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Assessment of Single Kidney GFR by Dynamic Contrast-enhanced MRI (DCE-MRI):

DCE-MRI involves the serial acquisition of MR images of a tissue of interest before and after an intravenous injection of contrast agent (CA). As the CA enters into the tissue under investigation, the T1, T2 and T2* values of tissue water decrease to an extent that is determined by the concentration of the agent. By considering a set of images acquired before, during, and after a CA infusion, a region of interest (ROI) or individual voxels will display a characteristic signal intensity time course, which can be related to CA concentration. By fitting the DCE-MRI data to an appropriate pharmacokinetic model, physiological parameters can be extracted that relate to EF, GFR and renal blood flow. Determination of GFR by MRI is feasible because the standard CA, Gd-DTPA, is freely filtered at the glomerulus and is not excreted nor reabsorbed (REF). VUIIS investigators have advanced DCE-MRI to allow for data to be acquired at both increased signal to noise and increased spatial resolution (7, 8, 9, 10). Numerous studies have attempted to use DCE-MRI to assess renal function in humans (11, 12, 13). A recent study by Hackstein et al demonstrated a good correlation between MRI-derived renal function and the GFR as measured by iopromide (12). But there has been a paucity of data available in which truly quantitative modeling is applied to DCE-MRI data applied to the liver. Only very recently, has a realistic model for glomerular filtration been proposed for the analysis of DCE-MRI data in the kidney (14). We propose to apply, refine, and optimize this model in the kidney diseases described in this proposal. We have extensive experience in building, applying, and validating such models and we anticipate being able to synthesize the DCE-MRI metrics with other functional parameters to provide a more complete (imaging) description of the kidney.

(Preliminary DCE-MRI Studies)
Figure 5 shows kidney and muscle DCE-MRI signal time courses acquired using a fast multiecho gradient echo sequence (1 image / sec). This sequence enables a rapid characterization of the contrast agent kinetics and when acquired simultaneously with a respiratory gating system can be used to removal single time points corrupted by motion artifacts. We have previosuly shown that such a sequence can be used to separate and quantify changes in T1 and T2* so that a more accurate assessment of contrast agent contration can be derived. For the time curves shown in Figure 5 no images were removed. The initial uptake of contrast agent into the kidney was much faster than that found in muscle tissue following a relatively slow injection (3.5 µL / sec, 100 µL total volume, 0.1 mmol / kg concentration). We also noted substantial spatial heterogeneity in the shape of the time curves across the kidney which indicates the sensitivity of this approach to the underlying tissue hemodynamics, vascular characteristics and microenvironment.

(Developmental DCE-MRI Studies)
We will develop improved methods of using dynamic contrast enhancement to assess renal GFR and clearance. Our group will continue the development of pharmacokinetic models of dynamic contrast enhancement (DCE-MRI) from exogenous agents in tissues. Dr. Yankeelov, who has extensive experience in the development of DCE-MRI models, recently developed a reference region model for application to cancer which allows for extraction of the pharmacokinetic parameters Ktrans and ve at a level of precision previously not feasible. The repeatability and correlation with previous methods of DCE-MRI analysis of this technique has been assessed and has enabled us to utilize a minimum number of animals in cancer related studies (8, 9). We have recently incorporated the effects of water exchange into this model making it one of the most rigorous and precise DCE-MRI models currently available(Yankeelov in press). Future work in this field will focus on building a combined diffusion-perfusion model to separate voxels enhanced due to active deliver of the contrast agent (perfusion) from those enhancing do to contrast agent diffusion. For the proposed core Dr. Yankeelov will optimize similar models specific for the dynamics and physiology of kidney tracer kinetics enabling the computation of renal GFR and clearance rates. In particular, a significant limitation of current DCE-MRI analysis based on compartmental modeling is the requirement of measuring the time course of the concentration of the tracer in the blood plasma, the so-called arterial input function. This puts fundamental limits on the spatial resolution and signal-to-noise that can be obtained during a DCE-MRI study. We have experience constructing models that eliminate this necessity in other applications of DCE-MRI and we propose to do the same here. To test the accuracy of the methodology, we will compare MRI-derived GFR measures to those obtained using the FITC-inulin clearance method in mice with uni-nephrectomy.

