Rapid measurement of arterial input function in mouse tail from projection phases

Toward precise arterial input functions derived from DCE-MRI through a novel extracorporeal circulation approach in mice

PURPOSE

Dynamic contrast-enhanced MRI can be used in pharmacokinetic models to quantify functional parameters such as perfusion and permeability. However, precise quantification in preclinical models is challenged by the difficulties to dynamically measure the true arterial blood contrast agent concentration. We propose a novel approach toward a precise and experimentally feasible method to derive the arterial input function from DCE-MRI in mice.

METHODS

Arterial blood was surgically shunted from the femoral artery to the tail vein and led through an extracorporeal circulation that resided on the head of brain tumor-bearing mice inside the FOV of a 9.4T MRI scanner. Dynamic 3D-FLASH scanning was performed after injection of gadobutrol with an effective resolution of 0.175 × 0.175 × 1 mm and a temporal resolution of 4 seconds. Pharmacokinetic modeling was performed using the extended Tofts and two-compartment exchange model.

RESULTS

Arterial input functions measured inside the extracorporeal circulation showed little noise, small interindividual variance, and typical curve shapes. Ex vivo and mass spectrometry validation measurements documented the influence of shunt flow velocity and hematocrit on estimation of contrast agent concentrations. Modeling of tumors and muscles allowed fitting of the recorded dynamic concentrations, resulting in quantitative plausible parameters.

CONCLUSION

The extracorporeal circulation allows deriving the contrast agent dynamics in arterial blood with high robustness and at acceptable experimental effort from DCE-MRI, previously not achievable in mice. It sets the basis for quantitative precise pharmacokinetic modeling in small animals to enhance the translatability of preclinical DCE-MRI measurements to patients.

Dynamic Contrast-Enhanced MRI

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

An extended reference region model for DCE-MRI that accounts for plasma volume

The reference region model (RRM) for dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) provides pharmacokinetic parameters without requiring the arterial input function. A limitation of the RRM is that it assumes that the blood plasma volume in the tissue of interest is zero, but this is often not true in highly vascularized tissues, such as some tumours. This study proposes an extended reference region model (ERRM) to account for tissue plasma volume. Furthermore, ERRM was combined with a two-fit approach to reduce the number of fitting parameters, and this was named the constrained ERRM (CERRM). The accuracy and precision of RRM, ERRM and CERRM were evaluated in simulations covering a range of parameters, noise and temporal resolutions. These models were also compared with the extended Tofts model (ETM) on in vivo glioblastoma multiforme data. In simulations, RRM overestimated K^trans by over 10% at v_p  = 0.01 under noiseless conditions. In comparison, ERRM and CERRM were both accurate, with CERRM showing better precision when noise was included. On in vivo data, CERRM provided maps that had the highest agreement with ETM, whilst also being robust at temporal resolutions as poor as 30 s. ERRM can provide pharmacokinetic parameters without an arterial input function in tissues with non-negligible v_p where RRM provides inaccurate estimates. The two-fit approach, named CERRM, further improves on the accuracy and precision of ERRM.

Multi-modal magnetic resonance imaging and histology of vascular function in xenografts using macromolecular contrast agent hyperbranched polyglycerol (HPG-GdF)

Macromolecular gadolinium (Gd)-based contrast agents are in development as blood pool markers for MRI. HPG-GdF is a 583 kDa hyperbranched polyglycerol doubly tagged with Gd and Alexa 647 nm dye, making it both MR and histologically visible. In this study we examined the location of HPG-GdF in whole-tumor xenograft sections matched to in vivo DCE-MR images of both HPG-GdF and Gadovist. Despite its large size, we have shown that HPG-GdF extravasates from some tumor vessels and accumulates over time, but does not distribute beyond a few cell diameters from vessels. Fractional plasma volume (fPV) and apparent permeability-surface area product (aPS) parameters were derived from the MR concentration-time curves of HPG-GdF. Non-viable necrotic tumor tissue was excluded from the analysis by applying a novel bolus arrival time (BAT) algorithm to all voxels. aPS derived from HPG-GdF was the only MR parameter to identify a difference in vascular function between HCT116 and HT29 colorectal tumors. This study is the first to relate low and high molecular weight contrast agents with matched whole-tumor histological sections. These detailed comparisons identified tumor regions that appear distinct from each other using the HPG-GdF biomarkers related to perfusion and vessel leakiness, while Gadovist-imaged parameter measures in the same regions were unable to detect variation in vascular function. We have established HPG-GdF as a biocompatible multi-modal high molecular weight contrast agent with application for examining vascular function in both MR and histological modalities.

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

PURPOSE

To establish the experimental factors that dominate the uncertainty of hemodynamic parameters in commonly used pharmacokinetic models.

METHODS

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.

RESULTS

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.

CONCLUSION

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.