Investigating the effect of exchange and multicomponentT1 relaxation on the short repetition time spoiled steady-state signal and the DESPOT1T1 quantification method

Mitigating the impact of flip angle and orientation dependence in single compartment R2* estimates via 2-pool modeling

PURPOSE

The effective transverse relaxation rate (R 2 * $$ {\mathrm{R}}_2^{\ast } $$ ) is influenced by biological features that make it a useful means of probing brain microstructure. However, confounding factors such as dependence on flip angle (α) and fiber orientation with respect to the main field (θ $$ \uptheta $$ ) complicate interpretation. The α- andθ $$ \uptheta $$ -dependence stem from the existence of multiple sub-voxel micro-environments (e.g., myelin and non-myelin water compartments). Ordinarily, it is challenging to quantify these sub-compartments; therefore, neuroscientific studies commonly make the simplifying assumption of a mono-exponential decay obtaining a singleR 2 * $$ {\mathrm{R}}_2^{\ast } $$ estimate per voxel. In this work, we investigated how the multi-compartment nature of tissue microstructure affects single compartmentR 2 * $$ {\mathrm{R}}_2^{\ast } $$ estimates.

METHODS

We used 2-pool (myelin and non-myelin water) simulations to characterize the bias in single compartmentR 2 * $$ {\mathrm{R}}_2^{\ast } $$ estimates. Based on our numeric observations, we introduced a linear model that partitionsR 2 * $$ {\mathrm{R}}_2^{\ast } $$ into α-dependent and α-independent components and validated this in vivo at 7T. We investigated the dependence of both components on the sub-compartment properties and assessed their robustness, orientation dependence, and reproducibility empirically.

RESULTS

R 2 * $$ {\mathrm{R}}_2^{\ast } $$ increased with myelin water fraction and residency time leading to a linear dependence on α. We observed excellent agreement between our numeric and empirical results. Furthermore, the α-independent component of the proposed linear model was robust to the choice of α and reduced dependence on fiber orientation, although it suffered from marginally higher noise sensitivity.

CONCLUSION

We have demonstrated and validated a simple approach that mitigates flip angle and orientation biases in single-compartmentR 2 * $$ {\mathrm{R}}_2^{\ast } $$ estimates.

Improvement in the contrast-to-noise ratio and quantitative measurement of T1 and T2* values for carotid atherosclerotic plaque using multi-echo phase-sensitive inversion recovery

Quantitative magnetic resonance imaging is required to accurately evaluate carotid plaque vulnerability. We prospectively evaluated the potential for fast quantitative black-blood carotid vessel wall imaging using a three-dimensional (3D) multi-echo phase-sensitive inversion recovery (mPSIR) sequence. Forty-nine patients with carotid atherosclerotic plaques were examined. Two-dimensional (2D) turbo spin-echo (TSE), 3D volumetric isotropic turbo spin-echo, and 3D mPSIR imaging were performed. The contrast-to-noise ratios (CNRs) between the carotid plaque and adjacent muscle were compared for the three imaging methods. The T₁ and T₂* values of the carotid plaques were measured using 3D mPSIR images. These values were compared with those of symptomatic and asymptomatic plaques. For carotid plaques with a signal intensity ratio ≥ 1.55, between the carotid plaque and adjacent muscle in 2D TSE images, the CNR of the mPSIR images was significantly higher than that of the other sequences. T₁ values for symptomatic and asymptomatic plaques were 544.0 ± 258.0 and 569.1 ± 301.7, respectively. T₂* values for symptomatic and asymptomatic plaques were 34.0 ± 33.0 and 21.8 ± 20.3 ms, respectively. There were no significant differences in the T₁ and T₂* values between the symptomatic and asymptomatic plaques. 3D mPSIR improves the CNR of T₁-weighted images for carotid plaques and the adjacent muscle while simultaneously providing the T₁ and T₂* values of the carotid plaque. This improved CNR may be useful for assessing the vulnerability of carotid plaques.

