Optimal location for arterial input function measurements near the middle cerebral artery in first-pass perfusion MRI

The Choroid Plexus as an Alternative Locus for the Identification of the Arterial Input Function for Calculating Cerebral Perfusion Metrics Using MRI

BACKGROUND AND PURPOSE

MR imaging-based cerebral perfusion metrics can be obtained by tracing the passage of a bolus of contrast through the microvasculature of the brain parenchyma. Thus, the temporal signal pattern of the contrast agent is typically measured over a large artery such as the MCA to generate the arterial input function. The largest intracranial arteries in the brain may not always be suitable for selecting the arterial input function due to skull base susceptibility artifacts or reduced size from steno-occlusive disease. Therefore, a suitable alternative arterial input function window would be useful. The choroid plexus is a highly vascular tissue composed essentially of arterialized blood vessels and acellular stroma with low metabolic requirements relative to its blood flow and may be a suitable alternative to identify the arterial input function.

MATERIALS AND METHODS

We studied 8 healthy participants and 7 patients with gliomas who were administered a bolus of gadolinium. We selected an arterial input function from both the left and right M1 segments of the MCA and both lateral ventricles of the choroid plexus for each participant. We compared the changes in the T2* signal and the calculated resting perfusion metrics using the arterial input functions selected from the MCA and choroid plexus.

RESULTS

We found no systematic difference between resting perfusion metrics in GM and WM when calculated using an arterial input function from the MCA or choroid plexus in the same participant.

CONCLUSIONS

The choroid plexus provides an alternative location from which an arterial input function may be sampled when a suitable measure over an MCA is not available.

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.

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.

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.

Multi-stage automated local arterial input function selection in perfusion MRI

OBJECTIVE

Cerebral blood flow (CBF) quantification using dynamic-susceptibility contrast MRI can be achieved via model-independent deconvolution, with local arterial input function (AIF) deconvolution methods identifying multiple arterial regions with unique corresponding arterial input functions. The clinical application of local AIF methods necessitates an efficient and fully automated solution. To date, such local AIF methods have relied on the computation of a singular surrogate measure of bolus arrival time or custom arterial scoring functions to infer vascular supply origins. This paper aims to introduce a new local AIF method that alternatively utilises a multi-stage approach to perform AIF selection.

MATERIAL AND METHODS

A fully automated, multi-stage local AIF method is proposed, leveraging both signal-based cluster analysis and priority flooding to define arterial regions and their corresponding vascular supply origins. The introduced method was applied to data from four patients with cerebrovascular disease who showed significant artefacts when using a prevailing automated local AIF method.

RESULTS

The immediately apparent image artefacts found using the pre-existing method due to poor AIF selection were found to be absent when using the proposed method.

CONCLUSION

The results suggest the proposed solution provides a more robust approach to perfusion quantification than currently available fully automated local AIF methods.

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.

Low-dose T1W DCE-MRI for early time points perfusion measurement in patients with intracranial tumors: A pilot study applying the microsphere model to measure absolute cerebral blood flow

BACKGROUND

Previous studies have measured cerebral blood flow (CBF) with DSC-MRI using an "early time points" (ET) method based on microsphere theory.

PURPOSE

To develop and assess a new ET method for absolute CBF estimation using low-dose high-temporal (LDHT) T1W-DCE-MRI.

STUDY TYPE

Retrospective cohort study.

SUBJECTS

Seven patients with sporadic vestibular schwannoma (VS) who underwent test-retest imaging; one patient with glioblastoma multiforme (GBM) imaged pretreatment; and 12 neurofibromatosis type 2 (NF2) patients undergoing bevacizumab treatment, imaged pre- and 90 days posttreatment.

FIELD STRENGTH/SEQUENCE

LDHT-DCE-MRI was performed at 1.5 and 3.0T, using 3D spoiled gradient echo with phase cycling. DSC-MRI performed in one patient, using 3D echo-shifted multi-shot echo-planar imaging (PRESTO) at 3T.

ASSESSMENT

Through Monte Carlo simulations, CBF estimation using three newly developed average contrast agent concentration (AC) -based methods (ACrPK, ACrMG, ACcomb), was compared against conventional maximum gradient (MG) approaches, at varying Rician noise levels. Reproducibility and applicability of the ACcomb method was assessed in our sporadic-VS/GBM/NF2 patient cohort, respectively.

STATISTICAL TESTS

Reproducibility was measured using test-retest coefficient of variation (CoV). Pre- and posttreatment CBF values were compared using paired t-test with Bonferroni correction.

RESULTS

Monte Carlo stimulations demonstrated that AC-based methods, particularly ACcomb, offered superior accuracy to conventional MG approaches. Overall test-retest CoV using the ACcomb method was 5.76 in normal-appearing white matter (NAWM). The new ACcomb method produced gray matter/white matter CBF estimates in the NF2 patient cohort of 55.9 ± 13.9/25.8 ± 3.5 on day 0; compared with 155.6 ± 17.2/128.4 ± 29.1 for the classical MG method. There was a moderate (10% using ACcomb and ACrPK) increase in CBF of NAWM 90 days post therapy (P = 0.03 and 0.005).

DATA CONCLUSION

Our new AC-based method of CBF estimation offers excellent reproducibility, and displays more accuracy in both Monte Carlo analysis and clinical data application, than conventional MG-based approaches.

