Dynamic susceptibility contrast MRI with localized arterial input functions

Compared to gold‐standard measurements of cerebral perfusion with positron emission tomography using H₂[¹⁵O] tracers, measurements with dynamic susceptibility contrast MR are more accessible, less expensive, and less invasive. However, existing methods for analyzing and interpreting data from dynamic susceptibility contrast MR have characteristic disadvantages that include sensitivity to incorrectly modeled delay and dispersion in a single, global arterial input function. We describe a model of tissue microcirculation derived from tracer kinetics that estimates for each voxel a unique, localized arterial input function. Parameters of the model were estimated using Bayesian probability theory and Markov‐chain Monte Carlo, circumventing difficulties arising from numerical deconvolution. Applying the new method to imaging studies from a cohort of 14 patients with chronic, atherosclerotic, occlusive disease showed strong correlations between perfusion measured by dynamic susceptibility contrast MR with localized arterial input function and perfusion measured by quantitative positron emission tomography with H₂[¹⁵O]. Regression to positron emission tomography measurements enabled conversion of dynamic susceptibility contrast MR to a physiologic scale. Regression analysis for localized arterial input function gave estimates of a scaling factor for quantitation that described perfusion accurately in patients with substantial variability in hemodynamic impairment. Magn Reson Med 63:1305–1314, 2010. © 2010 Wiley‐Liss, Inc.     

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.     

Automatic calculation of the arterial input function for cerebral perfusion imaging with MR imaging

An automated method for determination of arterial input function (AIF) for rapid determination of cerebral perfusion with dynamic susceptibility contrast magnetic resonance (MR) imaging was derived. In 100 patients, the automated method was used to create images of relative blood flow, relative cerebral blood volume, and mean transit time. In 20 patients, the voxel chosen with the automated AIF correlated with a large cerebral artery and exhibited less partial-volume averaging when compared with an AIF chosen manually. It is possible to reliably determine the AIF at dynamic susceptibility contrast MR imaging and eliminate the need for operator input and lengthy postprocessing.     

Iterative blind deconvolution in magnetic resonance brain perfusion imaging.

In first pass magnetic resonance brain perfusion imaging, arterial input functions are used in the deconvolution of the observed contrast concentrations to obtain quantitative hemodynamic parameters. Ideally, arterial input functions should be measured in each imaged voxel to eliminate the effects of delay and dispersion of the contrast agent from the injection site. An approach based on iterative blind deconvolution with the Richardson-Lucy algorithm is proposed for the simultaneous estimation of voxel-specific arterial input functions and voxel-specific tissue residue functions. An extended contrast concentration model was used to separate the first pass bolus from additional recirculation and leakage signals. The extended model was evaluated using in vivo data. Computer simulations examined the feasibility of iterative blind deconvolution in perfusion imaging. Preliminary in vivo results from a patient with fibromuscular dysplasia showed territories with delayed/dispersed arterial input functions that coincided with the location of territories supplied by collateral circulation as described from the complete radiologic examination. Higher flow values and shorter mean transit times compared to conventional methods were obtained in these areas, suggesting that the effects of dispersion were minimized. The in vivo estimated arterial input functions visualized the patient's blood supply patterns as a function of time.     

Quantitative cerebral blood flow in dynamic susceptibility contrast MRI using total cerebral flow from phase contrast magnetic resonance angiography

Dynamic susceptibility contrast magnetic resonance imaging during bolus injection of gadolinium contrast agent is commonly used to investigate cerebral hemodynamics. The large majority of clinical applications of dynamic susceptibility contrast magnetic resonance imaging to date have reported relative cerebral blood flow values because of dependence of the result on the accuracy of determining the arterial input function, the robustness of the singular value decomposition algorithm, and others. We propose a calibration approach that directly measures the total (i.e., whole brain) cerebral blood flow in individual subjects using phase contrast magnetic resonance angiography. The method was applied to data from 11 patients with intracranial pathology. The sum of squares variance about the mean (uncorrected: white matter = 105.6, gray matter = 472.2; corrected: white matter = 34.1, gray matter = 99.8) after correction was significantly lower for white matter (P = 0.045) and for gray matter (P = 0.011). However, the mean gray and white matter cerebral blood flow in the contralateral hemisphere were not significantly altered by the correction. The proposed phase contrast magnetic resonance angiography calibration technique appears to be one of the most direct correction schemes available for dynamic susceptibility contrast magnetic resonance imaging cerebral blood flow values and can be performed rapidly, requiring only a few minutes of additional scan time. Magn Reson Med, 2011. © 2011 Wiley‐Liss, Inc.     

