Contrast-agent phase effects: an experimental system for analysis of susceptibility, concentration, and bolus input function kinetics

The Direction of Flow and Phase-encoding Schemes Effects on Signal Intensity in T1-weighted Inversion Recovery TurboFLASH Images

Background

It is needed to minimize the effect of flow direction on the desired area, such as arterial input function (AIF) in magnetic resonance imaging (MRI).

Objective

The current study aimed to investigate the effect of flow direction on different velocities (0-80.39 cm/s) for the strength of the signal intensity (SI) at the linear phase-encoding (LPE) and the center out phase-encoding (COPE) schemes and to recommend the best flow direction in a selected slice and scheme for absolute perfusion measurement by inversion recovery T1-weighted turbo fast low-angle shot (TurboFLASH) MR images.

Material and Methods

In this experimental study, the flow rates were measured using a flow phantom, and the signal intensity (SI) was measured at the two opposite flow directions in the Z-axis perpendicular to the coronal image at a concentration of 0.8 mmol/L of gadolinium-diethylenetriaminepantaacetic acid (Gd-DTPA) by using the LPE and COPE schemes.

Results

The increase in velocity along with the growth in SI and inflow affected the use of LPE and COPE acquisitions in both directions. The velocity of the arterial input function is needed to calculate the inflow correction factor by using two schemes in two opposite flow directions to investigate perfusion.

Conclusion

The COPE scheme was better than the LPE scheme in measuring perfusion since the velocity and direction of blood flow affect SI less.

Free-breathing motion-informed locally low-rank quantitative 3D myocardial perfusion imaging

PURPOSE

To propose respiratory motion-informed locally low-rank reconstruction (MI-LLR) for robust free-breathing single-bolus quantitative 3D myocardial perfusion CMR imaging. Simulation and in-vivo results are compared to locally low-rank (LLR) and compressed sensing reconstructions (CS) for reference.

METHODS

Data were acquired using a 3D Cartesian pseudo-spiral in-out k-t undersampling scheme (R = 10) and reconstructed using MI-LLR, which encompasses two stages. In the first stage, approximate displacement fields are derived from an initial LLR reconstruction to feed a motion-compensated reference system to a second reconstruction stage, which reduces the rank of the inverse problem. For comparison, data were also reconstructed with LLR and frame-by-frame CS using wavelets as sparsifying transform ( ℓ 1 $$ {\ell}_1 $$ -wavelet). Reconstruction accuracy relative to ground truth was assessed using synthetic data for realistic ranges of breathing motion, heart rates, and SNRs. In-vivo experiments were conducted in healthy subjects at rest and during adenosine stress. Myocardial blood flow (MBF) maps were derived using a Fermi model.

RESULTS

Improved uniformity of MBF maps with reduced local variations was achieved with MI-LLR. For rest and stress, intra-volunteer variation of absolute and relative MBF was lower in MI-LLR (±0.17 mL/g/min [26%] and ±1.07 mL/g/min [33%]) versus LLR (±0.19 mL/g/min [28%] and ±1.22 mL/g/min [36%]) and versus ℓ 1 $$ {\ell}_1 $$ -wavelet (±1.17 mL/g/min [113%] and ±6.87 mL/g/min [115%]). At rest, intra-subject MBF variation was reduced significantly with MI-LLR.

CONCLUSION

The combination of pseudo-spiral Cartesian undersampling and dual-stage MI-LLR reconstruction improves free-breathing quantitative 3D myocardial perfusion CMR imaging under rest and stress condition.

Phantom-based quality assurance for multicenter quantitative MRI in locally advanced cervical cancer

BACKGROUND AND PURPOSE

A wide variation of MRI systems is a challenge in multicenter imaging biomarker studies as it adds variation in quantitative MRI values. The aim of this study was to design and test a quality assurance (QA) framework based on phantom measurements, for the quantitative MRI protocols of a multicenter imaging biomarker trial of locally advanced cervical cancer.

MATERIALS AND METHODS

Fifteen institutes participated (five 1.5 T and ten 3 T scanners). Each institute optimized protocols for T2, diffusion-weighted imaging, T1, and dynamic contrast-enhanced (DCE-)MRI according to system possibilities, institutional preferences and study-specific constraints. Calibration phantoms with known values were used for validation. Benchmark protocols, similar on all systems, were used to investigate whether differences resulted from variations in institutional protocols or from system variations. Bias, repeatability (%RC), and reproducibility (%RDC) were determined. Ratios were used for T2 and T1 values.

RESULTS

The institutional protocols showed a range in bias of 0.88-0.98 for T2 (median %RC = 1%; %RDC = 12%), -0.007 to 0.029 × 10^-3 mm²/s for the apparent diffusion coefficient (median %RC = 3%; %RDC = 18%), and 0.39-1.29 for T1 (median %RC = 1%; %RDC = 33%). For DCE a nonlinear vendor-specific relation was observed between measured and true concentrations with magnitude data, whereas the relation was linear when phase data was used.

CONCLUSION

We designed a QA framework for quantitative MRI protocols and demonstrated for a multicenter trial for cervical cancer that measurement of consistent T2 and apparent diffusion coefficient values is feasible despite protocol differences. For DCE-MRI and T1 mapping with the variable flip angle method, this was more challenging.

