An efficient computational approach to characterize DSC-MRI signals arising from three-dimensional heterogeneous tissue structures

Comprehensive characterization of tumor therapeutic response with simultaneous mapping cell size, density, and transcytolemmal water exchange

Early assessment of tumor therapeutic response is an important topic in precision medicine to optimize personalized treatment regimens and reduce unnecessary toxicity, cost, and delay. Although diffusion MRI (dMRI) has shown potential to address this need, its predictive accuracy is limited, likely due to its unspecific sensitivity to overall pathological changes. In this work, we propose a new quantitative dMRI-based method dubbed EXCHANGE (MRI of water Exchange, Confined and Hindered diffusion under Arbitrary Gradient waveform Encodings) for simultaneous mapping of cell size, cell density, and transcytolemmal water exchange. Such rich microstructural information comprehensively evaluates tumor pathologies at the cellular level. Validations using numerical simulations and in vitro cell experiments confirmed that the EXCHANGE method can accurately estimate mean cell size, density, and water exchange rate constants. The results from in vivo animal experiments show the potential of EXCHANGE for monitoring tumor treatment response. Finally, the EXCHANGE method was implemented in breast cancer patients with neoadjuvant chemotherapy, demonstrating its feasibility in assessing tumor therapeutic response in clinics. In summary, a new, quantitative dMRI-based EXCHANGE method was proposed to comprehensively characterize tumor microstructural properties at the cellular level, suggesting a unique means to monitor tumor treatment response in clinical practice.

Detection of Treatment Response in Triple-Negative Breast Tumors to Paclitaxel Using MRI Cell Size Imaging

BACKGROUND

Breast cancer treatment response evaluation using the response evaluation criteria in solid tumors (RECIST) guidelines, based on tumor volume changes, has limitations, prompting interest in novel imaging markers for accurate therapeutic effect determination.

PURPOSE

To use MRI-measured cell size as a new imaging biomarker for assessing chemotherapy response in breast cancer.

STUDY TYPE

Longitudinal; animal model.

STUDY POPULATION

Triple-negative human breast cancer cell (MDA-MB-231) pellets (4 groups, n = 7) treated with dimethyl sulfoxide (DMSO) or 10 nM of paclitaxel for 24, 48, and 96 hours, and 29 mice with MDA-MB-231 tumors in right hind limbs treated with paclitaxel (n = 16) or DMSO (n = 13) twice weekly for 3 weeks.

FIELD STRENGTH/SEQUENCE

Oscillating gradient spin echo and pulsed gradient spin echo sequences at 4.7 T.

ASSESSMENT

MDA-MB-231 cells were analyzed using flowcytometry and light microscopy to assess cell cycle phases and cell size distribution. MDA-MB-231 cell pellets were MR imaged. Mice were imaged weekly, with 9, 6, and 14 being sacrificed for histology after MRI at weeks 1, 2, and 3, respectively. Microstructural parameters of tumors/cell pellets were derived by fitting diffusion MRI data to a biophysical model.

STATISTICAL TESTS

One-way ANOVA compared cell sizes and MR-derived parameters between treated and control samples. Repeated measures 2-way ANOVA with Bonferroni post-tests compared temporal changes in MR-derived parameters. A P-value <0.05 was considered statistically significant.

RESULTS

In vitro experiments showed that the mean MR-derived cell sizes of paclitaxel-treated cells increased significantly with a 24-hours treatment and decreased (P = 0.06) with a 96-hour treatment. For in vivo xenograft experiments, the paclitaxel-treated tumors showed significant decreases in cell size at later weeks. MRI observations were supported by flowcytometry, light microscopy, and histology.

DATA CONCLUSIONS

MR-derived cell size may characterize the cell shrinkage during treatment-induced apoptosis, and may potentially provide new insights into the assessment of therapeutic response.

LEVEL OF EVIDENCE

2 TECHNICAL EFFICACY STAGE: 4.

DSC MRI in the human brain using deoxyhemoglobin and gadolinium-Simulations and validations at 3T

INTRODUCTION

Dynamic susceptibility contrast (DSC) MRI allows clinicians to determine perfusion parameters in the brain, such as cerebral blood flow, cerebral blood volume, and mean transit time. To enable quantification, susceptibility changes can be induced using gadolinium (Gd) or deoxyhemoglobin (dOHb), the latter just recently introduced as a contrast agent in DSC. Previous investigations found that experimental parameters and analysis choices, such as the susceptibility amplitude and partial volume, affect perfusion quantification. However, the accuracy and precision of DSC MRI has not been systematically investigated, particularly in the lower susceptibility range.