Technical Note: The effect of 2D excitation profile on T1 measurement accuracy using the variable flip angle method with an average flip angle assumption

PURPOSE

To study the accuracy and precision of T₁ estimates using the Variable Flip Angle (VFA) method in 2D and 3D acquisitions.

METHODS

Excitation profiles were simulated using numerical implementation of the Bloch equations for Hamming-windowed sinc excitation pulses with different time-bandwidth products (TBP) of 2, 6, and 10 and for T₁ values of 295 ms and 1045 ms. Experimental data were collected in 5° increments from 5° to 90° for the same T₁ and TBP values. T₁ was calculated for every combination of flip angle with and without a correction for B₁ and slice profile variation. Calculations were also made for flat slice profile such as obtained in 3D acquisition. Monte Carlo simulations were performed to obtain T₁ measurement uncertainty.

RESULTS

VFA T₁ measurements in 2D without correction can result in a 40-80% underestimation of true T₁ . Flip angle correction can reduce the underestimation, but results in accurate measurements of T₁ only within a narrow band of flip angle combinations. The narrow band of accuracy increases with TBP, but remains too narrow for any practical range of T₁ values or B₁ variation. Simulated noisy VFA T₁ measurements in 3D were accurate as long as the two angles chosen are on either side of the Ernst angle.

CONCLUSIONS

Accurate T1 estimates from VFA 2D acquisitions are possible, but only a narrow range of T1 values within a narrow range of flip angle combinations can be accurately calculated using a 2D slice. Unless a better flip angle correction method is used, these results demonstrate that accurate measurements of T1 in 2D cannot be obtained robustly enough for practical use and are more likely obtained by a thin slab 3D VFA acquisition than from multiple-slice 2D acquisitions. VFA T₁ measurements in 3D are accurate for wide ranges of flip angle combinations and T₁ values.

Biexponential T2 relaxation estimation of human knee cartilage in vivo at 3T

PURPOSE

To evaluate biexponential T₂ relaxation mapping of human knee cartilage in vivo in clinically feasible scan times.

MATERIALS AND METHODS

T₂ -weighted magnetic resonance (MR) images were acquired from eight healthy volunteers using a standard 3T clinical scanner. A 3D Turbo-Flash sequence was modified to enable T₂ -weighted imaging with different echo times. Series of T₂ -weighted images were fitted using mono- and biexponential models with two- and four-parametric nonlinear approaches, respectively.

RESULTS

Biexponential relaxation of T₂ was detected in the knee cartilage in five regions of interest in all eight healthy volunteers. Short/long relaxation components of T₂ were estimated to be 8.27 ± 0.68 / 45.35 ± 3.79 msec with corresponding fractions of 41.3 ± 1.1% / 58.6 ± 4.6%, respectively. The monoexponential relaxation of T₂ was measured to be 26.9 ± 2.27 msec. The experiments showed good repeatability with coefficient of variation root mean square (CV_rms ) < 18% in all regions. The only difference in gender was observed in medial tibial cartilage, where the biexponential T₂ in female volunteers was significantly higher compared to male volunteers (P = 0.014). Significant differences were observed in T₂ relaxation between different regions on interest.

CONCLUSION

Biexponential relaxation of T₂ was observed in the human knee cartilage in vivo. The short and long components are thought to be related to the tightly bound and loosely bound macromolecular water compartments. These preliminary results of biexponential T₂ analysis could potentially be used to increase the specificity for detection of early osteoarthritis by measuring different water compartments and their fractions.

LEVEL OF EVIDENCE

1 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2018;47:809-819.

