for MRI including fast spin-echo, echo-planar imaging, magnetization transfer contrast and gradient-echo techniques. The MRI sequences had calculated whole-body averaged SARs and local head SARs ranging from 0.1 to 1.6 W/kg and 0.1 to 3.2 W/kg, respectively. Temperature elevations of less than 1.0 degrees C were found with the fast spin-echo, magnetization transfer contrast, gradient-echo and echo-planar clinical imaging sequences. Using the highest SAR levels, whole-body averaged, 1.6 W/kg, local exposed-body, 3.2 W/kg, and local head, 2.9 W/kg, the temperature increase was 2.1 degrees C. These results showed that temperature elevations associated with clinical sequences were within an acceptable physiologically safe range for the MR conditions used in this evaluation, especially for the use of relatively low SAR levels. Notably, these findings are highly specific to the neurostimulation systems, device positioning technique, MR system and imaging conditions used in this investigation.     

GPU based parallel framework for receiver coil sensitivity estimation in SENSE reconstruction

Magnetic Resonance Imaging (MRI) uses non-ionizing radiations and is safer as compared to CT and X-ray imaging. MRI is broadly used around the globe for medical diagnostics. One main limitation of MRI is its long data acquisition time. Parallel MRI (pMRI) was introduced in late 1990's to reduce the MRI data acquisition time. In pMRI, data is acquired by under-sampling the Phase Encoding (PE) steps which introduces aliasing artefacts in the MR images. SENSitivity Encoding (SENSE) is a pMRI based method that reconstructs fully sampled MR image from the acquired under-sampled data using the sensitivity information of receiver coils. In SENSE, precise estimation of the receiver coil sensitivity maps is vital to obtain good quality images. Eigen-value method (a recently proposed method in literature for the estimation of receiver coil sensitivity information) does not require a pre-scan image unlike other conventional methods of sensitivity estimation. However, Eigen-value method is computationally intensive and takes a significant amount of time to estimate the receiver coil sensitivity maps. This work proposes a parallel framework for Eigen-value method of receiver coil sensitivity estimation that exploits its inherent parallelism using Graphics Processing Units (GPUs). We evaluated the performance of the proposed algorithm on in-vivo and simulated MRI datasets (i.e. human head and simulated phantom datasets) with Peak Signal-to-Noise Ratio (PSNR) and Artefact Power (AP) as evaluation metrics. The results show that the proposed GPU implementation reduces the execution time of Eigen-value method of receiver coil sensitivity estimation (providing up to 30 times speed up in our experiments) without degrading the quality of the reconstructed image.     

磁流变减振系统参数辨识

在对磁流变体的力学性能、减振系统设计和实验建模方法深入研究的基础上,提出了采用非线性顺序滤波来辨识磁流变化减振装置粘弹性模型参数的实验建模方法。研究表明,基于粘塑性假设,可用于该辨识算法获得库仑摩擦力和粘性摩擦系数。     

1H MR spatially resolved spectroscopy of human tissues in situ

SPAtially Resolved Spectroscopy (SPARS) has been developed as a method to obtain localized MR spectra in a whole body MRI system. It is based upon a combination of selective and non-selective pulses such that longitudinal magnetization is preserved in a particular volume of interest (VOI), whereas outside this volume the magnetization is dephased in the transversal plane. After this selection phase the spectrum of the VOI can be obtained after a single excitation pulse. In this respect it is similar to the VSE sequence as proposed by Aue et al. The difference is that even by using relatively large body and head coils the SPARS sequence requires much lower rf powers levels, such that it can be implemented on a whole body MRI system.     

Pharmacokinetic analysis of glioma compartments with dynamic Gd-DTPA-enhanced magnetic resonance imaging

Dynamic contrast-enhanced magnetic resonance imaging (MRI) is widely used for measuring perfusion and blood volume, especially cerebral blood volume (CBV). In case of blood-brain barrier (BBB) disruption, the conventional techniques only partially determine the pharmacokinetic parameters of contrast medium (CM) exchange between different compartments. Here a modified pharmacokinetic model is applied, which is based on the bidirectional CM exchange between blood and two interstitial compartments in terms of the fractional volumes of the compartments and the vessel permeabilities between them. The evaluation technique using this model allows one to quantify the fractional volumes of the different compartments (blood, cells, slowly and fast enhancing interstitium) as well as the vessel permeabilities and cerebral blood flow (CBF) with a single T1-weighted dynamic MRI measurement. The method has been successfully applied in 25 glioma patients for generating maps of all of these parameters. The fractional volume maps allow for the differentiation of glioma vascularization types. The maps show a good correlation with the histological grading of these tumors. Furthermore, regions with enhanced interstitial volumes are found in high-grade gliomas. Differences in permeability maps of Gd-DTPA apart from BBB disruption do not exist between different tissue types. CBF measured in high-grade glioma is less pronounced than it would be expected from their blood volume. Therefore pharmacokinetic imaging provides an additional tool for glioma characterization.     