METHODS

In this study, we compared perfusion values determined using Gd with values determined using a contrast agent with a lower susceptibility-dOHb-under different physiological conditions, such as varying the baseline blood oxygenation and/or magnitude of hypoxic bolus, by utilizing numerical simulations and conducting experiments on healthy subjects at 3T. The simulation framework we developed for DSC incorporates MRI signal contributions from intravascular and extravascular proton spins in arterial, venous, and cerebral tissue voxels. This framework allowed us to model the MRI signal in response to both Gd and dOHb.

RESULTS AND DISCUSSION

We found, both in the experimental results and simulations, that a reduced intravascular volume of the selected arterial voxel, reduced baseline oxygen saturation, greater susceptibility of applied contrast agent (Gd vs. dOHb), and/or larger magnitude of applied hypoxic bolus reduces the overestimation and increases precision of cerebral blood volume and flow. As well, we found that normalizing tissue to venous rather than arterial signal increases the accuracy of perfusion quantification across experimental paradigms. Furthermore, we found that shortening the bolus duration increases the accuracy and reduces the calculated values of mean transit time. In summary, we experimentally uncovered an array of perfusion quantification dependencies, which agreed with the simulation framework predictions, using a wider range of susceptibility values than previously investigated. We argue for caution when comparing absolute and relative perfusion values within and across subjects obtained from a standard DSC MRI analysis, particularly when employing different experimental paradigms and contrast agents.

Evaluation of single bolus, dual-echo dynamic susceptibility contrast MRI protocols in brain tumor patients

Relative cerebral blood volume (rCBV) obtained from dynamic susceptibility contrast (DSC) MRI is adversely impacted by contrast agent leakage in brain tumors. Using simulations, we previously demonstrated that multi-echo DSC-MRI protocols provide improvements in contrast agent dosing, pulse sequence flexibility, and rCBV accuracy. The purpose of this study is to assess the in-vivo performance of dual-echo acquisitions in patients with brain tumors (n = 59). To verify pulse sequence flexibility, four single-dose dual-echo acquisitions were tested with variations in contrast agent dose, flip angle, and repetition time, and the resulting dual-echo rCBV was compared to standard single-echo rCBV obtained with preload (double-dose). Dual-echo rCBV was comparable to standard double-dose single-echo protocols (mean (standard deviation) tumor rCBV 2.17 (1.28) vs. 2.06 (1.20), respectively). High rCBV similarity was observed (CCC = 0.96), which was maintained across both flip angle (CCC = 0.98) and repetition time (CCC = 0.96) permutations, demonstrating that dual-echo acquisitions provide flexibility in acquisition parameters. Furthermore, a single dual-echo acquisition was shown to enable quantification of both perfusion and permeability metrics. In conclusion, single-dose dual-echo acquisitions provide similar rCBV to standard double-dose single-echo acquisitions, suggesting contrast agent dose can be reduced while providing significant pulse sequence flexibility and complementary tumor perfusion and permeability metrics.

Tissue characterization using R1rho dispersion imaging at low locking fields

Measurements of the variations of spin-locking relaxation rates (R_1ρ) with locking field amplitude allow the derivation of quantitative parameters that describe different dynamic processes, such as slow molecular motions, chemical exchange and diffusion. In some samples, changes in R_1ρ values between locking frequency 0 and 200 Hz may be dominated mainly by diffusion of water in intrinsic field gradients, while those at higher locking fields are due to exchange processes. The exchange and diffusion effects act independently of each other, as confirmed by simulation and experimentally. In tissues, the relevant intrinsic field gradients may arise from the magnetic inhomogeneities caused by microvascular blood so that R_1ρ dispersion over weak locking field amplitudes (≤ 200 Hz) is affected by changes in capillary density and geometry. Here we first review the theoretical and experimental background to the interpretation of R_1ρ dispersions caused by intrinsic magnetic susceptibility variations within the tissue. We then provide new empirical results of R_1ρ dispersion imaging of the human brain and skeletal muscle at low locking field amplitudes for the first time and identify potential applications of R_1ρ dispersion imaging in clinical studies.

