Models and methods for analyzing DCE-MRI: A review

Diagnostic and interventional imaging, 2013

The microvascular network formed by the capillaries supplies the tissues and permits their function. It provides a considerable surface area for exchanges between blood and tissues. All pathological conditions cause changes in the microcirculation. These changes can be used as imaging biomarkers for the diagnosis of lesions and optimisation of treatment. Among the many imaging techniques developed to study the microcirculation, the analysis of the tissue kinetics of intravenously injected contrast agents is the most widely used, either as positive enhancement for CT, T1-weighted MRI and ultrasound - dynamic contrast-enhanced-imaging (DCE-imaging) - or negative enhancement in T2*-weighted brain MRI - dynamic susceptibility contrast-MRI (DSC-MRI) -. Acquisition involves an injection of contrast agent during the acquisition of a dynamic series of images on a zone of interest. These kinetics may be analyzed visually, to define qualitative criteria, or with software using mathematical mo...

NMR in Biomedicine, 2000

The British Journal of Radiology, 2000

The purpose of this study was to examine the bene®ts of routine generation of a parametric image of scaled curve ®tting errors in the analysis of dynamic susceptibility contrast enhanced MR perfusion imaging. We describe the scaled ®tting error (SFE), which re¯ects the magnitude of potential errors in the estimation of perfusion parameters from dynamic susceptibility contrast enhanced studies. The SFE is the root-mean-square error between the observed values in the time course of change of effective transverse relaxation rate (DR2*(t)) in tissue and the theoretical values derived by C variate curve ®tting, scaled with a simple function related to the area under the ®tted C variate curve. The SFE was tested using Monte Carlo simulation and by observations in normal volunteers and patients. This demonstrated that the SFE was linearly related to uncertainties in calculation of the values of relative cerebral blood volume (rCBV) and relative mean transit time (rMTT). High spatial resolution SFE maps were obtained in all volunteers and patients. In normal brain, SFE was consistently higher in white matter than in grey matter. In 54/85 patients with neurodegenerative or vascular brain disease, SFE maps showed focal areas with high values owing to poor signal to noise ratio in DR2*(t). Increased SFE was also found in 11/54 brain tumours owing to loss of conformance of DR2*(t) to the C variate function. SFE mapping is simple to implement and the computational overhead is negligible. It is concluded that parametric maps of SFE allow visual and quantitative comparison of ®tting errors with the theoretical C variate model between anatomical regions and provide a quality control device to rapidly assess the reliability of the associated rCBV and rMTT estimations. Several methods have been described for studying cerebral blood¯ow using high speed MRI of bolus passage of paramagnetic contrast agents (CAs), such as gadolinium (Gd) compounds [1±7]. These methods allow derivation of estimates of relative cerebral blood volume (rCBV) and relative mean transit time (rMTT), which are proportional to the area under a CA concentration time curve and to the ®rst moment of the curve, respectively. Relative cerebral blood¯ow (rCBF) can be estimated using the central volume theorem [6±8], which states that the mean transit time (MTT) of a tracer bolus is equal to the ratio of the¯uid volume to its rate of¯ow. These calculations allow production of parametric images since the data are available for each pixel in the original images.

Magnetic Resonance Imaging, 2005

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) can assess tumor perfusion, microvascular vessel wall permeability and extravascular-extracellular volume fraction. Analysis of DCE-MRI data is usually based on indicator dilution theory that requires knowledge of the concentration of the contrast agent in the blood plasma, the arterial input function (AIF). A method is presented that compares the tissues of interest (TOI) curve shape to that of a reference region (RR), thereby eliminating the need for direct AIF measurement. By assigning literature values for Ktrans (the blood perfusion-vessel permeability product) and v(e) (extravascular-extracellular volume fraction) in a reference tissue, it is possible to extract the Ktrans and v(e) values for a TOI without knowledge of the AIF. The operational RR equation for DCE-MRI analysis is derived, and its sensitivity to noise and incorrect assignment of the RR parameters is tested via simulations. The method is robust at noise levels of 10%, returning accurate (+/-20% in the worst case) and precise (+/-15% in the worst case) values. Errors in the TOI Ktrans and v(e) values scale approximately linearly with the errors in the assigned RR Ktrans and v(e) values. The methodology is then applied to a Lewis Lung Carcinoma mouse tumor model. A slowly enhancing TOI yielded Ktrans=0.039+/-0.002 min-1 and v(e)=0.46+/-0.01, while a rapidly enhancing region yielded Ktrans=0.35+/-0.05 min-1 and v(e)=0.31+/-0.01. Parametric Ktrans and v(e) mappings manifested a tumor periphery with elevated Ktrans (>0.30 min-1) and v(e) (>0.30) values. The main advantage of the RR approach is that it allows for quantitative assessment of tissue properties without having to obtain high temporal resolution images to characterize an AIF. This allows for acquiring images with higher spatial resolution and/or SNR, and therefore, increased ability to probe tissue heterogeneity.