Analysis of longitudinal relaxation rate constants from magnetization transfer MR images of human tissues at 0.1 T.

The human calf muscle was examined by using the magnetization transfer MR imaging technique. The time-dependent saturation transfer (TDST) method was applied at low magnetic field 0.1 T in order to measure the mobile water relaxation time T1w, the magnetization transfer rate Rwm from water to solid macromolecules, and the magnetization transfer contrast (MTC) of the human tissue. The magnetization transfer contrast of 0.67 was attained. The transfer rate Rwm was 4.5 sec-1 (+/- 0.3 sec-1) for the anterior tibial muscle and 5.0 sec-1 (+/- 0.4 sec-1) for the gastrocnemius muscles. The values of Rwm are considerably larger than the values of corresponding relaxation rates measured at high fields. The relaxation rate measurements of human tissues in vivo was shown to be possible at 0.1 T even within the framework of normal routine MR imaging. Magnetization transfer MR imaging is a very promising and practical method in order to assess the relaxation processes in heterogeneous human tissues in vivo, and it can improve the tissue characterization possibilities of MR imaging techniques.     

Optimization of a transmit/receive surface coil for squirrel monkey spinal cord imaging

MR Imaging the spinal cord of non-human primates (NHP), such as squirrel monkey, is important since the injuries in NHP resemble those that afflict human spinal cords. Our previous studies have reported a multi-parametric MRI protocol, including functional MRI, diffusion tensor imaging, quantitative magnetization transfer and chemical exchange saturation transfer, which allows non-invasive detection and monitoring of injury-associated structural, functional and molecular changes over time. High signal-to-noise ratio (SNR) is critical for obtaining high-resolution images and robust estimates of MRI parameters. In this work, we describe our construction and use of a single channel coil designed to maximize the SNR for imaging the squirrel monkey cervical spinal cord in a 21 cm bore magnet at 9.4 T. We first numerically optimized the coil dimension of a single loop coil and then evaluated the benefits of a quadrature design. We then built an optimized coil based on the simulation results and compared its SNR performance with a non-optimized single coil in both phantoms and in vivo.     

SPRITE MRI with Prepared Magnetization and Centrick-Space Sampling

A technique for imaging materials with short transverse relaxation times and prepared longitudinal magnetization is proposed. The technique is single-point ramped imaging withT₁-enhancement (SPRITE) MRI with centrick-space sampling. The effects of transient state behavior on image resolution and signal/noise are estimated. Centric sampling in the basic SPRITE sequence gives increased signal-to-noise and permits a quantitative determination of the MR parameters associated with longitudinal spin preparation. Spin-lock and inversion recovery preparation experiments are presented.     

基于单片FPGA的多通道磁共振成像接收模块

提出了一种基于FPGA的多通道磁共振成像接收模块,能对多个独立通道的磁共振信号进行直接采样、数字下变频,以及数据流控制,并对其进行了成像实验. 设计中采用Xilinx公司的系统级DSP开发工具--System Generator对FPGA内部所有功能进行建模、仿真并生成相应的硬件描述语言. 模块的采样速率为80MSPS,能灵活实现1 kHz~1 MHz范围的可变接收带宽,适用于1 T以下的磁共振成像系统;在单片FPGA内完成1~4个通道采样信号的数字正交解调,抽取滤波和数据流的处理,并可扩展至8通道. 实验证明模块具有体积小,集成度高,可重构性强和成本低等特点,为磁共振成像谱仪的多通道接收系统提供了一种高性能的数字化解决方案.     

Quantitative MR temperature monitoring of high-intensity focused ultrasound therapy

A new quantitative method has been developed for real-time mapping of temperature changes induced by high intensity focused ultrasound (HIFU). It is based on the temperature dependence of the T1 relaxation time and the equilibrium magnetization. To calibrate the temperature measurement, the functional relationship between T1 and temperature was examined in different samples of porcine muscle and fatty tissue. The method was validated by a comparison of calculated temperature maps with fiber-optic measurements in heated muscle tissue. The experiment showed that the accuracy of the MR method for temperature measurements is better than 1 degree C. Since the acquisition time of the employed MR sequence takes only 3 s per slice and the calculation of the temperature map can be performed within seconds, the imaging technique works nearly in real-time. The temperature measurement could be realized during HIFU showing no disturbances by ultrasound sonication. In comparison to other MR approaches, the advantages of the introduced method lie in a sufficient accuracy and time resolution combined with a reasonable robustness against motion as well as the feasibility for temperature monitoring in fatty tissues.     

