Geometric Mean T2 Research Articles

Quantitative T2 analysis: The effects of noise, regularization, and multivoxel approaches

Typical quantitative T2 (qT2) analysis involves creating T2 distributions using a regularized algorithm from region-of-interest averaged decay data. This study uses qT2 analysis of simulated and experimental decay signals to determine how (a) noise-type, (b) regularization, and (c) region-of-interest versus multivoxel analyses affect T2 distributions. Our simulations indicate that regularization causes myelin water fraction and intra/extracellular water geometric mean T2 underestimation that worsens as the signal-to-noise ratio decreases. The underestimation was greater for intra/extracellular water geometric mean T2 measures using Rician noise. Simulations showed significant differences between myelin water fractions determined using region-of-interest and multivoxel approaches compared to the true value. The nonregularized voxel-based approach gave the most accurate measure of myelin water fraction and intra/extracellular water geometric mean T2 for a given signal-to-noise ratio and noise type. Additionally, multivoxel analysis provides important information about the variability of the analysis. Results obtained from in vivo rat data were similar to our simulation results. In each case, a nonregularized, multivoxel analysis provided myelin water fractions significantly different from the regularized approaches and obtained the largest myelin water fraction. We conclude that quantitative T2 analysis is best performed using a nonregularized, multivoxel approach.

In vivo multiecho T2 relaxation measurements using variable TR to decrease scan time

Multiecho T2 relaxation measurements to determine geometric mean T2 (GMT2) and myelin water fraction (MWF) are lengthy, resulting in increased motion artefacts from patient discomfort and reduced patient compliance. The goal of this study was to shorten the acquisition time for multiecho T2 measurements without affecting T1 weighting by varying TR across k-space. Six phantoms and 10 healthy volunteers were imaged with both a constant TR and a variable TR multiecho T2 sequence. T1 weighting was determined by TR at the center of k-space; for variable TR measurement, TR was shortened linearly from the center to the edges of k-space. Phantoms showed excellent agreement for proton density and GMT2 between constant and variable TR measurements. No significant differences were found in proton density or MWF for any of the brain structures between the two measurements. The average GMT2 over all structures between the two experiments was not significantly different. In summary, with the variable TR approach, scan time was reduced by >20%, with minimal loss of image resolution and no significant affect on proton density, MWF or GMT2.

The effect of varying echo spacing within a multiecho acquisition: better characterization of long T2 components

A 48-echo pulse sequence with five different echo-spacing combinations was examined to determine how one can most effectively measure the T2 relaxation characteristics of cerebral tissue containing a long T2 component. For each scan, the first 32 echoes had an echo spacing of 10 ms, while the spacing for Echoes 33-48 (DeltaTE2) was 10, 20, 30, 40 or 50 ms. In an in vivo study using 10 normal volunteers, it was found that the resolution of T2 distribution peaks for both myelin water (approximately 20 ms) and intracellular/extracellular (IE) water (approximately 80 ms) improved as DeltaTE2 increased. The geometric mean T2 values of the main peak agreed within the error for all DeltaTE2 values. A phantom study simulated T2 relaxation distributions that are expected in the brains of patients with demyelinating diseases. For phantoms in which the T2 values of the IE and lesion (200-500 ms) water compartments were separated by at least a factor of 3, each compartment in the distribution was better resolved when DeltaTE2=40 or 50 ms. On the basis of these results, we recommend the use of extended DeltaTE2 values for imaging patients with lesions, without the risk of losing valuable short T2 information.