Magnetic Resonance in Medicine, 2001

A quantitative analysis was undertaken to calibrate the perfusion quantification technique based on tracking the first pass of a bolus of a blood pool contrast agent. A complete simulation of the bolus passage, of the associated changes in the T 2 and T* 2 signals, and of the data processing was performed using the tracer dilution theory, an analytical theory of the MR signal from living tissues and numerical simulations. The noise was excluded in the simulation in order to analyze the ultimate accuracy of the method. It is demonstrated that the relationship between the contrast agent concentration and the associated changes in the transverse relaxation rate shows essentially different forms in studied tissue and in the reference artery. This effect results in systematic deviations of the measured blood flow, blood volume, and the residue function obtained with conventional processing from their true values. The error depends on the microvascular composition, the properties of the contrast agent, and the weights of the various compartments in the total signal. The results show that dynamic susceptibility contrast MRI can reach the goal of absolute perfusion quantification only with additional input from measurements of the microvascular architecture. Alternatively, the method can be used to provide such information if the perfusion is quantified by another modality. Magn Reson Med 46: 1113-1122, 2001.

2011 IEEE Signal Processing in Medicine and Biology Symposium (SPMB), 2011

Estimation of physiological parameters by fitting data to a proper pharmacokinetic model plays a fundamental role in application of DCE-MRI for characterization of tissue microvasculature in diagnosis and prognosis of various diseases. In this study, by allowing asymmetric permeability a generalized two-compartment exchange model (G2CXM) is presented that uniformly includes the extensively applied Patlak model, Tofts model, and extended Tofts model as well as the two-compartment exchange model as special instances. The identifiable physiological parameters in the G2CXM for various tissue types determined by the boundary values of physiological parameters are indicated by analyzing its impulse response function. To obviate failures occurring at times in the conventional fitting method, an approach of estimating physiological parameters in the subspace of arterial input function (SAIF) is proposed. Simulation result shows that the SAIF can obviate failure, significantly increase accuracy and decrease bias of estimated physiological parameters in a wide signal to noise ratio range.

Medical Physics, 2008

For pharmacokinetic modeling of tissue physiology, there is great interest in measuring the arterial input function ͑AIF͒ from dynamic contrast-enhanced ͑DCE͒ magnetic resonance imaging ͑MRI͒ 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 ͑2D͒ 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 beat͒ 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.

Magnetic Resonance Materials in Physics Biology and Medicine, 2020

Objective In dynamic susceptibility contrast MRI (DSC-MRI), an arterial input function (AIF) is required to quantify perfusion. However, estimation of the concentration of contrast agent (CA) from magnitude MRI signal data is challenging. A reasonable alternative would be to quantify CA concentration using quantitative susceptibility mapping (QSM), as the CA alters the magnetic susceptibility in proportion to its concentration. Material and methods AIFs with reasonable appearance, selected on the basis of conventional criteria related to timing, shape, and peak concentration, were registered from both ΔR2* and QSM images and mutually compared by visual inspection. Both ΔR2*-and QSM-based AIFs were used for perfusion calculations based on tissue concentration data from ΔR2*as well as QSM images. Results AIFs based on ΔR2* and QSM data showed very similar shapes and the estimated cerebral blood flow values and mean transit times were similar. Analysis of corresponding ΔR2* versus QSM-based concentration estimates yielded a transverse relaxivity estimate of 89 s −1 mM −1 , for voxels identified as useful AIF candidate in ΔR2* images according to the conventional criteria. Discussion Interestingly, arterial concentration time curves based on ΔR2* versus QSM data, for a standard DSC-MRI experiment, were generally very similar in shape, and the relaxivity obtained in voxels representing blood was similar to tissue relaxivity obtained in previous studies.

Medical Physics, 2010

Purpose:The goal of this study was to optimize dynamic contrast‐enhanced (DCE)‐MRI analysis for differently sized contrast agents and to evaluate the sensitivity for microvascular differences in skeletal muscle.Methods:In rabbits, pathophysiological perfusion differences between hind limbs were induced by unilateral femoral artery ligation. On days 14 and 21, DCE‐MRI was performed using a medium‐sized contrast agent (MCA) (Gadomer) or a small contrast agent (SCA) (Gd‐DTPA). Acquisition protocols were adapted to the pharmacokinetic properties of the contrast agent. Model‐based data analysis was optimized by selecting the optimal model, considering fit error, estimation uncertainty, and parameter interdependency from three two‐compartment pharmacokinetic models (normal and extended generalized kinetic models and Patlak model). Model‐based parameters were compared to the model‐free parameter area‐under‐curve (AUC). Finally, the sensitivity of transfer constant and AUC for physiological...

Journal of Magnetic Resonance Imaging, 2006

Purpose: To evaluate and compare the reproducibility of the preferred phenomenological parameter IAUC 60 (initial area under the time-concentration curve [IAUC] defined over the first 60 seconds postenhancement) with the preferred modeling parameter (K trans ), as derived using two simple models, in abdominal and cerebral data collected in typical Phase I clinical trial conditions.