Two-compartment Exchange Model Research Articles

Assessment of regional pulmonary blood flow using 68Ga-DOTA PET

BackgroundIn vivo determination of regional pulmonary blood flow (PBF) is a valuable tool for the evaluation of many lung diseases. In this study, the use of 68Ga-DOTA PET for the in vivo quantitative determination of regional PBF is proposed. This methodology was implemented and tested in healthy pigs and validated using fluorescent microspheres. The study was performed on young large white pigs (n = 4). To assess the reproducibility and consistency of the method, three PET scans were obtained for each animal. Each radiotracer injection was performed simultaneously to the injection of fluorescent microspheres. PBF images were generated applying a two-compartment exchange model over the dynamic PET images. PET and microspheres values were compared by regression analysis and Bland–Altman plot.ResultsThe capability of the proposed technique to produce 3D regional PBF images was demonstrated. The correlation evaluation between 68Ga-DOTA PET and microspheres showed a good and significant correlation (r = 0.74, P < 0.001).ConclusionsAssessment of PBF with the proposed technique allows combining the high quantitative accuracy of PET imaging with the use of 68Ga/68Ge generators. Thus, 68Ga-DOTA PET emerges as a potential inexpensive method for measuring PBF in clinical settings with an extended use.

Validation of a Multimodality Flow Phantom and Its Application for Assessment of Dynamic SPECT and PET Technologies.

Simple and robust techniques are lacking to assess performance of flow quantification using dynamic imaging. We therefore developed a method to qualify flow quantification technologies using a physical compartment exchange phantom and image analysis tool. We validate and demonstrate utility of this method using dynamic PET and SPECT. Dynamic image sequences were acquired on two PET/CT and a cardiac dedicated SPECT (with and without attenuation and scatter corrections) systems. A two-compartment exchange model was fit to image derived time-activity curves to quantify flow rates. Flowmeter measured flow rates (20-300 mL/min) were set prior to imaging and were used as reference truth to which image derived flow rates were compared. Both PET cameras had excellent agreement with truth ( [Formula: see text]). High-end PET had no significant bias (p > 0.05) while lower-end PET had minimal slope bias (wash-in and wash-out slopes were 1.02 and 1.01) but no significant reduction in precision relative to high-end PET (<15% vs. <14% limits of agreement, p > 0.3). SPECT (without scatter and attenuation corrections) slope biases were noted (0.85 and 1.32) and attributed to camera saturation in early time frames. Analysis of wash-out rates from non-saturated, late time frames resulted in excellent agreement with truth ( [Formula: see text], slope = 0.97). Attenuation and scatter corrections did not significantly impact SPECT performance. The proposed phantom, software and quality assurance paradigm can be used to qualify imaging instrumentation and protocols for quantification of kinetic rate parameters using dynamic imaging.

A model describing diffusion in prostate cancer.

Quantitative diffusion MRI has frequently been studied as a means of grading prostate cancer. Interpretation of results is complicated by the nature of prostate tissue, which consists of four distinct compartments: vascular, ductal lumen, epithelium, and stroma. Current diffusion measurements are an ill-defined weighted average of these compartments. In this study, prostate diffusion is analyzed in terms of a model that takes explicit account of tissue compartmentalization, exchange effects, and the non-Gaussian behavior of tissue diffusion. The model assumes that exchange between the cellular (ie, stromal plus epithelial) and the vascular and ductal compartments is slow. Ductal and cellular diffusion characteristics are estimated by Monte Carlo simulation and a two-compartment exchange model, respectively. Vascular pseudodiffusion is represented by an additional signal at b = 0. Most model parameters are obtained either from published data or by comparing model predictions with the published results from 41 studies. Model prediction error is estimated using 10-fold cross-validation. Agreement between model predictions and published results is good. The model satisfactorily explains the variability of ADC estimates found in the literature. A reliable model that predicts the diffusion behavior of benign and cancerous prostate tissue of different Gleason scores has been developed. Magn Reson Med 78:316-326, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Improved accuracy and precision of tracer kinetic parameters by joint fitting to variable flip angle and dynamic contrast enhanced MRI data.