LEVEL OF EVIDENCE

1 Technical Efficacy: Stage 4 J. MAGN. RESON. IMAGING 2018;48:543-557.

Arterial input function in a dedicated slice for cerebral perfusion measurements in humans

OBJECT

We aimed to modify our previously published method for arterial input function measurements for evaluation of cerebral perfusion (dynamic susceptibility contrast MRI) such that it can be applied in humans in a clinical setting.

MATERIALS AND METHODS

Similarly to our previous work, a conventional measurement sequence for dynamic susceptibility contrast MRI is extended with an additional measurement slice at the neck. Measurement parameters at this slice were optimized for the blood signal (short echo time, background suppression, magnitude and phase images). Phase-based evaluation of the signal in the carotid arteries is used to obtain quantitative arterial input functions.

RESULTS

In all pilot measurements, quantitative arterial input functions were obtained. The resulting absolute perfusion parameters agree well with literature values (gray and white matter mean values of 46 and 24 mL/100 g/min, respectively, for cerebral blood flow and 3.0% and 1.6%, respectively, for cerebral blood volume).

CONCLUSIONS

The proposed method has the potential to quantify arterial input functions in the carotid arteries from a direct measurement without any additional normalization.

Slice-accelerated gradient-echo echo planar imaging dynamic susceptibility contrast-enhanced MRI with blipped CAIPI: effect of increasing temporal resolution

PURPOSE

To assess the influence of high temporal resolution on the perfusion measurements and image quality of perfusion maps, by applying simultaneous-multi-slice acquisition (SMS) dynamic susceptibility contrast-enhanced (DSC) magnetic resonance imaging (MRI).

MATERIALS AND METHODS

DSC-MRI data using SMS gradient-echo echo planar imaging sequences in 10 subjects with no intracranial abnormalities were retrospectively analyzed. Three additional data sets with temporal resolution of 1.0, 1.5, and 2.0 s were created from the raw data sets of 0.5 s. Cerebral blood flow (CBF), cerebral blood volume, mean transit time (MTT), time to peak (TTP), and time to maximum tissue residue function (T _max) measurements were performed, as was visual perfusion map analysis. The perfusion parameter for temporal resolution of 0.5 s (reference) was compared with each synthesized perfusion parameter.

RESULTS

CBF, MTT, and TTP values at temporal resolutions of 1.5 and 2.0 s differed significantly from the reference. The image quality of MTT, TTP, and T _max maps deteriorated with decreasing temporal resolution.

CONCLUSION

The temporal resolution of DSC-MRI influences perfusion parameters and SMS DSC-MRI provides better image quality for MTT, TTP, and T _max maps.

Effects of arterial input function selection on kinetic parameters in brain dynamic contrast-enhanced MRI

PURPOSE

Kinetic parameters derived from dynamic contrast-enhanced MRI (DCE-MRI) were suggested as a possible instrument for multi-parametric lesion characterization, but have not found their way into clinical practice yet due to inconsistent results. The quantification is heavily influenced by the definition of an appropriate arterial input functions (AIF). Regarding brain tumor DCE-MRI, there are currently several co-existing methods to determine the AIF frequently including different brain vessels as sources. This study quantitatively and qualitatively analyzes the impact of AIF source selection on kinetic parameters derived from commonly selected AIF source vessels compared to a population-based AIF model.

MATERIAL AND METHODS

74 patients with brain lesions underwent 3D DCE-MRI. Kinetic parameters [transfer constants of contrast agent efflux and reflux K^trans and k_ep and, their ratio, v_e, that is used to measure extravascular-extracellular volume fraction and plasma volume fraction v_p] were determined using extended Tofts model in 821 ROI from 4 AIF sources [the internal carotid artery (ICA), the closest artery to the lesion, the superior sagittal sinus (SSS), the population-based Parker model]. The effect of AIF source alteration on kinetic parameters was evaluated by tissue type selective intra-class correlation (ICC) and capacity to differentiate gliomas by WHO grade [area under the curve analysis (AUC)].

RESULTS

Arterial AIF more often led to implausible v_e >100% values (p<0.0001). AIF source alteration rendered different absolute kinetic parameters (p<0.0001), except for k_ep. ICC between kinetic parameters of different AIF sources and tissues were variable (0.08-0.87) and only consistent >0.5 between arterial AIF derived kinetic parameters. Differentiation between WHO III and II glioma was exclusively possible with v_p derived from an AIF in the SSS (p=0.03; AUC 0.74).

CONCLUSION

The AIF source has a significant impact on absolute kinetic parameters in DCE-MRI, which limits the comparability of kinetic parameters derived from different AIF sources. The effect is also tissue-dependent. The SSS appears to be the best choice for AIF source vessel selection in brain tumor DCE-MRI as it exclusively allowed for WHO grades II/III and III/IV glioma distinction (by v_p) and showed the least number of implausible v_e values.

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.

