CORSICA: correction of structured noise in fMRI by automatic identification of ICA components

When applied to functional magnetic resonance imaging (fMRI) data, spatial independent component analysis (sICA), a data-driven technique that addresses the blind source separation problem, seems able to extract components specifically related to physiological noise and brain movements. These components should be removed from the data to achieve structured noise reduction and improve any subsequent detection and analysis of signal fluctuations related to neural activity. We propose a new automatic method called CORSICA (CORrection of Structured noise using spatial Independent Component Analysis) to identify the components related to physiological noise, using prior information on the spatial localization of the main physiological fluctuations in fMRI data. As opposed to existing spectral priors, which may be subject to aliasing effects for long-TR data sets (typically acquired with TR >1 s), such spatial priors can be applied to fMRI data, regardless of the TR of the acquisitions. By comparing the proposed automatic selection to a manual selection performed visually by a human operator, we first show that CORSICA is able to identify the noise-related components for long-TR data with a high sensitivity and a specificity of 1. On short-TR data sets, we validate that the proposed method of noise reduction allows a substantial improvement of the signal-to-noise ratio evaluated at the cardiac and respiratory frequencies, even in the gray matter, while preserving the main fluctuations related to neural activity.     

Pure uterine lipoma

Lipomatous tumors of the uterus are unusual, benign neoplasms seen in postmenopausal women. Although many of the mixed-type cases such as lipoleiomyoma and fibrolipoma have been reported, pure uterine lipomas are extremely rare. In the literature, a few cases with pure uterine lipoma have been reported. We first present the advanced magnetic resonance findings of pure uterine lipoma, followed by those of ultrasonography (US) and computed tomography (CT). We markedly detected lipid peaks on the magnetic resonance spectroscopy (MRS) and the apparent diffusion coefficient value to be 0.00 due to chemical-shift effects with diffusion-weighted imaging (DWI). Although pelvic lipomatous tumors can be diagnosed with US and CT, in some cases, further workup may be required to localize the lesion. MRI may yield more valuable data for differential diagnosis. MRS and DWI findings provide additional clues on the nature of the lesion.     

Reduction of flow- and eddy-currents-induced image artifacts in coronary magnetic resonance angiography using a linear centric-encoding SSFP sequence

Coronary magnetic resonance angiography (MRA) acquired using steady-state free precession (SSFP) sequences tends to suffer from image artifacts caused by local magnetic field inhomogeneities. Flow- and gradient-switching-induced eddy currents are important sources of such phase errors, especially under off-resonant conditions. In this study, we propose to reduce these image artifacts by using a linear centric-encoding (LCE) scheme in the phase-encoding (PE) direction. Abrupt change in gradients, including magnitude and polarity between consecutive radiofrequency cycles, is minimized using the LCE scheme. Results from numeric simulations and phantom studies demonstrated that signal oscillation can be markedly reduced using LCE as compared to conventional alternating centric-encoding (ACE) scheme. The image quality of coronary arteries was improved at both 1.5 and 3.0 T using LCE compared to those acquired using ACE PE scheme (1.5 T: ACE/LCE=2.2+/-0.8/3.0+/-0.6, P=.02; 3.0 T: ACE/LCE=2.1+/-1.1/3.0+/-0.8, P=.01). In conclusion, flow- and eddy-currents-induced imaging artifacts in coronary MRA using SSFP sequence can be markedly reduced with LCE acquisition of PE lines.     

Spatial and temporal resolution effects on dynamic contrast-enhanced magnetic resonance mammography

We tested the hypothesis that partial volume effects due to poor in-plane resolution and/or low temporal resolution used in clinical dynamic contrast-enhanced magnetic resonance imaging results in erroneous diagnostic information based on inaccurate estimates of tumor contrast agent extravasation and tested whether reduced encoding techniques can correct for dynamic data volume averaging. Image spatial resolution was reduced from 469 x 469 microm2 to those reported below by selecting a subset of k-space data. We then compared the top five K(trans)/V(T) "hot spots" obtained from the original data set, 469 x 469-microm in-plane spatial resolution and an 18-s temporal resolution processed by fast Fourier transform (FFT), with values obtained from data sets having in-plane spatial resolutions of 938 x 938, 1875 x 1875 and 2500 x 2500 microm2 and a temporal resolution of 18 s, or data sets with temporal resolutions of 36, 54 and 72 and a spatial resolution of 469 x 469 microm2, and found them to statistically differ from the parent data sets. We then tested four different post processing methods for improving the spatial resolution without sacrificing temporal resolution: zero-filled FFT, keyhole, reduced-encoding imaging by generalized-series reconstruction (RIGR) and two-reference RIGR (TRIGR). The top five values of K(trans)/V(T) obtained from data sets, the in-plane spatial resolutions of which were improved to 469 x 469 microm2 by zero-filling FFT, Keyhole and RIGR, statistically differed from those obtained from the original 469 x 469 microm2 FFT parent image data set. Only the 938 x 938 and 1875 x 1875 microm2 data sets reconstructed to 469 x 469 microm2 with TRIGR reconstruction method yielded values of the top five K(trans)/V(T) hot spots statistically the same as the original parent data set, 469 x 469 microm2 in-plane spatial and 18-s temporal-resolution FFT. That is, partial volume effects from data sets of different in-plane spatial resolution resulted in statistically different values of the top five K(trans)/V(T) hot spots relative to a high spatial and temporal resolution data set, and TRIGR reconstruction of these low resolution data sets to high resolution images provided statistically similar values with a savings in temporal resolution of 2 to 4 times.     