To improve the accuracy and precision of tracer kinetic model parameter estimates for use in dynamic contrast enhanced (DCE) MRI studies of solid tumors. Quantitative DCE-MRI requires an estimate of precontrast T1 , which is obtained prior to fitting a tracer kinetic model. As T1 mapping and tracer kinetic signal models are both a function of precontrast T1 it was hypothesized that its joint estimation would improve the accuracy and precision of both precontrast T1 and tracer kinetic model parameters. Accuracy and/or precision of two-compartment exchange model (2CXM) parameters were evaluated for standard and joint fitting methods in well-controlled synthetic data and for 36 bladder cancer patients. Methods were compared under a number of experimental conditions. In synthetic data, joint estimation led to statistically significant improvements in the accuracy of estimated parameters in 30 of 42 conditions (improvements between 1.8% and 49%). Reduced accuracy was observed in 7 of the remaining 12 conditions. Significant improvements in precision were observed in 35 of 42 conditions (between 4.7% and 50%). In clinical data, significant improvements in precision were observed in 18 of 21 conditions (between 4.6% and 38%). Accuracy and precision of DCE-MRI parameter estimates are improved when signal models are fit jointly rather than sequentially. Magn Reson Med 76:1270-1281, 2016. © 2015 Wiley Periodicals, Inc.

Value of dynamic contrast-enhanced MRI parameters of Extended Tofts and Exchange model in the differential diagnosis of hepatocellular carcinoma and hepatic metastases

Objective To analyze the value of dynamic contrast-enhanced MRI(DCE-MRI) parameters of Extended Tofts and Exchange model in the differential diagnosis of hepatocellular carcinoma (HCC) and hepatic metastases of colorectal cancer. Methods A retrospective analysis of 40 pathologically confirmed cases was conducted, including 25 cases of HCC and 15 cases of hepatic metastases of colorectal cancer,all patients underwent DCE-MRI. Applying liver double blood supplement model, and respectively using Extended Tofts two-compartment model and Exchange model liver microvascular permeability parameters [volume transfer constant of the contrast agent(Ktrans), efflux rate from extracellular extravascular space to plasma(Kep), extravascular extracellular volume fraction(Ve)and blood plasma space volume fraction (Vp)] and the perfusion parameter hepatic arterial perfusion index(HPI) in the lesion parenchyma of HCC and metastases were calculated. We used t test to compare the differences of the parameters measured from the two types of tumors, statistically significant parameters between HCC and metastases were screened which compared with the gold standard of pathological findings in order to draw the ROC curves to evaluate the diagnostic efficacy of different model parameters, using χ2 test compared the diagnostic accuracy of optimal parameters between the two models. Results By using Extended Tofts and Exchange model, Ktrans value of HCC were (0.661±0.402)/min and (0.604±0.316)/min respectively, Ktrans value of hepatic metastases were (0.196±0.175)/min and (0.179±0.135)/min respectively; Vp value of HCC were (0.334±0.217) and (0.294±0.098), Vp value of hepatic metastases were (0.089±0.015) and (0.089±0.022),respectively; HPI value of HCC were (0.680±0.281) and (0.769±0.245), HPI value of hepatic metastases were (0.326±0.216), (0.373±0.298), respectively. There were significant differences between HCC and hepatic metastases in Ktrans, Vp and HPI values in both models(P 0.05).Drawn ROC curves of Ktrans, Vp, HPI, the Ktrans value (area under the curve of 0.869) among Extended Tofts model parameters was selected as optimal parameter to identify HCC and hepatic metastases; the HPI value (area under the curve of 0.845) among Exchange model parameters was selected as optimal parameter to differentiate these two types of tumors.The diagnostic accordance rate of Extended Tofts model and Exchange model were 80.0% (32/40) , 82.5% (33/40), respectively; There was no significant difference between them (χ2=0.082, P=0.775). Conclusions Parameters including Ktrans, Vp, HPI of the Extended Tofts model and Exchange model in DCE-MRI perfusion can be used to identify HCC and hepatic metastases of colorectal cancer. Among these parameters, Ktrans of Extended Tofts model and HPI of Exchange model have higher diagnostic value in differentiating HCC and hepatic metastases of colorectal cancer. Key words: Liver neoplasms; Magnetic resonance imaging; Comparative study

Using Single-Channel Blind Deconvolution to Choose the Most Realistic Pharmacokinetic Model in Dynamic Contrast-Enhanced MR Imaging

