Correction for arterial-tissue delay and dispersion in absolute quantitative cerebral perfusion DSC MR imaging

The singular value decomposition deconvolution of cerebral tissue concentration-time curves with the arterial input function is commonly used in dynamic susceptibility contrast cerebral perfusion MR imaging. However, it is sensitive to the time discrepancy between the arrival of the bolus in the tissue concentration-time curve and the arterial input function signal. This normally causes inaccuracy in the quantitative perfusion maps due to delay and dispersion effects. A comprehensive correction algorithm has been achieved through slice-dependent time-shifting of the arterial input function, and a delay-dependent dispersion correction model. The correction algorithm was tested in 11 healthy subjects and three ischemic stroke patients scanned with a quantitative perfusion pulse sequence at 1.5 T. A validation study was performed on five patients with confirmed cerebrovascular occlusive disease scanned with MRI and positron emission tomography at 3.0 T. A significant effect (P < 0.05) was reported on the quantitative cerebral blood flow and mean transit time measurements (up to 50%). There was no statistically significant effect on the quantitative cerebral blood volume values. The in vivo results were in agreement with the simulation results, as well as previous literature. This minimizes the bias in patient diagnosis due to the existing errors and artifacts in dynamic susceptibility contrast imaging.     

Relative cerebral blood volume maps corrected for contrast agent extravasation significantly correlate with glioma tumor grade, whereas uncorrected maps do not

BACKGROUND AND PURPOSE: Relative cerebral blood volume (rCBV) estimates for high-grade gliomas computed with dynamic susceptibility contrast MR imaging are artificially lowered by contrast extravasation through a disrupted blood-brain barrier. We hypothesized that rCBV corrected for agent leakage would correlate significantly with histopathologic tumor grade, whereas uncorrected rCBV would not. METHODS: We performed dynamic T2*-weighted perfusion MR imaging on 43 patients with a cerebral glioma after prebolus gadolinium diethylene triamine penta-acetic acid administration to diminish competing extravasation-induced T1 effects. The rCBV was computed from non-necrotic enhancing tumor regions by integrating the relaxivity-time data, with and without contrast extravasation correction by using a linear fitting algorithm, and was normalized to contralateral brain. We determined the statistical correlation between corrected and uncorrected normalized rCBV and histopathologic tumor grade with the Spearman rank correlation test. RESULTS: Eleven, 9, and 23 patients had WHO grades II, III, and IV glioma, respectively. Mean uncorrected normalized rCBVs were 1.53, 2.51, and 2.14 (grade II, III, and IV). Corrected normalized rCBVs were 1.52, 2.84, and 3.96. Mean absolute discrepancies between uncorrected and corrected rCBVs were 2% (0%-15%), 16% (0%-106%), and 74% (0%-411%). The correlation between corrected rCBV and tumor grade was significant (0.60; P < .0001), whereas it was not for uncorrected rCBV (0.15; P = .35). CONCLUSION: For gliomas, rCBV estimation that correlates significantly with WHO tumor grade necessitates contrast extravasation correction. Without correction, artificially lowered rCBV may be construed erroneously to reflect lower tumor grade.     

Perfusion patterns in CT transit studies

Summary Transit studies consist of a rapid sequence of single cross-section CT scans performed during and following the bolus injection of contrast medium into the venous system. The low vascular volume of the brain leads to small changes in attenuation thereby reflecting the perfusion of vasculature. Studies were carried out following 45 examinations on 24 stroke patients and 15 tumor patients. Hypo-, normo- and hyperperfusion were observed in different tissue categories and related to specific tissue elements. The comparison of perfusion patterns with pre-contrast CT values and enhancement after 5 min elucidates cerebral hemodynamics in hypodense to hyperdense lesions with or without damage of the blood-brain barrier (BBB)Cystic lesions and edema were found to have slight damage of the BBB and markedly reduced perfusion. Infarcts demonstrated, depending on their state of evolution to cystic defects or recovery to normal, hypoperfusion and extravasation of contrast medium or hyperperfusion with or without damage of the BBB. A diagnostically valuable difference between edema and infarcts was seen in the phase of stable distribution after 5 min. In most tumors hypervascularity and pathological extravasation were seen, whereby the cause of enhancement could be differentiated.Owing to the properties of the contrast medium used, and to the fact that transit times can not yet be measured, quantification of CBV and CBF was not possible. Definition of large cerebral vessels, especially in the neighborhood of brain tumors, and the improvement in detectability of small lesions by low dose contrast injection, will be demonstrated as a spin-off of CT transit studies.     