Publications for DCE-MRI (GFR, Blood flow) (8)

Yankeelov TE, Cron GO, Addison CL, Wallace JC, Wilkins RC, Pappas BA, Santyr GE, Gore JC. Comparison of a reference region model with direct measurement of an AIF in the analysis of DCE-MRI data. Magn Reson Med (2007) 57:353-61
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Models have been developed for analyzing dynamic contrast-enhanced (DCE)-MRI data that do not require measurements of the arterial input function (AIF). In this study, experimental results obtained from a reference region (RR) analysis are compared with results of an AIF analysis in the same set of five animals (four imaged twice, yielding nine data sets), returning estimates of the volume transfer constant (Ktrans) and the extravascular extracellular volume fraction (ve). Student's t-test values for comparisons of Ktrans and ve between the two models were 0.14 (P=0.88) and 0.85 (P>0.4), respectively (where the high P-values indicate no significant difference between values derived from the two models). Linear regression analysis indicated there was a correlation between Ktrans extracted by the two methods: r2=0.80, P=0.001 (where the low P-value indicates a significant linear correlation). For ve there was no such correlation (r2=0.02). The mean (absolute) percent difference between the models was 22.0% for Ktrans and 28.1% for ve. However, the RR parameter values were much less precise than the AIF method. The mean SDs for Ktrans and ve for the RR analysis were 0.024 min-1 and 0.06, respectively, vs. 0.002 min-1 and 0.03 for AIF analysis. CI Copyright (c) 2007 Wiley-Liss, Inc.

Lee VS, Rusinek H, Bokacheva L, Huang AJ, Oesingmann N, Chen Q, Kaur M, Prince K, Song T, Kramer EL, Leonard EF. Renal function measurements from MR renography and a simplified multicompartmental model. Am J Physiol Renal Physiol (2007) 292:F1548-59
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The purpose of this study was to determine the accuracy and sources of error in estimating single-kidney glomerular filtration rate (GFR) derived from low-dose gadolinium-enhanced T1-weighted MR renography. To analyze imaging data, MR signal intensity curves were converted to concentration vs. time curves, and a three-compartment, six-parameter model of the vascular-nephron system was used to analyze measured aortic, cortical, and medullary enhancement curves. Reliability of the parameter estimates was evaluated by sensitivity analysis and by Monte Carlo analyses of model solutions to which random noise had been added. The dominant sensitivity of the medullary enhancement curve to GFR 1-4 min after tracer injection was supported by a low coefficient of variation in model-fit GFR values (4%) when measured data were subjected to 5% noise. These analyses also showed the minimal effects of bolus dispersion in the aorta on parameter reliability. Single-kidney GFR from MR renography analyzed by the three-compartment model (4.0-71.4 ml/min) agreed well with reference measurements from (99m)Tc-DTPA clearance and scintigraphy (r = 0.84, P < 0.001). Bland-Altman analysis showed an average difference of 11.9 ml/min (95% confidence interval = 5.8-17.9 ml/min) between model and reference values. We conclude that a nephron-based multicompartmental model can be used to derive clinically useful estimates of single-kidney GFR from low-dose MR renography.

