Theoretical model of intravascular paramagnetic tracers effect on tissue relaxation

Contrast-free dynamic susceptibility contrast using sinusoidal and bolus oxygenation challenges

Deoxygenation-based dynamic susceptibility contrast (dDSC) MRI uses respiratory challenges as a source of endogenous contrast as an alternative to gadolinium injection. These gas challenges induce T2*-weighted MRI signal losses, after which tracer kinetics modeling was applied to calculate cerebral perfusion. This work compares three gas challenges, desaturation (transient hypoxia), resaturation (transient normoxia), and SineO2 (sinusoidal modulation of end-tidal oxygen pressures) in a cohort of 10 healthy volunteers (age 37 ± 11 years; 60% female). Perfusion estimates consisted of cerebral blood flow (CBF), cerebral blood volume (CBV), and mean transit time (MTT). Calculations were computed using a traditional tracer kinetics model in the time domain for desaturation and resaturation and in the frequency domain for SineO2. High correlations and limits of agreement were observed among the three deoxygenation-based paradigms for CBV, although MTT and CBF estimates varied with the hypoxic stimulus. Cross-modality correlation with gadolinium DSC was lower, particularly for MTT, but on a par with agreement between the other perfusion references. Overall, this work demonstrated the feasibility and reliability of oxygen respiratory challenges to measure brain perfusion. Additional work is needed to assess the utility of dDSC in the diagnostic evaluation of various pathologies such as ischemic strokes, brain tumors, and neurodegenerative diseases.

Dynamic Susceptibility Contrast Perfusion, Part 1: The Fundamentals

Measuring blood flow has been of long-standing interest in medicine and physiology. Initially conceived to measure blood flow to the whole organ, attention turned quickly to measure capillary blood flow as a measure of local delivery of nutrients to a small region of tissue. Originally proposed with gases and microspheres, early on, the method of indicator dilution has become the most prevalent approach because of the impracticality of using microspheres.

Improved reliability of perfusion estimation in dynamic susceptibility contrast MRI by using the arterial input function from dynamic contrast enhanced MRI

The arterial input function (AIF) plays a crucial role in estimating quantitative perfusion properties from dynamic susceptibility contrast (DSC) MRI. An important issue, however, is that measuring the AIF in absolute contrast-agent concentrations is challenging, due to uncertainty in relation to the measuredR 2 ∗ -weighted signal, signal depletion at high concentration, and partial-volume effects. A potential solution could be to derive the AIF from separately acquired dynamic contrast enhanced (DCE) MRI data. We aim to compare the AIF determined from DCE MRI with the AIF from DSC MRI, and estimated perfusion coefficients derived from DSC data using a DCE-driven AIF with perfusion coefficients determined using a DSC-based AIF. AIFs were manually selected in branches of the middle cerebral artery (MCA) in both DCE and DSC data in each patient. In addition, a semi-automatic AIF-selection algorithm was applied to the DSC data. The amplitude and full width at half-maximum of the AIFs were compared statistically using the Wilcoxon rank-sum test, applying a 0.05 significance level. Cerebral blood flow (CBF) was derived with different AIF approaches and compared further. The results showed that the AIFs extracted from DSC scans yielded highly variable peaks across arteries within the same patient. The semi-automatic DSC-AIF had significantly narrower width compared with the manual AIFs, and a significantly larger peak than the manual DSC-AIF. Additionally, the DCE-based AIF provided a more stable measurement of relative CBF and absolute CBF values estimated with DCE-AIFs that were compatible with previously reported values. In conclusion, DCE-based AIFs were reproduced significantly better across vessels, showed more realistic profiles, and delivered more stable and reasonable CBF measurements. The DCE-AIF can, therefore, be considered as an alternative AIF source for quantitative perfusion estimations in DSC MRI.

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.

MR multitasking-based dynamic imaging for cerebrovascular evaluation (MT-DICE): Simultaneous quantification of permeability and leakage-insensitive perfusion by dynamic T 1 / T 2 * mapping

PURPOSE

To develop an MR multitasking-based dynamic imaging for cerebrovascular evaluation (MT-DICE) technique for simultaneous quantification of permeability and leakage-insensitive perfusion with a single-dose contrast injection.

METHODS

MT-DICE builds on a saturation-recovery prepared multi-echo fast low-angle shot sequence. The k-space is randomly sampled for 7.6 min, with single-dose contrast agent injected 1.5 min into the scan. MR multitasking is used to model the data into six dimensions, including three spatial dimensions for whole-brain coverage, a saturation-recovery time dimension, and a TE dimension for dynamicT 1 $$ {\mathrm{T}}_1 $$ andT 2 * $$ {\mathrm{T}}_2^{\ast } $$ quantification, respectively, and a contrast dynamics dimension for capturing contrast kinetics. The derived pixel-wiseT 1 / T 2 * $$ {\mathrm{T}}_1/{\mathrm{T}}_2^{\ast } $$ time series are converted into contrast concentration-time curves for calculation of kinetic metrics. The technique was assessed for its agreement with reference methods inT 1 $$ {\mathrm{T}}_1 $$ andT 2 * $$ {\mathrm{T}}_2^{\ast } $$ measurements in eight healthy subjects and, in three of them, inter-session repeatability of permeability and leakage-insensitive perfusion parameters. Its feasibility was also demonstrated in four patients with brain tumors.

RESULTS

MT-DICET 1 / T 2 * $$ {\mathrm{T}}_1/{\mathrm{T}}_2^{\ast } $$ values of normal gray matter and white matter were in excellent agreement with reference values (intraclass correlation coefficients = 0.860/0.962 for gray matter and 0.925/0.975 for white matter ). Both permeability and perfusion parameters demonstrated good to excellent intersession agreement with the lowest intraclass correlation coefficients at 0.694. Contrast kinetic parameters in all healthy subjects and patients were within the literature range.

CONCLUSION

Based on dynamicT 1 / T 2 * $$ {\mathrm{T}}_1/{\mathrm{T}}_2^{\ast } $$ mapping, MT-DICE allows for simultaneous quantification of permeability and leakage-insensitive perfusion metrics with a single-dose contrast injection.

Towards differentiation of brain tumor from radiation necrosis using multi-parametric MRI: Preliminary results at 4.7 T using rodent models

BACKGROUND

It remains a clinical challenge to differentiate brain tumors from radiation-induced necrosis in the brain. Despite significant improvements, no single MRI method has been validated adequately in the clinical setting.

METHODS

Multi-parametric MRI (mpMRI) was performed to differentiate 9L gliosarcoma from radiation necrosis in animal models. Five types of MRI methods probed complementary information on different scales i.e., T2 (relaxation), CEST based APT (probing mobile proteins/peptides) and rNOE (mobile macromolecules), qMT (macromolecules), diffusion based ADC (cell density) and SSIFT iAUC (cell size), and perfusion based DSC (blood volume and flow).

RESULTS

For single MRI parameters, iAUC and ADC provide the best discrimination of radiation necrosis and brain tumor. For mpMRI, a combination of iAUC, ADC, and APT shows the best classification performance based on a two-step analysis with the Lasso and Ridge regressions.

CONCLUSION

A general mpMRI approach is introduced to choosing candidate multiple MRI methods, identifying the most effective parameters from all the mpMRI parameters, and finding the appropriate combination of chosen parameters to maximize the classification performance to differentiate tumors from radiation necrosis.

