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Experimental Studies |
1 From the Department of Radiology (Q.G.d.L., R.G.H.B.T., J.M.A.v.E., W.H.B.) and Angiogenesis Laboratory, Departments of Pathology and Internal Medicine (A.W.G.), Maastricht University Hospital, P. Debyelaan 25, 6202 AZ Maastricht, the Netherlands; and Laboratory of Macromolecular and Organic Chemistry (S.L., M.H.P.v.G.) and Department of Biomedical Engineering (M.H.P.v.G., J.M.A.v.E., W.H.B.), Eindhoven University of Technology, Eindhoven, the Netherlands. Received March 2, 2004; revision requested May 13; revision received June 4; accepted July 8. Supported in part by the Cardiovascular Research Institute, Maastricht, the Netherlands. Address correspondence to Q.G.d.L. (e-mail: qdlu@rdia.azm.nl).
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONMATERIALS AND METHODS RESULTSDISCUSSIONREFERENCES |
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MATERIALS AND METHODS: This study was approved by the ethical review committee. Maintenance and care of animals was in compliance with guidelines set by the institutional animal care committee. Dynamic contrast-enhanced MR imaging was performed with dendritic contrast agents in 16 mice with tumor xenografts; mice were placed in groups of four for each molecular weight of the contrast agent. The magnitude and spatial distribution of kinetic parameters (transfer coefficient [KPS] and plasma fraction [fPV]) were compared with molecular weight of the contrast agent by determining the Spearman correlation coefficient (r) and the quantitative relationship between the endothelial KPS and molecular weight.
RESULTS: Inverse relationships between molecular weight of contrast agent and KPS and fPV of tumor rim (r = –0.8, P < .001 and r = –0.5, P = .04, respectively) and core (r = –0.7, P = .004 and r = –0.6, P = .01, respectively) were observed. The quantitative relationship between KPS and molecular weight (MW) was KPS = 0.4/MW0.44. A decreasing stepwise pattern in fPV was noted between contrast agents with low (0.7- and 3.0-kDa) molecular weight and those with high (12- and 51-kDa) molecular weight.
CONCLUSION: Macromolecular permeability is best measured with high-molecular-weight contrast agents; endothelial KPS values measured with low-molecular-weight contrast agents incorporate tissue perfusion and permeability and demonstrate heterogeneous microcirculatory flow.
© RSNA, 2005
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODS RESULTSDISCUSSIONREFERENCES |
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One area of discussion in the field of dynamic contrast-enhanced MR imaging of tumor angiogenesis is the choice of contrast agent (4), particularly the molecular weight or particle size of the contrast agent. Results of previous experimental comparison studies performed with different contrast agents in tumor angiogenesis models have suggested that molecular weight of the contrast agent affects the measured KPS and fPV values (12,14). For example, KPS, which represents the rate of transfer of contrast agent from the blood to the interstitial space, is highly dependent on the permeability and surface area of the endothelium. As contrast agents with a low molecular weight have a large first-pass extraction, KPS values are dominated by flow in tumors. Alternatively, contrast agents with a high molecular weight leak from the blood more slowly, and transfer into the interstitial matrix is limited in relation to tumor blood flow. In this situation, KPS values will approximate the permeability surface area product. The KPS of contrast agents with an intermediate molecular weight is influenced both by permeability surface area product and by flow (ie, flow contamination).
In tumor angiogenesis, microvessel permeability and surface area may be greatly increased, but the microcirculatory flow may also be increased and highly heterogeneous (2,7,8). Thus, increases in flow levels and heterogeneity may be best assessed by using low-molecular-weight contrast agents. The fPV parameter might be best measured by using a high-molecular-weight MR contrast agent because of relatively long intravascular life times, and it might be overestimated when using low-molecular-weight contrast agents that rapidly diffuse from the vascular compartment to the interstitial space. These discussions have resulted from experimental work by using a variety of contrast agents (12,14). The contrast agents that have been evaluated to date (ie, low-molecular-weight gadolinium complexes, gadolinium complexes conjugated to linear polymers or albumin, and iron oxide particles) (4,9–14), however, may have been too different in molecular composition and paramagnetic properties to allow fair comparisons between different agents.