Diffusion changes in patients with systemic lupus erythematosus

BACKGROUND AND PURPOSE: Systemic lupus erythematosus (SLE) is an autoimmune disease in which almost all the organs are involved. Neuropsychiatric SLE is of one of the major concerns in the clinical evaluation of this disease. Routine magnetic resonance imaging (MRI) findings are often nonspecific or negative. In this study, we explored the use of diffusion tensor imaging in assisting with the diagnosis of SLE. METHODS: Data from 34 SLE patients (age range, 18-73 years) and 29 age-matched volunteers (age range, 29-64 years) were analyzed. MRI was performed on a 1.5-T clinical MR scanner with a quadrature head coil. The average diffusion constant (D(av)) and diffusion anisotropy maps [fractional anisotropy (FA)] were determined on a pixel-by-pixel basis. Regional diffusion measurements were made by region of interest in the genu and splenium of the corpus callosum (CC), anterior and posterior limb of the internal capsule (IC) and frontal lobe and thalamus. The diffusion distribution was fitted to a triple-Gaussian model. The mean of the brain tissue distribution was determined as a mean diffusion constant for the whole brain (BD(av)). Student's t test was used to determine the diffusion difference between SLE patients and control subjects. The SLE patients were separated into two groups according to their MRI results. A P value lower than .05 was considered to be statistically significant. RESULTS: Twenty of the 34 SLE patients with abnormal MRI results showed findings dominated by nonspecific white matter disease. The BD(av) and D(av) values of the frontal lobe, splenium CC and anterior IC were significantly higher in all SLE patients as compared with the control subjects. The SLE patients with normal MRI results also showed higher BD(av) and D(av) values in the frontal lobe, splenium and anterior and posterior limbs of the IC as compared with the control subjects. There was no significant difference in the D(av) values of the thalamus between the SLE patients and the control subjects. The BD(av) value in the SLE patient group was robustly correlated with the D(av) values of the frontal lobe, splenium and thalamus. These correlations were found to be similarly significant for the SLE patients with normal MRI findings. The diffusion anisotropy measurements showed that splenium CC had the highest FA value in both the control subjects and SLE patients. Overall, SLE patients had lower FA values in the genu and splenium CC as compared with the control subjects. In the group of patients with normal MRI findings, the FA values of the genu and splenium CC as well as the anterior IC were also lower than those in the control subjects. Pearson's correlation statistics revealed robust correlations between the measurements of D(av) and FA values in the SLE patient group. CONCLUSION: Quantitative diffusion imaging and diffusion anisotropy showed early changes in the brains of the SLE patients. Increased BD(av) and D(av) values of the frontal lobe as well as decreased anisotropy in the genu CC and anterior IC may represent preclinical signs of central nervous system involvement of SLE even when the routine MRI findings are negative or nonspecific. Quantitative diffusion analysis may prove to be useful in detecting the initial brain involvement of SLE and may enable monitoring of early disease progression and treatment efficacy.     

Correcting saturation effects of the arterial input function in dynamic susceptibility contrast-enhanced MRI: a Monte Carlo simulation

To prevent systematic errors in quantitative brain perfusion studies using dynamic susceptibility contrast-enhanced magnetic resonance imaging (DSC-MRI), a reliable determination of the arterial input function (AIF) is essential. We propose a novel algorithm for correcting distortions of the AIF caused by saturation of the peak amplitude and discuss its relevance for longitudinal studies. The algorithm is based on the assumption that the AIF can be separated into a reliable part at low contrast agent concentrations and an unreliable part at high concentrations. This unreliable part is reconstructed, applying a theoretical framework based on a transport-diffusion theory and using the bolus-shape in the tissue. A validation of the correction scheme is tested by a Monte Carlo simulation. The input of the simulation was a wide range of perfusion, and the main aim was to compare this input to the determined perfusion parameters. Another input of the simulation was an AIF template derived from in vivo measurements. The distortions of this template was modeled via a Rician distribution for image intensities. As for a real DSC-MRI experiment, the simulation returned the AIF and the tracer concentration-dependent signal in the tissue. The novel correction scheme was tested by deriving perfusion parameters from the simulated data for the corrected and the uncorrected case. For this analysis, a common truncated singular value decomposition approach was applied. We find that the saturation effect caused by Rician-distributed noise leads to an overestimation of regional cerebral blood flow and regional cerebral blood volume, as compared to the input parameter. The aberration can be amplified by a decreasing signal-to-noise ratio (SNR) or an increasing tracer concentration. We also find that the overestimation can be successfully eliminated by the proposed saturation-correction scheme. In summary, the correction scheme will allow DSC-MRI to be expanded towards higher tracer concentrations and lower SNR and will help to increase the measurement to measurement reproducibility for longitudinal studies.     

