Total variation-based method for generation of intravoxel incoherent motion parametric images in MRI.

PURPOSE: Total variation (TV) method has been used widely for image restoration and reconstruction. In this work, we propose a TV-based algorithm for parametric image generation in intravoxel incoherent motion (IVIM) diffusion-weighted magnetic resonance imaging (DW-MRI). METHODS: We used simulated and real data to investigate whether the proposed TV-based method can provide reliable parametric images. Parametric images of IVIM parameters including perfusion fraction (PF), diffusion coefficient (D), and pseudo-diffusion coefficient (D*) were estimated using DW-MRI data and TV through fitting the IVIM model. The Levenberg-Marquardt (LM) method, which has often been used in the context of IVIM analysis, was employed as the standard method for comparison of the resulting parametric images. RESULTS: The simulation results show that the proposed method outperforms the LM algorithm in terms of precision, providing a 40-81%, 90-93%, and 68-84% improvement for PF, D and D*, respectively, at signal-to-noise ratio (SNR) of 30. For real data, the proposed method showed an average five-fold, three-fold, and four-fold improvement in the SNR for PF, D and D*, respectively. CONCLUSION: We introduced the use of TV to produce parametric images, and demonstrated that the proposed TV-based method is effective in improving the parametric image quality. Magn Reson Med 78:1383-1391, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Formation of parametric images using mixed-effects models: a feasibility study.

Mixed-effects models have been widely used in the analysis of longitudinal data. By presenting the parameters as a combination of fixed effects and random effects, mixed-effects models incorporating both within- and between-subject variations are capable of improving parameter estimation. In this work, we demonstrate the feasibility of using a non-linear mixed-effects (NLME) approach for generating parametric images from medical imaging data of a single study. By assuming that all voxels in the image are independent, we used simulation and animal data to evaluate whether NLME can improve the voxel-wise parameter estimation. For testing purposes, intravoxel incoherent motion (IVIM) diffusion parameters including perfusion fraction, pseudo-diffusion coefficient and true diffusion coefficient were estimated using diffusion-weighted MR images and NLME through fitting the IVIM model. The conventional method of non-linear least squares (NLLS) was used as the standard approach for comparison of the resulted parametric images. In the simulated data, NLME provides more accurate and precise estimates of diffusion parameters compared with NLLS. Similarly, we found that NLME has the ability to improve the signal-to-noise ratio of parametric images obtained from rat brain data. These data have shown that it is feasible to apply NLME in parametric image generation, and the parametric image quality can be accordingly improved with the use of NLME. With the flexibility to be adapted to other models or modalities, NLME may become a useful tool to improve the parametric image quality in the future. Copyright © 2015 John Wiley & Sons, Ltd.

Pushing CT and MR imaging to the molecular level for studying the "omics": current challenges and advancements.

During the past decade, medical imaging has made the transition from anatomical imaging to functional and even molecular imaging. Such transition provides a great opportunity to begin the integration of imaging data and various levels of biological data. In particular, the integration of imaging data and multiomics data such as genomics, metabolomics, proteomics, and pharmacogenomics may open new avenues for predictive, preventive, and personalized medicine. However, to promote imaging-omics integration, the practical challenge of imaging techniques should be addressed. In this paper, we describe key challenges in two imaging techniques: computed tomography (CT) and magnetic resonance imaging (MRI) and then review existing technological advancements. Despite the fact that CT and MRI have different principles of image formation, both imaging techniques can provide high-resolution anatomical images while playing a more and more important role in providing molecular information. Such imaging techniques that enable single modality to image both the detailed anatomy and function of tissues and organs of the body will be beneficial in the imaging-omics field.

High spatial resolution brain functional MRI using submillimeter balanced steady-state free precession acquisition.