Phantom Validation of DCE-MRI Magnitude and Phase-Based Vascular Input Function Measurements

Accurate, patient-specific measurement of arterial input functions (AIF) may improve model-based analysis of vascular permeability. This study investigated factors affecting AIF measurements from magnetic resonance imaging (MRI) magnitude (AIFMAGN) and phase (AIFPHA) signals, and compared them against computed tomography (CT) (AIFCT), under controlled conditions relevant to clinical protocols using a multimodality flow phantom. The flow phantom was applied at flip angles of 20° and 30°, flow rates (3-7.5 mL/s), and peak bolus concentrations (0.5-10 mM), for in-plane and through-plane flow. Spatial 3D-FLASH signal and variable flip angle T1 profiles were measured to investigate in-flow and radiofrequency-related biases, and magnitude- and phase-derived Gd-DTPA concentrations were compared. MRI AIF performance was tested against AIFCT via Pearson correlation analysis. AIFMAGN was sensitive to imaging orientation, spatial location, flip angle, and flow rate, and it grossly underestimated AIFCT peak concentrations. Conversion to Gd-DTPA concentration using T1 taken at the same orientation and flow rate as the dynamic contrast-enhanced acquisition improved AIFMAGN accuracy; yet, AIFMAGN metrics remained variable and significantly reduced from AIFCT at concentrations above 2.5 mM. AIFPHA performed equivalently within 1 mM to AIFCT across all tested conditions. AIFPHA, but not AIFMAGN, reported equivalent measurements to AIFCT across the range of tested conditions. AIFPHA showed superior robustness.

Improved repeatability of dynamic contrast-enhanced MRI using the complex MRI signal to derive arterial input functions: a test-retest study in prostate cancer patients

Purpose

The arterial input function (AIF) is a major source of uncertainty in tracer kinetic (TK) analysis of dynamic contrast‐enhanced (DCE)‐MRI data. The aim of this study was to investigate the repeatability of AIFs extracted from the complex signal and of the resulting TK parameters in prostate cancer patients.

Methods

Twenty‐two patients with biopsy‐proven prostate cancer underwent a 3T MRI exam twice. DCE‐MRI data were acquired with a 3D spoiled gradient echo sequence. AIFs were extracted from the magnitude of the signal (AIF_MAGN), phase (AIF_PHASE), and complex signal (AIF_COMPLEX). The Tofts model was applied to extract K^trans, k_ep and v_e. Repeatability of AIF curve characteristics and TK parameters was assessed with the within‐subject coefficient of variation (wCV).

Results

The wCV for peak height and full width at half maximum for AIF_COMPLEX (7% and 8%) indicated an improved repeatability compared to AIF_MAGN (12% and 12%) and AIF_PHASE (12% and 7%). This translated in lower wCV values for K^trans (11%) with AIF_COMPLEX in comparison to AIF_MAGN (24%) and AIF_PHASE (15%). For k_ep, the wCV was 16% with AIF_MAGN, 13% with AIF_PHASE, and 13% with AIF_COMPLEX.

Conclusion

Repeatability of AIF_PHASE and AIF_COMPLEX is higher than for AIF_MAGN, resulting in a better repeatability of TK parameters. Thus, use of either AIF_PHASE or AIF_COMPLEX improves the robustness of quantitative analysis of DCE‐MRI in prostate cancer.

Dynamic Contrast-Enhanced MRI

Dynamic contrast-enhanced MRI in pre-clinical imaging allows the in-vivo monitoring of vascular, physiological properties in normal and diseased tissue. There is considerable variation in the methods employed owing to the different questions that can be asked and answered about the physiologic alterations as well as morphologic changes in tissue. Here we review the typical decisions in the design and execution of a dynamic contrast-enhanced MRI study in mice although the findings can easily be transferred to other species. Emphasis is placed on highlighting the many pitfalls that wait for the unaware pre-clinical MRI practitioner and that go often unmentioned in the abundant literature dealing with dynamic contrast-enhanced MRI in animal models.

Impact of contrast agent injection duration on dynamic contrast-enhanced MRI quantification in prostate cancer

The volume transfer constant K^trans , which describes the leakage of contrast agent (CA) from vasculature into tissue, is the most commonly reported quantitative parameter for dynamic contrast-enhanced (DCE-) MRI. However, the variation in reported K^trans values between studies from different institutes is large. One of the primary sources of uncertainty is quantification of the arterial input function (AIF). The aim of this study is to determine the influence of the CA injection duration on the AIF and tracer kinetic analysis (TKA) parameters (i.e. K^trans , k_ep and v_e ). Thirty-one patients with prostate cancer received two DCE-MRI examinations with an injection duration of 5 s in the first examination and a prolonged injection duration in the second examination, varying between 7.5 s and 30 s. The DCE examination was carried out on a 3.0 T MRI scanner using a transversal T₁ -weighted 3D spoiled gradient echo sequence (300 s duration, dynamic scan time of 2.5 s). Data of 29 of the 31 were further analysed. AIFs were determined from the phase signal in the left and right femoral arteries. K^trans , k_ep and v_e were estimated with the standard Tofts model for regions of healthy peripheral zone and tumour tissue. We observed a significantly smaller peak height and increased width in the AIF for injection durations of 15 s and longer. However, we did not find significant differences in K^trans , k_ep or v_e for the studied injection durations. The study demonstrates that the TKA parameters K^trans , k_ep and v_e , measured in the prostate, do not show a significant change as a function of injection duration.

Dynamic Contrast-Enhanced MRI to Study Atherosclerotic Plaque Microvasculature

Rupture of a vulnerable atherosclerotic plaque of the carotid artery is an important underlying cause of clinical ischemic events, such as stroke. Abundant microvasculature has been identified as an important aspect contributing to plaque vulnerability. Plaque microvasculature can be studied non-invasively with dynamic contrast-enhanced (DCE-)MRI in animals and patients. In recent years, several DCE-MRI studies have been published evaluating the association between microvasculature and other key features of plaque vulnerability (e.g., inflammation and intraplaque hemorrhage), as well as the effects of novel therapeutic interventions. The present paper reviews this literature, focusing on DCE-MRI methods of acquisition and analysis of atherosclerotic plaques, the current state and future potential of DCE-MRI in the evaluation of plaque microvasculature in clinical and preclinical settings.

Phase-based vascular input function: Improved quantitative DCE-MRI of atherosclerotic plaques

PURPOSE

Quantitative pharmacokinetic modeling of dynamic contrast-enhanced (DCE)-MRI can be used to assess atherosclerotic plaque microvasculature, which is an important marker of plaque vulnerability. Purpose of the present study was (1) to compare magnitude- versus phase-based vascular input functions (m-VIF vs ph-VIF) used in pharmacokinetic modeling and (2) to perform model calculations and flow phantom experiments to gain more insight into the differences between m-VIF and ph-VIF.

