The robust identification of exchange from T2-T2 time-domain features.

Two-dimensional spin-spin relaxation (T2-T2) techniques have been developed to probe coupling between different environments such as diffusive coupling between small and large pores or chemical exchange with clays. In these studies, Numerical Laplace Inversion (NLI) is used to obtain two-dimensional T2-T2 relaxation distribution spectrum from the T2-T2 signal decays, and the off-diagonal peaks characterize coupling. Often, these coupling peaks are both weak and close to the diagonal and combined with the inherently ill-conditioned nature of the inversion, their presence is difficult to differentiate from inversion related artifacts and blurring. This manuscript presents a time domain based analysis to identify the presence of coupling that avoids the ambiguities present in T2-T2 spectra. The approach utilizes the symmetric nature of the two-dimensional time domain data, where the presence of curvature along one of these symmetries gives an unambiguous indicator of coupling. Measurements on porous glass beads are used to verify the technique.

Detecting compartmental non-Gaussian diffusion with symmetrized double-PFG MRI.

Diffusion in tissue and porous media is known to be non-Gaussian and has been used for clinical indications of stroke and other tissue pathologies. However, when conventional NMR techniques are applied to biological tissues and other heterogeneous materials, the presence of multiple compartments (pores) with different Gaussian diffusivities will also contribute to the measurement of non-Gaussian behavior. Here we present symmetrized double PFG (sd-PFG), which can separate these two contributions to non-Gaussian signal decay as having distinct angular modulation frequencies. In contrast to prior angular d-PFG methods, sd-PFG can unambiguously extract kurtosis as an oscillation from samples with isotropic or uniformly oriented anisotropic pores, and can generally extract a combination of compartmental anisotropy and kurtosis. The method further fixes its sensitivity with respect to the time dependence of the apparent diffusion coefficient. We experimentally demonstrate the measurement of the fourth cumulant (kurtosis) of diffusion and find it consistent with theoretical predictions. By enabling the unambiguous identification of contributions of compartmental kurtosis to the signal, sd-PFG has the potential to help identify the underlying micro-structural changes corresponding to current kurtosis based diagnostics, and act as a novel source of contrast to better resolve tissue micro-structure.

Two-dimensional diffusion time correlation experiment using a single direction gradient.

The time dependence of the diffusion coefficient is a well known property of porous media and commonly obtained by pulsed field gradient (PFG) NMR. In practical materials, its analysis can be complicated by the presence of a broad pore size distribution and multiple fluid phases with different diffusion coefficients. We propose a two-dimensional Diffusion Time Correlation experiment (DTC), which utilizes the double-PFG with a single-direction gradient to yield a two-dimensional correlation function of the diffusion coefficient for two different diffusion times. This correlation map separates out restricted diffusion from the bulk diffusion process and we demonstrate this on a plant and bulk water sample. In its development, we show that the d-PFG should then be thought of as correlating two apparent diffusion coefficients measured by two overlapping gradient waveforms.

Temporal/spatial resolution improvement of in vivo DCE-MRI with compressed sensing-optimized FLASH.

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) provides critical information regarding tumor perfusion and permeability by injecting a T(1) contrast agent, such as Gd-DTPA, and making a time-resolved measurement of signal increase. Both temporal and spatial resolutions are required to be high to achieve an accurate and reproducible estimation of tumor perfusion. However, the dynamic nature of the DCE experiment limits simultaneous improvement of temporal and spatial resolution by conventional methods. Compressed sensing (CS) has become an important tool for the acceleration of imaging times in MRI, which is achieved by enabling the reconstruction of subsampled data. Similarly, CS algorithms can be utilized to improve the temporal/spatial resolution of DCE-MRI, and several works describing retrospective simulations have demonstrated the feasibility of such improvements. In this study, the fast low angle shot sequence was modified to implement a Cartesian, CS-optimized, sub-Nyquist phase encoding acquisition/reconstruction with multiple two-dimensional slice selections and was tested on water phantoms and animal tumor models. The mean voxel-level concordance correlation coefficient for Ak(ep) values obtained from ×4 and ×8 accelerated and the fully sampled data was 0.87±0.11 and 0.83±0.11, respectively (n=6), with optimized CS parameters. In this case, the reduction of phase encoding steps made possible by CS reconstruction improved effectively the temporal/spatial resolution of DCE-MRI data using an in vivo animal tumor model (n=6) and may be useful for the investigation of accelerated acquisitions in preclinical and clinical DCE-MRI trials.

Compressive sampling with prior information in remotely detected MRI of microfluidic devices.