Predicting the tissue outcome of acute ischemic stroke from acute 4D computed tomography perfusion imaging using temporal features and deep learning

Predicting follow-up lesions from baseline CT perfusion (CTP) datasets in acute ischemic stroke patients is important for clinical decision making. Deep convolutional networks (DCNs) are assumed to be the current state-of-the-art for this task. However, many DCN classifiers have not been validated against the methods currently used in research (random decision forests, RDF) and clinical routine (Tmax thresholding). Specialized DCNs have even been designed to extract complex temporal features directly from spatiotemporal CTP data instead of using standard perfusion parameter maps. However, the benefits of applying deep learning to source or deconvolved CTP data compared to perfusion parameter maps have not been formally investigated so far. In this work, a modular UNet-based DCN is proposed that separates temporal feature extraction from tissue outcome prediction, allowing for both model validation using perfusion parameter maps as well as end-to-end learning from spatiotemporal CTP data. 145 retrospective datasets comprising baseline CTP imaging, perfusion parameter maps, and follow-up non-contrast CT with manual lesion segmentations were assembled from acute ischemic stroke patients treated with intravenous thrombolysis alone (IV; n = 43) or intra-arterial mechanical thrombectomy (IA; n = 102) with or without combined IV. Using the perfusion parameter maps as input, the proposed DCN (mean Dice: 0.287) outperformed the RDF (0.262) and simple Tmax-thresholding (0.249). The performance of the proposed DCN was approximately equal using features optimized from the deconvolved residual curves (0.286) compared to perfusion parameter maps (0.287), while using features optimized from the source concentration-time curves (0.296) provided the best tissue outcome predictions.

Dependency of R2 and R2 * relaxation on Gd-DTPA concentration in arterial blood: Influence of hematocrit and magnetic field strength

Dynamic susceptibility contrast (DSC) MRI is clinically used to measure brain perfusion by monitoring the dynamic passage of a bolus of contrast agent through the brain. For quantitative analysis of the DSC images, the arterial input function is required. It is known that the original assumption of a linear relation between the R₂^(*) relaxation and the arterial contrast agent concentration is invalid, although the exact relation is as of yet unknown. Studying this relation in vitro is time-consuming, because of the widespread variations in field strengths, MRI sequences, contrast agents, and physiological conditions. This study aims to simulate the R₂^(*) versus contrast concentration relation under varying physiological and technical conditions using an adapted version of an open-source simulation tool. The approach was validated with previously acquired data in human whole blood at 1.5 T by means of a gradient-echo sequence (proof-of-concept). Subsequently, the impact of hematocrit, field strength, and oxygen saturation on this relation was studied for both gradient-echo and spin-echo sequences. The results show that for both gradient-echo and spin-echo sequences, the relaxivity increases with hematocrit and field strength, while the hematocrit dependency was nonlinear for both types of MRI sequences. By contrast, oxygen saturation has only a minor effect. In conclusion, the simulation setup has proven to be an efficient method to rapidly calibrate and estimate the relation between R₂^(*) and gadolinium concentration in whole blood. This knowledge will be useful in future clinical work to more accurately retrieve quantitative information on brain perfusion.

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.

Magnetic particle imaging for assessment of cerebral perfusion and ischemia

Stroke is one of the leading worldwide causes of death and sustained disability. Rapid and accurate assessment of cerebral perfusion is essential to diagnose and successfully treat stroke patients. Magnetic particle imaging (MPI) is a new technology with the potential to overcome some limitations of established imaging modalities. It is an innovative and radiation-free imaging technique with high sensitivity, specificity, and superior temporal resolution. MPI enables imaging and diagnosis of stroke and other neurological pathologies such as hemorrhage, tumors, and inflammatory processes. MPI scanners also offer the potential for targeted therapies of these diseases. Due to lower field requirements, MPI scanners can be designed as resistive magnets and employed as mobile devices for bedside imaging. With these advantages, MPI could accelerate and improve the diagnosis and treatment of neurological disorders. This review provides a basic introduction to MPI, discusses its current use for stroke imaging, and addresses future applications, including the potential for clinical implementation. This article is categorized under: Diagnostic Tools > In Vivo Nanodiagnostics and Imaging Therapeutic Approaches and Drug Discovery > Nanomedicine for Neurological Disease.

A dynamic susceptibility contrast MRI digital reference object for testing software with leakage correction: Effect of background simulation

PURPOSE

Dynamic susceptibility contrast (DSC)-MRI is a perfusion imaging technique from which useful quantitative imaging biomarkers can be derived. Relative cerebral blood volume (rCBV) is such a biomarker commonly used for evaluating brain tumors. To account for the extravasation of contrast agents in tumors, post-processing leakage correction is often applied to improve rCBV accuracy. Digital reference objects (DRO) are ideal for testing the post-processing software, because the biophysical model used to generate the DRO can be matched to the one that the software uses. This study aims to develop DROs to validate the leakage correction of software using Weisskoff model and to examine the effect of background signal time curves that are required by the model.

METHODS

Three DROs were generated using the Weisskoff model, each composed of nine foreground lesion objects with combinations of different levels of rCBV and contrast leakage parameter (K2). Three types of background were implemented for these DROs: (1) a multi-compartment brain-like background, (2) a sphere background with a constant signal time curve, and (3) a sphere background with signal time curve identical to that of the brain-like DRO's white matter (WM). The DROs were then analyzed with an FDA-cleared software with and without leakage correction. Leakage correction was tested with and without brain segmentation.

RESULTS

Accuracy of leakage correction was able to be verified using the brain-like phantom and the sphere phantom with WM background. The sphere with constant background did not perform well with leakage correction with or without brain segmentation. The DROs were able to verify that for the particular software tested, leakage correction with brain segmentation achieved the lowest error.

CONCLUSIONS

DSC-MRI DROs with biophysical model matched to that of the post-processing software can be well used for the software's validation, provided that the background signals are also properly simulated for generating the reference time curve required by the model. Care needs to be taken to consider the interaction of the design of the DRO with the software's implementation of brain segmentation to extract the reference time curve.

Development of a spiral spin- and gradient-echo (spiral-SAGE) approach for improved multi-parametric dynamic contrast neuroimaging

PURPOSE

The purpose of this study was to develop a spiral-based combined spin- and gradient-echo (spiral-SAGE) method for simultaneous dynamic contrast-enhanced (DCE-MRI) and dynamic susceptibility contrast MRI (DSC-MRI).

METHODS

Using this sequence, we obtained gradient-echo TEs of 1.69 and 26 ms, a SE TE of 87.72 ms, with a TR of 1663 ms. Using an iterative SENSE reconstruction followed by deblurring, spiral-induced image artifacts were minimized. Healthy volunteer images are shown to demonstrate image quality using the optimized reconstruction, as well as for comparison with EPI-based SAGE. A bioreactor phantom was used to compare dynamic-contrast time courses with both spiral-SAGE and EPI-SAGE. A proof-of-concept cohort of patients with brain tumors shows the range of hemodynamic maps available using spiral-SAGE.

RESULTS

Comparison of spiral-SAGE images with conventional EPI-SAGE images illustrates substantial reductions of image distortion and artifactual image intensity variations. Bioreactor phantom data show similar dynamic contrast time courses between standard EPI-SAGE and spiral-SAGE for the second and third echoes, whereas first-echo data show improvements in quantifying T₁ changes with shorter echo times. In a cohort of patients with brain tumors, spiral-SAGE-based perfusion and permeability maps are shown with comparison with the standard single-echo EPI perfusion map.