Predicting Cerebral Hyperperfusion Syndrome Following Superficial Temporal Artery to Middle Cerebral Artery Bypass based on Intraoperative Perfusion-Weighted Magnetic Resonance Imaging

Moyamoya disease leads to the formation of stenosis in the cerebrovasculature. A superficial temporal artery to middle cerebral artery (STA-MCA) bypass is an effective treatment for the disease, yet it is usually associated with postoperative cerebral hyperperfusion syndrome (CHS). This study aimed to evaluate cerebral hemodynamic changes immediately after surgery and assess whether a semiquantitative analysis of an intraoperative magnetic resonance perfusion-weighted image (PWI) is useful for predicting postoperative CHS. Fourteen patients who underwent the STA-MCA bypass surgery were included in this study. An atlas-based registration method was employed for studying hemodynamics in different cerebral regions. Pre- versus intraoperative and group-wise comparisons were conducted to evaluate the hemodynamic changes. A postoperative increase in relative cerebral blood flow (CBF) at the terminal MCA territory (P = 0.035) and drop in relative mean-time-transit at the central MCA territory (P = 0.012) were observed in all patients. However, a significant raise in the increasing ratio of relative-CBF at the terminal MCA territory was only found in CHS patients (P = 0.023). The cerebrovascular changes of the patients after revascularization treatment were confirmed. Intraoperative PWI might be helpful in predicting the change in relative-CBF at MCA terminal territory which might indicate a risk of CHS.

ASFNR recommendations for clinical performance of MR dynamic susceptibility contrast perfusion imaging of the brain

MR perfusion imaging is becoming an increasingly common means of evaluating a variety of cerebral pathologies, including tumors and ischemia. In particular, there has been great interest in the use of MR perfusion imaging for both assessing brain tumor grade and for monitoring for tumor recurrence in previously treated patients. Of the various techniques devised for evaluating cerebral perfusion imaging, the dynamic susceptibility contrast method has been employed most widely among clinical MR imaging practitioners. However, when implementing DSC MR perfusion imaging in a contemporary radiology practice, a neuroradiologist is confronted with a large number of decisions. These include choices surrounding appropriate patient selection, scan-acquisition parameters, data-postprocessing methods, image interpretation, and reporting. Throughout the imaging literature, there is conflicting advice on these issues. In an effort to provide guidance to neuroradiologists struggling to implement DSC perfusion imaging in their MR imaging practice, the Clinical Practice Committee of the American Society of Functional Neuroradiology has provided the following recommendations. This guidance is based on review of the literature coupled with the practice experience of the authors. While the ASFNR acknowledges that alternate means of carrying out DSC perfusion imaging may yield clinically acceptable results, the following recommendations should provide a framework for achieving routine success in this complicated-but-rewarding aspect of neuroradiology MR imaging practice.

Automatic determination of the arterial input function in dynamic susceptibility contrast MRI: comparison of different reproducible clustering algorithms

Introduction

Arterial input function (AIF) plays an important role in the quantification of cerebral hemodynamics. The purpose of this study was to select the best reproducible clustering method for AIF detection by comparing three algorithms reported previously in terms of detection accuracy and computational complexity.

Methods

First, three reproducible clustering methods, normalized cut (Ncut), hierarchy (HIER), and fast affine propagation (FastAP), were applied independently to simulated data which contained the true AIF. Next, a clinical verification was performed where 42 subjects participated in dynamic susceptibility contrast MRI (DSC-MRI) scanning. The manual AIF and AIFs based on the different algorithms were obtained. The performance of each algorithm was evaluated based on shape parameters of the estimated AIFs and the true or manual AIF. Moreover, the execution time of each algorithm was recorded to determine the algorithm that operated more rapidly in clinical practice.

Results

In terms of the detection accuracy, Ncut and HIER method produced similar AIF detection results, which were closer to the expected AIF and more accurate than those obtained using FastAP method; in terms of the computational efficiency, the Ncut method required the shortest execution time.

Conclusion

Ncut clustering appears promising because it facilitates the automatic and robust determination of AIF with high accuracy and efficiency.

Perfusion magnetic resonance imaging: a comprehensive update on principles and techniques

Perfusion is a fundamental biological function that refers to the delivery of oxygen and nutrients to tissue by means of blood flow. Perfusion MRI is sensitive to microvasculature and has been applied in a wide variety of clinical applications, including the classification of tumors, identification of stroke regions, and characterization of other diseases. Perfusion MRI techniques are classified with or without using an exogenous contrast agent. Bolus methods, with injections of a contrast agent, provide better sensitivity with higher spatial resolution, and are therefore more widely used in clinical applications. However, arterial spin-labeling methods provide a unique opportunity to measure cerebral blood flow without requiring an exogenous contrast agent and have better accuracy for quantification. Importantly, MRI-based perfusion measurements are minimally invasive overall, and do not use any radiation and radioisotopes. In this review, we describe the principles and techniques of perfusion MRI. This review summarizes comprehensive updated knowledge on the physical principles and techniques of perfusion MRI.

Correcting for large vessel contamination in dynamic susceptibility contrast perfusion MRI by extension to a physiological model of the vasculature

PURPOSE

Dynamic susceptibility contrast (DSC) perfusion images are contaminated by contributions from macro vascular signal arising from contrast agent within the larger arteries that do not contribute directly to the local tissue perfusion.

METHODS

A vascular model of the DSC perfusion signal was extended by the inclusion of a macro vascular component based on the arterial input function. This was implemented within a Bayesian nonlinear model-fitting algorithm that included automatic model complexity reduction. Results were compared with existing methods that do not correct for the macro vascular contamination as well as an independent component analysis technique.

RESULTS

Macro vascular signal was identified in regions corresponding to larger arteries resulting in reductions by 62% within a region of interest identified with high contamination. Whereas visually similar results could be achieved with independent component analysis, it resulted in reductions in global tissue perfusion and was not robustly applicable to patient data.