Gadolinium-based dendrimers are macromolecular MR contrast agents with well-defined molecular weights; most important, they are of equal chemical composition (15,16). The properties of gadolinium-based dendrimers suggest that these dendritic contrast agents might be ideal for comparing molecular weights for MR imaging of tumor angiogenesis.
Thus, the purpose of our study was to evaluate the relationship between dynamic contrast-enhanced MR imaging–derived kinetic parameters and contrast agents of equal chemical composition and configuration but with different molecular weights in a tumor angiogenesis model. We hypothesized that KPS and fPV would increase as the molecular weight of the MR contrast agent decreased.
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MATERIALS AND METHODS |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODS RESULTSDISCUSSIONREFERENCES |
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MR Imaging
MR imaging was performed (Q.G.d.L., S.L., W.H.B.) as described previously (10), with a small surface coil (diameter, 5 cm) and a 1.5-T system (Philips Medical Systems, Best, the Netherlands). The imaging protocol included a T2-weighted anatomic acquisition (multisection fast spin echo, echo train length of 28, repetition time msec/echo time msec of 3300/200, and flip angle of 90°) for locating and delineating the tumor, a precontrast T1-weighted measurement (three-dimensional fast field echo, 50/7, and flip angles of 2°, 5°, 10°, 15°, 25°, and 35°), and a T1-weighted dynamic contrast enhanced series (three-dimensional fast field echo, 50/7, and flip angle of 35°) with 55 dynamic volume acquisitions of 39 seconds each. The T1- and T2-weighted acquisitions had the same positioning with 16 transverse sections. Sections were 2.0 mm thick for T2-weighted acquisitions and 4.0 mm thick for T1-weighted acquisitions, for which adjacent sampled sections were displaced 2.0 mm and subsequently interpolated to 2.0-mm-thick sections during reconstruction. Matrix dimensions were 128 x 128, with a field of view of 64 x 64 mm; reconstructed voxel sizes were 0.5 x 0.5 x 2.0 mm.
Analysis of MR Imaging Data
MR imaging data were analyzed (Q.G.d.L., W.H.B.) by using a general kinetic two-compartment bidirectional exchange model as described previously (19) in the Matlab programming environment (MathWorks, Natick, Mass). In short, local T1 relaxation rates (ie, R1) of the precontrast time-averaged images and postcontrast image signal intensity time courses were used to determine the plasma concentration of the contrast agent in the aorta, which represents the arterial input function for each mouse individually and the tissue concentration in the tumor. Voxel-wise signal intensity time courses were converted to T1 relaxation rates (R1[t]). Application of the general kinetic two-compartment bidirectional exchange model (10,19) yielded the KPS and reflux rate (k) values, both of which are measured in milliliters per minute per 100 cm3 of tissue, and the fPV value, which is expressed as milliliters per 100 cm3 of tissue. The reflux rate describes the transfer from the interstitial space back to the plasma space. Kinetic analysis was performed for each tumor voxel in the central section through the tumor. Values for individual voxels were (a) collected for histogram analysis of KPS; (b) averaged to obtain whole tumor values of KPS, k, and fPV values for each tumor; and (c) used to create a color-coded map of KPS values for each tumor. To allow for inferences on differences between tumor rim and tumor core, regions of interest were drawn in consensus (Q.G.d.L., W.H.B.) to delineate the peripheral tumor margin (ie, rim) (thickness, about 2 mm) from the remaining central (ie, core) portion, respectively, by using the T2-weighted anatomic image.
To quantify the relationship between the mean whole tumor KPS value and molecular weight (MW) of the contrast agent, an author (W.H.B.) determined the parameters a, which is the KPS for molecular weight equal to 1 kDa, and power 
in the mathematic expression KPS = a/(MW) by using a minimum of least-squares linearized fitting procedure. Linearization of this equation was performed with log transformation of both sides: log KPS = (log a) – (log MW). After linearization, linear regression was applied (x = log MW and y = log KPS) to yield the slope ().
Blood circulation times and renal clearance rates were approximated for the dendritic contrast agents by means of visual comparison of normalized signal enhancement time courses for regions of interest drawn by means of consensus (Q.G.d.L., S.L., W.H.B.) in the aorta, renal parenchyma, renal pelvis, and bladder.