CONCLUSION

Spiral-SAGE provides a substantial improvement for the assessment of perfusion and permeability by mitigating artifacts typically encountered with EPI and by providing a shorter echo time for improved characterization of permeability. Spiral-SAGE enables quantification of perfusion, permeability, and vessel architectural parameters, as demonstrated in brain tumors.

Robust arterial input function surrogate measurement from the superior sagittal sinus complex signal for fast dynamic contrast-enhanced MRI in the brain

PURPOSE

Accurately estimating the arterial input function for dynamic contrast-enhanced MRI is challenging. An arterial input function is typically determined from signal magnitude changes related to a contrast agent, often leading to underestimation of peak concentrations. Alternatively, signal phase recovers the accurate peak concentration for straight vessels but suffers from high noise. A recent method proposed to fit the signal in the complex plane by combining the advantages of the previous 2 methods. The purpose of this work is to refine this complex-based method to determine the venous output function (VOF), an arterial input function surrogate, from the superior sagittal sinus.

METHODS

We propose a state-of-the-art complex-based method that includes direct compensation for blood inflow and signal phase correction accounting for the curvature of the superior sagittal sinus, generally assumed collinear with B₀ . We compared the magnitude-, phase-, and complex-based VOF determination methods against various simulated biases as well as for 29 brain metastases patients.

RESULTS

Angulation of the superior sagittal sinus relative to B₀ varied widely within patients, and its effect on the signal phase caused an underestimation of peak concentrations of up to 65%. Correction significantly increased the VOF peak concentration for the phase- and complex-based VOFs in the cohort. The phase-based method recovered accurate peak concentrations but lacked precision in the tail of the VOF. Our complex-based VOF completely recovered the effect of inflow and resulted in a high-peak concentration with limited noise.

CONCLUSION

The new complex-based method resulted in high-quality VOF robust against superior sagittal sinus curvature and variations in patient positioning.

Dynamic contrast-enhanced QSM for perfusion imaging: a systematic comparison of ΔR2*- and QSM-based contrast agent concentration time curves in blood and tissue

OBJECTIVE

In dynamic susceptibility contrast MRI (DSC-MRI), an arterial input function (AIF) is required to quantify perfusion. However, estimation of the concentration of contrast agent (CA) from magnitude MRI signal data is challenging. A reasonable alternative would be to quantify CA concentration using quantitative susceptibility mapping (QSM), as the CA alters the magnetic susceptibility in proportion to its concentration.

MATERIAL AND METHODS

AIFs with reasonable appearance, selected on the basis of conventional criteria related to timing, shape, and peak concentration, were registered from both ΔR2* and QSM images and mutually compared by visual inspection. Both ΔR2*- and QSM-based AIFs were used for perfusion calculations based on tissue concentration data from ΔR2*as well as QSM images.

RESULTS

AIFs based on ΔR2* and QSM data showed very similar shapes and the estimated cerebral blood flow values and mean transit times were similar. Analysis of corresponding ΔR2* versus QSM-based concentration estimates yielded a transverse relaxivity estimate of 89 s^-1 mM^-1, for voxels identified as useful AIF candidate in ΔR2* images according to the conventional criteria.

DISCUSSION

Interestingly, arterial concentration time curves based on ΔR2* versus QSM data, for a standard DSC-MRI experiment, were generally very similar in shape, and the relaxivity obtained in voxels representing blood was similar to tissue relaxivity obtained in previous studies.

Measurements of cerebral blood volume using quantitative susceptibility mapping, R2 * relaxometry, and ferumoxytol-enhanced MRI

Ferumoxytol-enhanced MRI holds potential for the non-invasive assessment of vascular architecture using estimates of cerebral blood volume (CBV). Ferumoxytol specifically enables steady-state imaging with extended acquisition times, for substantial improvements in resolution and contrast-to-noise ratio. With such data, quantitative susceptibility mapping (QSM) can be used to obtain images of local tissue magnetic susceptibility and hence estimate the increase in blood susceptibility after administration of a contrast agent, which in turn can be correlated to tissue CBV. Here, we explore the use of QSM for CBV estimation and compare it with R₂ * (1/T₂ *)-based results. Institutional review board approval was obtained, and all subjects provided written informed consent. For this prospective study, MR images were acquired on a 3.0 T scanner in 19 healthy subjects using a multiple-echo T₂ *-weighted sequence. Scanning was performed before and after the administration of two doses of ferumoxytol (1 mg FE/kg and 4 mg FE/kg). Different QSM approaches were tested on numerical phantom simulations. Results showed that the accuracy of magnetic susceptibility measurements improved with increasing image resolution and decreasing vascular density. In vivo changes in magnetic susceptibility were measured after the administration of ferumoxytol utilizing QSM, and significantly higher QSM-based CBV was measured in gray matter compared with white matter. QSM- and R₂ *-based CBV estimates correlated well, with similar average values, but a larger variance was found in QSM-based estimates.

Technical considerations of multi-parametric tissue outcome prediction methods in acute ischemic stroke patients

Decisions regarding acute stroke treatment rely heavily on imaging, but interpretation can be difficult for physicians. Machine learning methods can assist clinicians by providing tissue outcome predictions for different treatment approaches based on acute multi-parametric imaging. To produce such clinically viable machine learning models, factors such as classifier choice, data normalization, and data balancing must be considered. This study gives comprehensive consideration to these factors by comparing the agreement of voxel-based tissue outcome predictions using acute imaging and clinical parameters with manual lesion segmentations derived from follow-up imaging. This study considers random decision forest, generalized linear model, and k-nearest-neighbor machine learning classifiers in conjunction with three data normalization approaches (non-normalized, relative to contralateral hemisphere, and relative to contralateral VOI), and two data balancing strategies (full dataset and stratified subsampling). These classifier settings were evaluated based on 90 MRI datasets from acute ischemic stroke patients. Distinction was made between patients recanalized using intraarterial and intravenous methods, as well as those without successful recanalization. For primary quantitative comparison, the Dice metric was computed for each voxel-based tissue outcome prediction and its corresponding follow-up lesion segmentation. It was found that the random forest classifier outperformed the generalized linear model and the k-nearest-neighbor classifier, that normalization did not improve the Dice score of the lesion outcome predictions, and that the models generated lesion outcome predictions with higher Dice scores when trained with balanced datasets. No significant difference was found between the treatment groups (intraarterial vs intravenous) regarding the Dice score of the tissue outcome predictions.

Evaluation of contrast agent dose and diffusion coefficient measurement on vessel size index estimation

OBJECTIVES

The goal of this study is to examine the effect of contrast agent (CA) dose and diffusion coefficient on the estimation of vessel size index (VSI).

MATERIALS AND METHODS

Three groups of four participants were enrolled in this study and two different experiments were performed. Different dose of CA, namely 0.1 mmol/kg and 0.05 mmol/kg were assessed in two groups of normal subjects. Diffusion coefficient effect was assessed in the third group with high-grade glioma. Imaging included gradient echo and spin-echo DSC and DTI on a 3-T MR Scanner.