Maximum likelihood estimation of cerebral blood flow in dynamic susceptibility contrast MRI.

For quantification of cerebral blood flow (CBF) using dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI), knowledge of the tissue response function is necessary. To obtain this, the tissue contrast passage measurement must be corrected for the arterial input. This study proposes an iterative maximum likelihood expectation maximization (ML-EM) algorithm for this correction, which takes into account the noise in T2- or T2*-weighted image sequences. The ML-EM algorithm does not assume a priori knowledge of the shape of the response function; it automatically corrects for arrival time offsets and inherently yields positive response values. The results on synthetic image sequences are presented, for which the recovered flow values and the response functions are in good agreement with their expectation values. The method is illustrated by calculating the gray and white matter flow in a clinical example.     

Correcting partial volume artifacts of the arterial input function in quantitative cerebral perfusion MRI.

To quantify cerebral perfusion with dynamic susceptibility contrast MRI (DSC-MRI), one needs to measure the arterial input function (AIF). Conventionally, one derives the contrast concentration from the DSC sequence by monitoring changes in either the amplitude or the phase signal on the assumption that the signal arises completely from blood. In practice, partial volume artifacts are inevitable because a compromise has to be reached between the temporal and spatial resolution of the DSC acquisition. As the concentration of the contrast agent increases, the vector of the complex blood signal follows a spiral-like trajectory. In the case of a partial-volume voxel, the spiral is located around the static contribution of the surrounding tissue. If the static contribution of the background tissue is disregarded, estimations of the contrast concentration will be incorrect. By optimizing the correspondence between phase information and amplitude information one can estimate the origin of the spiral, and thereupon correct for partial volume artifacts. This correction is shown to be accurate at low spatial resolutions for phantom data and to improve the AIF determination in a clinical example. Magn Reson Med 45:477-485, 2001.     

Automated macrovessel artifact correction in dynamic susceptibility contrast magnetic resonance imaging using independent component analysis

Dynamic susceptibility contrast‐MRI is the most commonly used functional MRI‐based method for studying changes in cerebral perfusion. However, several studies indicated a systematic overestimation of perfusion parameters compared with other imaging modalities related to the high sensitivity of dynamic susceptibility contrast‐MRI for blood flow in large vessels. In this study, we therefore suggest an improved, automated, robust, and efficient method allowing for generating hemodynamic parameter maps where signal influence from large vessels is minimized. Based on independent component analysis, this fully automated approach corrects dynamic susceptibility contrast‐MRI data without any user interaction, thus making a clinical applicability possible. The accuracy of the proposed method was tested in 10 patients with cerebrovascular disease. Application of our correction algorithm resulted in a significant reduction of the effect of macrovessel signal on hemodynamic parameters like the cerebral blood flow and the cerebral blood volume compared with uncorrected data. As desired, our method specifically corrected for macrovessel artifacts in cortical grey matter tissue, leaving white matter tissue parameters largely unaffected. This may increase sensitivity and reliability of detecting perfusion abnormalities in patient groups, in particular with regard to stroke and other cerebrovascular disorders. Magn Reson Med, 2011. © 2010 Wiley‐Liss, Inc.     

Comparison of quantitative dynamic susceptibility-contrast MRI perfusion estimates obtained using different contrast-agent administration schemes at 3 T

Absolute cerebral perfusion parameters were obtained by dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI) carried out using different contrast-agent administration protocols. Sixteen healthy volunteers underwent three separate DSC-MRI examinations each, receiving single-dose (0.1 mmol/kg b.w.) gadobutrol, double-dose gadobutrol and single-dose gadobenate-dimeglumine on different occasions. DSC-MRI was performed using single-shot gradient-echo echo-planar imaging at 3 T. The arterial input functions (AIFs) were averages (4-9 pixels) of arterial curves from middle cerebral artery branches, automatically identified according to standard criteria. Absolute estimates of cerebral blood volume (CBV), cerebral blood flow (CBF) and mean transit time (MTT) were calculated without corrections for non-linear contrast-agent (CA) response in blood or for different T2* relaxivities in tissue and artery. Perfusion estimates obtained using single and double dose of gadobutrol correlated moderately well, while the relationship between estimates obtained using gadobutrol and gadobenate-dimeglumine showed generally lower correlation. The observed degree of CBV and CBF overestimation, compared with literature values, was most likely caused by different T2* relaxivities in blood and tissue in combination with partial-volume effects. The present results showed increased absolute values of CBV and CBF at higher dose, not predicted by the assumption of a quadratic response to contrast-agent concentration in blood. This indicates that the signal components of measured AIFs were not purely of arterial origin and that arterial signal components were more effectively extinguished at higher CA dose. This study also indicates that it may not be completely straightforward to compare absolute perfusion estimates obtained with different CA administration routines.     