In dynamic contrast-enhanced magnetic resonance imaging, there has been no consensus in the choice of the pharmacokinetic model. In this paper, a new approach for assessment of the most realistic model for a given tissue is presented. Non-blind and single-channel blind deconvolution algorithms were used in quantitative magnetic resonance dynamic contrast-enhanced imaging of the mouse masseter muscle to compare the realism of two different pharmacokinetic models for the tissue residue function. The first was the adiabatic approximation tissue homogeneity model (aaJW) and the second, the two-compartment exchange model (2CXM). Normals and mice treated with the substance C48/80 were studied. C48/80 increases both blood flow and contrast leakage in muscle substantially. The obtained approximation accuracy was evaluated for both pharmacokinetic models. In addition, the arterial input functions (aifs) estimated using blind deconvolution were compared to the corresponding observed aifs. The hypothesis is that the most realistic model of the tissue residue function leads to the best fits. The non-blind deconvolution did not result in any clear answer. For blind deconvolution, the aifs of the aaJW model were very similar to the corresponding observed aifs, and clearly more so than the aifs of the 2CXM model. Also, the approximation of the observed tracer time sequences was more accurate for the aaJW than the 2CXM model. The realism of different pharmacokinetic models in describing the passage of a tracer through a microvascular bed of a single tissue could be assessed using single-channel blind deconvolution.

Intravoxel incoherent motion diffusion-weighted imaging in head and neck squamous cell carcinoma: Assessment of perfusion-related parameters compared to dynamic contrast-enhanced MRI

PurposeTo investigate the correlation between perfusion-related parameters obtained with intravoxel incoherent motion (IVIM) and classical perfusion parameters obtained with dynamic contrast-enhanced (DCE) magnetic resonance imaging in patients with head and neck squamous cell carcinoma (HNSCC), and to compare direct and asymptotic fitting, the pixel-by-pixel approach, and a region of interest (ROI)-based approach respectively for IVIM parameter calculation. Materials and methodsSeventeen patients with HNSCC were included in this retrospective study. All magnetic resonance (MR) scanning was performed using a 3T MR unit. Acquisition of IVIM was performed using single-shot spin-echo echo-planar imaging with three orthogonal gradients with 12 b-values (0, 10, 20, 30, 50, 80, 100, 200, 400, 800, 1000, and 2000). Perfusion-related parameters of perfusion fraction ‘f’ and the pseudo-diffusion coefficient ‘D*’ were calculated from IVIM data by using least square fitting with the two fitting methods of direct and asymptotic fitting, respectively. DCE perfusion was performed in a total of 64 dynamic phases with a 3.2-s phase interval. The two-compartment exchange model was used for the quantification of tumor blood volume (TBV) and tumor blood flow (TBF). Each tumor was delineated with a polygonal ROI for the calculation of f, f∙D* performed using both the pixel-by-pixel approach and the ROI-based approach. In the pixel-by-pixel approach, after fitting each pixel to obtain f, f∙D* maps, the mean value in the delineated ROI on these maps was calculated. In the ROI-based approach, the mean value of signal intensity was calculated within the ROI for each b-value in IVIM images, and then fitting was performed using these values. Correlations between f in a total of four combinations (direct or asymptotic fitting and pixel-by-pixel or ROI-based approach) and TBV were respectively analyzed using Pearson's correlation coefficients. Correlations between f∙D* and TBF were also similarly analyzed. ResultsIn all combinations of f and TBV, f∙D* and TBF, there was a significant correlation. In the comparison of f and TBV, a moderate correlation was observed only between f obtained by direct fitting with the pixel-by-pixel approach, whereas a good correlation was observed in the comparisons using the other three combinations. In the comparison of f∙D* and TBF, a good correlation was observed only with f∙D* obtained by asymptotic fitting with the ROI-based approach. In contrast, moderate correlations were observed in the comparisons using the other three combinations. ConclusionIVIM was found to be feasible for the analysis of perfusion-related parameters in patients with HNSCC. Especially, the combination of asymptotic fitting with the ROI-based approach was better correlated with DCE perfusion.

Dynamic contrast-enhanced MRI in mice: an investigation of model parameter uncertainties.