RESULTS

VSI estimation using half of standard dose of CA showed higher values compared to the application of standard, with a ratio of 2 for the WM and 1.5 for the GM. VSI estimates for tumor tissues (22 µm) were considerably higher compared to contra-lateral Normal-Appearing WM (NAWM, 4 µm, P < 0.01) and Normal-Appearing GM (NAGM, 8 µm, P < 0.04).

DISCUSSION

Application of standard dose for CA injection and also taking into account the effect of diffusion coefficient can lead to a better correlation of VSI with previous theoretically predicted values and improvement of individual diagnostics in tumor evaluations.

Increased precision in the intravascular arterial input function with flow compensation

PURPOSE

In this study, we investigate the effects of pulsatile flow and inflow on dynamic susceptibility-contrast MRI intravascular arterial input function measurement in human brain arteries and measure how they are affected by first-order flow compensation.

METHODS

A dual-echo single-shot EPI sequence with alternating flow compensation gradients was used to acquire dynamic susceptibility-contrast images with electrocardiogram monitoring. The dynamic signal variations measured inside the middle cerebral and internal carotid arteries were associated to the pulsatile arterial blood velocities measured with a single-slice quantitative flow sequence throughout the cardiac cycle.

RESULTS

Major inverse correlations between intravascular signal and blood velocity were found for the standard single-shot EPI sequence. Flow compensation reduces these correlated variations that contribute to signal physiological noise. This causes a significant twofold increase of intravascular SNR in the middle cerebral and the internal carotid arteries (2.3 ± 0.9, P = 0.03) and (2.0 ± 0.9, P = 0.04), respectively; and reduced phase SD for the internal carotid arteries (0.72 ± 0.14, P = 0.004). The correction proposed in this work translates into a quantitative arterial input function with reduced noise in the internal carotid arteries.

CONCLUSION

The physiological noise added by pulsatile flow and inflow for intravascular arterial input function measurement in the brain arteries is significantly reduced by flow compensation.

Measurement of microvascular cerebral blood volume changes over the cardiac cycle with ferumoxytol-enhanced T2 * MRI

PURPOSE

This feasibility study investigates the non-invasive measurement of microvascular cerebral blood volume (BV) changes over the cardiac cycle using cardiac-gated, ferumoxytol-enhanced T 2 ∗ MRI.

METHODS

Institutional review board approval was obtained and all subjects provided written informed consent. Cardiac gated MR scans were prospectively acquired on a 3.0T scanner in 22 healthy subjects using T 2 ∗ -weighted sequences with 2D-EPI and 3D spiral trajectories. Images were collected before and after the intravenous administration of 2 doses of ferumoxytol (1 mg FE/kg and 4 mg FE/kg). Cardiac cycle-induced R 2 ∗ (1/ T 2 ∗ ) changes (Δ R 2 ∗ ) and BV changes (ΔBV) throughout the cardiac cycle in gray matter (GM) and white matter (WM) were quantified and differences assessed using ANOVA followed by post hoc analysis.

RESULTS

Δ R 2 ∗ was found to increase in a dose-dependent fashion. A significantly larger increase was observed in GM compared to WM in both 2D and 3D acquisitions (P < 0.050). In addition, Δ R 2 ∗ increased significantly (P < 0.001) post versus pre-contrast injection in GM in both T 2 ∗ MRI acquisitions. Mean GM Δ R 2 ∗ derived from 2D-EPI images was 0.14 ± 0.06 s^-1 pre-contrast and 0.33 ± 0.13 s^-1 after 5 mg FE/kg. In WM, Δ R 2 ∗ was 0.19 ± 0.06 s^-1 pre-contrast, and 0.23 ± 0.06 s^-1 after 5 mg FE/kg. The fractional changes in BV throughout the cardiac cycle were 0.031 ± 0.019% in GM and 0.011 ± 0.008% in WM (P < 0.001) after 5 mg FE/kg.

CONCLUSION

Cardiac-gated, ferumoxytol-enhanced T 2 ∗ MRI enables characterization of microvascular BV changes throughout the cardiac cycle in GM and WM tissue of healthy subjects.

Simultaneous perfusion and permeability assessments using multiband multi-echo EPI (M2-EPI) in brain tumors

PURPOSE

To study a multiband multi-echo EPI (M2-EPI) sequence for dynamic susceptibility contrast (DSC) perfusion imaging with leakage correction and vascular permeability measurements, and to evaluate the benefits of increased temporal resolution provided by this acquisition strategy on the accuracy of perfusion and permeability estimations.

METHODS

A novel M2-EPI sequence was developed, and a pharmacokinetic model accounting for contrast agent extravasation was used to produce perfusion maps and additional vascular permeability maps. The advantage of M2-EPI for DSC perfusion imaging was demonstrated in vivo in 5 patients with brain tumors, and numerical simulations were performed to evaluate the advantage of improved temporal resolution afforded by the technique.

RESULTS

In contrast to underestimations of cerebral blood volume (CBV) in tumors using the single-echo acquisition strategy, M2-EPI provided more plausible estimates of CBV. A quantitative evaluation showed higher estimated values of CBV and mean transit time in tumor tissues using M2-EPI (CBV: 3.08 ± 0.78 mL/100 g versus 1.56 ± 1.38 mL/100 g [P = .006]; mean transit time: 4.94 ± 1.17 seconds versus 1.83 ± 2.06 seconds [P = 0.033]). Numerical simulations showed that higher temporal resolution provided by M2-EPI was associated with more accurate estimates of cerebral blood flow, CBV, and permeability parameters.

CONCLUSION

The novel M2-EPI acquisition strategy for DSC imaging facilitates leakage-corrected perfusion measurements with additional permeability assessments and more accurate estimates of perfusion/permeability parameters, and may be used as a quantitative tool for the diagnosis, prognosis, and treatment monitoring of brain tumors.

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.

The effect of carotid artery stenting on capillary transit time heterogeneity in patients with carotid artery stenosis

Introduction

Carotid revascularisation improves haemodynamic compromise in cerebral circulation as an additional benefit to the primary goal of reducing future thromboembolic risk. We determined the effect of carotid artery stenting on cerebral perfusion and oxygenation using a perfusion-weighted MRI algorithm that is based on assessment of capillary transit-time heterogeneity together with other perfusion and metabolism-related metrics.

Patients and methods

A consecutive series of 33 patients were evaluated by dynamic susceptibility contrast perfusion-weighted MRI prior to and within 24 h of the endovascular procedure. The level of relative change induced by stenting, and relationship of these changes with respect to baseline stenosis degree were analysed.

Results

Stenting led to significant increase in cerebral blood flow (p < 0.001), and decrease in cerebral blood volume (p = 0.001) and mean transit time (p < 0.001); this was accompanied by reduction in oxygen extraction fraction (p < 0.001) and capillary transit-time heterogeneity (p < 0.001), but an overall increase in relative capillary transit-time heterogeneity (RTH: CTH divided by MTT; p = 0.008). No significant change was observed with respect to cerebral metabolic rate of oxygen. The median volume of tissue with MTT > 2s decreased from 24 ml to 12 ml (p = 0.009), with CTH > 2s from 29 ml to 19 ml (p = 0.041), and with RTH < 0.9 from 61 ml to 39 ml (p = 0.037) following stenting. These changes were correlated with the baseline degree of stenosis.Discussion: Stenting improved the moderate stage of haemodynamic compromise at baseline in our cohort. The decreased relative transit-time heterogeneity, which increases following stenting, is probably a reflection of decreased functional capillary density secondary to chronic hypoperfusion induced by the proximal stenosis.Conclusion: Carotid artery stenting, is not only important for prophylaxis of future vascular events, but also is critical for restoration of microvascular function in the cerebral tissue.