Improved determination of the myelin water fraction in human brain using magnetic resonance imaging through Bayesian analysis of mcDESPOT

Myelin water fraction (MWF) mapping with magnetic resonance imaging has led to the ability to directly observe myelination and demyelination in both the developing brain and in disease. Multicomponent driven equilibrium single pulse observation of T1 and T2 (mcDESPOT) has been proposed as a rapid approach for multicomponent relaxometry and has been applied to map MWF in the human brain. However, even for the simplest two-pool signal model consisting of myelin-associated and non-myelin-associated water, the dimensionality of the parameter space for obtaining MWF estimates remains high. This renders parameter estimation difficult, especially at low-to-moderate signal-to-noise ratios (SNRs), due to the presence of local minima and the flatness of the fit residual energy surface used for parameter determination using conventional nonlinear least squares (NLLS)-based algorithms. In this study, we introduce three Bayesian approaches for analysis of the mcDESPOT signal model to determine MWF. Given the high-dimensional nature of the mcDESPOT signal model, and, therefore the high-dimensional marginalizations over nuisance parameters needed to derive the posterior probability distribution of the MWF, the Bayesian analyses introduced here use different approaches to reduce the dimensionality of the parameter space. The first approach uses normalization by average signal amplitude, and assumes that noise can be accurately estimated from signal-free regions of the image. The second approach likewise uses average amplitude normalization, but incorporates a full treatment of noise as an unknown variable through marginalization. The third approach does not use amplitude normalization and incorporates marginalization over both noise and signal amplitude. Through extensive Monte Carlo numerical simulations and analysis of in vivo human brain datasets exhibiting a range of SNR and spatial resolution, we demonstrated markedly improved accuracy and precision in the estimation of MWF using these Bayesian methods as compared to the stochastic region contraction (SRC) implementation of NLLS.

Incorporation of nonzero echo times in the SPGR and bSSFP signal models used in mcDESPOT

PURPOSE

To analyze the effect of neglecting nonzero echo times (TEs) in the conventional model of multicomponent driven equilibrium single pulse observation of T1 and T2 (mcDESPOT).

THEORY AND METHODS

Formulations of the two-component spoiled gradient recalled echo (SPGR) and balanced steady state free precession (bSSFP) models that incorporate nonzero TE effects are presented in the context of mcDESPOT and compared with the conventionally used SPGR and bSSFP models which ignore nonzero TEs. Relative errors in derived parameter estimates from conventional mcDESPOT, omitting TE effects, are assessed using simulations over a wide range of experimental and sample parameters.

RESULTS

The neglect of nonzero TE leads to an overestimate of the SPGR signal and an underestimate of the bSSFP signal. These effects can introduce large errors in parameter estimates derived from conventional mcDESPOT under realistic imaging conditions.

CONCLUSION

SPGR and bSSFP signal models accounting for nonzero TE effects should be incorporated into quantitative mcDESPOT analyses.

Analysis of mcDESPOT- and CPMG-derived parameter estimates for two-component nonexchanging systems

PURPOSE

To compare the reliability and stability of the multicomponent-driven equilibrium single pulse observation of T1 and T2 (mcDESPOT) and Carl-Purcell-Meiboom-Gill (CPMG) approaches to parameter estimation.

METHODS

The stability and reliability of mcDESPOT and CPMG-derived parameter estimates were compared through examination of energy surfaces, evaluation of model sloppiness, and Monte Carlo simulations. Comparisons were performed on an equal time basis and assuming a two-component system. Parameter estimation bias, reflecting accuracy, and dispersion, reflecting precision, were derived for a range of signal-to-noise ratios (SNRs) and relaxation parameters.

RESULTS

The energy surfaces for parameters incorporated into the mcDESPOT signal model exhibit flatness, a complex structure of local minima, and instability to noise to a much greater extent than the corresponding surfaces for CPMG. Although both mcDESPOT and CPMG performed well at high SNR, the CPMG approach yielded parameter estimates of considerably greater accuracy and precision at lower SNR.