To establish the experimental factors that dominate the uncertainty of hemodynamic parameters in commonly used pharmacokinetic models. By fitting simulation results from a multiregion tissue exchange model (Multiple path, Multiple tracer, Indicator Dilution, 4 region), the precision and accuracy of hemodynamic parameters in dynamic contrast-enhanced MRI with four tracer kinetic models is investigated. The impact of various injection rates as well as imprecise knowledge of the arterial input functions is examined. Fast injections are beneficial for K(trans) precision within the extended Tofts model and within the two-compartment exchange model but do not affect the other models under investigation. Biases from errors in the arterial input functions are mostly consistent in size and direction for the simple and the extended Tofts model, while they are hardly predictable for the other models. Errors in the hematocrit introduce the greatest loss in parameter accuracy, amounting to an average K(trans) bias of 40% for a 30% overestimation throughout all models. This simulation study allows the detailed inspection of the isolated impact from various experimental conditions on parameter uncertainty. Because parameter uncertainty comparable to human studies was found, this study represents a validation of preclinical dynamic contrast-enhanced MRI for modeling human tumor physiology.

Distribution of Intravascular and Extravascular Extracellular Volume Fractions by Total Area under Curve for Neovascularization Assessment by Dynamic Contrast-Enhanced Magnetic Resonance Imaging

In this paper, we propose and investigate distribution of intravascular and extravascular extracellular volume fractions (DIEEF) as a noninvasive biomarker for neovascularization assessment by dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). A generalized two-compartment exchange model (G2CXM) that uniformly includes the Patlak model, Tofts model, extended Tofts model, and recent two-compartment exchange model as special instances is first presented. Based on the total area under curve of the G2CXM a method of DIEEF estimation without knowing the artery input function is proposed. The mean square error of DIEEF estimate in the presence of noise and with incomplete DCE-MRI data is analyzed. Simulation results demonstrate that DIEEF estimate is accurate when signal to noise ratio is only 5 dB in both cases of tracer infusion and bolus injection, and slightly favors the bolus injection. Tested on a model of atherosclerotic rabbits, the DIEEF of aorta plaques is positively correlated with the histological neovessel count with correlation coefficient of 0.940 and P = 0.017, and outperforms six semiquantitative parameters in the literature. DIEEF might be useful as a biomarker for noninvasive neovascularization assessment by DCE-MRI.

Leakage and water exchange characterization of gadofosveset in the myocardium

PurposeTo determine the compartmentalization of the blood pool agent gadofosveset and the effect of its transient binding to albumin on the quantification of steady-state fractional myocardial blood volume (fMBV). MethodsMyocardial vascular fraction measurements were simulated assuming the limiting cases (slow or fast) of two-compartment water exchange for different contrast agent injection concentrations, binding fractions, bound and free relaxivities, and true cardiac vascular fractions.fMBV was measured in five healthy volunteers (4 males, 1 female, average age 33) at 1.5T after administration of five injections of gadofosveset. The measurements in the volunteers were retrospectively compared to measurements of fMBV after three serial injections of the ultra-small, paramagnetic iron oxide (USPIO) blood pool agent ferumoxytol in an experimental animal. The true fMBV and exchange rate of water protons in both human and animal data sets was determined by chi square minimization. ResultsSimulations showed an error in the measurement of fMBV due to partial binding of gadofosveset of less than 30%. Measured fMBV values over-estimate simulation predictions, and approach cardiac extracellular volume (22%), which suggests that the intravascular assumption may not be appropriate for the myocardium, although it may apply to more distal perfusion beds. In comparison, fMBV measured with ferumoxytol (5%, with slow water proton exchange across vascular wall) agree with published values of myocardial vascular fraction. Further comparison between myocardium relaxation rates induced by gadofosveset and by other extracellular and intravascular contrast agents showed that gadofosveset behaves like an extracellular contrast agent. ConclusionsThe distribution of the volunteer data indicates that a three-compartment model, with slow water exchange of gadofosveset and water protons between the vascular and interstitial compartments, and fast water exchange between the interstitium and the myocytes, is appropriate. The ferumoxytol measurements indicate that this USPIO is an intravascular contrast agent that can be used to quantify myocardial blood volume, with the appropriate correction for water exchange using a two-compartment water exchange model.