Statistical Analysis
The number of animals included was estimated by performing a power analysis (20) (95% confidence interval and 80% power) and considering a predetermined possible dropout rate of less than 10%; this amounted to four mice per contrast agent group, for a total of 16 animals. All pixels in the central MR section in each tumor (ie, tumor volume) were averaged for each contrast agent group and compared by using the two-tailed Student t test. Molecular weights of the contrast agents and the tumor volumes were compared with (a) average KPS, k, and fPV values for the whole tumor volume, tumor rim, and tumor core; (b) the rim–core ratio, defined as the quotient of tumor rim divided by tumor core values; and (c) the spatial heterogeneity, defined as the second moment (ie, the standard deviation) of the relative distribution of the voxel KPS values in a tumor, by using the one-tailed Spearman rank correlation coefficient, which allows for nonnormal distribution of variables. Histograms, normalized for the tumor extent, were created (Q.G.d.L., W.H.B.) with voxel KPS, k, and fPV values for each contrast agent to allow us to visually assess the distribution of the variables. Average KPS, k, and fPV values for the whole tumor, tumor rim, and tumor core were compared between the different contrast agent groups. Averaged whole tumor values for the 0.7- and 3.0-kDa groups were compared with those for the 12- and 51-kDa groups by using the one-tailed Student t test. Statistical analyses were performed by using commercial software (SPSS 11.0.1; SPSS, Chicago, Ill), and a P value of less than .05 was considered to indicate a statistically significant difference.
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RESULTS |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODS RESULTSDISCUSSIONREFERENCES |
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= 0.44 ± 0.14.
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fPV Values
Our results showed that decreases in fPV in relation to the molecular weight of contrast agents followed a stepwise pattern, with a sudden decrease in fPV values (Fig 2c) between contrast agents with a molecular weight of 3.0 kDa and those with a molecular weight of 12 kDa. Whole-tumor fPV values were between six and 10 times greater (P = .01) for the 0.7- and 3.0-kDa agents than for the 12- and 51-kDa agents (Table 2).
Plasma fraction values showed little difference between the tumor rim and tumor core when low-molecular-weight contrast agents were used, and fPV values were at least four times greater in the tumor rim than in the tumor core when high-molecular-weight contrast agents were used. Average rim–core fPV ratios were 1.1 ± 0.6, 3.4 ± 1.3, 10.7 ± 6.8, and 4.7 ± 4.0 for the 0.7-, 3.0-, 12-, and 51-kDa groups, respectively. Differences between tumor rim and tumor core fPV values showed a significant positive relationship (r = 0.5, P = .04) with the molecular weights of the MR contrast agents.
Correlation coefficient values between molecular weight and fPV value were –0.5 (P = .03) for the whole tumor, –0.6 (P = .01) for the tumor core, and –0.5 (P = .04) for the tumor rim. The differences in ranges in spatial distribution of fPV values showed an inverse relationship (r = –0.6, P = .02) with the molecular weight of the contrast agent.
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DISCUSSION |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODS RESULTSDISCUSSIONREFERENCES |
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Interpreting our results requires a detailed understanding of contrast agent kinetics in dynamic contrast-enhanced MR imaging. KPS represents the rate of transfer of particles (ie, leakage) from the blood to the interstitial space, and it is defined as the product of the flow (Fp) and the extraction fraction (E), which is calculated with the following equation: E = [1 – exp (–PS/Fp)], where PS is the permeability surface area product (14). With dynamic contrast-enhanced MR imaging, the basis for calculating this KPS value is determined by the leakage of an intravenously injected contrast agent. It is hypothesized that low-molecular-weight contrast agent molecules leak relatively easily from the blood through the interstitial matrix (away from the vessel) compared with high-molecular-weight contrast agents. If this is true, KPS values, which are measured by using low-molecular-weight contrast agents, will be influenced by the flow because their relatively fast rate of transfer to the interstitial space will increase as the blood flow increases and vice versa. In this situation (ie, permeability surface area product > product of the flow), the extraction fraction approaches a value of 1, and KPS will be relatively large and approximate the tumor blood flow. Alternatively, high-molecular-weight contrast agents leak from the blood and move through the interstitial matrix with relative difficulty. Transfer to the interstitial matrix is limited by the relatively low intrinsic permeability and is independent of tumor blood flow. In this situation (ie, permeability surface area product < product of the flow), KPS values will approximate permeability surface area product best. The KPS of intermediate-molecular-weight contrast agents is influenced by both permeability surface area product and product of the flow (ie, flow contamination).