Inflow effect correction in fast gradient-echo perfusion imaging.

The purposes of this study were to assess the extent of the inflow effect on signal intensity (SI) for fast gradient-recalled-echo (GRE) sequences used to observe first-pass perfusion, and to develop and validate a correction method for this effect. A phantom experiment with a flow apparatus was performed to determine SI as a function of Gd-DTPA concentration for various velocities. Subsequently a flow-sensitive calibration method was developed, and validated on bolus injections into an open-circuit flow apparatus and in vivo. It is shown that calibration methods based on static phantoms are not appropriate for accurate signal-to-concentration conversion in images affected by high flow. The flow-corrected calibration method presented here can be used to improve the accuracy and robustness of the arterial input function (AIF) determination for tissue perfusion quantification using MRI and contrast media.     

DSC perfusion MRI-Quantification and reduction of systematic errors arising in areas of reduced cerebral blood flow.

Dynamic susceptibility contrast (DSC)-MRI is commonly used to measure cerebral perfusion in acute ischemic stroke. Quantification of perfusion parameters involves deconvolution of the tissue concentration-time curves with an arterial input function (AIF), typically with the use of singular value decomposition (SVD). To mitigate the effects of noise on the estimated cerebral blood flow (CBF), a regularization parameter or threshold is used. Often a single global threshold is applied to every voxel, and its value has a dramatic effect on the CBF values obtained. When a single global threshold was applied to simulated concentration-time curves produced using exponential, triangular, and boxcar residue functions, significant systematic errors were found in the measured perfusion parameters. We estimate the errors obtained for different sampling intervals and signal-to-noise ratios (SNRs), and discuss the source of the systematic error. We present a method that partially corrects for the systematic error in the presence of an exponential residue function by applying a linear fit, which removes underestimates of long mean transit time (MTT) and overestimates of short MTT. For example, the correction reduced the error at a temporal resolution of 2.5 s and an SNR of 30 from 29.1% to 11.7%. However, the error is largest in the presence of noise and at MTTs that are likely to be encountered in areas of hypoperfusion; furthermore, even though it is reduced, it cannot be corrected for exactly.     

Simulation model for contrast agent dynamics in brain perfusion scans

Standardization efforts are currently under way to reduce the heterogeneity of quantitative brain perfusion methods. A brain perfusion simulation model is proposed to generate test data for an unbiased comparison of these methods. This model provides realistic simulated patient data and is independent of and different from any computational method. The flow of contrast agent solute and blood through cerebral vasculature with disease‐specific configurations is simulated. Blood and contrast agent dynamics are modeled as a combination of convection and diffusion in tubular networks. A combination of a cerebral arterial model and a microvascular model provides arterial‐input and time‐concentration curves for a wide range of flow and perfusion statuses. The model is configured to represent an embolic stroke in one middle cerebral artery territory and provides physiologically plausible vascular dispersion operators for major arteries and tissue contrast agent retention functions. These curves are fit to simpler template curves to allow the use of the simulation results in multiple validation studies. A γ‐variate function with fit parameters is proposed as the vascular dispersion operator, and a combination of a boxcar and exponential decay function is proposed as the retention function. Such physiologically plausible operators should be used to create test data that better assess the strengths and the weaknesses of various analysis methods. Magn Reson Med, 2010. © 2010 Wiley‐Liss, Inc.     

Principles of cerebral perfusion imaging by bolus tracking

The principles of cerebral perfusion imaging by the method of dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI) (bolus tracking) are described. The MRI signals underlying DSC-MRI are discussed. Tracer kinetics procedures are defined to calculate images of cerebral blood volume (CBV), cerebral blood flow (CBF), and mean transit time (MTT). Two general categories of numerical procedures are reviewed for deriving CBF from the residue function. Procedures that involve deconvolution, such as Fourier deconvolution or singular value decomposition (SVD), are classified as model-independent methods because they do not require a model of the microvascular hemodynamics. Those methods in principle also yield a measure of the tissue impulse response function and the residue function, from which microvascular hemodynamics can be characterized. The second category of methods is the model-dependent methods, which use models of tracer transport and retention in the microvasculature. These methods do not yield independent measures of the residue function and may introduce bias when the physiology does not follow the model. Statistical methods are sometimes used, which involve treating the residue function as a deconvolution kernel and optimizing (fitting) the kernel from the experimental data using procedures such as maximum likelihood. Finally, other hemodynamic indices that can be measured from DSC-MRI data are described.     