Dynamic contrast-enhanced MRI in patients with muscle-invasive transitional cell carcinoma of the bladder can distinguish between residual tumour and post-chemotherapy effect

IntroductionTreatment of muscle-invasive bladder cancer with chemotherapy results in haemorrhagic inflammation, mimicking residual tumour on conventional MR images and making interpretation difficult. The aim of this study was to use dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to estimate descriptive and tracer kinetic parameters post-neoadjuvant chemotherapy and to investigate whether parameters differed in areas of residual tumour and chemotherapy-induced haemorrhagic inflammation (treatment effect, Tr-Eff). Methods and materialsTwenty-one patients underwent DCE-MRI scans with 2.5s temporal resolution before and following neoadjuvant chemotherapy. Regions-of-interest (ROIs) were defined in areas suspicious of residual tumour on T2-weighted MRI scans. Data were analysed semi-quantitatively and with a two-compartment exchange model to obtain parameters including relative signal intensity (rSI80s) and plasma perfusion (Fp) respectively. The bladder was subsequently examined histologically after cystectomy for evidence of residual tumour and/or Tr-Eff. Differences in parameters measured in areas of residual tumour and Tr-Eff were examined using Student's t-test. ResultsTwenty-four abnormal sites were defined after neoadjuvant chemotherapy. On pathology, 10 and 14 areas were identified as residual tumour and Tr-Eff respectively. Median rSI80s and Fp were significantly higher in areas of residual tumour than Tr-Eff (rSI80s=2.9 vs 1.7, p<0.001; Fp=20.7 vs 9.1ml/100ml/min, p=0.03). The sensitivity and specificity for differentiating residual tumour from Tr-Eff were 70% and 100% (rSI80s), 60% and 86% (Fp), and 75% and 100% when combined. ConclusionDCE-MRI parameters obtained post-treatment are capable of distinguishing between residual tumour and treatment effect in patients treated for bladder cancer with neoadjuvant chemotherapy.

Modeling DCE-MRI at low temporal resolution: A case study on rheumatoid arthritis

To identify the optimal tracer-kinetic modeling strategy for dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) data acquired at low temporal resolution. DCE-MRI was performed on 13 patients with rheumatoid arthritis of the hand before and after anti-tumor necrosis factor alpha (TNFα) therapy, using a 3D sequence with a temporal resolution of 13 seconds, imaging for 4 minutes postcontrast injection. Concentration-time curves were extracted from regions of interest (ROIs) in enhancing synovium and fitted to the 3-parameter modified Tofts model (MT) and the 4-parameter two-compartment exchange model (2CXM). To assist the interpretation of the data, the same analysis was applied to simulated data with similar characteristics. Both models fitted the data closely, and showed similar therapy effects. The MT plasma volume was significantly lower than with 2CXM, but the differences in permeability and interstitial volume were not significant. 2CXM was less precise than MT, with larger standard deviations relative to the mean in most parameters. The additional perfusion parameter determined with 2CXM did not provide a statistically significant trend due to low precision. The standard MT model is the optimal modeling strategy at low temporal resolution. Advanced models improve the accuracy and generate an additional parameter, but these benefits are offset by low precision.

Combined Diffusion-Weighted, Blood Oxygen Level–Dependent, and Dynamic Contrast-Enhanced MRI for Characterization and Differentiation of Renal Cell Carcinoma

To investigate a multiparametric magnetic resonance imaging (MRI) approach comprising diffusion-weighted imaging (DWI), blood oxygen-dependent (BOLD), and dynamic contrast-enhanced (DCE) MRI for characterization and differentiation of primary renal cell carcinoma (RCC). Fourteen patients with clear-cell carcinoma and four patients with papillary RCC were examined with DWI, BOLD MRI, and DCE MRI at 1.5T. The apparent diffusion coefficient (ADC) was calculated with a monoexponential decay. The spin-dephasing rate R2* was derived from parametric R2* maps. DCE-MRI was analyzed using a two-compartment exchange model allowing separation of perfusion (plasma flow [FP] and plasma volume [VP]), permeability (permeability surface area product [PS]), and extravascular extracellular volume (VE). Statistical analysis was performed with Wilcoxon signed-rank test, Pearson's correlation coefficient, and receiver operating characteristic curve analysis. Clear-cell RCC showed higher ADC and lower R2* compared to papillary subtypes, but differences were not significant. FP of clear-cell subtypes was significantly higher than in papillary RCC. Perfusion parameters showed moderate but significant inverse correlation with R2*. VE showed moderate inverse correlation with ADC. Fp and Vp showed best sensitivity for histological differentiation. Multiparametric MRI comprising DWI, BOLD, and DCE MRI is feasible for assessment of primary RCC. BOLD moderately correlates to DCE MRI-derived perfusion. ADC shows moderate correlation to the extracellular volume, but does not correlate to tumor oxygenation or perfusion. In this preliminary study DCE-MRI appeared superior to BOLD and DWI for histological differentiation.