A multiscale subvoxel perfusion model to estimate diffusive capillary wall conductivity in multiple sclerosis lesions from perfusion MRI data

We propose a new mathematical model to learn capillary leakage coefficients from dynamic susceptibility contrast MRI data. To this end, we derive an embedded mixed-dimension flow and transport model for brain tissue perfusion on a subvoxel scale. This model is used to obtain the contrast agent concentration distribution in a single MRI voxel during a perfusion MRI sequence. We further present a magnetic resonance signal model for the considered sequence including a model for local susceptibility effects. This allows modeling MR signal-time curves that can be compared with clinical MRI data. The proposed model can be used as a forward model in the inverse modeling problem of inferring model parameters such as the diffusive capillary wall conductivity. Acute multiple sclerosis lesions are associated with a breach in the integrity of the blood-brain barrier. Applying the model to perfusion MR data of a patient with acute multiple sclerosis lesions, we conclude that diffusive capillary wall conductivity is a good indicator for characterizing activity of lesions, even if other patient-specific model parameters are not well-known.

Spin-lock imaging of intrinsic susceptibility gradients in tumors

PURPOSE

Previous studies have shown that diffusion of water through intrinsic susceptibility gradients produces a dispersion of the spin-lattice relaxation rate in the rotating frame (R_{1 ρ} ) over a low range of spin-locking amplitudes (0 < ω₁ < 100 Hz), whereas at higher ω₁ and high magnetic fields, a second dispersion arises due to chemical exchange. Here, we separated these different effects and evaluated their contributions in tumors.

METHODS

Maps of R_{1 ρ} and its changes with locking field were acquired on intracranial 9-L tumor models. The R_{1 ρ} changes due to diffusion ( R 1 ρ Diff ) were calculated by subtracting maps of R_{1 ρ} at 100 Hz (R_{1 ρ} [100 Hz]) from those at 0 Hz (R_{1 ρ} [0 Hz]). The R_{1 ρ} changes due to exchange ( R 1 ρ Ex ) were calculated by subtracting maps of R_{1 ρ} at 5620 Hz (R_{1 ρ} [5620 Hz]) from those of R_{1 ρ} at 100 Hz (R_{1 ρ} [100 Hz]). Measurements of vascular dimensions and spacing were performed ex vivo using 3D confocal microscopy.

RESULTS

The R_{1 ρ} changes at low ω₁ in tumors (5.24 ± 1.78 s^-1 ) are substantially (p = 3.7⁶ ) greater than those in normal tissues (1.36 ± 0.70 s^-1 ), which we suggest are due to greater contributions from diffusion through susceptibility gradients. Tumor vessels were larger and spaced less closely compared with normal brain, which may be 1 factor contributing the susceptibility within 9-L tumors. The contrast between tumor and normal tissues for R 1 ρ Diff is larger than for R 1 ρ Ex and for the apparent R_2w .

CONCLUSION

Images that are sensitive to the variations of spin-lock relaxation rates at low ω₁ provide a novel form of contrast that reflects the heterogeneous nature of intrinsic variations within tumors.

Systematic assessment of multi-echo dynamic susceptibility contrast MRI using a digital reference object

PURPOSE

Brain tumor dynamic susceptibility contrast (DSC) MRI is adversely impacted by T₁ and T 2 ∗ contrast agent leakage effects that result in inaccurate hemodynamic metrics. While multi-echo acquisitions remove T₁ leakage effects, there is no consensus on the optimal set of acquisition parameters. Using a computational approach, we systematically evaluated a wide range of acquisition strategies to determine the optimal multi-echo DSC-MRI perfusion protocol.

METHODS

Using a population-based DSC-MRI digital reference object (DRO), we assessed the influence of preload dosing (no preload and full dose preload), field strength (1.5 and 3T), pulse sequence parameters (echo time, repetition time, and flip angle), and leakage correction on relative cerebral blood volume (rCBV) and flow (rCBF) accuracy. We also compared multi-echo DSC-MRI protocols with standard single-echo protocols.

RESULTS

Multi-echo DSC-MRI is highly consistent across all protocols, and multi-echo rCBV (with or without use of a preload dose) had higher accuracy than single-echo rCBV. Regression analysis showed that choice of repetition time and flip angle had minimal impact on multi-echo rCBV and rCBV, indicating the potential for significant flexibility in acquisition parameters. The echo time combination had minimal impact on rCBV, though longer echo times should be avoided, particularly at higher field strengths. Leakage correction improved rCBV accuracy in all cases. Multi-echo rCBF was less biased than single-echo rCBF, although rCBF accuracy was reduced overall relative to rCBV.