CONCLUSION

mcDESPOT and CPMG both permit high-quality parameter estimates under SNR that are clinically achievable under many circumstances, depending upon available hardware and resolution and acquisition time constraints. At moderate to high SNR, the mcDESPOT approach incorporating two-step phase increments can yield accurate parameter estimates while providing values for longitudinal relaxation times that are not available through CPMG. However, at low SNR, the CPMG approach is more stable and provides superior parameter estimates. Magn Reson Med 75:2406-2420, 2016. © 2015 Wiley Periodicals, Inc.

Articular Cartilage of the Human Knee Joint: In Vivo Multicomponent T2 Analysis at 3.0 T

PURPOSE

To compare multicomponent T2 parameters of the articular cartilage of the knee joint measured by using multicomponent driven equilibrium single-shot observation of T1 and T2 (mcDESPOT) in asymptomatic volunteers and patients with osteoarthritis.

MATERIALS AND METHODS

This prospective study was performed with institutional review board approval and with written informed consent from all subjects. The mcDESPOT sequence was performed in the knee joint of 13 asymptomatic volunteers and 14 patients with osteoarthritis of the knee. Single-component T2 (T2(Single)), T2 of the fast-relaxing water component (T2F) and of the slow-relaxing water component (T2S), and the fraction of the fast-relaxing water component (F(F)) of cartilage were measured. Wilcoxon rank-sum tests and multivariate linear regression models were used to compare mcDESPOT parameters between volunteers and patients with osteoarthritis. Receiver operating characteristic analysis was used to assess diagnostic performance with mcDESPOT parameters for distinguishing morphologically normal cartilage from morphologically degenerative cartilage identified at magnetic resonance imaging in eight cartilage subsections of the knee joint.

RESULTS

Higher cartilage T2(Single) (P < .001), lower cartilage F(F) (P < .001), and similar cartilage T2F (P = .079) and T2S (P = .124) values were seen in patients with osteoarthritis compared with those in asymptomatic volunteers. Differences in T2(Single) and F(F) remained significant (P < .05) after consideration of age differences between groups of subjects. Diagnostic performance was higher with F(F) than with T2(Single) for distinguishing between normal and degenerative cartilage (P < .05), with greater areas under the curve at receiver operating characteristic analysis.

CONCLUSION

Patients with osteoarthritis of the knee had significantly higher cartilage T2(Single) and significantly lower cartilage F(F) than did asymptomatic volunteers, and receiver operating characteristic analysis results suggested that F(F) may allow greater diagnostic performance than that with T2(Single) for distinguishing between normal and degenerative cartilage.

Recent imaging advances in neurology

Over the recent years, the application of neuroimaging techniques such as magnetic resonance imaging (MRI) and positron emission tomography (PET) has considerably advanced the understanding of complex neurological disorders. PET is a powerful molecular imaging tool, which investigates the distribution and binding of radiochemicals attached to biologically relevant molecules; as such, this technique is able to give information on biochemistry and metabolism of the brain in health and disease. MRI uses high intensity magnetic fields and radiofrequency pulses to provide structural and functional information on tissues and organs in intact or diseased individuals, including the evaluation of white matter integrity, grey matter thickness and brain perfusion. The aim of this article is to review the most recent advances in neuroimaging research in common neurological disorders such as movement disorders, dementia, epilepsy, traumatic brain injury and multiple sclerosis, and to evaluate their contribution in the diagnosis and management of patients.

On the accuracy of T1 mapping: searching for common ground

PURPOSE

There are many T1 mapping methods available, each of them validated in phantoms and reporting excellent agreement with literature. However, values in literature vary greatly, with T1 in white matter ranging from 690 to 1100 ms at 3 Tesla. This brings into question the accuracy of one of the most fundamental measurements in quantitative MRI. Our goal was to explain these variations and look into ways of mitigating them.

THEORY AND METHODS

We evaluated the three most common T1 mapping methods (inversion recovery, Look-Locker, and variable flip angle) through Bloch simulations, a white matter phantom and the brains of 10 healthy subjects (single-slice). We pooled the T1 histograms of the subjects to determine whether there is a sequence-dependent bias and whether it is reproducible across subjects.