CONCLUSION

A model-based strategy for correction of macro vascular contamination in DSC perfusion images is feasible, although the model may currently need extending to more accurately account for nonlinear effects of contrast agent in large arteries. Magn Reson Med 74:280-290, 2015. © 2014 Wiley Periodicals, Inc.

Evaluating the feasibility of an agglomerative hierarchy clustering algorithm for the automatic detection of the arterial input function using DSC-MRI

During dynamic susceptibility contrast-magnetic resonance imaging (DSC-MRI), it has been demonstrated that the arterial input function (AIF) can be obtained using fuzzy c-means (FCM) and k-means clustering methods. However, due to the dependence on the initial centers of clusters, both clustering methods have poor reproducibility between the calculation and recalculation steps. To address this problem, the present study developed an alternative clustering technique based on the agglomerative hierarchy (AH) method for AIF determination. The performance of AH method was evaluated using simulated data and clinical data based on comparisons with the two previously demonstrated clustering-based methods in terms of the detection accuracy, calculation reproducibility, and computational complexity. The statistical analysis demonstrated that, at the cost of a significantly longer execution time, AH method obtained AIFs more in line with the expected AIF, and it was perfectly reproducible at different time points. In our opinion, the disadvantage of AH method in terms of the execution time can be alleviated by introducing a professional high-performance workstation. The findings of this study support the feasibility of using AH clustering method for detecting the AIF automatically.

Perfusion MRI: the five most frequently asked clinical questions

OBJECTIVE

This article addresses questions that radiologists frequently ask when planning, performing, processing, and interpreting MRI perfusion studies in CNS imaging.

CONCLUSION

Perfusion MRI is a promising tool in assessing stroke, brain tumors, and neurodegenerative diseases. Most of the impediments that have limited the use of per-fusion MRI can be overcome to allow integration of these methods into modern neuroimaging protocols.

Arterial input function in perfusion MRI: a comprehensive review

Cerebral perfusion, also referred to as cerebral blood flow (CBF), is one of the most important parameters related to brain physiology and function. The technique of dynamic-susceptibility contrast (DSC) MRI is currently the most commonly used MRI method to measure perfusion. It relies on the intravenous injection of a contrast agent and the rapid measurement of the transient signal changes during the passage of the bolus through the brain. Central to quantification of CBF using this technique is the so-called arterial input function (AIF), which describes the contrast agent input to the tissue of interest. Due to its fundamental role, there has been a lot of progress in recent years regarding how and where to measure the AIF, how it influences DSC-MRI quantification, what artefacts one should avoid, and the design of automatic methods to measure the AIF. The AIF is also directly linked to most of the major sources of artefacts in CBF quantification, including partial volume effect, bolus delay and dispersion, peak truncation effects, contrast agent non-linearity, etc. While there have been a number of good review articles on DSC-MRI over the years, these are often comprehensive but, by necessity, with limited in-depth discussion of the various topics covered. This review article covers in greater depth the issues associated with the AIF and their implications for perfusion quantification using DSC-MRI.

The 39 steps: evading error and deciphering the secrets for accurate dynamic susceptibility contrast MRI

Dynamic susceptibility contrast (DSC) MRI is the most commonly used MRI method to assess cerebral perfusion and other related haemodynamic parameters. Although the technique is well established and used routinely in clinical centres, there are still many problems that impede accurate perfusion quantification. In this review article, we present 39 steps which guide the reader through the theoretical principles, practical decisions, potential problems, current limitations and latest advances in DSC-MRI. The 39 steps span the collection, analysis and interpretation of DSC-MRI data, expounding issues and possibilities relating to the contrast agent, the acquisition of DSC-MRI data, data pre-processing, the contrast concentration-time course, the arterial input function, deconvolution, common perfusion parameters, post-processing possibilities, patient studies, absolute versus relative quantification and automated analysis methods.

T2-*weighted perfusion MRI

T2*-weighted perfusion MRI is based on the so-called "first passage" approach: the modifications in the T2-weighted MRI signal are followed during the first passage of a bolus of contrast agent. The pixel-by-pixel analysis of the curves is used to obtain parametric maps (time of arrival, time of the peak, mean transit time, relative volume and blood flow). Further analysis, with deconvolution by arterial input function (concentration of contrast agent in the blood), helps improve the quantification. It is possible to pre-inject a small dose of contrast agent to limit the impact of the extravasation of the contrast agent.

Effects of blood ΔR2* non-linearity on absolute perfusion quantification using DSC-MRI: comparison with Xe-133 SPECT

PURPOSE

To evaluate whether a non-linear blood ΔR2*-versus-concentration relationship improves quantitative cerebral blood flow (CBF) estimates obtained by dynamic susceptibility contrast (DSC) MRI in a comparison with Xe-133 SPECT CBF in healthy volunteers.

MATERIAL AND METHODS

Linear as well as non-linear relationships between ΔR2* and contrast agent concentration in blood were applied to the arterial input function (AIF) and the venous output function (VOF) from DSC-MRI. To reduce partial volume effects in the AIF, the arterial time integral was rescaled using a corrected VOF scheme.