CONCLUSIONS

Multi-echo acquisitions were more robust than single-echo, essentially decoupling both repetition time and flip angle from rCBV accuracy. Multi-echo acquisitions obviate the need for preload dosing, although leakage correction to remove residual T 2 ∗ leakage effects remains compulsory for high rCBV accuracy.

Imaging vascular and hemodynamic features of the brain using dynamic susceptibility contrast and dynamic contrast enhanced MRI

In the context of neurologic disorders, dynamic susceptibility contrast (DSC) and dynamic contrast enhanced (DCE) MRI provide valuable insights into cerebral vascular function, integrity, and architecture. Even after two decades of use, these modalities continue to evolve as their biophysical and kinetic basis is better understood, with improvements in pulse sequences and accelerated imaging techniques and through application of more robust and automated data analysis strategies. Here, we systematically review each of these elements, with a focus on how their integration improves kinetic parameter accuracy and the development of new hemodynamic biomarkers that provide sub-voxel sensitivity (e.g., capillary transit time and flow heterogeneity). Regarding contrast mechanisms, we discuss the dipole-dipole interactions and susceptibility effects that give rise to simultaneous T₁, T₂ and T₂^∗ relaxation effects, including their quantification, influence on pulse sequence parameter optimization, and use in methods such as vessel size and vessel architectural imaging. The application of technologic advancements, such as parallel imaging, simultaneous multi-slice, undersampled k-space acquisitions, and sliding window strategies, enables improved spatial and/or temporal resolution of DSC and DCE acquisitions. Such acceleration techniques have also enabled the implementation of, clinically feasible, simultaneous multi-echo spin- and gradient echo acquisitions, providing more comprehensive and quantitative interrogation of T₁, T₂ and T₂^∗ changes. Characterizing these relaxation rate changes through different post-processing options allows for the quantification of hemodynamics and vascular permeability. The application of different biophysical models provides insight into traditional hemodynamic parameters (e.g., cerebral blood volume) and more advanced parameters (e.g., capillary transit time heterogeneity). We provide insight into the appropriate selection of biophysical models and the necessary post-processing steps to ensure reliable measurements while minimizing potential sources of error. We show representative examples of advanced DSC- and DCE-MRI methods applied to pathologic conditions affecting the cerebral microcirculation, including brain tumors, stroke, aging, and multiple sclerosis. The maturation and standardization of conventional DSC- and DCE-MRI techniques has enabled their increased integration into clinical practice and use in clinical trials, which has, in turn, spurred renewed interest in their technological and biophysical development, paving the way towards a more comprehensive assessment of cerebral hemodynamics.

MRI Simulation Study Investigating Effects of Vessel Topology, Diffusion, and Susceptibility on Transverse Relaxation Rates Using a Cylinder Fork Model

Brain vasculature is conventionally represented as straight cylinders when simulating blood oxygenation level dependent (BOLD) contrast effects in functional magnetic resonance imaging (fMRI). In reality, the vasculature is more complicated with branching and coiling especially in tumors. Diffusion and susceptibility changes can also introduce variations in the relaxation mechanisms within tumors. This study introduces a simple cylinder fork model (CFM) and investigates the effects of vessel topology, diffusion, and susceptibility on the transverse relaxation rates R2* and R2. Simulations using Monte Carlo methods were performed to quantify R2* and R2 by manipulating the CFM at different orientations, bifurcation angles, and rotation angles. Other parameters of the CFM were chosen based on physiologically relevant values: vessel diameters (~2‒10 µm), diffusion rates (1 × 10⁻¹¹‒1 × 10⁻⁹ m²/s), and susceptibility values (3 × 10⁻⁸–4 × 10⁻⁷ cgs units). R2* and R2 measurements showed a significant dependence on the bifurcation and rotation angles in several scenarios using different vessel diameters, orientations, diffusion rates, and susceptibility values. The angular dependence of R2* and R2 using the CFM could potentially be exploited as a tool to differentiate between normal and tumor vessels. The CFM can also serve as the elementary building block to simulate a capillary network reflecting realistic topological features.