Tracer-kinetic modeling of dynamic contrast-enhanced MRI and CT: a primer

Dynamic contrast-enhanced computed tomography (DCE-CT) and magnetic resonance imaging (DCE-MRI) are functional imaging techniques. They aim to characterise the microcirculation by applying the principles of tracer-kinetic analysis to concentration-time curves measured in individual image pixels. In this paper, we review the basic principles of DCE-MRI and DCE-CT, with a specific emphasis on the use of tracer-kinetic modeling. The aim is to provide an introduction to the field for a broader audience of pharmacokinetic modelers. In a first part, we first review the key aspects of data acquisition in DCE-CT and DCE-MRI, including a review of basic measurement strategies, a discussion on the relation between signal and concentration, and the problem of measuring reference data in arterial blood. In a second part, we define the four main parameters that can be measured with these techniques and review the most common tracer-kinetic models that are used in this field. We first discuss the models for the capillary bed and then define the most general four-parameter models used today: the two-compartment exchange model, the tissue-homogeneity model, the "adiabatic approximation to the tissue-homogeneity model" and the distributed-parameter model. In simpler tissue types or when the data quality is inadequate to resolve all the features of the more complex models, it is often necessary to resort to simpler models, which are special cases of the general models and hence have less parameters. We discuss the most common of these special cases, i.e. the uptake models, the extended Tofts model, and the one-compartment model. Models for two specific tissue types, liver and kidney, are discussed separately. We conclude with a review of practical aspects of DCE-CT and DCE-MRI data analysis, including the problem of identifying a suitable model for any given data set, and a brief discussion of the application of tracer-kinetic modeling in the context of drug development. Here, an important application of DCE techniques is the derivation of quantitative imaging biomarkers for the assessment of effects of targeted therapeutics on tumors.

The Akaike information criterion in DCE-MRI: Does it improve the haemodynamic parameter estimates?

The Akaike information criterion and the associated Akaike weights (AW) rank pharmacokinetic models on the basis of goodness-of-fit and number of parameters. The usefulness of this information for improving the haemodynamic parameter estimates from DCE-MRI was investigated through two examples. In each of these, the estimates from the two-compartment exchange model (2CXM) were combined on the basis of the AW with those of a simplified model (either the uptake model or the extended Tofts model). Data were simulated using the 2CXM for a range of experimental and tissue conditions. Two multimodel approaches exploiting the AW were investigated: the ‘best model’ approach which selects the parameter estimates from the model with highest AW and the ‘weighted model’ approach in which AW-weighted averages of the estimates from the competing models are calculated. Although these approaches were shown to be beneficial in some cases, they were found to frequently lead to unexpected increases in the bias and/or uncertainty of the resulting parameter estimates. Within the limited scope of this simulation study, the use of the Akaike criterion showed no systematic benefit over a fitting strategy involving only the more complex model.

Calibration and validation of TRUST MRI for the estimation of cerebral blood oxygenation

Recently, a T(2) -Relaxation-Under-Spin-Tagging (TRUST) MRI technique was developed to quantitatively estimate blood oxygen saturation fraction (Y) via the measurement of pure blood T(2) . This technique has shown promise for normalization of fMRI signals, for the assessment of oxygen metabolism, and in studies of cognitive aging and multiple sclerosis. However, a human validation study has not been conducted. In addition, the calibration curve used to convert blood T(2) to Y has not accounted for the effects of hematocrit (Hct). In this study, we first conducted experiments on blood samples under physiologic conditions, and the Carr-Purcell-Meiboom-Gill T(2) was determined for a range of Y and Hct values. The data were fitted to a two-compartment exchange model to allow the characterization of a three-dimensional plot that can serve to calibrate the in vivo data. Next, in a validation study in humans, we showed that arterial Y estimated using TRUST MRI was 0.837 ± 0.036 (N=7) during the inhalation of 14% O2, which was in excellent agreement with the gold-standard Y values of 0.840 ± 0.036 based on Pulse-Oximetry. These data suggest that the availability of this calibration plot should enhance the applicability of T(2) -Relaxation-Under-Spin-Tagging MRI for noninvasive assessment of cerebral blood oxygenation.