RESULTS

We found good agreement between the three methods in phantoms, but poor agreement in vivo, with the white matter T1 histogram peak in healthy subjects varying by more than 30% depending on the method used. We also found that the pooled brain histograms displayed three distinct white matter peaks, with Look-Locker consistently underestimating, and variable flip angle overestimating the inversion recovery T1 values. The Bloch simulations indicated that incomplete spoiling and inaccurate B1 mapping could account for the observed differences.

CONCLUSION

We conclude that the three most common T1 mapping protocols produce stable T1 values in phantoms, but not in vivo. To improve the accuracy of T1 mapping, we recommend that sites perform in vivo validation of their T1 mapping method against the inversion recovery reference method, as the first step toward developing a robust calibration scheme.

Rapid multicomponent T2 analysis of the articular cartilage of the human knee joint at 3.0T

PURPOSE

To determine the feasibility of using multicomponent-driven equilibrium single-shot observation of T1 and T2 (mcDESPOT) for evaluating the human knee joint at 3.0T and to investigate depth-dependent and regional-dependent variations in multicomponent T2 parameters within articular cartilage.

MATERIALS AND METHODS

mcDESPOT was performed on the knee joint of 10 asymptomatic volunteers at 3.0T. Single-component T2 relaxation time (T2single ), multicomponent T2 relaxation time for water tightly bound to proteoglycan (T2PG ) and bulk water loosely bound to the macromolecular matrix (T2BW ), and fraction of water tightly bound to proteoglycan (FPG ) were measured in eight cartilage subsections and within the superficial and deep layers of patellar cartilage. Statistical analysis was used to investigate depth-dependent and regional-dependent variations in parameters.

RESULTS

There was lower (P = 0.001) T2single and T2PG and higher (P < 0.001) FPG in the deep than superficial layer of patellar cartilage. There was higher (P < 0.001) FPG on the weight-bearing surfaces than nonweight-bearing surfaces. There was higher (P < 0.001) T2single , T2PG , and T2BW on the trochlea and posterior medial and lateral femoral condyles than the patella, central medial and lateral femoral condyles, and medial and lateral tibia plateaus.

CONCLUSION

Multicomponent T2 parameters of the articular cartilage of the human knee joint can be measured at 3.0T using mcDESPOT and show depth-dependent and regional-dependent variations.

One component? Two components? Three? The effect of including a nonexchanging "free" water component in multicomponent driven equilibrium single pulse observation of T1 and T2

Quantitative myelin content imaging provides novel and pertinent information related to underlying pathogenetic mechanisms of myelin-related disease or disorders arising from aberrant connectivity. Multicomponent driven equilibrium single pulse observation of T1 and T2 is a time-efficient multicomponent relaxation analysis technique that provides estimates of the myelin water fraction, a surrogate measure of myelin volume. Unfortunately, multicomponent driven equilibrium single pulse observation of T1 and T2 relies on a two water-pool model (myelin-associated water and intra/extracellular water), which is inadequate within partial volume voxels, i.e., containing brain tissue and ventricle or meninges, resulting in myelin water fraction underestimation. To address this, a third, nonexchanging "free-water" component was introduced to the multicomponent driven equilibrium single pulse observation of T1 and T2 model. Numerical simulations and experimental in vivo data show that the model to perform advantageously within partial volume regions while providing robust and reproducible results. It is concluded that this model is preferable for future studies and analysis.

Flip angle profile correction for T₁ and T₂ quantification with look-locker inversion recovery 2D steady-state free precession imaging

Fast methods using balanced steady-state free precession have been developed to reduce the scan time of T₁ and T₂ mapping. However, flip angle (FA) profiles created by the short radiofrequency pulses used in steady-state free precession deviate substantially from the ideal rectangular profile, causing T₁ and T₂ mapping errors. The purpose of this study was to develop a FA profile correction for T₁ and T₂ mapping with Look-Locker 2D inversion recovery steady-state free precession and to validate this method using 2D spin echo as a reference standard. Phantom studies showed consistent improvement in T₁ and T₂ accuracy using profile correction at multiple FAs. Over six human calves, profile correction provided muscle T₁ estimates with mean error ranging from excellent (-0.6%) at repetition time/FA = 18 ms/60° to acceptable (6.8%) at repetition time/FA = 4.9 ms/30°, while muscle T₂ estimates were less accurate with mean errors of 31.2% and 47.9%, respectively.