METHODS

Population averaged m-VIF and ph-VIFs were acquired from 11 patients with carotid plaques and used for pharmacokinetic analysis in another 17 patients. Simulations, using the Bloch equations and the MRI scan geometry, and flow phantom experiments were performed to determine the effect of local blood velocity on the magnitude and phase signal enhancement.

RESULTS

Simulations and flow phantom experiments revealed that flow within the lumen can lead to severe underestimation of m-VIF, while this is not the case for the ph-VIF. In line, the peak concentration of the m-VIF is significantly lower than ph-VIF (p < 0.001), in vivo. Quantitative model parameters for m- and ph-VIF differed in absolute values but were moderate to strongly correlated with each other [K(trans) Spearman's ρ > 0.93 (p < 0.001) and vp Spearman's ρ > 0.58 (p < 0.05)].

CONCLUSIONS

m-VIF is strongly influenced by local blood velocity, which leads to underestimation of the contrast medium concentration. Therefore, it is advised to use ph-VIF for DCE-MRI analysis of carotid plaques for accurate quantification.

Dynamic contrast-enhanced MRI in mice at high field: estimation of the arterial input function can be achieved by phase imaging

PURPOSE

Quantitative dynamic contrast-enhanced MRI requires an accurate arterial input function (AIF). At high field, increased susceptibility effects and decreased longitudinal relaxivity of contrast agents lead to predominant T2* effects in blood vessels, producing a dip in signal during passage of the contrast agent bolus. This study determined phase-derived AIFs in mice at 11.7 T.

METHODS

AIFs were measured in aorta/vena cava for five FBV/N mice and in iliac arteries/veins for five NMRI mice with a fast low angle shot sequence, simultaneously with tumor imaging (temporal resolution: 1.19 s). Gadoterate was injected into the tail vein as a bolus (0.286 mmol Gd/kg). An in vitro study was also performed to calculate the relationship between ΔΦ and gadolinium concentration.

RESULTS

The phantom system confirmed the linear relationship between measured ΔΦ and gadolinium concentration. In vivo, a dip in arterial magnitude signal made it impossible to quantify the AIF. With phase imaging, a clear quantifiable bolus peak was obtained; peak measured concentration in plasma was 4.9 ± 0.9 mM for FBV/N mice and 8.0 ± 0.6 mM for NMRI mice, close to the expected concentration of 6.8 mM.

CONCLUSION

Phase imaging seems to be an appropriate means to measure the AIF of mice at high field.

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.

Voxelwise comparison of perfusion parameters estimated using dynamic contrast enhanced (DCE) computed tomography and DCE-magnetic resonance imaging in locally advanced cervical cancer

PURPOSE

Dynamic contrast enhanced (DCE) imaging has gained interest as an imaging modality for assessment of tumor characteristics and response to cancer treatment. However, for DCE-magnetic resonance imaging (MRI) tissue contrast enhancement may vary depending on imaging sequence and temporal resolution. The aim of this study is to compare DCE-MRI to DCE-computed tomography (DCE-CT) as the gold standard.

MATERIAL AND METHODS

Thirteen patients with advanced cervical cancer were scanned once prior to chemo-radiation and during chemo-radiation with DCE-CT and -MRI in immediate succession. A total of 22 paired DCE-CT and -MRI scans were acquired for comparison. Kinetic modeling using the extended Tofts model was applied to both image series. Furthermore the similarity of the spatial distribution was evaluated using a Γ analysis. The correlation between the two imaging techniques was evaluated using Pearson's correlation and the parameter means were compared using a Student's t-test (p < 0.05).

RESULTS

A significant positive correlation between DCE-CT and -MRI was found for all kinetic parameters. The results showing the best correlation with the DCE-CT-derived parameters were obtained using a population-based input function for MRI. The median Pearson's correlations were: volume transfer constant K(trans) (r = 0.9), flux rate constant kep (r = 0.77), extracellular volume fraction ve (r = 0.58) and blood plasma volume fraction vp (r = 0.83). All quantitative parameters were found to be significantly different as estimated by DCE-CT and -MRI. The Γ analysis in normalized maps revealed that 45% of the voxels failed to find a voxel with the corresponding value allowing for an uncertainty of 3 mm in position and 3% in value (Γ3,3). By reducing the criteria, the Γ-failure rates were: Γ3,5 (37% failure), Γ3,10 (26% failure) and at Γ3,15 (19% failure).

CONCLUSION

Good to excellent correlations but significant bias was found between DCE-CT and -MRI. Both the Pearson's correlation and the Γ analysis proved that the spatial information was similar when analyzing the two sets of DCE data using the extended Tofts model. Improvement of input function sampling is needed to improve kinetic quantification using DCE-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.

Principles of magnetic resonance imaging

This article aims to provide an educational document of magnetic resonance imaging principles for applied biomedical users of the technology. Basic principles are illustrated using simple experimental models on a preclinical imaging system.

Phase-based arterial input functions in humans applied to dynamic contrast-enhanced MRI: potential usefulness and limitations

OBJECT

Phase-based arterial input functions (AIFs) provide a promising alternative to standard magnitude-based AIFs, for example, because inflow effects are avoided. The usefulness of phase-based AIFs in clinical dynamic contrast-enhanced MRI (DCE-MRI) was investigated, and relevant pitfalls and sources of uncertainty were identified.

MATERIALS AND METHODS

AIFs were registered from eight human subjects on, in total, 21 occasions. AIF quality was evaluated by comparing AIFs from right and left internal carotid arteries and by assessing the reliability of blood plasma volume estimates.

RESULTS

Phase-based AIFs yielded an average bolus peak of 3.9 mM and a residual concentration of 0.37 mM after 3 min, (0.033 mmol/kg contrast agent injection). The average blood plasma volume was 2.7% when using the AIF peak in the estimation, but was significantly different (p < 0.0001) and less physiologically reasonable when based on the AIF tail concentration. Motion-induced phase shifts and accumulation of contrast agent in background tissue regions were identified as main sources of uncertainty.