Comparison of ferumoxytol-based cerebral blood volume estimates using quantitative R1 and R2* relaxometry

PURPOSE

Cerebral perfusion is commonly assessed clinically with dynamic susceptibility contrast MRI using a bolus injection of gadolinium-based contrast agents, resulting in semi-quantitative values of cerebral blood volume (CBV). Steady-state imaging with ferumoxytol allows estimation of CBV with the potential for higher precision and accuracy. Prior CBV studies have focused on the signal disrupting T2* effects, but ferumoxytol also has high signal-enhancing T₁ relaxivity. The purpose of this study was to investigate and compare CBV estimation using T₁ and T2*, with the goal of understanding the contrast mechanisms and quantitative differences.

METHODS

Changes in R₁ (1/T₁ ) and R2* (1/ T2*) were measured after the administration of ferumoxytol using high-resolution quantitative approaches. Images were acquired at 3.0T and R₁ was estimated from an ultrashort echo time variable flip angle approach, while R2* was estimated from a multiple gradient echo sequence. Twenty healthy volunteers were imaged at two doses. CBV was derived and compared from relaxometry in gray and white matter using different approaches.

RESULTS

R₁ measurements showed a linear dependence of blood R₁ with respect to dose in large vessels, in contrast to the nonlinear dose-dependence of blood R2* estimates. In the brain parenchyma, R2* showed linear dose-dependency whereas R₁ showed nonlinearity. CBV calculations based on R2* changes in tissue and ferumoxytol blood concentration estimates based on R₁ relaxivity showed the lowest variability in our cohort.

CONCLUSIONS

CBV measurements were successfully derived using a combined approach of R₁ and R2* relaxometry. Magn Reson Med 79:3072-3081, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Dynamic Susceptibility Contrast MRI at 7 T: Tail-Scaling Analysis and Inferences About Field Strength Dependence

Dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI) following bolus injection of gadolinium contrast agent (CA) is widely used for the estimation of brain perfusion parameters such as cerebral blood volume (CBV), cerebral blood flow (CBF), and mean transit time (MTT) for both clinical and research purposes. Although it is predicted that DSC-MRI will have superior performance at high magnetic field strengths, to the best of our knowledge, there are no reports of 7 T DSC-MRI in the literature. It is plausible that the transfer of DSC-MRI to 7 T may be accompanied by increased R₂* relaxivity in tissue and a larger difference in ΔR₂*-versus-concentration relationships between tissue and large vessels. If not accounted for, this will subsequently result in apparent CBV and CBF estimates that are higher than those reported previously at lower field strengths. The aims of this study were therefore to assess the feasibility of 7 T DSC-MRI and to investigate the apparent field-strength dependence of CBV and CBF estimates. In total, 8 healthy volunteers were examined using DSC-MRI at 7 T. A reduced CA dose of 0.05 mmol/kg was administered to decrease susceptibility artifacts. CBV, CBF, and MTT maps were calculated using standard DSC-MRI tracer-kinetic theory. Subject-specific arterial partial volume correction factors were obtained using a tail-scaling approach. Compared with literature values obtained using the tail-scaling approach at 1.5 T and 3 T, the CBV and CBF values of the present study were found to be further overestimated. This observation is potentially related to an inferred field-strength dependence of transverse relaxivities, although issues related to the CA dose must also be considered.

Utilization of MR angiography in perfusion imaging for identifying arterial input function

OBJECTIVE

This research utilizes magnetic resonance angiography (MRA) to identify arterial locations during the parametric evaluation of concentration time curves (CTCs), and to prevent shape distortions in arterial input function (AIF).

MATERIALS AND METHODS

We carried out cluster analysis with the CTC parameters of voxels located within and around the middle cerebral artery (MCA). Through MRA, we located voxels that meet the AIF criteria and those with distorted CTCs. To minimize partial volume effect, we re-scaled the time integral of CTCs by the time integral of venous output function (VOF). We calculated the steady-state value to area under curve ratio (SS:AUC) of VOF and used it as a reference in selecting AIF. CTCs close to this reference value (selected AIF) and those far from it were used (eliminated AIF) to compute cerebral blood flow (CBF).

RESULTS

Eliminated AIFs were found to be either on or anterior to MCA, whereas selected AIFs were located superior, inferior, posterior, or anterior to MCA. If the SS:AUC of AIF was far from the reference value, CBF was either under- or over-estimated by a maximum of 41.1 ± 14.3 and 36.6 ± 19.2%, respectively.

CONCLUSION

MRA enables excluding voxels on the MCA during cluster analysis, and avoiding the risk of shape distortions.

Assessment of MRI contrast agent concentration by quantitative susceptibility mapping (QSM): application to estimation of cerebral blood volume during steady state

Objective

One major issue in dynamic susceptibility contrast MRI (DSC-MRI) is to accurately determine contrast agent (CA) concentration, since T2* relaxivity in vivo is generally unknown and varies between blood and tissue. In this study, quantitative susceptibility mapping (QSM) was used for quantification of CA concentration.

Materials and methods

A DSC-MRI protocol, including phase data acquisition, was applied to 20 healthy volunteers in a test–retest study. By selecting a CSF reference region of interest (ROI), the values of all QSM images were shifted to show no CA-induced change in CSF. CA concentration and cerebral blood volume (CBV) were estimated using shifted QSM data. CSF reference ROI optimization was evaluated by investigation of CBV repeatability. The CBV age dependence was analysed and tissue T2* relaxivity was estimated.

Results

The best repeatability of CBV, using an optimal CSF reference ROI, showed test-versus-retest correlations of r = 0.81 and r = 0.91 for white and grey matter, respectively. A slight CBV decrease with age was observed, and the estimated in vivo T2* relaxivity was 85 mM⁻¹s⁻¹.

Conclusion

Provided that a carefully selected CSF reference ROI is used to shift QSM image values, susceptibility information can be used to estimate concentration of contrast agent and to calculate CBV.

Electronic supplementary material

The online version of this article (doi:10.1007/s10334-017-0637-9) contains supplementary material, which is available to authorized users.

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.

Dynamic Susceptibility Contrast MR Imaging in Glioma: Review of Current Clinical Practice

Dynamic susceptibility contrast (DSC) MR imaging, a perfusion-weighted MR imaging technique typically used in neuro-oncologic applications for estimating the relative cerebral blood volume within brain tumors, has demonstrated much potential for determining prognosis, predicting therapeutic response, and assessing early treatment response of gliomas. This review highlights recent developments using DSC-MR imaging and emphasizes the need for technical standardization and validation in prospective studies in order for this technique to become incorporated into standard-of-care imaging for patients with brain tumors.