Automatic motion correction for quantification of myocardial perfusion with dynamic magnetic resonance imaging.

Respiratory motion makes it difficult to quantify myocardial perfusion with dynamic magnetic resonance imaging (MRI). The purpose of this study was to evaluate an automatic registration method for motion correction for quantification of myocardial perfusion with dynamic MRI. The present method was based on the gradient-based method with robust estimation of displacement parameters. For comparison, we also corrected for motion with manual registration as the benchmark. The myocardial kinetic parameters, K1 (rate constant for transfer of contrast agent from blood to myocardium) and k2 (rate constant for transfer from myocardium to blood), were calculated from dynamic images with a two-compartment model. The images corrected by the present method were similar to those corrected by manual registration. The kinetic parameters obtained after motion correction with the present method were close to those obtained after motion correction with manual registration. These results suggest that the present method is useful for motion correction for quantification of myocardial perfusion with dynamic MRI.     

Intravascular contrast injection in ischaemic lesions

Summary In a consecutive series of patients with cerebral infarcts, the degree of recovery was better in those who were not administered contrast medium (sodium iothalamate). The various factors known to influence recovery were examined but did not appear to account fully for the difference. It is postulated that extravasation of the contrast medium may adversely affect potentially viable neural tissue.     

Dynamic susceptibility contrast-enhanced echo-planar imaging of cerebral gliomas. Effect of contrast medium extravasation

PURPOSE: To assess the influence of the degree of contrast medium extravasation on different DSC EPI MR sequences for perfusion MR imaging. MATERIAL AND METHODS: 60 patients with cerebral gliomas were examined by either an FID EPI or an SE EPI DSC MR sequence. The acquired images were evaluated on a qualitative and quantitative basis. For qualitative assessment, the homogeneity of the signal time curve, image artifacts, the degree of signal drop and the degree of enhancement were evaluated. The quantitative assessment included the percentage of signal drop and the contrast-to-noise ratio of the different EPI sequences was analyzed. RESULTS: FID EPI presented a more homogeneous signal time curve and a more pronounced susceptibility effect than the SE EPI sequence. Due to the lesser susceptibility effect, the SE EPI sequence was not as sensitive to contrast media extravasation. The signal returned to baseline in all patients. In patients with strongly enhancing lesions, the FID EPI sequence suffered from considerable T1 effects, causing problems in the quantification of perfusion data. CONCLUSION: FID EPI sequences were preferred for perfusion MR imaging in patients without strong enhancing lesions, e.g. in ischemia or tumors with intact blood-brain barrier. In patients with suspected strong enhancing lesions, an SE EPI sequence should be used.     

Cerebrovascular changes in rats during ischemia and reperfusion: A comparison of bold and first pass bolus tracking techniques

Both first pass bolus tracking of a susceptibility contrast agent and blood oxygenation level dependent (BOLD) sequences provide information on the tissue perfusion and the cerebral blood volume, but each sequence has its own particular limitations. In this article, both techniques were used to assess the cerebrovascular changes occurring in a rat model of focal cerebral ischemia with reperfusion after 2 h of ischemia. The blood oxygenation level dependent studies were performed before, during, and after 60 s of anoxia to observe the response of the tissue to a respiratory challenge. Both techniques were able to detect ischemia and reperfusion; however, first pass bolus tracking provided better sensitivity and was easier to interpret. Because the blood oxygenation level dependent sequence did not provide any additional information, bolus tracking would appear to be the method of choice for studies of cerebral ischemia with reperfusion.     

脑出血患者早期造影剂外渗率的临床意义简

目的：脑出血患者CT造影外渗率可提示血肿扩大,本研究评价脑灌注CT（PCT）推导表面渗透性（PS）是否可检测早期CT造影剂外渗率差异及其意义。方法20例脑出血患者入院时及入院24 h后进行CT检查,入院时进行PCT-PS扫描。采用Wilcoxon秩和检验比较下列兴趣区的PS值：①斑点征病灶;②造影剂渗漏（PCCT-L）病灶;③排除外渗的血肿;④外渗至对侧区域;⑤无外渗患者的血肿;⑥无外渗患者血肿的对侧面积。此外,比较24 h后的血肿扩展情况。结果上述6项参数的PS分别为（6．5±1．6）、（1．0±0．4）、（0．12±0．39）、（0．26±0．09）、（0．4±0．3）、（0．09±0．32）ml×min-1×（100 g）-1。斑点征病灶的PS值和PCCT-L病灶的PS与其他几项参数比较差异有统计学意义（P＜0．05）。外渗阳性患者的血肿体积由（34±41）ml增加至（40±46）ml,外渗阴性患者则由（20±32）ml降至（17±27）ml。结论与PCCT-L病灶和血肿比较,PCT-PS参数检测显示CTA斑点征病灶造影剂较高外渗率,早期外渗与血肿扩展相关。     

Advantages of frequency-domain modeling in dynamic-susceptibility contrast magnetic resonance cerebral blood flow quantification.