CONCLUSION

Phase-based AIFs are a feasible alternative to magnitude AIFs, but sources of errors exist, making quantification difficult, especially of the AIF tail. Improvement of the technique is feasible and also required for the phase-based AIF approach to reach its full potential.

Determination of the venous output function from MR signal phase: feasibility for quantitative DCE-MRI in human brain

For dynamic contrast-enhanced MRI studies in the human brain, it is useful to measure the venous output function (VOF). The purpose of this work was to explore the feasibility of measuring the VOF using the MR signal phase (in absolute units of gadolinium concentration) in the superior sagittal sinus. Phantom experiments were performed to validate the technique for different superior sagittal sinus angles (theta = 0-48 degrees relative to the main magnetic field), different curvatures (straight or radius = 45 mm), and different spatial resolutions (2.2-5.5 mm, to study partial-volume effects). Additionally, the technique was tested on three patients. The phantom experimental results (echo time = 5.5 ms, theta <or= 21 degrees) agreed with theoretical predictions to within 10%. For the patient studies, the measured VOFs had reasonable amplitude and shape characteristics and the patients' superior sagittal sinus angles (<15 degrees) and curvatures (radii approximately 40 mm) were within the range explored with phantoms. Our results suggest that partial-volume contributions to the VOF will be <5% and that the VOF can be evaluated in vivo to within 10% error. In conclusion, it is highly feasible to use MR signal phase to measure the VOF in the superior sagittal sinus for human dynamic contrast-enhanced MRI.

Quantitative susceptibility map reconstruction from MR phase data using bayesian regularization: validation and application to brain imaging

The diagnosis of many neurologic diseases benefits from the ability to quantitatively assess iron in the brain. Paramagnetic iron modifies the magnetic susceptibility causing magnetic field inhomogeneity in MRI. The local field can be mapped using the MR signal phase, which is discarded in a typical image reconstruction. The calculation of the susceptibility from the measured magnetic field is an ill-posed inverse problem. In this work, a bayesian regularization approach that adds spatial priors from the MR magnitude image is formulated for susceptibility imaging. Priors include background regions of known zero susceptibility and edge information from the magnitude image. Simulation and phantom validation experiments demonstrated accurate susceptibility maps free of artifacts. The ability to characterize iron content in brain hemorrhage was demonstrated on patients with cavernous hemangioma. Additionally, multiple structures within the brain can be clearly visualized and characterized. The technique introduces a new quantitative contrast in MRI that is directly linked to iron in the brain.

On the dual contrast enhancement mechanism in frequency-selective inversion-recovery magnetic resonance angiography (IRON-MRA)

The susceptibility of blood changes after administration of a paramagnetic contrast agent that shortens T(1). Concomitantly, the resonance frequency of the blood vessels shifts in a geometry-dependent way. This frequency change may be exploited for incremental contrast generation by applying a frequency-selective saturation prepulse prior to the imaging sequence. The dual origin of vascular enhancement depending first on off-resonance and second on T(1) lowering was investigated in vitro, together with the geometry dependence of the signal at 3T. First results obtained in an in vivo rabbit model are presented.

Susceptibility-weighted imaging: clinical angiographic applications

By combining filtered phase and magnitude information to create a novel and intrinsic source of contrast, susceptibility-weighted imaging (SWI) has shown great promise in clinical angiography and venography. SWI has contributed to new insights into traumatic brain injury, the role of calcification in atherosclerosis, and the possible relationship between blood settling and deep venous thrombosis. A further contribution from SWI to deep venous thrombosis research (and also stroke) involves its application to the noninvasive measurement of oxygen saturation in the brain and in other tissues. Altogether, SWI offers manifold and diverse avenues for further research using angiographic and venographic techniques.

In vivo quantification of contrast agent concentration using the induced magnetic field for time-resolved arterial input function measurement with MRI

For pharmacokinetic modeling of tissue physiology, there is great interest in measuring the arterial input function (AIF) from dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) using paramagnetic contrast agents. Due to relaxation effects, the measured signal is a nonlinear function of the injected contrast agent concentration and depends on sequence parameters, system calibration, and time-of-flight effects, making it difficult to accurately measure the AIF during the first pass. Paramagnetic contrast agents also affect susceptibility and modify the magnetic field in proportion to their concentration. This information is contained in the MR signal phase which is discarded in a typical image reconstruction. However, quantifying AIF through contrast agent susceptibility induced phase changes is made difficult by the fact that the induced magnetic field is nonlocal and depends upon the contrast agent spatial distribution and thus on organ and vessel shapes. In this article, the contrast agent susceptibility was quantified through inversion of magnetic field shifts using a piece-wise constant model. Its feasibility is demonstrated by a determination of the AIF from the susceptibility-induced field changes of an intravenous bolus. After in vitro validation, a time-resolved two-dimensional (2D) gradient echo scan, triggered to diastole, was performed in vivo on the aortic arch during a bolus injection of 0.1 mmol/kg Gd-DTPA. An approximate geometrical model of the aortic arch constructed from the magnitude images was used to calculate the spatial variation of the field associated with the bolus. In 14 subjects, Gd concentration curves were measured dynamically (one measurement per heart beat) and indirectly validated by independent 2D cine phase contrast flow rate measurements. Flow rate measurements using indicator conservation with this novel quantitative susceptibility imaging technique were found to be in good agreement with those obtained from the cine phase contrast measurements in all subjects. Contrary to techniques that rely on intensity, the accuracy of this signal phase based method is insensitive to factors influencing signal intensity such as flip angle, coil sensitivity, relaxation changes, and time-of-flight effects extending the range of pulse sequences and contrast doses for which quantitative DCE-MRI can be applied.