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.     

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.     

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.     

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.     

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.     

Hemodynamic segmentation of MR brain perfusion images using independent component analysis, thresholding, and Bayesian estimation.

Dynamic-susceptibility-contrast MR perfusion imaging is a widely used imaging tool for in vivo study of cerebral blood perfusion. However, visualization of different hemodynamic compartments is less investigated. In this work, independent component analysis, thresholding, and Bayesian estimation were used to concurrently segment different tissues, i.e., artery, gray matter, white matter, vein and sinus, choroid plexus, and cerebral spinal fluid, with corresponding signal-time curves on perfusion images of five normal volunteers. Based on the spatiotemporal hemodynamics, sequential passages and microcirculation of contrast-agent particles in these tissues were decomposed and analyzed. Late and multiphasic perfusion, indicating the presence of contrast agents, was observed in the choroid plexus and the cerebral spinal fluid. An arterial input function was modeled using the concentration-time curve of the arterial area on the same slice, rather than remote slices, for the deconvolution calculation of relative cerebral blood flow.     

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.     

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.     

RF excitation profiles with FAIR: impact of truncation of the arterial input function on quantitative perfusion

This study investigates the impact of imaging coil length and consequent truncation of the arterial input function on the perfusion signal contrast obtained in the flow-sensitive alternating inversion recovery (FAIR) perfusion imaging measurement. We examined the difference in perfusion contrast achieved with head, head and neck, and body imaging coils based on the hypothesis that the standard head coil provides a truncated input function compared with that provided by the body coil and that this effect will be accentuated at long inversion times. The TI-dependent cerebral response of the FAIR sequence was examined at 1.5 T by varying the TI from 200 to 3500 msec with both the head and whole body coils (n = 5) as well as using a head and neck coil (n = 3). Difference signal intensity DeltaM and quantitative cerebral blood flow (CBF) were plotted against TI for each coil configuration. Despite a lower signal-to-noise ratio, relative CBF was significantly greater when measured with the body or head and neck coil compared with the standard head coil for longer inversion times (two-way ANOVA, P < or = 0.002). This effect is attributed to truncation of the arterial input function of labeled water by the standard head coil and the resultant inflow of unlabeled spins to the image slice during control image acquisition, resulting in overestimation of CBF. The results support the conclusion that the arterial input function depends on the anatomic extent of the inversion pulse in FAIR, particularly at longer mixing times (TI > 1200 msec at 1.5 T). Use of a head and neck coil ensures adequate inversion while preserving SNR that is lost in the body coil.     

Absolute quantification of cerebral blood flow in neurologically normal volunteers: Dynamic‐susceptibility contrast MRI‐perfusion compared with computed tomography (CT)‐perfusion

To improve the reproducibility of arterial input function (AIF) registration and absolute cerebral blood flow (CBF) quantification in dynamic‐susceptibility MRI‐perfusion (MRP) at 1.5T, we rescaled the AIF by use of a venous output function (VOF). We compared CBF estimates of 20 healthy, elderly volunteers, obtained by computed tomography (CT)‐perfusion (CTP) and MRP on two consecutive days. MRP, calculated without the AIF correction, did not result in any significant correlation with CTP. The rescaled MRP showed fair to moderate correlation with CTP for the central gray matter (GM) and the whole brain. Our results indicate that the method used for correction of partial volume effects (PVEs) improves MRP experiments by reducing AIF‐introduced variance at 1.5T. Magn Reson Med, 2009. © 2009 Wiley‐Liss, Inc.     

The effect of blood inflow and B1‐field inhomogeneity on measurement of the arterial input function in axial 3D spoiled gradient echo dynamic contrast‐enhanced MRI

A major potential confound in axial 3D dynamic contrast‐enhanced magnetic resonance imaging studies is the blood inflow effect; therefore, the choice of slice location for arterial input function measurement within the imaging volume must be considered carefully. The objective of this study was to use computer simulations, flow phantom, and in vivo studies to describe and understand the effect of blood inflow on the measurement of the arterial input function. All experiments were done at 1.5 T using a typical 3D dynamic contrast‐enhanced magnetic resonance imaging sequence, and arterial input functions were extracted for each slice in the imaging volume. We simulated a set of arterial input functions based on the same imaging parameters and accounted for blood inflow and radiofrequency field inhomogeneities. Measured arterial input functions along the vessel length from both in vivo and the flow phantom agreed with simulated arterial input functions and show large overestimations in the arterial input function in the first 30 mm of the vessel, whereas arterial input functions measured more centrally achieve accurate contrast agent concentrations. Use of inflow‐affected arterial input functions in tracer kinetic modeling shows potential errors of up to 80% in tissue microvascular parameters. These errors emphasize the importance of careful placement of the arterial input function definition location to avoid the effects of blood inflow. Magn Reson Med, 2010. © 2010 Wiley‐Liss, Inc.     