Our results show that the dynamic contrast-enhanced MR imaging–derived kinetic parameters (ie, KPS and fPV) increase in magnitude and spatial heterogeneity as the molecular weight of dendritic contrast agent decreases.
The assumption that KPS represents the microvessel permeability surface area product when high-molecular-weight contrast agents are used but represents the flow when low-molecular-weight contrast agents are used is supported in the present study by two observations. First, the use of low-molecular-weight contrast agents resulted in increased magnitude and spatial heterogeneity of KPS compared with high-molecular-weight contrast agents. The increase in KPS magnitude, particularly KPS heterogeneity, is a result of the contribution of flow and an increase of permeability surface area product magnitude. Flow is known to be inhomogeneous in angiogenic regions (7,8); thus, it yields a heterogeneous pattern.
Second, the use of low-molecular-weight contrast agents resulted in higher rim–core KPS ratios compared with high-molecular-weight contrast agents. This finding supports the notion that KPS represents flow when low-molecular-weight contrast agents are used because angiogenesis-related increases in flow level and heterogeneity are most prominent in the rim of the tumor (7). Flow in the tumor core is additionally reduced in comparison with the tumor rim because of relatively high local pressures. Elevated interstitial fluid pressure is a pathophysiologic characteristic of most human and experimental tumors. Interstitial fluid pressure increases toward the deeper core layers of the tumor by a large gradient, which is associated with lower perfusion or flow levels compared with the tumor rim (21).
On the contrary, the entire tumor is expected to exhibit a high degree of leakiness (ie, high permeability surface area product) (8). As KPS values for low-molecular-weight contrast agents are increased by flow level and high-molecular-weight contrast agents are flow independent, the ratio between tumor rim and tumor core values of KPS will be higher for low-molecular-weight contrast agents than for high-molecular-weight contrast agents. Thus, relatively small rim–core differences in KPS, as measured by using high-molecular-weight contrast agents, support the notion that KPS represents microvessel permeability surface area product. Surface area is not expected to be an important contributing factor for differences in KPS rim–core ratios measured by using either low- or high-molecular-weight contrast agents. The found quantitative relationship KPS = 0.4/MW0.44 predicts that doubling of the molecular weight will reduce KPS values by approximately 25%.
The hypothesis that fPV values might be overestimated with rapidly diffusing low-molecular-weight contrast agents when compared with high-molecular-weight contrast agents is supported by the inverse relationship found between molecular weight of the contrast agents, although the correct fPV remains unknown. Our results also suggest a threshold effect, with a marked decrease of fPV between 3.0- and 12-kDa contrast agents. This step-wise decrease in fPV reflects the intravascular compartmentalization of molecules with a higher molecular weight. The high spatial variations of fPV values may reflect the degree of heterogeneity of the microcirculation, which as mentioned previously, is a characteristic feature of tumor angiogenesis (7).
Measured k values are in the same order of magnitude (mean k value ± standard deviation, 14.0 mL/100 cm3/sec ± 15.0) as reported (10) for MR evaluations in a similar model with the use of gadopentetate dimeglumine. The positive relationship observed between tumor core k values and molecular weight could have several explanations. Rates of diffusion through the interstitial matrix (ie, away from the vessel) were lower for high-molecular-weight contrast agents than for low-molecular-weight contrast agents, which might enhance local interstitial concentration (ie, near the vessel) and increase the chance to transfer back into the blood, resulting in slightly higher k values for the high-molecular-weight contrast agents.
It should be noted that the parameters KPS and k are related, but they are not equal. The reflux rate is the ratio of KPS and the extracellular extravascular space fraction. As low-molecular-weight contrast agents will have a higher rate of diffusion through the extracellular extravascular space, so will this space be larger, which may compensate for the higher KPS value in the ratio for the reflux rate. Another explanation might be that higher rates of lymphatic drainage caused the smaller reflux to the blood compartment for the contrast agents with a low molecular weight. Finally, the dendritic agents were assumed to have no cellular interactions or matrix binding because the overall charge of the agents is slightly negative; nevertheless, processes like endocytosis and the unpredictable dependency on molecular weight could also have affected the apparent reflux rate. Contradictory k values are reported (10,11) for high-molecular-weight contrast agents (iron oxide particles and gadolinium conjugated with albumin) in the order of 10 times less than (mean k value, less than 1) k values measured with the 51-kDa dendritic agent (mean k value, 19.1 ± 11.2). Thus, the positive relationship between tumor k values and molecular weight may not be generalized or extrapolated for all agents with a high molecular weight than the 51-kDa contrast agent. A possible explanation is that the 51-kDa contrast agent is cleared by the kidneys, albeit at a slower rate than the contrast agents with a low molecular weight, whereas iron oxide particles and albumin conjugates are not cleared by the kidneys and circulate in high concentrations for prolonged periods of time (10,11), thus preventing a reflux.