Viscosity Determination of Heavy Oil and Bitumen Using NMR Relaxometry

Abstract Knowledge of oil viscosity is important when estimating hydrocarbon reserves and evaluating the potential for waterflooding or EOR processes. This information is especially important in heavy oil and bitumen, as viscosity is usually the major impediment to recovery of these reserves. As oil viscosity increases, obtaining a laboratory measurement is difficult and prone to error, and viscosities measured in the lab may not be representative of field conditions. Nuclear magnetic resonance (NMR) is therefore presented as an attractive alternative method for determining oil viscosity. Several correlations already exist for determining oil viscosity using NMR. Some of these correlations compare the geometric mean T2 relaxation time to oil viscosity, while others relate viscosity to the apparent hydrogen index. This paper examines these different models on a suite of conventional and heavy oil samples. It is concluded that none of the existing models can accurately predict oil viscosity for both conventional and heavy oils, especially for oils with viscosity higher than 20,000 cP. All the measured oil samples show a correlation between oil viscosity and the geometric mean T2 relaxation time, and also between viscosity and relative hydrogen index. This is consistent with what other experimenters have noticed. An empirical model is developed, correlating oil viscosity to both of these parameters. Unlike previous models, this model can accurately predict oil viscosity for both conventional and heavy oil. The wider range of this model makes it useful for laboratory analysis of oil viscosity using NMR. If the results of this model can be applied to in situ oils, NMR can be used as a logging tool to characterize heavy oil and bitumen formations. The model presented in this paper is the first step towards successfully predicting viscosity in situ. Introduction Determination of oil viscosity is extremely important to the development of any potential oil reservoir. If waterflooding is being considered as a recovery scheme, the mobility ratio between oil and water will have a strong effect on the macroscopic sweep efficiency of the waterflood. Likewise, when considering possible EOR schemes, oil viscosity is one of the most serious impediments to the success of these schemes. Oil viscosity is also a required input parameter for reservoir simulation and well testing. In heavy oil and bitumen reservoirs, the high oil viscosity is often the limiting factor to efficient oil recovery. Waterflooding cannot be used in these reservoirs, due to the adverse mobility ratio between oil and water. The oil is so much more viscous than water that injected water will move through the oil in the form of "viscous fingers," which lead to early water breakthrough and poor sweep efficiency. If attempting a miscible solvent or gas flood, knowledge of oil viscosity is necessary for estimating the efficiency of the flood. Due to the negative effects of the adverse mobility ratio, viscosity reduction is the main focus of EOR schemes in heavy oil reservoirs.

Normal-appearing white matter in multiple sclerosis has heterogeneous, diffusely prolonged T2

T2 relaxation in normal-appearing white matter (NAWM) of multiple sclerosis (MS) patients was reexamined using more complete sampling and analysis of decay curves, and to assess focal vs. diffuse abnormalities. Nine MS patients and 10 controls were scanned using a single-slice 32-echo pulse sequence with a 10-ms echo spacing. Decay curves from outlined white and gray matter structures were analyzed using non-negative least-squares (NNLS). Resulting T2 distributions were each summarized by the geometric mean T2, T2. Different white matter structures had different mean (over the subjects in a group) T2. Mean T2 in NAWM was always greater than that of controls. Differences were not caused by a few voxels with extreme T2 (i.e., focal lesions), but rather by shifts of the entire T2 distribution (diffuse prolongation). This T2 increase suggests diffuse myelin or axonal pathology. Magn Reson Med 47:403–408, 2002. © 2002 Wiley-Liss, Inc.

In vitro measurements of water content and T2 relaxation times in lung using a clinical MRI scanner

The purpose of this study was to validate water content measurements and to determine the T2 distribution in lung on a 1.5 T clinical magnetic resonance imaging (MRI) scanner. A single-slice 16 echo pulse sequence with an echo spacing of 10 msec was employed to scan 19 healthy juvenile pig lungs. The in vitro water content of each lung was measured using MRI techniques and compared with gravimetric measurements. The mean difference between the gravimetric and MRI water contents was −4.1 ± 7.6% , and an excellent linear correlation (R2 = 0.98) was observed between the two independent measurements. The dependence of the geometric mean T2 time upon lung water density exhibited two distinct regions (inflated and deflated) separated by a threshold density of about 0.4 g/mL. J. Magn. Reson. Imaging 1999;9:699–703. © 1999 Wiley-Liss, Inc.

In vitro measurements of water content and T2 relaxation times in lung using a clinical MRI scanner.

The purpose of this study was to validate water content measurements and to determine the T2 distribution in lung on a 1.5 T clinical magnetic resonance imaging (MRI) scanner. A single-slice 16 echo pulse sequence with an echo spacing of 10 msec was employed to scan 19 healthy juvenile pig lungs. The in vitro water content of each lung was measured using MRI techniques and compared with gravimetric measurements. The mean difference between the gravimetric and MRI water contents was -4.1 +/- 7.6%, and an excellent linear correlation (R2 = 0.98) was observed between the two independent measurements. The dependence of the geometric mean T2 time upon lung water density exhibited two distinct regions (inflated and deflated) separated by a threshold density of about 0.4 g/mL.

In vivo measurement of T2 distributions and water contents in normal human brain.

Using a 32-echo imaging pulse sequence, T2 relaxation decay curves were acquired from five white- and six gray-matter brain structures outlined in 12 normal volunteers. The water contents of white and gray matter were 0.71 (0.01) and 0.83 (0.03) g/ml, respectively. All white-matter structures had significantly higher myelin water percentages (signal percentage with T2 between 10 and 50 ms) than all gray-matter structures. The range in geometric mean T2 of the main peak for both white and gray matter was from 70 to 86 ms. T2 distributions from the posterior internal capsules and splenium of the corpus callosum were significantly wider (width is related to water environment inhomogeneity) than those from any other white- or gray-matter structures. Thus, quantitative measurement and analysis of T2 relaxation reveals differences in brain tissue water environments not discernible on conventional MR images. These differences may make short T2 components reliable markers for normal myelin.