Automated Determination of Arterial Input Function for Dynamic Susceptibility Contrast MRI from Regions around Arteries Using Independent Component Analysis

Purpose. Quantitative cerebral blood flow (CBF) measurement using dynamic susceptibility contrast- (DSC-) MRI requires accurate estimation of the arterial input function (AIF). The present work utilized the independent component analysis (ICA) method to determine the AIF in the regions adjacent to the middle cerebral artery (MCA) by the alleviated confounding of partial volume effect. Materials and Methods. A series of spin-echo EPI MR scans were performed in 10 normal subjects. All subjects received 0.2 mmol/kg Gd-DTPA contrast agent. AIFs were calculated by two methods: (1) the region of interest (ROI) selected manually and (2) weighted average of each component selected by ICA (weighted-ICA). The singular value decomposition (SVD) method was then employed to deconvolve the AIF from the tissue concentration time curve to obtain quantitative CBF values. Results. The CBF values calculated by the weighted-ICA method were 41.1 ± 4.9 and 22.1 ± 2.3 mL/100 g/min for cortical gray matter (GM) and deep white matter (WM) regions, respectively. The CBF values obtained based on the manual ROIs were 53.6 ± 12.0 and 27.9 ± 5.9 mL/100 g/min for the same two regions, respectively. Conclusion. The weighted-ICA method allowed semiautomatic and straightforward extraction of the ROI adjacent to MCA. Through eliminating the partial volume effect to minimum, the CBF thus determined may reflect more accurate physical characteristics of the T2(⁎) signal changes induced by the contrast agent.

Assessment of a simplified spin and gradient echo (sSAGE) approach for human brain tumor perfusion imaging

The goal of this study was to validate a simplified spin- and gradient-echo (sSAGE) approach to obtain T₁-corrected dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI) data in a clinical brain tumor population. A five-echo SAGE sequence was used to acquire DSC-MRI data (n=8 patients, 3 primary glioma, and 5 brain metastases). The ΔR₂^⁎ and ΔR₂ time series obtained from a nonlinear fit of all echoes (SAGE) were compared to ΔR₂^⁎ and ΔR₂ time series obtained analytically (sSAGE) using three echoes (two GEs and one SE). Through the use of multiple echoes, both methods removed T₁ leakage effects from the ΔR₂^⁎ and ΔR₂ time series, and the sSAGE ΔR₂^⁎ and ΔR₂ time series were highly correlated with those from SAGE, with average correlations of 0.9. The resulting hemodynamic parameters included GE and SE cerebral blood volume (CBV), cerebral blood flow (CBF), mean vessel diameter (mVD), volume transfer constant (K^trans), and volume fraction of the extravascular extracellular space (v_e). For each metric, there was good correlation (>0.86) between sSAGE and SAGE, with no significant differences. The sSAGE method provides T₁-corrected GE and SE DSC-MRI parameters in an efficient and clinically feasible manner.

Improving Perfusion Measurement in DSC-MR Imaging with Multiecho Information for Arterial Input Function Determination

BACKGROUND AND PURPOSE

Clinical measurements of cerebral perfusion have been increasingly performed with multiecho dynamic susceptibility contrast-MR imaging techniques due to their ability to remove confounding T1 effects of contrast agent extravasation from perfusion quantification. However, to this point, the extra information provided by multiecho techniques has not been used to improve the process of estimating the arterial input function, which is critical to accurate perfusion quantification. The purpose of this study is to investigate methods by which multiecho DSC-MRI data can be used to automatically avoid voxels whose signal decreases to the level of noise when calculating the arterial input function.

MATERIALS AND METHODS

Here we compare postprocessing strategies for clinical multiecho DSC-MR imaging data to test whether arterial input function measures could be improved by automatically identifying and removing voxels exhibiting signal attenuation (truncation) artifacts.

RESULTS

In a clinical pediatric population, we found that the Pearson correlation coefficient between ΔR2* time-series calculated from each TE individually was a valuable criterion for automated estimation of the arterial input function, resulting in higher peak arterial input function values while maintaining smooth and reliable arterial input function shapes.

CONCLUSIONS

This work is the first to demonstrate that multiecho information may be useful in clinically important automatic arterial input function estimation because it can be used to improve automatic selection of voxels from which the arterial input function should be measured.

A linear mixed perfusion model for tissue partial volume correction of perfusion estimates in dynamic susceptibility contrast MRI: Impact on absolute quantification, repeatability, and agreement with pseudo-continuous arterial spin labeling

PURPOSE

The partial volume effect (PVE) is an important source of bias in brain perfusion measurements. The impact of tissue PVEs in perfusion measurements with dynamic susceptibility contrast MRI (DSC-MRI) has not yet been well established. The purpose of this study was to suggest a partial volume correction (PVC) approach for DSC-MRI and to study how PVC affects DSC-MRI perfusion results.

METHODS

A linear mixed perfusion model for DSC-MRI was derived and evaluated by way of simulations. Twenty healthy volunteers were scanned twice, including DSC-MRI, arterial spin labeling (ASL), and partial volume measurements. Two different algorithms for PVC were employed and assessed.

RESULTS

Simulations showed that the derived model had a tendency to overestimate perfusion values in voxels with high fractions of cerebrospinal fluid. PVC reduced the tissue volume dependence of DSC-MRI perfusion values from 44.4% to 4.2% in gray matter and from 55.3% to 14.2% in white matter. One PVC method significantly improved the voxel-wise repeatability, but PVC did not improve the spatial agreement between DSC-MRI and ASL perfusion maps.

CONCLUSION

Significant PVEs were found for DSC-MRI perfusion estimates, and PVC successfully reduced those effects. The findings suggest that PVC might be an important consideration for DSC-MRI applications. Magn Reson Med 77:2203-2214, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Dynamic susceptibility contrast perfusion MRI using phase-based venous output functions: comparison with pseudo-continuous arterial spin labelling and assessment of contrast agent concentration in large veins

OBJECTIVES

Contrast agent (CA) relaxivities are generally not well established in vivo, and the relationship between frequency/phase shift and magnetic susceptibility might be a useful alternative for CA quantification.

MATERIALS AND METHODS

Twenty volunteers (25-84 years old) were investigated using test-retest pre-bolus dynamic susceptibility-contrast (DSC) magnetic resonance imaging (MRI). The pre-bolus phase-based venous output function (VOF) time integral was used for arterial input function (AIF) rescaling. Resulting cerebral blood flow (CBF) data for grey matter (GM) were compared with pseudo-continuous arterial spin labelling (ASL). During the main bolus CA passage, the apparent spatial shift (pixel shift) of the superior sagittal sinus (seen in single-shot echo-planar imaging (EPI)) was converted to CA concentration and compared with conventional ΔR2*-based data and with a predicted phase-based VOF from the pre-bolus experiment.

RESULTS

The phase-based pre-bolus VOF resulted in a reasonable inter-individual GM CBF variability (coefficient of variation 28 %). Comparison with ASL CBF values implied a tissue R2*-relaxivity of 32 mM^-1 s^-1. Pixel-shift data at low concentrations (data not available at peak concentrations) were in reasonable agreement with the predicted phase-based VOF.

CONCLUSION

Susceptibility-induced phase shifts and pixel shifts are potentially useful for large-vein CA quantification. Previous predictions of a higher R2*-relaxivity in tissue than in blood were supported.