Susceptibility-weighted imaging: technical aspects and clinical applications, part 1

Susceptibility-weighted imaging (SWI) is a new neuroimaging technique, which uses tissue magnetic susceptibility differences to generate a unique contrast, different from that of spin density, T1, T2, and T2*. In this review (the first of 2 parts), we present the technical background for SWI. We discuss the concept of gradient-echo images and how we can measure local changes in susceptibility. Armed with this material, we introduce the steps required to transform the original magnitude and phase images into SWI data. The use of SWI filtered phase as a means to visualize and potentially quantify iron in the brain is presented. Advice for the correct interpretation of SWI data is discussed, and a set of recommended sequence parameters for different field strengths is given.

Quantitative estimation of permeability surface-area product in astroglial brain tumors using perfusion CT and correlation with histopathologic grade

BACKGROUND AND PURPOSE

Glioma angiogenesis and its different hemodynamic features, which can be evaluated by using perfusion CT (PCT) imaging of the brain, have been correlated with the grade and the aggressiveness of gliomas. Our hypothesis was that quantitative estimation of permeability surface area product (PS), cerebral blood volume (CBV), cerebral blood flow (CBF), and mean transit time (MTT) in astroglial brain tumors by using PCT will correlate with glioma grade. High-grade gliomas will show higher PS and CBV as compared with low-grade gliomas.

MATERIALS AND METHODS

PCT was performed in 32 patients with previously untreated astroglial tumors (24 high-grade gliomas and 8 low-grade gliomas) by using a total acquisition time of 170 seconds. World Health Organization (WHO) glioma grades were compared with PCT parameter absolute values by using Student or nonparametric Wilcoxon 2-sample tests. Receiver operating characteristic (ROC) analyses were also done for each of the parameters.

RESULTS

The differences in PS, CBV, and CBF between the low- and high-grade tumor groups were statistically significant, with the low-grade group showing lower mean values than the high-grade group. ROC analyses showed that both CBV (C-statistic 0.930) and PS (C-statistic 0.927) were very similar to each other in differentiating low- and high-grade gliomas and had higher predictability compared with CBF and MTT. Within the high-grade group, differentiation of WHO grade III and IV gliomas was also possible by using PCT parameters, and PS showed the highest C-statistic value (0.926) for the ROC analyses in this regard.

CONCLUSIONS

Both PS and CBV showed strong association with glioma grading, high-grade gliomas showing higher PS and CBV as compared with low-grade gliomas. Perfusion parameters, especially PS, can also be used to differentiate WHO grade III from grade IV in the high-grade tumor group.

Establishing a baseline phase behavior in magnetic resonance imaging to determine normal vs. abnormal iron content in the brain

PURPOSE

To establish a baseline of phase differences between tissues in a number of regions of the human brain as a means of detecting iron abnormalities using magnetic resonance imaging (MRI).

MATERIALS AND METHODS

A fully flow-compensated, three-dimensional (3D), high-resolution, gradient-echo (GRE) susceptibility-weighted imaging (SWI) sequence was used to collect magnitude and phase data at 1.5 T. The phase images were high-pass-filtered and processed region by region with hand-drawn areas. The regions evaluated included the motor cortex (MC), putamen (PUT), globus pallidus (GP), caudate nucleus (CN), substantia nigra (SN), and red nucleus (RN). A total of 75 subjects, ranging in age from 55 to 89 years, were analyzed.

RESULTS

The phase was found to have a Gaussian-like distribution with a standard deviation (SD) of 0.046 radians on a pixel-by-pixel basis. Most regions of interest (ROIs) contained at least 100 pixels, giving a standard error of the mean (SEM) of 0.0046 radians or less. In the MC, phase differences were found to be roughly 0.273 radians between CSF and gray matter (GM), and 0.083 radians between CSF and white matter (WM). The difference between CSF and the GP was 0.201 radians, and between CSF and the CN (head) it was 0.213 radians. For CSF and the PUT (the lower outer part) the difference was 0.449 radians, and between CSF and the RN (third slice vascularized region) it was 0.353 radians. Finally, the phase difference between CSF and SN was 0.345 radians.

CONCLUSION

The Gaussian-like distributions in phase make it possible to predict deviations from normal phase behavior for tissues in the brain. Using phase as an iron marker may be useful for studying absorption of iron in diseases such as Parkinson's, Huntington's, neurodegeneration with brain iron accumulation (NBIA), Alzheimer's, and multiple sclerosis (MS), and other iron-related diseases. The phases quoted here will serve as a baseline for future studies that look for changes in iron content.

Precision, signal-to-noise ratio, and dose optimization of magnitude and phase arterial input functions in dynamic susceptibility contrast MRI

PURPOSE

To determine optimal conditions for precise measurement of arterial input function (AIFs) in dynamic susceptibility contrast (DSC) perfusion MRI.

MATERIALS AND METHODS

Magnitude-based (DeltaR(2)*) and phase-based (Deltaphi) AIFs were numerically simulated for several doses and baseline MRI noise levels [SNR(I(0))]. Random noise (1000 realizations) was added to real/imaginary MRI signals (derived from an internal carotid AIF), and AIF signal, noise, and signal-to-noise ratio (SNR) were determined. The optimal dose was defined as the dose that maximizes mean AIF SNR over the first-pass (SNR(mean)), rather than SNR at the AIF peak (SNR(peak)) because, compared to SNR(peak), doses predicted by SNR(mean) reduced the AIF-induced variability in cerebral blood flow (CBF) by 24% to 40%.

RESULTS

The AIF SNR is most influenced by choice of AIF signal, then optimal dosing, each with little penalty. Compared to DeltaR(2)*, Deltaphi signal has 4 to 80 times the SNR over all doses and time points, and approximately 10-fold SNR(mean) at respective optimal doses. Optimal doses induce 85% to 90% signal drop for the DeltaR(2)* method, and 70% to 75% for Deltaphi, with two-fold dose errors causing approximately 1.7-fold loss in SNR(mean). Increases in SNR(I(0)) proportionally increase AIF SNR, but at a cost.