A Population-Based Digital Reference Object (DRO) for Optimizing Dynamic Susceptibility Contrast (DSC)-MRI Methods for Clinical Trials

The standardization and broad-scale integration of dynamic susceptibility contrast (DSC)-magnetic resonance imaging (MRI) have been confounded by a lack of consensus on DSC-MRI methodology for preventing potential relative cerebral blood volume inaccuracies, including the choice of acquisition protocols and postprocessing algorithms. Therefore, we developed a digital reference object (DRO), using physiological and kinetic parameters derived from in vivo data, unique voxel-wise 3-dimensional tissue structures, and a validated MRI signal computational approach, aimed at validating image acquisition and analysis methods for accurately measuring relative cerebral blood volume in glioblastomas. To achieve DSC-MRI signals representative of the temporal characteristics, magnitude, and distribution of contrast agent-induced T₁ and T₂* changes observed across multiple glioblastomas, the DRO's input parameters were trained using DSC-MRI data from 23 glioblastomas (>40 000 voxels). The DRO's ability to produce reliable signals for combinations of pulse sequence parameters and contrast agent dosing schemes unlike those in the training data set was validated by comparison with in vivo dual-echo DSC-MRI data acquired in a separate cohort of patients with glioblastomas. Representative applications of the DRO are presented, including the selection of DSC-MRI acquisition and postprocessing methods that optimize CBV accuracy, determination of the impact of DSC-MRI methodology choices on sample size requirements, and the assessment of treatment response in clinical glioblastoma trials.

In vivo imaging of cancer cell size and cellularity using temporal diffusion spectroscopy

PURPOSE

A temporal diffusion MRI spectroscopy based approach has been developed to quantify cancer cell size and density in vivo.

METHODS

A novel imaging microstructural parameters using limited spectrally edited diffusion (IMPULSED) method selects a specific limited diffusion spectral window for an accurate quantification of cell sizes ranging from 10 to 20 μm in common solid tumors. In practice, it is achieved by a combination of a single long diffusion time pulsed gradient spin echo (PGSE) and three low-frequency oscillating gradient spin echo (OGSE) acquisitions. To validate our approach, hematoxylin and eosin staining and immunostaining of cell membranes, in concert with whole slide imaging, were used to visualize nuclei and cell boundaries, and hence, enabled accurate estimates of cell size and cellularity.

RESULTS

Based on a two compartment model (incorporating intra- and extracellular spaces), accurate estimates of cell sizes were obtained in vivo for three types of human colon cancers. The IMPULSED-derived apparent cellularities showed a stronger correlation (r = 0.81; P < 0.0001) with histology-derived cellularities than conventional ADCs (r = -0.69; P < 0.03).

CONCLUSION

The IMPULSED approach samples a specific region of temporal diffusion spectra with enhanced sensitivity to length scales of 10-20 μm, and enables measurements of cell sizes and cellularities in solid tumors in vivo. Magn Reson Med 78:156-164, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

A theoretical framework for determining cerebral vascular function and heterogeneity from dynamic susceptibility contrast MRI

Mapping the complex heterogeneity of vascular tissue in the brain is important for understanding cerebrovascular disease. In this translational study, we build on previous work using vessel architectural imaging (VAI) and present a theoretical framework for determining cerebral vascular function and heterogeneity from dynamic susceptibility contrast magnetic resonance imaging (MRI). Our tissue model covers realistic structural architectures for vessel branching and orientations, as well as a range of hemodynamic scenarios for blood flow, capillary transit times and oxygenation. In a typical image voxel, our findings show that the apparent MRI relaxation rates are independent of the mean vessel orientation and that the vortex area, a VAI-based parameter, is determined by the relative oxygen saturation level and the vessel branching of the tissue. Finally, in both simulated and patient data, we show that the relative distributions of the vortex area parameter as a function of capillary transit times show unique characteristics in normal-appearing white and gray matter tissue, whereas tumour-voxels in comparison display a heterogeneous distribution. Collectively, our study presents a comprehensive framework that may serve as a roadmap for in vivo and per-voxel determination of vascular status and heterogeneity in cerebral tissue.