Response Assessment and Magnetic Resonance Imaging Issues for Clinical Trials Involving High-Grade Gliomas

There exist multiple challenges associated with the current response assessment criteria for high-grade gliomas, including the uncertain role of changes in nonenhancing T2 hyperintensity, and the phenomena of pseudoresponse and pseudoprogression in the setting of antiangiogenic and chemoradiation therapies, respectively. Advanced physiological magnetic resonance imaging (MRI), including diffusion and perfusion (dynamic susceptibility contrast MRI and dynamic contrast-enhanced MRI) sensitive techniques for overcoming response assessment challenges, has been proposed, with their own potential advantages and inherent shortcomings. Measurement variability exists for conventional and advanced MRI techniques, necessitating the standardization of image acquisition parameters in order to establish the utility of these imaging methods in multicenter trials for high-grade gliomas. This review chapter highlights the important features of MRI in clinical brain tumor trials, focusing on the current state of response assessment in brain tumors, advanced imaging techniques that may provide additional value for determining response, and imaging issues to be considered for multicenter trials.

Impact of Severe Extracranial ICA Stenosis on MRI Perfusion and Diffusion Parameters in Acute Ischemic Stroke

Purpose: The aim of this study was to investigate the impact of a coexisting internal carotid artery (ICA) stenosis on lesion volumes as well as diffusion and perfusion parameters in acute ischemic stroke resulting from middle cerebral artery (MCA) occlusion.

Material and methods: Magnetic resonance imaging data of 32 patients with MCA occlusion with or without additional ICA stenosis imaged within 4.5 h of symptom onset were analyzed. Both groups consisted of 16 patients. Acute diffusion lesions were semi-automatically segmented in apparent diffusion coefficient (ADC) MRI datasets. Perfusion maps of cerebral blood volume (CBV), cerebral blood flow, mean transit time and T_max were calculated using perfusion-weighted MRI datasets. Tissue-at-risk (TAR) volumes were generated by subtracting the ADC lesion from the hypoperfusion lesion defined by T_max >6 s. Median ADC and perfusion parameter values were extracted separately for the diffusion lesion and TAR and used for statistical analysis.

Results: No significant differences were found between the groups regarding the diffusion lesion and TAR volumes. Statistical analysis of diffusion and perfusion parameters revealed CBV as the only parameter with a significant difference (p = 0.009) contributing a small effect (η² = 0.11) to the group comparison with higher CBV values for the patient group with a coexisting ICA stenosis, while no significant effects were found for the other diffusion and perfusion parameters analyzed.

Conclusion: The results of this study suggest that a coexisting ICA stenosis does not have a strong effect on tissue status or perfusion parameters in acute stroke patients except for a moderate elevation of CBV. This may reflect improved collateral circulation or ischemic preconditioning in patients with a pre-existing proximal stenosis balancing impaired perfusion from the stenosis.

ANTONIA perfusion and stroke. A software tool for the multi-purpose analysis of MR perfusion-weighted datasets and quantitative ischemic stroke assessment

OBJECTIVES

The objective of this work is to present the software tool ANTONIA, which has been developed to facilitate a quantitative analysis of perfusion-weighted MRI (PWI) datasets in general as well as the subsequent multi-parametric analysis of additional datasets for the specific purpose of acute ischemic stroke patient dataset evaluation.

METHODS

Three different methods for the analysis of DSC or DCE PWI datasets are currently implemented in ANTONIA, which can be case-specifically selected based on the study protocol. These methods comprise a curve fitting method as well as a deconvolution-based and deconvolution-free method integrating a previously defined arterial input function. The perfusion analysis is extended for the purpose of acute ischemic stroke analysis by additional methods that enable an automatic atlas-based selection of the arterial input function, an analysis of the perfusion-diffusion and DWI-FLAIR mismatch as well as segmentation-based volumetric analyses.

RESULTS

For reliability evaluation, the described software tool was used by two observers for quantitative analysis of 15 datasets from acute ischemic stroke patients to extract the acute lesion core volume, FLAIR ratio, perfusion-diffusion mismatch volume with manually as well as automatically selected arterial input functions, and follow-up lesion volume. The results of this evaluation revealed that the described software tool leads to highly reproducible results for all parameters if the automatic arterial input function selection method is used.

CONCLUSION

Due to the broad selection of processing methods that are available in the software tool, ANTONIA is especially helpful to support image-based perfusion and acute ischemic stroke research projects.

Reliable estimation of capillary transit time distributions using DSC-MRI

The regional availability of oxygen in brain tissue is traditionally inferred from the magnitude of cerebral blood flow (CBF) and the concentration of oxygen in arterial blood. Measurements of CBF are therefore widely used in the localization of neuronal response to stimulation and in the evaluation of patients suspected of acute ischemic stroke or flow-limiting carotid stenosis. It was recently demonstrated that capillary transit time heterogeneity (CTH) limits maximum oxygen extraction fraction (OEF(max)) that can be achieved for a given CBF. Here we present a statistical approach for determining CTH, mean transit time (MTT), and CBF using dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI). Using numerical simulations, we demonstrate that CTH, MTT, and OEF(max) can be estimated with low bias and variance across a wide range of microvascular flow patterns, even at modest signal-to-noise ratios. Mean transit time estimated by singular value decomposition (SVD) deconvolution, however, is confounded by CTH. The proposed technique readily identifies malperfused tissue in acute stroke patients and appears to highlight information not detected by the standard SVD technique. We speculate that this technique permits the non-invasive detection of tissue with impaired oxygen delivery in neurologic disorders such as acute ischemic stroke and Alzheimer's disease during routine diagnostic imaging.

Evaluation of a multiple spin- and gradient-echo (SAGE) EPI acquisition with SENSE acceleration: applications for perfusion imaging in and outside the brain

Perfusion-based changes in MR signal intensity can occur in response to the introduction of exogenous contrast agents and endogenous tissue properties (e.g. blood oxygenation). MR measurements aimed at capturing these changes often implement single-shot echo planar imaging (ssEPI). In recent years ssEPI readouts have been combined with parallel imaging (PI) to allow fast dynamic multi-slice imaging as well as the incorporation of multiple echoes. A multiple spin- and gradient-echo (SAGE) EPI acquisition has recently been developed to allow measurement of transverse relaxation rate (R2 and R2(*)) changes in dynamic susceptibility contrast (DSC)-MRI experiments in the brain. With SAGE EPI, the use of PI can influence image quality, temporal resolution, and achievable echo times. The effect of PI on dynamic SAGE measurements, however, has not been evaluated. In this work, a SAGE EPI acquisition utilizing SENSE PI and partial Fourier (PF) acceleration was developed and evaluated. Voxel-wise measures of R2 and R2(*) in healthy brain were compared using SAGE EPI and conventional non-EPI multiple echo acquisitions with varying SENSE and PF acceleration. A conservative SENSE factor of 2 with PF factor of 0.73 was found to provide accurate measures of R2 and R2(*) in white (WM) (rR2=[0.55-0.79], rR2*=[0.47-0.71]) and gray (GM) matter (rR2=[0.26-0.59], rR2*=[0.39-0.74]) across subjects. The combined use of SENSE and PF allowed the first dynamic SAGE EPI measurements in muscle, with a SENSE factor of 3 and PF factor of 0.6 providing reliable relaxation rate estimates when compared to multi-echo methods. Application of the optimized SAGE protocol in DSC-MRI of high-grade glioma patients provided T1 leakage-corrected estimates of CBV and CBF as well as mean vessel diameter (mVD) and simultaneous measures of DCE-MRI parameters K(trans) and ve. Likewise, application of SAGE in a muscle reperfusion model allowed dynamic measures of R2', a parameter that has been shown to correlate with muscle oxy-hemoglobin saturation.