RESULTS

Under the assumption of proportionality between the two modalities, the relationship CBF(MRI)=0.58CBF(SPECT) (r=0.64) was observed using the linear relationship and CBF(MRI)=0.51CBF(SPECT) (r=0.71) using the non-linear relationship.

DISCUSSION

A smaller ratio of the VOF time integral to the AIF time integral and a somewhat better correlation between global DSC-MRI and Xe-133 SPECT CBF estimates were observed using the non-linear relationship. The results did not, however, confirm the superiority of one model over the other, potentially because realistic AIF signal data may well originate from a combination of blood and surrounding tissue.

Evaluating quantitative approaches to dynamic susceptibility contrast MRI among carotid endarterectomy patients

PURPOSE

To evaluate two dynamic susceptibility contrast (DSC) quantification methods in symptomatic carotid artery disease patients undergoing carotid endarterectomy (CEA) surgery by comparing methods directly and assessing the reliability of each method in the hemisphere contralateral to surgery.

MATERIALS AND METHODS

Absolute cerebral blood flow (CBF) and volume (CBV) was calculated in putamen and sensorimotor gray matter of 17 patients using two methods: 1) The Bookend method that scales relative DSC images to CBV values calculated from the ratio of pre- and postcontrast T1-weighted images, and 2) the Tail-scaling method that uses the ratio of area under the tails of the venous and arterial concentration time-courses to scale the DSC images.

RESULTS

There was a positive correlation between the methods with significant correlation post-CEA (P < 0.035). Intersession correlation was greater when using the Tail-scaling method contralateral to surgery (P < 0.004).

CONCLUSION

We have demonstrated correlation between methods that is significant after surgery and have found that the Tail-scaling method produces better test-retest reliability than our implementation of the Bookend method. Results from this study suggest that DSC has the potential to measure hemodynamic changes after endarterectomy and future work is required to establish clinical value.

MR perfusion imaging in acute ischemic stroke

Magnetic resonance (MR) perfusion imaging offers the potential for measuring brain perfusion in acute stroke patients, at a time when treatment decisions based on these measurements may affect outcomes dramatically. Rapid advancements in both acute stroke therapy and perfusion imaging techniques have resulted in continuing redefinition of the role that perfusion imaging should play in patient management. This review discusses the basic pathophysiology of acute stroke, the utility of different kinds of perfusion images, and research on the continually evolving role of MR perfusion imaging in acute stroke care.

Feasibility of semiquantitative liver perfusion assessment by ferucarbotran bolus injection in double-contrast hepatic MRI

PURPOSE

To evaluate the feasibility of semiquantitative measurement of liver perfusion from analysis of ferucarbotran induced signal-dynamics in double-contrast liver MR-imaging (DC-MRI).

MATERIALS AND METHODS

In total 31 patients (21 men; 58 ± 10 years) including 18 patients with biopsy proven liver cirrhosis prospectively underwent clinically indicated DC-MRI at 1.5 Tesla (T) with dynamic T2-weighted gradient-echo imaging after ferucarbotran bolus injection. Breathing artefacts in tissue and input time curves were reduced by Savitzky-Golay-filtering and semiquantitative perfusion maps were calculated using a model free approach. Hepatic blood flow index (HBFI) and splenic blood flow index (SBFI) were determined by normalization of arbitrary perfusion values to the perfusion of the erector spinae muscle resulting in a semiquantitative perfusion measure.

RESULTS

In 30 of 31 patients the evaluated protocol could successfully be applied. Mean HBF was 7.7 ± 2.46 (range, 4.6-12.8) and mean SBF was 13.20 ± 2.57 (range, 8.5-17.8). A significantly lower total HBF was seen in patients with cirrhotic livers as compared to patients with noncirrhotic livers (P < 0.05). In contrast, similar SBF was observed in cirrhotic and noncirrhotic patients (P = 0.11).

CONCLUSION

Capturing the signal dynamics during bolus injection of ferucarbotran in DC-MRI of the liver allows for semiquantitative assessment of hepatic perfusion that may be helpful for a more precise characterisation of liver cirrhosis and focal liver lesions.

Cerebral perfusion changes in migraineurs: a voxelwise comparison of interictal dynamic susceptibility contrast MRI measurements

INTRODUCTION

The increased risk of cerebro- and cardiovascular disease in migraineurs may be the consequence of a systemic condition affecting whole body vasculature. At cerebrovascular level, this may be reflected by interictal global or regional cerebral perfusion abnormalities. Whether focal perfusion changes occur during interictal migraine has not been convincingly demonstrated.

METHODS

We measured brain perfusion with dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI) in 29 interictal female migraineurs (12 migraine with aura (MA), 17 migraine without aura (MO)), and 16 female controls. Perfusion maps were compared between these groups with a voxelwise (p < 0.001, uncorrected, minimum cluster size 20 voxels) and a region-of-interest approach.

RESULTS

In whole brain voxelwise analyses interictal hyperperfusion was observed in the left medial frontal gyrus in migraineurs and in the inferior and middle temporal gyrus in MO patients, in comparison with controls. Hypoperfusion was seen in the postcentral gyrus and in the inferior temporal gyrus in MA patients and in the inferior frontal gyrus in MO patients. Additional focal sites of hyperperfusion were noted in subgroups based on attack frequency and disease history. Region-of-interest analyses of the pons, hypothalamus, occipital lobe, and cerebellum did not show interictal perfusion differences between migraineurs and controls.