Yankeelov TE, DeBusk LM, Billheimer DD, Luci JJ, Lin PC, Price RR, Gore JC. Repeatability of a reference region model for analysis of murine DCE-MRI data at 7T. J Magn Reson Imaging (2006) 24:1140-7
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PURPOSE: To test the repeatability of a reference region (RR) model for the analysis of dynamic contrast-enhanced MRI (DCE-MRI) in a mouse model of cancer at high field. MATERIALS AND METHODS: Seven mice were injected with 10(6) 4T1 mammary carcinoma cells and imaged eight to 10 days later on a Varian 7.0T scanner. Two DCE-MRI studies were performed for each mouse (separated by 2.5 hours). The RR model was used to analyze the data, and returned estimates on the perfusion-permeability index (Ktrans) for the RR and the tissue of interest (TOI), as well as the extravascular extracellular volume fraction (ve) for the TOI. RESULTS: When the first injection was compared with the second injection, all parameters tested were highly correlated (r2=0.90, 0.62, 0.82 for the RR Ktrans, TOI Ktrans, and TOI ve, respectively, with P<0.001 for all). To observe a statistically significant change (at the 5% level) in a treatment study with seven animals in each group, log10 changes of 0.084 and 0.077 in the tumor Ktrans and ve, respectively, are required. CONCLUSION: If a reliable arterial input function (AIF) is unavailable, the RR model is a reasonable alternative to measuring MRI contrast-agent (CA) kinetics in mouse models of cancer at high field. CI Copyright (c) 2006 Wiley-Liss, Inc.

Buckley DL, Shurrab AE, Cheung CM, Jones AP, Mamtora H, Kalra PA. Measurement of single kidney function using dynamic contrast-enhanced MRI: comparison of two models in human subjects. J Magn Reson Imaging (2006) 24:1117-23
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PURPOSE: To compare two methods for assessing the single kidney glomerular filtration rate (SK-GFR) in humans using dynamic contrast-enhanced (DCE)-MRI. MATERIALS AND METHODS: Images were acquired from 39 separate MR studies of patients with atherosclerotic renovascular disease (ARVD). Data from the kidneys and descending aorta were analyzed using both a Rutland-Patlak plot and a compartmental model. MR estimates of the SK-GFR were compared with standard radioisotope measures in a total of 75 kidneys. RESULTS: Estimates of renal function using both techniques correlated well with radioisotope-assessed SK-GFR (Spearman's rho=0.81, Rutland-Patlak; rho=0.71, compartmental model). The Rutland-Patlak approach provided a near one-to-one correspondence, while the compartmental method tended to overestimate SK-GFR. However, the compartmental model fits to the experimental data were significantly better than those obtained using the Rutland-Patlak approach. CONCLUSION: DCE-MRI of the kidneys provides data that correlate well with reference measures of SK-GFR. However, further work, including image registration, is needed to isolate measurement of glomerular filtration to the level of the renal cortex. CI Copyright (c) 2006 Wiley-Liss, Inc.

Yankeelov TE, Niermann KJ, Huamani J, Kim DW, Quarles CC, Fleischer AC, Hallahan DE, Price RR, Gore JC. Correlation between estimates of tumor perfusion from microbubble contrast-enhanced sonography and dynamic contrast-enhanced magnetic resonance imaging. J Ultrasound Med (2006) 25:487-97
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OBJECTIVE: We compared measurements of tumor perfusion from microbubble contrast-enhanced sonography (MCES) and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in an animal tumor model. METHODS: Seven mice were implanted with Lewis lung carcinoma cells on their hind limbs and imaged 14 days later with a Philips 5to 7-MHz sonography system (Philips Medical Systems, Andover, MA) and a Varian 7.0-T MRI system (Varian, Inc, Palo Alto, CA). For sonographic imaging 100 microL of a perfluoropropane microbubble contrast agent (Definity; Bristol-Myers Squibb Medical Imaging, Billerica, MA) was injected and allowed to reach a pseudo steady state, after which a high-mechanical index pulse was delivered to destroy the microbubbles within the field of view, and the replenishment of the microbubbles was imaged for 30 to 60 seconds. The MRI included acquisition of a T(10) map and 35 serial T(1)-weighted images (repetition time, 100 milliseconds; echo time, 3.1 milliseconds; alpha, 30 degrees ) after the injection of 100 microL of 0.2-mmol/kg gadopentetate dimeglumine (Magnevist; Berlex, Wayne, NJ). Region-of-interest and voxel-by-voxel analyses of both data sets were performed; microbubble contrast-enhanced sonography returned estimates of microvessel cross-sectional area, microbubble velocity, and mean blood flow, whereas DCE-MRI returned estimates of a perfusion-permeability index and the extravascular extracellular volume fraction. RESULTS: Comparing similar regions of tumor tissue seen on sonography and MRI, region-of-interest analyses revealed a strong (r(2) = 0.57) and significant relationship (P < .002) between the estimates of perfusion obtained by the two modalities. CONCLUSIONS: Microbubble contrast-enhanced sonography can effectively depict intratumoral heterogeneity in preclinical xenograft models when voxel-by-voxel analysis is performed, and this analysis correlates with similar DCE-MRI measurements.