Characterization of cerebral white matter properties using quantitative magnetic resonance imaging stains

The image contrast in magnetic resonance imaging (MRI) is highly sensitive to several mechanisms that are modulated by the properties of the tissue environment. The degree and type of contrast weighting may be viewed as image filters that accentuate specific tissue properties. Maps of quantitative measures of these mechanisms, akin to microstructural/environmental-specific tissue stains, may be generated to characterize the MRI and physiological properties of biological tissues. In this article, three quantitative MRI (qMRI) methods for characterizing white matter (WM) microstructural properties are reviewed. All of these measures measure complementary aspects of how water interacts with the tissue environment. Diffusion MRI, including diffusion tensor imaging, characterizes the diffusion of water in the tissues and is sensitive to the microstructural density, spacing, and orientational organization of tissue membranes, including myelin. Magnetization transfer imaging characterizes the amount and degree of magnetization exchange between free water and macromolecules like proteins found in the myelin bilayers. Relaxometry measures the MRI relaxation constants T1 and T2, which in WM have a component associated with the water trapped in the myelin bilayers. The conduction of signals between distant brain regions occurs primarily through myelinated WM tracts; thus, these methods are potential indicators of pathology and structural connectivity in the brain. This article provides an overview of the qMRI stain mechanisms, acquisition and analysis strategies, and applications for these qMRI stains.

Three-dimensional T1 mapping of the mouse heart using variable flip angle steady-state MR imaging

Cardiac MR T(1) mapping is a promising quantitative imaging tool for the diagnosis and evaluation of cardiomyopathy. Here, we present a new preclinical cardiac MRI method enabling three-dimensional T(1) mapping of the mouse heart. The method is based on a variable flip angle analysis of steady-state MR imaging data. A retrospectively triggered three-dimensional FLASH (fast low-angle shot) sequence (3D IntraGate) enables a constant repetition time and maintains steady-state conditions. 3D T(1) mapping of the complete mouse heart could be achieved in 20 min. High-quality, bright-blood T(1) maps were obtained with homogeneous T(1) values (1764 ± 172 ms) throughout the myocardium. The repeatability coefficient of R(1) (1/T(1) ) in a specific region of the mouse heart was between 0.14 and 0.20 s(-1) , depending on the number of flip angles. The feasibility for detecting regional differences in ΔR(1) was shown with pre- and post-contrast T(1) mapping in mice with surgically induced myocardial infarction, for which ΔR(1) values up to 0.83 s(-1) were found in the infarct zone. The sequence was also investigated in black-blood mode, which, interestingly, showed a strong decrease in the apparent mean T(1) of healthy myocardium (905 ± 110 ms). This study shows that 3D T(1) mapping in the mouse heart is feasible and can be used to monitor regional changes in myocardial T(1), particularly in relation to pathology and in contrast-enhanced experiments to estimate local concentrations of (targeted) contrast agent.

Influence of RF spoiling on the stability and accuracy of T1 mapping based on spoiled FLASH with varying flip angles

There is increasing interest in quantitative T(1) mapping techniques for a variety of applications. Several methods for T(1) quantification have been described. The acquisition of two spoiled gradient-echo data sets with different flip angles allows for the calculation of T(1) maps with a high spatial resolution and a relatively short experimental duration. However, the method requires complete spoiling of transverse magnetization. To achieve this goal, RF spoiling has to be applied. In this work it is investigated whether common RF spoiling techniques are sufficiently effective to allow for accurate T(1) quantification. It is shown that for most phase increments the apparent T(1) can deviate considerably from the true value. Correct results may be achieved with phase increments of 118.2 degrees or 121.8 degrees. However, for these values the method suffers from instabilities. In contrast, stable results are obtained with a phase increment of 50 degrees. An algorithm is presented that allows for the calculation of corrected T(1) maps from the apparent values. The method is tested both in phantom experiments and in vivo by acquiring whole-brain T(1) maps of the human brain.