CONCLUSION

AIF SNR is affected most by signal type, then dosing, and lastly, SNR(I(0)).

Implementation of a rapid inversion-prepared dual-contrast gradient echo sequence for quantitative dynamic contrast-enhanced magnetic resonance imaging of the human prostate

The first step in quantitative pharmacokinetic modeling is to determine the arterial input function (AIF) by deriving the contrast medium (CM) concentration from an appropriate imaging sequence by monitoring changes in either the amplitude or the phase signal of an accommodative artery. The bolus passage is best detected on T2- or T2*-weighted images, while extravasation is best assessed on T1-weighted images. Here, an imaging sequence is used that employs a parallel acquisition technique for the interleaved acquisition of an inversion-prepared T1-weighted image and a T1/T2*-mixed-weighted image for determination of the AIF. The sequence was applied in six patients with prostate cancer. A method is presented for quantifying the AIF derived from the signal intensity-time courses of both the T1/T2*-mixed-weighted and the T1-weighted image. Furthermore, in some patients the signal intensity-time course of the T1-weighted image exhibits flow-induced signal modulations. To reduce the effect of this flow-related signal enhancement the corresponding phase information was used. The sequence presented here has the potential to improve the quantification of the AIF at all time points and pharmacokinetic modeling of the CM dynamics of the prostate.

Arterial input functions for dynamic susceptibility contrast MRI: requirements and signal options

Cerebral perfusion imaging using dynamic susceptibility contrast (DSC) has been the subject of considerable research and shows promise for basic science and clinical use. In DSC, the MRI signals in brain tissue and feeding arteries are monitored dynamically in response to a bolus injection of paramagnetic agents, such as gadolinium (Gd) chelates. DSC has the potential to allow quantitative imaging of parameters such as cerebral blood flow (CBF) with a high signal-to-noise ratio (SNR) in a short scan time; however, quantitation depends critically on accurate and precise measurement of the arterial input function (AIF). We discuss many requirements and factors that make it difficult to measure the AIF. The AIF signal should be linear with respect to Gd concentration, convertible to the same concentration scale as the tissue signal, and independent of hematocrit. Complicated relationships between signal and concentration can violate these requirements. The additional requirements of a high SNR and high spatial/temporal resolution are technically challenging. AIF measurements can also be affected by signal saturation and aliasing, as well as dispersion/delay between the AIF sampling site and the tissue. We present new in vivo preliminary results for magnitude-based (DeltaR2*) and phase-based (Deltaphi) AIF measurements that show a linearity advantage of phase, and a disparity in the scaling of Deltaphi AIFs, DeltaR2* AIFs, and DeltaR2* tissue curves. Finally, we discuss issues related to the choice of AIF signal for quantitative perfusion imaging.

Automatic selection of arterial input function using cluster analysis

Quantification of cerebral blood flow (CBF) using dynamic susceptibility contrast MRI requires determination of the arterial input function (AIF) representing the delivery of intravascular tracer to tissue. This is typically accomplished manually by inspection of concentration time curves (CTCs) in regions containing the ICA, VA, and MCA. This is, however, a time consuming and operator dependent procedure. We suggest a completely automatic procedure for establishing the AIF based on a cluster analysis algorithm. In 20 normal subjects CBF maps calculated in 2 slices by the automatic procedure were compared to maps obtained with AIFs selected individually by 7 experienced operators. The average manual to automatic CBF ratio was 1.03+/-0.15 in the lower slice and 1.05+/-0.12 in the upper slice, demonstrating excellent agreement between the manual and automatic method. The algorithm provides means for objectively assessing AIF candidates in local AIF search algorithms designed to reduce bias due to delay and dispersion. Given the reproducibility and speed (10 s) of the automatic method, we speculate that it will greatly improve the accuracy of perfusion images and facilitate their use in clinical diagnosis and decision-making, particularly in acute stroke but also in cerebrovascular disease in general.

A comparison of T2*-weighted magnitude and phase imaging for measuring the arterial input function in the rat aorta following intravenous injection of gadolinium contrast agent

The arterial input function (AIF) is important for quantitative MR imaging perfusion experiments employing Gd contrast agents. This study compared the accuracy of T(2)*-weighted magnitude and phase imaging for noninvasive measurement of the AIF in the rat aorta. Twenty-eight in vivo experiments were performed involving simultaneous arterial blood sampling and MR imaging following Gd injection. In vitro experiments were also performed to confirm the in vivo results. At 1.89 T and TE=3 ms, the relationship between changes in 1/T(2)* in blood (estimated from MR signal magnitude) and Gd concentration ([Gd]) was measured to be approximately 19 s(-1) mM(-1), while that between phase and [Gd] was approximately 0.19 rad mM(-1). Both of these values are consistent with previously published results. The in vivo phase data had approximately half as much scatter with respect to [Gd] than the in vivo magnitude data (r(2)=.34 vs. r(2)=.17, respectively). This is likely due to the fact that the estimated change in 1/T(2)* is more sensitive than the phase to a variety of factors such as partial volume effects and T(1) weighting. Therefore, this study indicates that phase imaging may be a preferred method for measuring the AIF in the rat aorta compared to T(2)*-weighted magnitude imaging.

MRI measurement of hepatic magnetic susceptibility-phantom validation and normal subject studies

A magnetic resonance (MR) imaging method with the potential for assessing hepatic iron overload from measurements of hepatic magnetic susceptibility in vivo is described. Using the blood in the portal and hepatic veins as an internal reference, this technique uses the orientation dependence of signal phase to measure the susceptibility of the liver parenchyma. Computer simulations were done to investigate the requirements on spatial resolution and contrast ratio between the vessels and the background liver tissue for data acquisition. Validation studies were conducted using tube-embedded gel phantoms doped with iron-dextran from 0 to 10 mg Fe/mL to mimic healthy and iron-overloaded livers. The phantom measurements were conducted without motion and flow, under respiration-like oscillatory motion, and with flow. Studies on six normal human subjects demonstrated excellent reproducibility and precision. All images were collected at 1.5 T using a 3D T(1)-weighted turbo field echo sequence for inflow MR angiographies with full flow compensation and capable of cardiac synchronization, navigator gating, and motion correction.