Dynamic contrast-enhanced T2*-weighted MRI in patients with cerebrovascular disease

Our purpose was to investigate the potential of dynamic susceptibility contrast-enhanced MRI in assessing regional haemodynamics in patients with cerebrovascular disease. T2^*-weighted FLASH sequences were performed on a control group of 10 healthy subjects, 13 patients with unilateral stenosis or occlusion of the internal carotid artery and 6 patients with acute onset of neurological symptoms, the observed signal intensities being converted into concentration-time curves. A gamma-variate function was fitted to the measured concentration-time curves to eliminate effects of tracer recirculation. In each patient the two cerebral hemispheres were compared and the difference between the mean transit times and the percental change of the regional cerebral blood volume, calculated for each side. Patients with haemodynamically significant unilateral carotid obstruction can be divided into two subgroups: those with good and those with poor collateral supply. Patients with good collateral supply had a slight but not statistically significant increase in mean transit time and cerebral blood volume on the diseased side, whereas those with poor collaterals had a significant increase compared with the control group. In patients with acute onset of neurological symptoms perfusion maps clearly demonstrated the disturbed perfusion at a time when T2-weighted images were still normal. Perfusion imaging is a reliable and noninvasive method of assessing changes in cerebral perfusion in patients with unilateral carotid stenosis. This MR technique permits monitoring of haemodynamic changes during therapy and thus may become an alternative to SPECT and PET scanning. In patients with acute occlusion of a cerebral artery, perfusion imaging reveals the entire perfusion deficit before conventional MRI and thus allows early intervention. Received: 10 April 1996 Accepted: 14 June 1996     

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.     

The impact of peak saturation of the arterial input function on quantitative evaluation of dynamic susceptibility contrast-enhanced MR studies

PURPOSE: The purpose of this work was to investigate systematic errors in dynamic contrast-enhanced MR perfusion studies due to peak saturation of the arterial input function (AIF) and to introduce a simple correction algorithm. METHOD: Computer simulations were performed to evaluate the influence of AIF peak saturation and to demonstrate the effectiveness of the presented correction algorithm. To compare the computer simulations with real MR data, MR perfusion measurements were performed on volunteers. RESULTS: The computer simulations show that AIF peak saturation leads to a systematic overestimation of cerebral blood volume (CBV) and cerebral blood flow (CBF) values, which was confirmed by comparing the obtained MR data with PET results. With use of an improved calculation algorithm correcting for AIF peak saturation, a significant improvement of the obtained CBV and CBF values could be demonstrated. CONCLUSION: Our results suggest that AIF peak saturation leads to a significant systematic error in the determination of CBV and CBF values and has necessarily to be taken into account for dynamic contrast-enhanced MR perfusion studies.     

Contrast-reduced imaging of tissue concentration and arterial level (CRITICAL) for assessment of cerebral hemodynamics in acute stroke by magnetic resonance

RATIONALE AND OBJECTIVES: To compare cerebral perfusion data obtained by using a low-dose, T1-weighted MRI technique with radionuclide (single positron emission computed tomography [SPECT]) brain imaging and to assess the reproducibility of parametric MRI data (cerebral blood flow [CBF], cerebral blood volume [CBV], and time to peak [TTP]) by applying a previously described nuclear medicine technique to derive quantitative perfusion data. METHODS: Single-slice brain and neck images were rapidly acquired during the passage of a small (1/10th of normal dose) bolus of contrast. Parametric images were constructed from the MR data by extracting the bolus transit curve for the brain and the peak arterial input curve from the carotid vessels in the neck. These were compared with SPECT perfusion imaging. Twenty-four patients with acute stroke were studied with both techniques; 13 underwent repeated scanning to assess data reproducibility. RESULTS: Relative CBF data were comparable to SPECT data (r = 0.584, P = 0.01). Results were reproducible for relative CBF, CBV, and TTP. The arterial input function was significantly different on the second injection with an average difference of 73.5, suggesting that the signal-concentration relationship had lost linearity with increased contrast load. Absolute quantitative MRI data produced values in the expected range (CBF = 42.6 mL x 100 g(-1) x min(-1)). CONCLUSIONS: This technique allows estimation of CBF in the setting of acute stroke with quantitative values in the expected range. Repeated measurements in the same patients showed that this technique provides a reproducible measure of relative CBF, CBV, and TTP.