In dynamic-susceptibility contrast magnetic resonance perfusion imaging, the cerebral blood flow (CBF) is estimated from the tissue residue function obtained through deconvolution of the contrast concentration functions. However, the reliability of CBF estimates obtained by deconvolution is sensitive to various distortions including high-frequency noise amplification. The frequency-domain Fourier transform-based and the time-domain singular-value decomposition-based (SVD) algorithms both have biases introduced into their CBF estimates when noise stability criteria are applied or when contrast recirculation is present. The recovery of the desired signal components from amid these distortions by modeling the residue function in the frequency domain is demonstrated. The basic advantages and applicability of the frequency-domain modeling concept are explored through a simple frequency-domain Lorentzian model (FDLM); with results compared to standard SVD-based approaches. The performance of the FDLM method is model dependent, well representing residue functions in the exponential family while less accurately representing other functions.     

Delay and dispersion effects in dynamic susceptibility contrast MRI: simulations using singular value decomposition.

Dynamic susceptibility contrast (DSC) MRI is now increasingly used for measuring perfusion in many different applications. The quantification of DSC data requires the measurement of the arterial input function (AIF) and the deconvolution of the tissue concentration time curve. One of the most accepted deconvolution methods is the use of singular value decomposition (SVD). Simulations were performed to evaluate the effects on DSC quantification of the presence of delay and dispersion in the estimated AIF. Both delay and dispersion were found to introduce significant underestimation of cerebral blood flow (CBF) and overestimation of mean transit time (MTT). While the error introduced by the delay can be corrected by using the information of the arrival time of the bolus, the correction for the dispersion is less straightforward and requires a model for the vasculature.     

Transverse relaxation effect of MRI contrast agents: a crucial issue for quantitative measurements of cerebral perfusion

Quantitative cerebral perfusion imaging using dynamic susceptibility contrast (DSC) MRI requires the dynamic measurement of changes in contrast agent concentration in cerebral tissue and its feeding artery. In this work the tracer kinetics approach to general tracer-based perfusion imaging is reviewed. In the typical practical setting, measurements of change in transverse relaxation (DeltaR(2)) derived from MR signals are assumed to be substitutes for true concentration measurements. The implications and limitations of this assumption are reviewed in the light of various results obtained in theoretical, simulated, and experimental studies. The mechanisms of R(2) changes in biological media are discussed. These mechanisms operate over different spatial scales and differentially influence gradient-echo (GE) and spin-echo (SE) MRI signals. This differential sensitivity can be used to assess vessel size in the microvasculature. Finally, the need for well controlled experimental data to provide input parameters and/or experimental tests of theoretical models is emphasized.     

Arterial input function measurements for bolus tracking perfusion imaging in the brain

Imaging of cerebral perfusion by tracking the first passage of an exogenous paramagnetic contrast agent (termed dynamic susceptibility contrast, MRI) has been used in the clinical practice for about a decade. However, the primary goal of dynamic susceptibility contrast MRI to directly quantify the local cerebral blood flow remains elusive. The major challenge of dynamic susceptibility contrast MRI is to measure the contrast inflow to the brain, i.e., the arterial input function. The measurement is complicated by the limited dynamic range of MRI pulse sequences that are optimized for a good contrast in brain tissue but are suboptimal for a much higher tracer concentration in arterial blood. In this work, we suggest a novel method for direct arterial input function quantification. The arterial input function is measured in the carotid arteries with a dedicated plug‐in to the conventional pulse sequence to enable resolution of T₂ on the order of a millisecond. The new technique is compatible with the clinical measurement protocols. Applied to the pig model (N = 13), the method demonstrates robustness of the arterial input function measurement. The cardiac output and cerebral blood volume, obtained without adjustable parameters, agree well with positron emission tomography measurements and values found in the literature. Magn Reson Med, 2013. © 2012 Wiley Periodicals, Inc.