CONCLUSIONS

We conclude that interictal migraine is characterized by discrete areas of hyper- and hypoperfusion unspecific for migraine pathophysiology and not explaining the increased vulnerability of particular brain regions for cerebrovascular damage.

Combined spin- and gradient-echo perfusion-weighted imaging

In this study, a spin- and gradient-echo echo-planar imaging (SAGE EPI) MRI pulse sequence is presented that allows simultaneous measurements of gradient-echo and spin-echo dynamic susceptibility-contrast perfusion-weighted imaging data. Following signal excitation, five readout trains were acquired using spin- and gradient-echo echo-planar imaging, all of them with echo times of less than 100 ms. Contrast agent concentrations in brain tissue were determined based on absolute R2* and R(2) estimates rather than relative changes in the signals of individual echo trains, producing T(1)-independent dynamic susceptibility-contrast perfusion-weighted imaging data. Moreover, this acquisition technique enabled vessel size imaging through the simultaneous quantification of R2* and R(2), without an increase in acquisition time. In this work, the concepts of SAGE EPI pulse sequence and results in stroke and tumor imaging are presented. Overall, SAGE EPI combined the advantages of higher sensitivity to contrast agent passage of gradient-echo perfusion-weighted imaging with better microvascular selectivity of spin-echo perfusion-weighted imaging.

Heterogeneity in malignant gliomas: a magnetic resonance analysis of spatial distribution of metabolite changes and regional blood volume

First-pass contrast-enhanced dynamic perfusion imaging provides information about the regional cerebral blood volume (rCBV), an increase of which indicates neovascularization. MR spectroscopic imaging informs about metabolite changes in brain tumors, with elevated choline (Cho) values revealing cell proliferation and density, and the glial metabolite creatine (Cr) representing high-energy storage. This study investigates metabolite changes within the tumor voxel of maximal rCBV value (rCBVmax). Anatomically coregistered parameter maps of rCBV, Cho and Cr were evaluated in 36 patients with primary or recurrent WHO grade III or IV gliomas. Apart from Cho and Cr values within the voxel of rCBVmax (Choperf, Crperf), the maximal Cho and Cr values of the tumor tissue were recorded (Chomax, Crmax). The correlation between these parameters was analyzed with Spearman’s rho test while a binomial test was performed to check whether Chomax = Choperf and Crmax = Crperf. We found that, in 29 of the 36 patients, neither Cho nor Cr had their maxima in the voxel of rCBVmax (Choperf, Crperf < Chomax, Crmax, P < 0.001). However, Choperf was highly correlated with Chomax (r = 0.76, P < 0.001) and Crperf with Crmax (r = 0.47, P < 0.001). Further Choperf correlated with Crperf (r = 0.55, P < 0.001). Neither of the spectroscopic parameters (Chomax, Crmax, Choperf, Crperf,) correlated with rCBVmax. In conclusion, in WHO grade III and IV gliomas the voxel with maximal rCBV often differs from the voxel with the maximal Cho and Cr, indicating the spatial divergence between neovascularization and tumor cell proliferation, cell density and glial processes. However, tCho and tCr changes within the area of neovascularization are positively correlated with the maximal increase within the tumor tissue. These results demonstrate aspects of regional tumor heterogeneity as characterized by different MR modalities that, apart from histopathological grading might be crucial for neurosurgical biopsy as well as for antiangiogenetic and future molecular therapies.

T1- and T2*-dominant extravasation correction in DSC-MRI: part I--theoretical considerations and implications for assessment of tumor hemodynamic properties

We present a novel contrast agent (CA) extravasation-correction method based on analysis of the tissue residue function for assessment of multiple hemodynamic parameters. The method enables semiquantitative determination of the transfer constant and can be used to distinguish between T(1)- and T(2)(*)-dominant extravasation effects, while being insensitive to variations in tissue mean transit time (MTT). Results in 101 patients with confirmed glioma suggest that leakage-corrected absolute cerebral blood volume (CBV) values obtained with the proposed method provide improved overall survival prediction compared with normalized CBV values combined with an established leakage-correction method. Using a standard gradient-echo echo-planar imaging sequence, ∼60% and 10% of tumors with detectable CA extravasation mainly exhibited T(1)- and T(2)(*)-dominant leakage effects, respectively. The remaining 30% of leaky tumors had mixed T(1)- and T(2)(*)-dominant effects. Using an MTT-sensitive correction method, our results show that CBV is underestimated when tumor MTT is significantly longer than MTT in the reference tissue. Furthermore, results from our simulations suggest that the relative contribution of T(1)- versus T(2)(*)-dominant extravasation effects is strongly dependent on the effective transverse relaxivity in the extravascular space and may thus be a potential marker for cellular integrity and tissue structure.

Perfusion MRI using dynamic-susceptibility contrast MRI: quantification issues in patient studies

OBJECTIVES

Measurement of perfusion accurately, noninvasively, and with good spatial resolution offers the chance to characterize abnormal tissue in many clinical conditions. Dynamic-susceptibility contrast (DSC) MRI, also known as bolus-tracking MRI, is a dynamic MRI method to measure perfusion and other related hemodynamic parameters. This review article describes the principles involved in perfusion quantification using DSC-MRI as well as discusses the main issues affecting its quantification in patient studies.