PURPOSE: One of the technical advantages of functional magnetic resonance imaging (fMRI) is its precise localization of changes from neuronal activities. While current practice of fMRI acquisition at voxel size around 3 × 3 × 3 mm(3) achieves satisfactory results in studies of basic brain functions, higher spatial resolution is required in order to resolve finer cortical structures. This study investigated spatial resolution effects on brain fMRI experiments using balanced steady-state free precession (bSSFP) imaging with 0.37 mm(3) voxel volume at 3.0 T. METHODS: In fMRI experiments, full and unilateral visual field 5 Hz flashing checkerboard stimulations were given to healthy subjects. The bSSFP imaging experiments were performed at three different frequency offsets to widen the coverage, with functional activations in the primary visual cortex analyzed using the general linear model. Variations of the spatial resolution were achieved by removing outer k-space data components. RESULTS: Results show that a reduction in voxel volume from 3.44 × 3.44 × 2 mm(3) to 0.43 × 0.43 × 2 mm(3) has resulted in an increase of the functional activation signals from (7.7 ± 1.7)% to (20.9 ± 2.0)% at 3.0 T, despite of the threefold SNR decreases in the original images, leading to nearly invariant functional contrast-to-noise ratios (fCNR) even at high spatial resolution. Activation signals aligning nicely with gray matter sulci at high spatial resolution would, on the other hand, have possibly been mistaken as noise at low spatial resolution. CONCLUSIONS: It is concluded that the bSSFP sequence is a plausible technique for fMRI investigations at submillimeter voxel widths without compromising fCNR. The reduction of partial volume averaging with nonactivated brain tissues to retain fCNR is uniquely suitable for high spatial resolution applications such as the resolving of columnar organization in the brain.

Vitamin C estimation with standard (1)H spectroscopy using a clinical 3T MR system: detectability and reliability within the human brain.

PURPOSE: To evaluate whether vitamin C is detectable using clinical routine MRS combined with LCModel analysis and verify the reliability of its estimated concentration. MATERIALS AND METHODS: In order to determine the reliability of the estimated ascorbic acid (Asc) concentrations, we analyzed 76 in vivo single voxel spectra (SVS) acquired on a 3T scanner (point-resolved spectroscopy with TE = 30 ms, TR = 3000 ms, voxel size = 8 mL, without spectral editing) from different regions within the brain using LCModel. In addition to this we simulated multiple concentration levels by adding adapted Asc spectra to the in vivo data. RESULTS: Asc was successfully detected in 71 of 76 in vivo spectra with a comparable concentration ratio to that of myo-inositol. Furthermore, we observed good linearity between added Asc concentrations and the LCModel estimates within the simulations having correlation coefficients larger than 0.985 at three different linewidth cases. CONCLUSION: This study demonstrates the ability to detect vitamin C in the human brain under common clinical magnetic resonance spectroscopy (MRS) standards in combination with LCModel. Furthermore, it supports the need to include Asc in the standard MRS analysis.

Frequency stabilization using infinite impulse response filtering for SSFP fMRI at 3T.

The steady-state free precession (SSFP) method has been shown to exhibit strong potential for distortion-free functional magnetic resonance imaging (fMRI). One major challenge of SSFP fMRI is that the frequency band corresponding to the highest functional sensitivity is extremely narrow, leading to substantial loss of functional contrast in the presence of magnetic field drifts. In this study we propose a frequency stabilization scheme whereby an RF pulse with small flip angle is applied before each image scan, and the initial phase of the free induction decay (FID) signals is extracted to reflect temporal field drifts. A simple infinite impulse response (IIR) filter is further employed to obtain a low-pass-filtered estimate of the central reference frequency for the upcoming scan. Experimental results suggest that the proposed scheme can stabilize the frequency settings in accordance with field drifts, with oscillation amplitudes of <0.5 Hz. Phantom studies showed that both slow drifts and fast fluctuations were prominently reduced, resulting in less than 5% signal variations. Visual fMRI at submillimeter in-plane resolution further demonstrated 15% activation signals that were nicely registered in the microvessels within the sulci. It is concluded that the IIR-filtered frequency stabilization is an effective technique for achieving reliable SSFP fMR images at high field strengths.