Anisotropic cerebral vascular architecture causes orientation dependency in cerebral blood flow and volume measured with dynamic susceptibility contrast magnetic resonance imaging

Measurements of cerebral perfusion using dynamic susceptibility contrast magnetic resonance imaging rely on the assumption of isotropic vascular architecture. However, a considerable fraction of vessels runs in parallel with white matter tracts. Here, we investigate the effects of tissue orientation on dynamic susceptibility contrast magnetic resonance imaging. Tissue orientation was measured using diffusion tensor imaging and dynamic susceptibility contrast was performed with gradient echo planar imaging. Perfusion parameters and the raw dynamic susceptibility contrast signals were correlated with tissue orientation. Additionally, numerical simulations were performed for a range of vascular volumes of both the isotropic vascular bed and anisotropic vessel components, as well as for a range of contrast agent concentrations. The effect of the contrast agent was much larger in white matter tissue perpendicular to the main magnetic field compared to white matter parallel to the main magnetic field. In addition, cerebral blood flow and cerebral blood volume were affected in the same way with angle-dependent variations of up to 130%. Mean transit time and time to maximum of the residual curve exhibited weak orientation dependency of 10%. Numerical simulations agreed with the measured data, showing that one-third of the white matter vascular volume is comprised of vessels running in parallel with the fibre tracts.

Effects of MRI Protocol Parameters, Preload Injection Dose, Fractionation Strategies, and Leakage Correction Algorithms on the Fidelity of Dynamic-Susceptibility Contrast MRI Estimates of Relative Cerebral Blood Volume in Gliomas

BACKGROUND AND PURPOSE

DSC perfusion MR imaging assumes that the contrast agent remains intravascular; thus, disruptions in the blood-brain barrier common in brain tumors can lead to errors in the estimation of relative CBV. Acquisition strategies, including the choice of flip angle, TE, TR, and preload dose and incubation time, along with post hoc leakage-correction algorithms, have been proposed as means for combating these leakage effects. In the current study, we used DSC-MR imaging simulations to examine the influence of these various acquisition parameters and leakage-correction strategies on the faithful estimation of CBV.

MATERIALS AND METHODS

DSC-MR imaging simulations were performed in 250 tumors with perfusion characteristics randomly generated from the distributions of real tumor population data, and comparison of leakage-corrected CBV was performed with a theoretic curve with no permeability. Optimal strategies were determined by protocol with the lowest mean error.

RESULTS

The following acquisition strategies (flip angle/TE/TR and contrast dose allocation for preload and bolus) produced high CBV fidelity, as measured by the percentage difference from a hypothetic tumor with no leakage: 1) 35°/35 ms/1.5 seconds with no preload and full dose for DSC-MR imaging, 2) 35°/25 ms/1.5 seconds with ¼ dose preload and ¾ dose bolus, 3) 60°/35 ms/2.0 seconds with ½ dose preload and ½ dose bolus, and 4) 60°/35 ms/1.0 second with 1 dose preload and 1 dose bolus.

CONCLUSIONS

Results suggest that a variety of strategies can yield similarly high fidelity in CBV estimation, namely those that balance T1- and T2*-relaxation effects due to contrast agent extravasation.

On the Use of DSC-MRI for Measuring Vascular Permeability

BACKGROUND AND PURPOSE

Contrast agent extravasation has been shown to confound brain tumor perfusion measurements with DSC-MR imaging, necessitating the use of correction techniques (eg, Weisskoff, Bjornerud). Leakage parameters (K2 and K(a)) postulated to reflect vessel permeability can be extracted from these correction methods; however, the biophysical interpretation of these parameters and their relationship to commonly used MR imaging measures of vascular permeability (eg, contrast agent volume transfer constant, [K(trans)]) remain unclear. Given that vascular density, as assessed by blood volume, and vascular permeability, as reflected by K(trans) (and potentially K2 or K(a)), report on unique and clinically informative vascular characteristics, there is a compelling interest to simultaneously assess these features.

MATERIALS AND METHODS

We acquired multiecho DSC-MR imaging data, allowing the simultaneous computation and voxelwise comparison of single- and dual-echo derived measures of K2, K(a) and K(trans) in patients with glioma. This acquisition enabled the investigation of competing T1 and T2* leakage effects and TE dependency on these parameters.

RESULTS

K2 and K(a) displayed nonsignificant (P = .150 and P = .060, respectively) voxelwise linear correlations with K(trans), while a significant (P < .001) inverse relationship was observed between K2 and Ka (coefficient of determination [r(2)] = 0.466-0.984). Significantly different (P < .005) mean estimates were found between voxels exhibiting predominately T1 and T2* effects for K2 and K(a). K(trans), however, was observed to be similar between these voxels (0.109 versus 0.092 minutes(-1)). Significant differences (P < .001) in extracellular-extravascular volume fraction (v(e)) (0.285 versus 0.167) were also observed between cohorts. Additionally, K2 and K(a) were found to have a significant quadratic relationship (P = .031 and P = .005, respectively) with v(e).