The results and implications of this study might be limited in several ways. The contrast agents that were used are experimental, and long-term effects are unknown because the mice were sacrificed immediately after imaging. The aim of this study was to correct for differences in excretion pathways and circulation properties by acquiring individual blood concentration time curves of the contrast agent for the arterial input function of each mouse.
Dose optimization studies were not performed. All contrast agents were administered with the same dose of gadolinium (ie, 0.03 mmol/kg). Traditionally, in MR studies for tumor angiogenesis, small-molecular-weight contrast agents (ie, gadopentetate dimeglumine) were administered at a dose of 0.1 mmol/kg, and high-molecular-weight contrast agents (ie, albumin-bound gadolinium dimeglumine) were administered at a dose of 0.03 mmol/kg. We chose to administer a gadolinium dose of 0.03 mmol/kg. When T1-weighted MR measurements with short echo times are used, as in this study, the signal enhancement depends predominantly on the T1 shortening of the contrast agent, while the T2* dependency is negligible. Alternatively, one could decide to match the signal enhancement per gadolinium atom between the different dendrimers; however, such an approach would still not account for the expected lower tumor concentrations for the molecules with a higher molecular weight, which do have higher T1 relaxivities. In the future, combining T1 relaxivities and known relationships between molecular weight and KPS, as found here, might prove to be a better approach to compare different contrast agents. For the application of the kinetic model, we calculated T1 relaxation rates from the nonlinear relation of a gradient-echo pulse sequence between the precontrast T1 value, the precontrast signal intensity, and the contrast-enhanced signal intensity. One might argue that the range of dendrimer relaxivities could have biased the correlation between KPS and molecular weight to be nonlinear by ignoring T2* effects. However, since we used a short echo time and obtained relatively low in vivo contrast agent concentrations, T2* effects are negligible; thus, they are too small to have confounded the correlations found in this study.
Independent measurements to validate accuracy of the estimates of KPS, k, or fPV were not performed here. Future studies might explore the accuracy of dynamic contrast-enhanced MR imaging–derived parameters as measured by using low-, intermediate-, or high-molecular-weight MR contrast agents in conjunction with validated absolute measurements of microcirculatory flow, permeability, surface area, and/or plasma volume.
Practical application: Results of this study may aid in choosing the best contrast agent for dynamic contrast-enhanced MR imaging. For example, these results may be used to evaluate effects of antiangiogenesis and other antitumor treatments. Depending on the biologic effects of the treatment strategy, high-molecular-weight contrast agents might be preferred over low-molecular-weight contrast agents in the evaluation of reductions in microvessel permeability and vascular volume. Low-molecular-weight contrast agents might be more applicable in the evaluation of therapeutic reductions in magnitude and heterogeneity of microcirculatory blood flow.
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ACKNOWLEDGMENTS |
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FOOTNOTES |
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Authors stated no financial relationship to disclose.
Author contributions: Guarantors of integrity of entire study, J.M.A.v.E., W.H.B.; study concepts and design, all authors; literature research, Q.G.d.L., S.L., M.H.P.v.G., A.W.G., W.H.B.; experimental studies, Q.G.d.L., S.L., A.W.G.; data acquisition, Q.G.d.L., S.L., W.H.B.; data analysis/interpretation, all authors; statistical analysis, Q.G.d.L., W.H.B.; manuscript preparation, Q.G.d.L., S.L., M.H.P.v.G., A.W.G., W.H.B.; manuscript definition of intellectual content, all authors; manuscript editing, Q.G.d.L., S.L., A.W.G., R.G.H.B.T., J.M.A.v.E., W.H.B.; manuscript revision/review and final version approval, all authors
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REFERENCES |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODS RESULTSDISCUSSIONREFERENCES |
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