The design and operation of microfluidic analytical devices depends critically on tools to probe microscale chemistry and flow dynamics. Magnetic resonance imaging (MRI) seems ideally suited to this task, but its sensitivity is compromised because the fluid-containing channels in "lab on a chip" devices occupy only a small fraction of the enclosing detector's volume; as a result, the few microfluidic applications of NMR have required custom-designed chips harboring many detectors at specific points of interest. To overcome this limitation, we have developed remotely detected microfluidic MRI, in which an MR image is stored in the phase and intensity of each analyte's NMR signal and sensitively detected by a single, volume-matched detector at the device outflow, and combined it with compressed sensing for rapid image acquisition. Here, we build upon our previous work and introduce a method that incorporates our prior knowledge of the microfluidic device geometry to further decrease acquisition times. We demonstrate its use in multidimensional velocimetric imaging of a microfluidic mixer, acquiring microscopically detailed images 128 times faster than is possible with conventional sampling. This prior information also informs our choice of sampling schedule, resulting in a scheme that is optimized for a specific flow geometry. Finally, we test our approach in synthetic data and explore potential reconstruction errors as a function of optimization and reconstruction parameters.

Stability of superparamagnetic iron oxide nanoparticles at different pH values: experimental and theoretical analysis.

The detection of superparamagnetic nanoparticles using NMR logging has the potential to provide enhanced contrast in oil reservoir rock formations. The stability of the nanoparticles is critical because the NMR relaxivity (R(2) ≡ 1/T(2)) is dependent on the particle size. Here we use a molecular theory to predict and validate experimentally the stability of citric acid-coated/PEGylated iron oxide nanoparticles under different pH conditions (pH 5, 7, 9, 11). The predicted value for the critical surface coverage required to produce a steric barrier of 5k(B)T for PEGylated nanoparticles (MW 2000) was 0.078 nm(-2), which is less than the experimental value of 0.143 nm(-2), implying that the nanoparticles should be stable at all pH values. Dynamic light scattering (DLS) measurements showed that the effective diameter did not increase at pH 7 or 9 after 30 days but increased at pH 11. The shifts in NMR relaxivity (from R(2) data) at 2 MHz agreed well with the changes in hydrodynamic diameter obtained from DLS data, indicating that the aggregation behavior of the nanoparticles can be easily and quantitatively detected by NMR. The unexpected aggregation at pH 11 is due to the desorption of the surface coating (citric acid or PEG) from the nanoparticle surface not accounted for in the theory. This study shows that the stability of the nanoparticles can be predicted by the theory and detected by NMR quantitatively, which suggests the nanoparticles to be a possible oil-field nanosensor.

Acceleration of multi-dimensional propagator measurements with compressed sensing.

NMR can probe the microstructures of anisotropic materials such as liquid crystals, stretched polymers and biological tissues through measurement of the diffusion propagator, where internal structures are indicated by restricted diffusion. Multi-dimensional measurements can probe the microscopic anisotropy, but full sampling can then quickly become prohibitively time consuming. However, for incompletely sampled data, compressed sensing is an effective reconstruction technique to enable accelerated acquisition. We demonstrate that with a compressed sensing scheme, one can greatly reduce the sampling and the experimental time with minimal effect on the reconstruction of the diffusion propagator with an example of anisotropic diffusion. We compare full sampling down to 64× sub-sampling for the 2D propagator measurement and reduce the acquisition time for the 3D experiment by a factor of 32 from ∼80 days to ∼2.5 days.

Remotely detected MRI velocimetry in microporous bead packs.

Many NMR and MRI methods probe fluid dynamics within macro- and mesoporous materials, but with few exceptions, they report on its macroscopically averaged properties. MRI methods are generally unable to localize microscopic features of flow within macroscopic samples because the fraction of the enclosing detector volume occupied by these features is so small. We have recently overcome this problem using remotely detected MRI velocimetry, a technique in which spatial, chemical, and velocity information about elements of the flow is encoded with a conventional NMR coil and detected sensitively at the sample outflow by a volume-matched microdetector. Here, we apply this method to microporous model systems, recording MRI images that correlate local velocity, spin relaxation, and time-of-flight in microscopic resolution and three spatial dimensions. Our results illustrate that remotely detected MRI is an effective approach to elucidate flow dynamics in porous materials including bead pack microreactors and chromatography columns.

Volume-selective magnetic resonance imaging using an adjustable, single-sided, portable sensor.

Portable, single-sided NMR sensors can operate under conditions inaccessible to conventional NMR while featuring lower cost, portability, and the ability to analyze arbitrary-sized objects. Such sensors can nondestructively probe the interior of samples by collecting images and measuring relaxation and diffusion constants, and, given careful shimming schemes, even perform chemical analysis. The inherently strong magnetic-field gradients of single-sided sensors developed so far has prevented imaging of materials with high water content, such as biological tissues, over large volumes whereas designs with more homogeneous fields suffer from low field strength and typically cannot probe volumes larger than approximately 10 cm(3). We present a design with a continuously adjustable sensitive volume, enabling the effective volume to be enlarged several fold. This capability allows for imaging in reasonable times of much bigger objects and opens the door to the possibility of clinical imaging with portable sensors. We demonstrate MRI in axial and sagittal planes, at different depths of the sensitive volume and T(1)-weighted contrast in a tissue sample.