CONCLUSIONS

It is shown that DSC-MRI is a very powerful technique that provides important information regarding cerebral hemodynamics. The relatively high contrast-to-noise ratio, fast acquisition, and wealth of information available have made DSC-MRI the most commonly used MRI technique for the rapid assessment of the brain hemodynamics in clinical investigations. While very important advances have been achieved in the last 2 decades, there are still some remaining limitations that users should be aware of to avoid misinterpretation of the findings and to make the most of the invaluable information provided by perfusion MRI.

Evaluation of signal formation in local arterial input function measurements of dynamic susceptibility contrast MRI

Correct arterial input function (AIF) measurements in dynamic susceptibility contrast-MRI are crucial for quantification of the hemodynamic parameters. Often a single global AIF is selected near a large brain-feeding artery. Alternatively, local AIF measurements aim for voxel-specific AIFs from smaller arteries. Because local AIFs are measured higher in the arterial-tree, it is assumed that these will reflect the true input of the microvasculature much better. However, do the measured local AIFs reflect the true concentration-time curves of small arteries? To answer this question, in vivo data were used to evaluate local AIF candidates selected based on two different types of angiograms. For interpretation purposes, a 3D numerical model that simulated partial-volume effects in local AIF measurements was created and the simulated local AIFs were compared to the ground truth. The findings are 2-fold. First, the in vivo data showed that the shape-characteristics of local AIFs are similar to the shape-characteristics of gray matter concentration-time curves. Second, these findings are supported by the simulations showing broadening of the measured local AIFs compared to the ground truth. These findings are suggesting that local AIF measurements do not necessarily reflect the true concentration-time curve in small arteries.

Phase-based arterial input function measurements for dynamic susceptibility contrast MRI

In dynamic susceptibility contrast perfusion MRI, arterial input function (AIF) measurements using the phase of the MR signal are traditionally performed inside an artery. However, phase-based AIF selection is also feasible in tissue surrounding an artery such as the middle cerebral artery, which runs approximately perpendicular to B(0) since contrast agents also induce local field changes in tissue surrounding the artery. The aim of this study was to investigate whether phase-based AIF selection is better performed in tissue just outside the middle cerebral artery than inside the artery. Additionally, phase-based AIF selection was compared to magnitude-based AIF selection. Both issues were studied theoretically and using numerical simulations, producing results that were validated using phantom experiments. Finally, an in vivo experiment was performed to illustrate the feasibility of phase-based AIF selection. Three main findings are presented: first, phase-based AIF selections are better made in tissue outside the middle cerebral artery, rather than within the middle cerebral artery, since in the latter approach partial-volume effects affect the shape of the estimated AIF. Second, optimal locations for phase-based AIF selection are similar for different clinical dynamic susceptibility contrast MRI sequences. Third, phase-based AIF selection allows more locations in tissue to be chosen that show the correct AIF than does magnitude-based AIF selection.

New criterion to aid manual and automatic selection of the arterial input function in dynamic susceptibility contrast MRI

Dynamic susceptibility contrast-MRI requires an arterial input function (AIF) to obtain cerebral blood flow, cerebral blood volume, and mean transit time. The current AIF selection criteria discriminate venous, capillary, and arterial profiles based on shape and timing characteristics of the first passage. Unfortunately, partial volume effects can lead to shape errors in the bolus passage, including a narrower and higher peak, which might be selected as a "correct" AIF. In this study, a new criterion is proposed that detects shape errors based on tracer kinetic principles for computing cerebral blood volume. This criterion uses the ratio of the steady-state value to the area-under-the-curve of the first passage, which should result in an equal value for tissue and arterial responses. By using a reference value from tissue, partial volume effects-induced shape errors of the AIF measurement can be detected. Different factors affecting the ratio were investigated using simulations. These showed that the new criterion should only be used in studies with T(1) -insensitive acquisition. In vivo data were used to evaluate the proposed approach. The data showed that the new criterion enables detection of shape errors, although false positives do occur, which could be easily avoided when combined with current AIF selection criteria.

Prognostic value of perfusion MR imaging in patients with oligodendroglioma: A survival study

OBJECTIVE

The purpose of this study was to evaluate retrospectively whether cerebral blood volume measurement based on pretreatment perfusion MRI is a prognostic biomarker for survival in patients with oligodendroglioma or mixed oligoastrocytoma.

PATIENTS AND METHODS

Between 1998 and 2004, 54 patients (23 females and 31 males), aged 21-73 years, with oligodendroglioma (or mixed tumour) were examined prior to beginning treatment with dynamic susceptibility-weighted contrast (DSC) perfusion MRI during gadolinium first-pass. The relative cerebral blood volume (rCBV) was calculated by dividing the measurement within the tumour by the measurement of the normal-appearing contralateral region. Patients were classified in two groups, grade A and grade B, according to the Saint-Anne Hospital classification and followed-up clinically and by means of MRI until their death or for a minimum of 5 years. Patients were also classified in grade II and grade III-IV, according to the World Health Organisation (WHO) classification, and were analysed with the same methods. Age, sex, treatment, tumour grade, contrast agent uptake, and rCBV were tested using survival curves with Kaplan-Meier's method, and their differences were analysed using the log-rank test.