An optimization method for designing SENSE imaging RF coil arrays

An optimization method in RF coil array design for SENSE imaging is described. Using this method the optimized RF coil geometries can be calculated numerically given the required SENSE imaging performance. Although this method can be applied to optimize the RF coil arrays for both 1D and 2D SENSE imaging, to demonstrate the potential applications of this method, we designed RF coil arrays for 2D SENSE imaging and compared their performance by simulation. An optimized 4-channel receive-only RF coil array designed for 2D SENSE imaging was implemented and tested to demonstrate the feasibility of the proposed technique. Imaging results showed reasonable agreement with the simulations, thus the method can be applied to RF coil array designs for SENSE imaging when optimum imaging performance is desired.     

Optimal estimation of the diffusion coefficient from non-averaged and averaged noisy magnitude data

The magnitude operation changes the signal distribution in MRI images from Gaussian to Rician. This introduces a bias that must be taken into account when estimating the apparent diffusion coefficient. Several estimators are known in the literature. In the present paper, two novel schemes are proposed. Both are based on simple least squares fitting of the measured signal, either to the median (MD) or to the maximum probability (MP) value of the Probability Density Function (PDF). Fitting to the mean (MN) or a high signal-to-noise ratio approximation to the mean (HS) is also possible. Special attention is paid to the case of averaged magnitude images. The PDF, which cannot be expressed in closed form, is analyzed numerically. A scheme for performing maximum likelihood (ML) estimation from averaged magnitude images is proposed. The performance of several estimators is evaluated by Monte Carlo (MC) simulations. We focus on typical clinical situations, where the number of acquisitions is limited. For non-averaged data the optimal choice is found to be MP or HS, whereas uncorrected schemes and the power image (PI) method should be avoided. For averaged data MD and ML perform equally well, whereas uncorrected schemes and HS are inadequate. MD provides easier implementation and higher computational efficiency than ML. Unbiased estimation of the diffusion coefficient allows high resolution diffusion tensor imaging (DTI) and may therefore help solving the problem of crossing fibers encountered in white matter tractography.     

A realization of digital wireless transmission for MRI signals based on 802.11b

In this paper, a digital wireless transmission system based on 802.11b standard for magnetic resonance imaging (MRI) application is designed and built for the first time to eliminate the interference aroused by coil array cables. The analysis shows that the wireless receiver has a very high sensitivity to detect MRI signals. The modulation technique of differential quadrature phase shift keyed (DQPSK) can be applied to MRI data transmission with rate of 2 Mbps and bandwidth of 2 MHz. The bench test verifies that this wireless link has a dynamic range over 86 dB supporting up to 3 T MRI system data transmission. The 2D spin echo imaging of phantom is performed and the SNR of the image obtained by the wireless transmission can be comparable with that got by the coaxial cables.     

Simultaneous acquisition of magnetic resonance spectroscopy (MRS) data and positron emission tomography (PET) images with a prototype MR-compatible, small animal PET imager

Multi-modality imaging (such as PET-CT) is rapidly becoming a valuable tool in the diagnosis of disease and in the development of new drugs. Functional images produced with PET, fused with anatomical images created by MRI, allow the correlation of form with function. Perhaps more exciting than the combination of anatomical MRI with PET, is the melding of PET with MR spectroscopy (MRS). Thus, two aspects of physiology could be combined in novel ways to produce new insights into the physiology of normal and pathological processes. Our team is developing a system to acquire MRI images and MRS spectra, and PET images contemporaneously. The prototype MR-compatible PET system consists of two opposed detector heads (appropriate in size for small animal imaging), operating in coincidence mode with an active field-of-view of approximately 14 cm in diameter. Each detector consists of an array of LSO detector elements coupled through a 2-m long fiber optic light guide to a single position-sensitive photomultiplier tube. The use of light guides allows these magnetic field-sensitive elements of the PET imager to be positioned outside the strong magnetic field of our 3T MRI scanner. The PET scanner imager was integrated with a 12-cm diameter, 12-leg custom, birdcage coil. Simultaneous MRS spectra and PET images were successfully acquired from a multi-modality phantom consisting of a sphere filled with 17 brain relevant substances and a positron-emitting radionuclide. There were no significant changes in MRI or PET scanner performance when both were present in the MRI magnet bore. This successful initial test demonstrates the potential for using such a multi-modality to obtain complementary MRS and PET data.