Combined dynamic contrast enhanced breast MR and proton spectroscopic imaging: A feasibility study

PURPOSE

To investigate the feasibility of combined dynamic contrast enhanced (DCE) and magnetic resonance spectroscopy (MRS) in evaluating breast lesions.

METHODS

Nine patients with positive mammograms scheduled for either biopsy or mastectomy were examined on a 1.5-T MR scanner. DCE was performed with administration of gadolinium-DTPA contrast using a two-dimensional spoiled gradient recall echo (SPGR) sequence. Proton spectroscopy (TR/TE = 2000/272 msec) was performed using PRESS single slice (10 mm). Lesion time intensity curves were classified as persistent (type 1), plateau (type 2), or washout (type 3) pattern enhancement. Choline (Cho) signal-to-noise ratios (SNRs) and enhancement patterns were compared between benign and malignant lesions as determined by histopathology.

RESULTS

Five patients had breast carcinoma and four had benign lesions. Type 1 enhancement was found in two benign cases, type 2 enhancement in two of four benign and four of five malignant lesions, and one malignant case exhibited a type 3 pattern. Choline SNR was significantly different (P < 0.003) between benign and malignant lesions (2.0 +/- 0.3 vs. 5.7 +/- 1.4; P < 0.003). Choline SNR was less than 4.0 in all of the benign lesions, including the two lesions with type 2 enhancement.

CONCLUSION

Proton MRS appears to be a promising technique for classification of breast lesions when DCE results are equivocal. A combination of DCE and MRS is feasible, and may have improved specificity compared to either modality alone.

Autoregressive moving average (ARMA) model applied to quantification of cerebral blood flow using dynamic susceptibility contrast-enhanced magnetic resonance imaging

PURPOSE

To investigate the feasibility of the autoregressive moving average (ARMA) model for quantification of cerebral blood flow (CBF) with dynamic susceptibility contrast-enhanced magnetic resonance imaging (DSC-MRI) in comparison with deconvolution analysis based on singular value decomposition (DA-SVD).

METHODS

Using computer simulations, we generated a time-dependent concentration of the contrast agent in the volume of interest (VOI) from the arterial input function (AIF) modeled as a gamma-variate function under various CBFs, cerebral blood volumes and signal-to-noise ratios (SNRs) for three different types of residue function (exponential, triangular, and box-shaped). We also considered the effects of delay and dispersion in AIF. The ARMA model and DA-SVD were used to estimate CBF values from the simulated concentration-time curves in the VOI and AIFs, and the estimated values were compared with the assumed values.

RESULTS

We found that the CBF value estimated by the ARMA model was more sensitive to the SNR and the delay in AIF than that obtained by DA-SVD. Although the ARMA model considerably overestimated CBF at low SNRs, it estimated the CBF more accurately than did DA-SVD at high SNRs for the exponential or triangular residue function.

CONCLUSION

We believe this study will contribute to an understanding of the usefulness and limitations of the ARMA model when applied to quantification of CBF with DSC-MRI.

Measuring the arterial input function with gradient echo sequences

The measurement of the arterial input function by use of gradient echo sequences was investigated by in vitro and in vivo experiments. First, calibration curves representing the influence of the concentration of Gd-DTPA on both the phase and the amplitude of the MR signal were measured in human blood by means of a slow-infusion experiment. The results showed a linear increase in the phase velocity and a quadratic increase in DeltaR(*) (2) as a function of the Gd-DTPA concentration. Next, the resultant calibration curves were incorporated in a partial volume correction algorithm for the arterial input function determination. The algorithm was tested in a phantom experiment and was found to substantially improve the accuracy of the concentration measurement. Finally, the reproducibility of the arterial input function measurement was estimated in 16 patients by considering the input function of the left and the right sides as replicate measurements. This in vivo study showed that the reproducibility of the arterial input function determination using gradient echo sequences is improved by employing a partial volume correction algorithm based on the calibration curve for the contrast agent used.

Proton magnetic resonance spectroscopic imaging of human breast cancer: A preliminary study

PURPOSE

To investigate the diagnostic value of proton magnetic resonance spectroscopic imaging (MRSI) in patients with breast lesions.

MATERIALS AND METHODS

Eighteen patients underwent breast MRSI and MRI at 1.5 T. Contrast-enhanced MR was used to identify the lesion, after which single-slice MRSI (TR/TE = 2000/272 msec, 10-mm slice thickness) was performed. Water, lipid, and choline (Cho) images were reconstructed from MRSI data. The area of the Cho was measured in the lesion and expressed relative to the background noise level (signal-to-noise ratio (SNR)), measured between 7.0 and 9.0 ppm. Cho SNRs were compared between benign and malignant lesions as determined by histopathology.

RESULTS

Three cases were considered technical failures on MRSI. Of the remaining 15 cases, on histopathology, eight were classified as malignant carcinoma and seven were benign. The Cho SNR from malignant tissue was significantly elevated compared to benign tissue (6.2 +/- 2.1 vs. 2.4 +/- 0.7, P < 0.0008).

CONCLUSIONS

MRSI measurements of Cho are feasible in the human breast, and the SNR for Cho was significantly different between benign and malignant lesions. The potential advantages of MRSI over SV spectroscopy include the ability to assess multiple lesions as well as tissue with normal MRI appearance, as well as to perhaps gauge lesion borders and infiltration into surrounding tissue.