Magnetic resonance imaging segmentation techniques using batch-type learning vector quantization algorithms

In this article, we propose batch-type learning vector quantization (LVQ) segmentation techniques for the magnetic resonance (MR) images. Magnetic resonance imaging (MRI) segmentation is an important technique to differentiate abnormal and normal tissues in MR image data. The proposed LVQ segmentation techniques are compared with the generalized Kohonen's competitive learning (GKCL) methods, which were proposed by Lin et al. [Magn Reson Imaging 21 (2003) 863-870]. Three MRI data sets of real cases are used in this article. The first case is from a 2-year-old girl who was diagnosed with retinoblastoma in her left eye. The second case is from a 55-year-old woman who developed complete left side oculomotor palsy immediately after a motor vehicle accident. The third case is from an 84-year-old man who was diagnosed with Alzheimer disease (AD). Our comparisons are based on sensitivity of algorithm parameters, the quality of MRI segmentation with the contrast-to-noise ratio and the accuracy of the region of interest tissue. Overall, the segmentation results from batch-type LVQ algorithms present good accuracy and quality of the segmentation images, and also flexibility of algorithm parameters in all the comparison consequences. The results support that the proposed batch-type LVQ algorithms are better than the previous GKCL algorithms. Specifically, the proposed fuzzy-soft LVQ algorithm works well in segmenting AD MRI data set to accurately measure the hippocampus volume in AD MR images.     

On the utility of spectroscopic imaging as a tool for generating geometrically accurate MR images and parameter maps in the presence of field inhomogeneities and chemical shift effects

Lack of spatial accuracy is a recognized problem in magnetic resonance imaging (MRI) which severely detracts from its value as a stand-alone modality for applications that put high demands on geometric fidelity, such as radiotherapy treatment planning and stereotactic neurosurgery. In this paper, we illustrate the potential and discuss the limitations of spectroscopic imaging as a tool for generating purely phase-encoded MR images and parameter maps that preserve the geometry of an object and allow localization of object features in world coordinates.     

Microtesla MRI of the human brain combined with MEG

One of the challenges in functional brain imaging is integration of complementary imaging modalities, such as magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI). MEG, which uses highly sensitive superconducting quantum interference devices (SQUIDs) to directly measure magnetic fields of neuronal currents, cannot be combined with conventional high-field MRI in a single instrument. Indirect matching of MEG and MRI data leads to significant co-registration errors. A recently proposed imaging method--SQUID-based microtesla MRI--can be naturally combined with MEG in the same system to directly provide structural maps for MEG-localized sources. It enables easy and accurate integration of MEG and MRI/fMRI, because microtesla MR images can be precisely matched to structural images provided by high-field MRI and other techniques. Here we report the first images of the human brain by microtesla MRI, together with auditory MEG (functional) data, recorded using the same seven-channel SQUID system during the same imaging session. The images were acquired at 46 microT measurement field with pre-polarization at 30 mT. We also estimated transverse relaxation times for different tissues at microtesla fields. Our results demonstrate feasibility and potential of human brain imaging by microtesla MRI. They also show that two new types of imaging equipment--low-cost systems for anatomical MRI of the human brain at microtesla fields, and more advanced instruments for combined functional (MEG) and structural (microtesla MRI) brain imaging--are practical.     

Validation of V-SS-PARSE for single-shot flow measurement

As a variant of Single-Shot Parameter Assessment by Retrieval from Signal Encoding, Velocity Single-Shot Parameter Assessment by Retrieval from Signal Encoding, a single-shot imaging method, has been developed to realize fast and straightforward flow quantification by solving inverse problems. A robust signal model, including its local magnetization and its phase evolution during signaling (resulting in a more precise representation of the sampled signal) is described here. Magnitude, velocity, relaxation rate and frequency information can be retrieved without any extra reference image acquisitions, as demonstrated by phantom studies. In the presence of stationary background, retrieved magnitude maps and velocity maps show results comparable to those obtained by phase-contrast methods (r>.99, P=.005), even with brief single-shot 70-ms acquisition.