Hackstein N, Kooijman H, Tomaselli S, Rau WS. Glomerular filtration rate measured using the Patlak plot technique and contrast-enhanced dynamic MRI with different amounts of gadolinium-DTPA. J Magn Reson Imaging (2005) 22:406-14
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We determined the optimum gadolinium (Gd)-DTPA dose and time window for calculating the glomerular filtration rate (GFR) using contrast-enhanced (CE) dynamic MRI and the Patlak plot technique. Twelve adult volunteers with healthy kidneys were included in the study. As a reference method the GFR was measured by iopromide plasma clearance. A three-dimensional gradient-echo (GRE) sequence with a flip angle of 50 degrees was used for MRI. Signal was measured using a body surface coil with four elements. Each volunteer was examined on four days using 2 mL, 4 mL, 8 mL, or 16 mL of Gd-DTPA 0.5 mmol/mL dissolved with sodium chloride (NaCl) 0.9% to a total of 60 mL. The injection rate was 1 mL/second. A Patlak plot was calculated from the kidney and aorta signals. The mean reference GFR was 133 mL/min (min-max, 116-153 mL/min). The best correlation of GFR calculated from MRI data compared to the reference method was found in a time window 30-90 seconds after aortic signal rise using 16 mL Gd-DTPA. Pearson's correlation coefficient was r = 0.83, and the standard deviation (SD) from the line of regression was 10.5 mL/minute. We found a significantly lower average GFR(MR) using 16 mL Gd-DTPA compared to 4 mL and 2 mL in the late time window 60-120 seconds post aortic rise. A dose of 16 mL Gd-DTPA was optimal for measuring GFR using dynamic MRI and the Patlak plot technique. The slope should be measured in a time window of 30-90 seconds post aortic rise. CI (c) 2005 Wiley-Liss, Inc.

Yankeelov TE, Luci JJ, Lepage M, Li R, Debusk L, Lin PC, Price RR, Gore JC. Quantitative pharmacokinetic analysis of DCE-MRI data without an arterial input function: a reference region model. Magn Reson Imaging (2005) 23:519-29
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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.

Annet L, Hermoye L, Peeters F, Jamar F, Dehoux JP, Van Beers BE. Glomerular filtration rate: assessment with dynamic contrast-enhanced MRI and a cortical-compartment model in the rabbit kidney. J Magn Reson Imaging (2004) 20:843-9
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PURPOSE: To describe the use of MRI and a cortical-compartment model to measure the glomerular filtration rate (GFR), and compare the results with those obtained with the Patlak-Rutland model. MATERIALS AND METHODS: Dynamic MRI of rabbit kidneys was performed during and after injection of gadoterate dimeglumine. The enhancement curves in the aorta and the kidney were analyzed with the cortical-compartment and Patlak-Rutland models to assess the GFR. RESULTS: A substantial correlation was observed between the GFR measured with MRI using the cortical-compartment model and the plasma clearance of 51Cr-EDTA (r=0.821, P=0.004). No significant correlation was observed between the 51Cr-EDTA clearance (r=0.628, P=0.052) and the GFR obtained with the Patlak-Rutland model in regions of interest (ROIs) encompassing the renal cortex and medulla. A Bland and Altman analysis showed that GFR(cortical) (compartment) agreed better with the 51Cr-EDTA clearance compared to GFR(Patlak) when ROIs were limited to the cortex. However, the GFR values obtained by MRI were lower than the plasma clearance of 51Cr-EDTA. CONCLUSION: MRI with a cortical-compartment model provides more accurate assessments of glomerular filtration than the Patlak-Rutland model.

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Last updated on 2013-11-06 Moderated by Takamune Takahashi