Effect of gradient pulse duration on MRI estimation of the diffusional kurtosis for a two-compartment exchange model

Hardware constraints typically require the use of extended gradient pulse durations for clinical applications of diffusion-weighted magnetic resonance imaging (DW-MRI), which can potentially influence the estimation of diffusion metrics. Prior studies have examined this effect for the apparent diffusion coefficient. This study employs a two-compartment exchange model in order to assess the gradient pulse duration sensitivity of the apparent diffusional kurtosis (ADK), a quantitative index of diffusional non-Gaussianity. An analytic expression is derived and numerically evaluated for parameter ranges relevant to DW-MRI of brain. It is found that the ADK differs from the true diffusional kurtosis by at most a few percent. This suggests that ADK estimates for brain may be robust with respect to changes in pulse gradient duration.

Validity of perfusion parameters obtained using the modified Tofts model: A simulation study

The two-compartment Tofts model (2CTM) has had widespread use in research and clinical practice. It assumes there is no broadening associated with the bolus transit through the capillary bed of the tissue under study. This assumption is often violated, with consequences that are hard to predict intuitively. The two-compartment exchange model is a generalization of 2CTM obtained by dropping the zero-broadening hypothesis, making it suitable for estimating the impact of violating this assumption. Using data simulated on the basis of the two-compartment exchange model, the correspondence between the hemodynamic parameters serving as input for the two-compartment exchange model and the parameters resulting from fitting the data with the 2CTM was investigated. The influence of tissue type and experimental setup was studied. Generally, a large tissue and setup dependent bias of the 2CTM fitting results with respect to the two-compartment exchange model input was observed. Extreme caution is needed when interpreting 2CTM data.

Error estimation for perfusion parameters obtained using the two-compartment exchange model in dynamic contrast-enhanced MRI: a simulation study

In theory, the application of the two-compartment exchange model (2CXM) to data from a dynamic contrast-enhanced (DCE) MRI exam allows the estimation of the plasma flow, plasma volume, extraction flow and extravascular-extracellular volume. The aim of this paper was to explore whether simulations based on the 2CXM could provide useful information on the trustworthiness of the results. The deviations from the input values of the haemodynamic quantities were estimated for a ‘reference tissue’ with a clear bi-phasic response and four ‘limit tissues’ with more challenging 2CXM fitting properties. The impact of the instrumental factors sampling step (Ts), acquisition window (Tacq) and contrast-to-noise ratio (CNR) was investigated. Each factor was varied separately, while keeping the other ones at a value above concern. Measurement guidelines to ensure that all deviations fell within a predefined range (±20%) could not be derived, but simulations for fixed Ts and Tacq were found to provide a practical tool for studying the error behaviour to be expected from a given experimental set-up and for comparing measurement protocols. At the level of an individual DCE exam, a bootstrap version of the simulation approach was shown to lead to a useful estimate of the errors on the fitted parameters.

Monte Carlo study of a two‐compartment exchange model of diffusion

Multisite exchange models have been applied frequently to quantify measurements of transverse relaxation and diffusion in living tissues. Although the simplicity of such models is attractive, the precise relationship of the model parameters to tissue properties may be difficult to ascertain. Here, we investigate numerically a two-compartment exchange (Kärger) model as applied to diffusion in a system of randomly packed identical parallel cylinders with permeable walls, representing cells with permeable membranes, that may serve particularly as a model for axons in the white matter of the brain. By performing Monte Carlo simulations of restricted diffusion, we show that the Kärger model may provide a reasonable coarse-grained description of the diffusion-weighted signal in the long time limit, as long as the cell membranes are sufficiently impermeable, i.e. whenever the residence time in a cell is much longer than the time it takes to diffuse across it. For larger permeabilities, the exchange time obtained from fitting to the Kärger model overestimates the actual exchange time, leading to an underestimated value of cell membrane permeability.