Gleaning multicomponent T1 and T2 information from steady-state imaging data

The driven-equilibrium single-pulse observation of T(1) (DESPOT1) and T(2) (DESPOT2) are rapid, accurate, and precise methods for voxelwise determination of the longitudinal and transverse relaxation times. A limitation of the methods, however, is the inherent assumption of single-component relaxation. In a variety of biological tissues, in particular human white matter (WM) and gray matter (GM), the relaxation has been shown to be more completely characterized by a summation of two or more relaxation components, or species, each believed to be associated with unique microanatomical domains or water pools. Unfortunately, characterization of these components on a voxelwise, whole-brain basis has traditionally been hindered by impractical acquisition times. In this work we extend the conventional DESPOT1 and DESPOT2 approaches to include multicomponent relaxation analysis. Following numerical analysis of the new technique, renamed multicomponent driven equilibrium single pulse observation of T(1)/T(2) (mcDESPOT), whole-brain multicomponent T(1) and T(2) quantification is demonstrated in vivo with clinically realistic times of between 16 and 30 min. Results obtained from four healthy individuals and two primary progressive multiple sclerosis (MS) patients demonstrate the future potential of the approach for identifying and assessing tissue changes associated with several neurodegenerative conditions, in particular those associated with WM.

Visualizing water clearance in the lung with MRI

Current indirect measurements of alveolar fluid clearance (AFC) suggest that the rate of fluid clearance correlates with morbidity and mortality in patients with pulmonary edema. In a traditional AFC-measurement, fluid laced with a tracer macromolecule is instilled into the lung and thereafter repeated samples of the instilled fluid are extracted from the lung's fluid-filled airspaces. The change in concentration of the tracer molecule indicates the AFC-rate. In this work, a new MRI technique was developed to image lung water clearance by adding Gadolinium-DTPA to the instilled fluid. As fluid is absorbed by the animal, the concentration of gadolinium will increase, reducing the T(1) relaxation time. By repeatedly measuring the T(1) relaxation time, the AFC can be tracked over time with high spatial resolution. The new technique was tested both in phantoms and 10 Yorkshire piglets.

Investigating exchange and multicomponent relaxation in fully-balanced steady-state free precession imaging

PURPOSE

To investigate the effect of chemical exchange and multicomponent relaxation on the rapid T(2) mapping method, DESPOT2 (driven equilibrium single pulse observation of T(2)) and the steady-state free precession (SSFP) sequence upon which it is based. Although capable of rapid T(2) determination, an assumption implicit of the method is single-component relaxation. In many biological tissues (such as white and gray matter), it is well established that the T(2) decay curve is more accurately described by the summation of more than one relaxation species.

MATERIALS AND METHODS

The effects of exchange were first incorporated into the general SSFP magnetization expressions and its effect on the measured SSFP signal investigated using Bloch-McConnell simulations. Corresponding imaging experiments were performed to support the presented theory.

RESULTS

Simulations show the measured multicomponent SSFP signal may be expressed as a linear summation of signal from each species under usual imaging conditions where the repetition time is much less than T(2). Imaging experiments performed using dairy cream demonstrate strong agreement with the presented theory. Finally, using a dairy cream model, we demonstrate quantification of multicomponent relaxation from multiangle SSFP data for the first time, showing good agreement with reference spin-echo values.

CONCLUSION

SSFP and DESPOT2 may provide a new method for investigating multicomponent systems, such as human brain, and disease processes, such as multiple sclerosis.