Accuracy of deconvolution analysis based on singular value decomposition for quantification of cerebral blood flow using dynamic susceptibility contrast-enhanced magnetic resonance imaging

Deconvolution analysis (DA) based on singular value decomposition (SVD) has been widely accepted for quantification of cerebral blood flow (CBF) using dynamic susceptibility contrast-enhanced magnetic resonance imaging (DSC-MRI). When using this method, the elements in the diagonal matrix obtained by SVD are set to zero when they are smaller than the threshold value given beforehand. In the present study, we investigated the effect of the threshold value on the accuracy of the CBF values obtained by this method using computer simulations. We also investigated the threshold value giving the CBF closest to the assumed value (optimal threshold value) under various conditions. The CBF values obtained by this method largely depended on the threshold value. Both the mean and the standard deviation of the estimated CBF values decreased with increasing threshold value. The optimal threshold value decreased with increasing signal-to-noise ratio and CBF, and increased with increasing cerebral blood volume. Although delay and dispersion in the arterial input function also affected the relationship between the estimated CBF and threshold values, the optimal threshold value tended to be nearly constant. In conclusion, our results suggest that the threshold value should be carefully considered when quantifying CBF in terms of absolute values using DSC-MRI for DA based on SVD. We believe that this study will be helpful in selecting the threshold value in SVD.

An anisotropic diffusion method for denoising dynamic susceptibility contrast-enhanced magnetic resonance images

The purpose of this study was to present an application of a novel denoising technique for improving the accuracy of cerebral blood flow (CBF) images generated from dynamic susceptibility contrast-enhanced magnetic resonance imaging (DSC-MRI). The method presented in this study was based on anisotropic diffusion (AD). The usefulness of this method was firstly investigated using computer simulations. We applied this method to patient data acquired using a 1.5 T MR system. After a bolus injection of Gd-DTPA, we obtained 40-50 dynamic images with a 1.32-2.08 s time resolution in 4-6 slices. The dynamic images were processed using the AD method, and then the CBF images were generated using pixel-by-pixel deconvolution analysis. For comparison, the CBF images were also generated with or without processing the dynamic images using a median or Gaussian filter. In simulation studies, the standard deviation of the CBF values obtained after processing by the AD method was smaller than that of the CBF values obtained without any processing, while the mean value agreed well with the true CBF value. Although the median and Gaussian filters also reduced image noise, the mean CBF values were considerably underestimated compared with the true values. Clinical studies also suggested that the AD method was capable of reducing the image noise while preserving the quantitative accuracy of CBF images. In conclusion, the AD method appears useful for denoising DSC-MRI, which will make the CBF images generated from DSC-MRI more reliable.

Determination of arterial input function using fuzzy clustering for quantification of cerebral blood flow with dynamic susceptibility contrast-enhanced MR imaging

An accurate determination of the arterial input function (AIF) is necessary for quantification of cerebral blood flow (CBF) using dynamic susceptibility contrast-enhanced magnetic resonance imaging. In this study, we developed a method for obtaining the AIF automatically using fuzzy c-means (FCM) clustering. The validity of this approach was investigated with computer simulations. We found that this method can automatically extract the AIF, even under very noisy conditions, e.g., when the signal-to-noise ratio is 2. The simulation results also indicated that when using a manual drawing of a region of interest (ROI) (manual ROI method), the contamination of surrounding pixels (background) into ROI caused considerable overestimation of CBF. We applied this method to six subjects and compared it with the manual ROI method. The CBF values, calculated using the AIF obtained using the manual ROI method [CBF(manual)], were significantly higher than those obtained with FCM clustering [CBF(fuzzy)]. This may have been due to the contamination of non-arterial pixels into the manually drawn ROI, as suggested by simulation results. The ratio of CBF(manual) to CBF(fuzzy) ranged from 0.99-1.83 [1.31 +/- 0.26 (mean +/- SD)]. In conclusion, our FCM clustering method appears promising for determination of AIF because it allows automatic, rapid and accurate extraction of arterial pixels. J. Magn. Reson. Imaging 2001;13:797-806.

Artery and vein separation using susceptibility-dependent phase in contrast-enhanced MRA

In magnetic resonance angiography, contrast agents are frequently used to help highlight arteries over background tissue. Unfortunately, enhancing veins hamper the visualization of arteries when data are collected over a long period of time after the arterial phase of the contrast agent. To overcome this problem, we have developed a novel imaging and postprocessing method that is capable of eliminating veins by utilizing the susceptibility difference between veins and surrounding tissue. This method was applied in the peripheral vasculature where the vessels are predominantly parallel to the main field and where the blood oxygen level-dependent effect is most pronounced. Results are presented for both long (15.8 msec) and short echo times (7.8 msec) and for sequential and centrally reordered acquisition schemes. The short echo scan approach appears to be the most promising, making it possible to obtain good suppression of the venous signal even when the timing is not perfect or when repeat scans are necessary.

Magnitude subtraction vs. complex subtraction in dynamic contrast-enhanced 3D-MR angiography: basic experiments and clinical evaluation

Magnitude subtraction and complex subtraction in dynamic contrast-enhanced three-dimensional magnetic resonance (3D-MR) angiography were compared using a phantom and 23 human subjects. In phantom studies, complex subtraction showed far better performance than magnitude subtraction, especially for longer echo times, with thicker slices, and without fat suppression. With complex subtraction, non-fat-suppressed studies showed contrast-to-noise ratios comparable to those in fat-suppressed studies. In human subjects, complex subtraction was superior to magnitude subtraction in 9 subjects, but comparable to magnitude subtraction in 14 subjects. There were no cases in which magnitude subtraction was superior to complex subtraction. Although the differences observed in human studies when complex subtraction was applied with thinner slices, shorter echo times, and the fat-suppression technique were not as pronounced as those seen in phantom studies, complex subtraction should be performed in dynamic contrast-enhanced 3D-MR angiography because there are no drawbacks in complex subtraction. Further research is necessary to assess the feasibility of dynamic contrast-enhanced 3D-MR angiography without fat suppression in human subjects using complex subtraction, as suggested by the results of phantom studies. If it is found to be feasible, dynamic contrast-enhanced 3D-MR angiography without fat suppression using complex subtraction may prove to be a robust technique that eliminates the need for shimming and can reduce the acquisition time. J. Magn. Reson. Imaging 1999;10:813-820.