CONCLUSIONS

Estimates of vascular permeability in brain tumors may be simultaneously acquired from multiple-echo DSC-MR imaging via K(trans); however, caution should be used in assuming a similar relationship for K2 and K(a).

Validation of a T1 and T2* leakage correction method based on multiecho dynamic susceptibility contrast MRI using MION as a reference standard

PURPOSE

A combined biophysical- and pharmacokinetic-based method is proposed to separate, quantify, and correct for both T1 and T2* leakage effects using dual-echo dynamic susceptibility contrast (DSC) acquisitions to provide more accurate hemodynamic measures, as validated by a reference intravascular contrast agent (CA).

THEORY AND METHODS

Dual-echo DSC-MRI data were acquired in two rodent glioma models. The T1 leakage effects were removed and also quantified to subsequently correct for the remaining T2* leakage effects. Pharmacokinetic, biophysical, and combined biophysical and pharmacokinetic models were used to obtain corrected cerebral blood volume (CBV) and cerebral blood flow (CBF), and these were compared with CBV and CBF from an intravascular CA.

RESULTS

T1 -corrected CBV was significantly overestimated compared with MION CBV, while T1 + T2*-correction yielded CBV values closer to the reference values. The pharmacokinetic and simplified biophysical methods showed similar results and underestimated CBV in tumors exhibiting strong T2* leakage effects. The combined method was effective for correcting T1 and T2* leakage effects across tumor types.

CONCLUSION

Correcting for both T1 and T2* leakage effects yielded more accurate measures of CBV. The combined correction method yields more reliable CBV measures than either correction method alone, but for certain brain tumor types (e.g., gliomas), the simplified biophysical method may provide a robust and computationally efficient alternative. Magn Reson Med 76:613-625, 2016. © 2015 Wiley Periodicals, Inc.

Modeling the effect of intra-voxel diffusion of contrast agent on the quantitative analysis of dynamic contrast enhanced magnetic resonance imaging

Quantitative dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) provides estimates of physiologically relevant parameters related to tissue blood flow, vascular permeability, and tissue volume fractions which can then be used for prognostic and diagnostic reasons. However, standard techniques for DCE-MRI analysis ignore intra-voxel diffusion, which may play an important role in contrast agent distribution and voxel signal intensity and, thus, will affect quantification of the aforementioned parameters. To investigate the effect of intra-voxel diffusion on quantitative DCE-MRI, we developed a finite element model of contrast enhancement at the voxel level. For diffusion in the range of that expected for gadolinium chelates in tissue (i.e., 1×10⁻⁴ to 4×10⁻⁴ mm²/s), parameterization errors range from −58% to 12% for K^trans, −9% to 8% for v_e, and −60% to 213% for v_p over the range of K^trans, v_e, v_p, and temporal resolutions investigated. Thus the results show that diffusion has a significant effect on parameterization using standard techniques.

Assessing tumor cytoarchitecture using multiecho DSC-MRI derived measures of the transverse relaxivity at tracer equilibrium (TRATE)

PURPOSE

In brain tumor dynamic susceptibility contrast (DSC)-MRI studies, multiecho acquisition methods are used to quantify the dynamic changes in T1 and T2 * that occur when contrast agent (CA) extravasates. Such methods also enable the estimation of the effective tissue CA transverse relaxivity. The goal of this study was to evaluate the sensitivity of the transverse relaxivity at tracer equilibrium (TRATE) to tumor cytoarchitecture.

METHODS

Computational and in vitro studies were used to evaluate the biophysical basis of TRATE. In 9L, C6, and human brain tumors, TRATE, the apparent diffusion coefficient (ADC), the CA transfer constant (K(trans) ), the extravascular extracellular volume fraction (ve ), and histological data were compared.

RESULTS

Simulations and in vitro results indicate that TRATE is highly sensitive to variations in cellular properties such as cell size and density. The histologic cell density and TRATE values were significantly higher in 9L tumors as compared to C6 tumors. In animal and human tumors, a voxel-wise comparison of TRATE with ADC, ve , and K(trans) maps showed low spatial correlation.

CONCLUSION

The assessment of TRATE is clinically feasible and its sensitivity to tissue cytoarchitectural features not present in other imaging methods indicate that it could potentially serve as a unique structural signature or "trait" of cancer.