RESULTS

In this population, median survival was 3 years. A rCBV threshold value of 2.2 was validated as a prognostic factor, for survival in these patients with oligodendrogliomas. Age, sex, contrast uptake, and maximum rCBV were found to be prognostic factors in univariate analysis. Multivariate analysis revealed that tumour grade (grade A/grade B), rCBV, age, and sex were prognostic factors independent of the other factors. The tumour grade according to the WHO classification (II versus III-IV) was also detected as an independent prognostic factor.

CONCLUSION

Pretreatment rCBV measured by DSC perfusion MRI was found to be a prognostic factor for survival in patients with oligodendroglioma or mixed tumour, by using the Saint-Anne Hospital classification, which separate the IIB from the IIA.

A fully automated method for quantitative cerebral hemodynamic analysis using DSC-MRI

Dynamic susceptibility contrast (DSC)-based perfusion analysis from MR images has become an established method for analysis of cerebral blood volume (CBV) in glioma patients. To date, little emphasis has, however, been placed on quantitative perfusion analysis of these patients, mainly due to the associated increased technical complexity and lack of sufficient stability in a clinical setting. The aim of our study was to develop a fully automated analysis framework for quantitative DSC-based perfusion analysis. The method presented here generates quantitative hemodynamic maps without user interaction, combined with automatic segmentation of normal-appearing cerebral tissue. Validation of 101 patients with confirmed glioma after surgery gave mean values for CBF, CBV, and MTT, extracted automatically from normal-appearing whole-brain white and gray matter, in good agreement with literature values. The measured age- and gender-related variations in the same parameters were also in agreement with those in the literature. Several established analysis methods were compared and the resulting perfusion metrics depended significantly on method and parameter choice. In conclusion, we present an accurate, fast, and automatic quantitative perfusion analysis method where all analysis steps are based on raw DSC data only.

Improving dynamic susceptibility contrast MRI measurement of quantitative cerebral blood flow using corrections for partial volume and nonlinear contrast relaxivity: A xenon computed tomographic comparative study

PURPOSE

To test whether dynamic susceptibility contrast MRI-based CBF measurements are improved with arterial input function (AIF) partial volume (PV) and nonlinear contrast relaxivity correction, using a gold-standard CBF method, xenon computed tomography (xeCT).

MATERIALS AND METHODS

Eighteen patients with cerebrovascular disease underwent xeCT and MRI within 36 h. PV was measured as the ratio of the area under the AIF and the venous output function (VOF) concentration curves. A correction was applied to account for the nonlinear relaxivity of bulk blood (BB). Mean CBF was measured with both techniques and regression analyses both within and between patients were performed.

RESULTS

Mean xeCT CBF was 43.3 +/- 13.7 mL/100g/min (mean +/- SD). BB correction decreased CBF by a factor of 4.7 +/- 0.4, but did not affect precision. The least-biased CBF measurement was with BB but without PV correction (45.8 +/- 17.2 mL/100 g/min, coefficient of variation [COV] = 32%). Precision improved with PV correction, although absolute CBF was mildly underestimated (34.3 +/- 10.8 mL/100 g/min, COV = 27%). Between patients correlation was moderate even with both corrections (R = 0.53).

CONCLUSION

Corrections for AIF PV and nonlinear BB relaxivity improve bolus MRI-based CBF maps. However, there remain challenges given the moderate between-patient correlation, which limit diagnostic confidence of such measurements in individual patients.

Reliable perfusion maps in stroke MRI using arterial input functions derived from distal middle cerebral artery branches

BACKGROUND AND PURPOSE

Perfusion imaging is widely used in stroke, but there are uncertainties with regard to the choice of arterial input function (AIF). Two important aspects of AIFs are signal-to-noise ratio and bolus-related signal drop, ideally close to 63%. We hypothesized that distal branches of the middle cerebral artery (MCA) provide higher quality of AIF compared with proximal branches.

METHODS

Over a period of 3 months, consecutive patients with suspected stroke were examined in a 3-T MRI scanner within 24 hours of symptom onset. AIFs were selected manually in M1, M2, and M3 branches of the MCA contralateral to the suspected ischemia. Signal-to-noise ratio and bolus-related signal drop were analyzed. Perfusion maps were created for every patient and mean values at the insular level as well as relative ranges were compared.

RESULTS

Mean age of 132 included patients (53 females) was 67.3 years (SD, 14.9) and median National Institutes of Health Stroke Scale was 3 (interquartile range [IQR] 0 to 6). For further analyses, 4 patients were excluded due to discontinuation of scanning or insufficient bolus arrival (signal drop <15%). Median signal-to-noise ratio was highest in M3 branches (36.41; IQR, 29.29 to 43.58). Median signal-to-noise ratio in M2 branches was intermediate (27.54; IQR, 20.78 to 34.00) and median signal-to-noise ratio in M1 was low (12.40; IQR, 9.11 to 17.15). Using AIFs derived from M1 and M2 branches of the MCA median signal drop was 77% (IQR, 72% to 82%) and 78% (IQR, 73% to 83%), respectively. Signal drop was significantly reduced when AIF was selected in M3 branches with a median of 72% (IQR, 63% to 77%; P<0.01). Highest variability of 3456 perfusion maps was found in those derived from M1.

CONCLUSIONS

The level of AIF selection in the MCA has a major impact on reliability and even quantitative parameters of perfusion maps. For better comparison of perfusion maps, the AIF should be defined by selection of distal branches of the MCA contralateral to the suspected ischemia. In future trials involving perfusion imaging, the MCA segment used for the AIF should be specified.