Technical considerations on the validity of blood oxygenation level-dependent-based MR assessment of vascular deoxygenation

A blood oxygenation level-dependent (BOLD)-based apparent relative oxygen extraction fraction (rOEF) as a semi-quantitative marker of vascular deoxygenation has recently been introduced in clinical studies of patients with glioma and stroke, yielding promising results. These rOEF measurements are based on independent quantification of the transverse relaxation times T2 and T2* and relative cerebral blood volume (rCBV). Simulations demonstrate that small errors in any of the underlying measures may result in a large deviation of the calculated rOEF. Therefore, we investigated the validity of such measurements. For this, we evaluated the quantitative measurements of T2 and T2* at 3 T in a gel phantom, in healthy subjects and in healthy tissue of patients with brain tumors. We calculated rOEF maps covering large portions of the brain from T2, T2* and rCBV [routinely measured in patients using dynamic susceptibility contrast (DSC)], and obtained rOEF values of 0.63 ± 0.16 and 0.90 ± 0.21 in healthy-appearing gray matter (GM) and white matter (WM), respectively; values of about 0.4 are usually reported. Quantitative T2 mapping using the fast, clinically feasible, multi-echo gradient spin echo (GRASE) approach yields significantly higher values than much slower multiple single spin echo (SE) experiments. Although T2* mapping is reliable in magnetically homogeneous tissues, uncorrectable macroscopic background gradients and other effects (e.g. iron deposition) shorten T2*. Cerebral blood volume (CBV) measurement using DSC and normalization to WM yields robust estimates of rCBV in healthy-appearing brain tissue; absolute quantification of the venous fraction of CBV, however, is difficult to achieve. Our study demonstrates that quantitative measurements of rOEF are currently biased by inherent difficulties in T2 and CBV quantification, but also by inadequacies of the underlying model. We argue, however, that standardized, reproducible measurements of apparent T2, T2* and rCBV may still allow the estimation of a meaningful apparent rOEF, which requires further validation in clinical studies.

Influence of blood/tissue differences in contrast agent relaxivity on tracer-based MR perfusion measurements

PURPOSE

Perfusion assessment by monitoring the transport of a tracer bolus depends critically on conversion of signal intensity into tracer concentration. Two main assumptions are generally applied for this conversion; (1) contrast agent relaxivity is identical in blood and tissue, (2) change in signal intensity depends only on the primary relaxation effect. The purpose of the study was to assess the validity and influence of these assumptions.

MATERIALS AND METHODS

Blood and cerebral tissue relaxivities r1, r2, and r2* for gadodiamide were measured in four pigs at 1.5 T. Gadolinium concentration was determined by inductively coupled plasma atomic emission spectroscopy. Influence of the relaxivities, secondary relaxation effects and choice of singular value decomposition (SVD) regularization threshold was studied by simulations.

RESULTS

In vivo relaxivities relative to blood concentration [in s(-1) mM(-1) for blood, gray matter (GM), white matter (WM)] were for r1 (2.614 ± 1.061, 0.010 ± 0.001, 0.004 ± 0.002), r2 (5.088 ± 0.952, 0.091 ± 0.008, 0.059 ± 0.014), and r2* (13.292 ± 3.928, 1.696 ± 0.157, 0.910 ± 0.139). Although substantial, by a nonparametric test for paired samples, the differences were not statistically significant. The GM to WM blood volume ratio was estimated to 2.6 ± 0.9 by r1, 1.6 ± 0.3 by r2, and 1.9 ± 0.2 by r2*. Secondary relaxation was found to reduce the tissue blood flow, as did the SVD regularization threshold.

CONCLUSION

Contrast agent relaxivity is not identical in blood and tissue leading to substantial errors. Further errors are introduced by secondary relaxation effects and the SVD regularization.

Quantification of cerebral perfusion using dynamic quantitative susceptibility mapping

PURPOSE

The purpose of this study is to develop a dynamic quantitative susceptibility mapping (QSM) technique with sufficient temporal resolution to map contrast agent concentration in cerebral perfusion imaging.

METHODS

The dynamic QSM used a multiecho three-dimensional (3D) spoiled gradient echo golden angle interleaved spiral sequence during contrast bolus injection. Four-dimensional (4D) space-time resolved magnetic field reconstruction was performed using the temporal resolution acceleration with constrained evolution reconstruction method. Deconvolution of the gadolinium-induced field was performed at each time point with the morphology enabled dipole inversion method to generate a 4D gadolinium concentration map, from which three-dimensional spatial distributions of cerebral blood volume and cerebral blood flow were computed.

RESULTS

Initial in vivo brain imaging demonstrated the feasibility of using dynamic QSM for generating quantitative 4D contrast agent maps and imaging three-dimensional perfusion. The cerebral blood flow obtained with dynamic QSM agreed with that obtained using arterial spin labeling.

CONCLUSION

Dynamic QSM can be used to perform 4D mapping of contrast agent concentration in contrast-enhanced magnetic resonance imaging. The perfusion parameters derived from this 4D contrast agent concentration map were in good agreement with those obtained using arterial spin labeling.

Reduction of arterial partial volume effects for improved absolute quantification of DSC-MRI perfusion estimates: comparison between tail scaling and prebolus administration

PURPOSE

To evaluate and mutually compare the tail-scaling approach and the prebolus administration concept for reduction of arterial partial volume effects (PVEs), because reproducible absolute quantification of cerebral blood flow (CBF) by dynamic susceptibility contrast magnetic resonance imaging (MRI) is often hampered by PVEs in the arterial input function (AIF) registration.

MATERIALS AND METHODS

Twenty healthy volunteers were scanned in a test-retest study with 7-20 days between investigations to examine the quantitative values and the repeatability of CBF estimates obtained from the tail-scaling and the prebolus administration approaches.

RESULTS

Average grey matter CBF was 80 ± 18 mL/100 g/min (mean ± SD) using tail-scaling and 56 ± 18 mL/100 g/min using prebolus administration. The intraclass correlation coefficient was 0.52 for the tail-scaling approach and 0.86 for the prebolus administration concept.

CONCLUSION

Both correction methods resulted in considerably reduced arterial PVEs, leading to quantitative estimates of perfusion approaching those typically obtained by other perfusion modalities. The CBF estimates obtained using the prebolus administration concept showed superior repeatability. Potential sources of uncertainty in the tail-scaling approach include the use of venous concentration curves influenced by PVEs or by geometric distortions (ie, vessel pixel shifts) in the steady-state period.

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

The systematic investigation of susceptibility-induced contrast in MRI is important to better interpret the influence of microvascular and microcellular morphology on DSC-MRI derived perfusion data. Recently, a novel computational approach called the Finite Perturber Method (FPM), which enables the study of susceptibility-induced contrast in MRI arising from arbitrary microvascular morphologies in 3D has been developed. However, the FPM has lower efficiency in simulating water diffusion especially for complex tissues. In this work, an improved computational approach that combines the FPM with a matrix-based finite difference method (FDM), which we call the Finite Perturber the Finite Difference Method (FPFDM), has been developed in order to efficiently investigate the influence of vascular and extravascular morphological features on susceptibility-induced transverse relaxation. The current work provides a framework for better interpreting how DSC-MRI data depend on various phenomena, including contrast agent leakage in cancerous tissues and water diffusion rates. In addition, we illustrate using simulated and micro-CT extracted tissue structures the improved FPFDM along with its potential applications and limitations.