Calculation of the renal perfusion and glomerular filtration rate from the renal impulse response obtained with MRI

Hermoye, Laurent; Annet, Laurence; Lemmerling, Philippe; Peeters, Frank; Jamar, François; Gianello, Pierre; Huffel, Sabine Van; Beers, Bernard E. Van

doi:10.1002/mrm.20026

Cited by 52 publications

(113 citation statements)

References 37 publications

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“…Several approaches have been proposed to analyze renography data, including the upslope method (2), deconvolution (3,4), the Rutland-Patlak method (5,6), and renal kinetic modeling (7)(8)(9)(10). The key prerequisite is the ability to segment dynamic MR images into functional regions (i.e., the cortical and medullary compartments).…”

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confidence: 99%

Performance of an automated segmentation algorithm for 3D MR renography

Rusinek

Boykov

Kaur

et al. 2007

Magnetic Resonance in Med

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The accuracy and precision of an automated graph-cuts (GC) segmentation technique for dynamic contrast-enhanced (DCE) 3D MR renography (MRR) was analyzed using 18 simulated and 22 clinical datasets. For clinical data, the error was 7.2 ؎ 6.1 cm 3 for the cortex and 6.5 ؎ 4.6 cm 3 for the medulla. The precision of segmentation was 7.1 ؎ 4.2 cm 3 for the cortex and 7.2 ؎ 2.4 cm 3 for the medulla. Compartmental modeling of kidney function in 22 kidneys yielded a renal plasma flow (RPF) error of 7.5% ؎ 4.5% and single-kidney GFR error of 13.5% ؎ 8.8%. The precision was 9.7% ؎ 6.4% for RPF and 14.8% ؎ 11.9% for GFR. It took 21 min to segment one kidney using GC, compared to 2.5 hr for manual segmentation. One technique to determine renal function consists of the intravenous injection of radioactive tracer followed by assessment of its plasma clearance 2-4 hr later. This technique is time-consuming, requires multiple blood samples, and measures only the global glomerular filtration rate (GFR)-a disadvantage when asymmetric or unilateral renal disease is present. The gold standard technique for assessing single-kidney GFR is inulin clearance, but this method is too invasive and complex for routine clinical application. As an alternative, dynamic gamma camera imaging with 99m Tc-DTPA has been shown to provide single-kidney GFR by analysis of the renal radioactivity. By combining measures of renal physiology with depiction of anatomical detail, dynamic contrast-enhanced (DCE) 3D MR renography (MRR) has the potential to improve upon nuclear medicine techniques and also provide useful functional information to supplement anatomic renal MRI examinations (1). Good spatial, temporal, and contrast resolution is achievable with current contrast-enhanced dynamic protocols, whereby serial 3D MR images of the kidneys are generated following an injection of contrast material. Gadolinium (Gd) chelates, such as gadopentetate dimeglumine (Gd-DTPA), are suitable MR contrast agents because they are freely filtered at the glomerulus without tubular secretion or resorption.Several approaches have been proposed to analyze renography data, including the upslope method (2), deconvolution (3,4), the Rutland-Patlak method (5,6), and renal kinetic modeling (7-10). The key prerequisite is the ability to segment dynamic MR images into functional regions (i.e., the cortical and medullary compartments). Fitting concentration-time activity (CTA) curves to kinetic models yields perfusion and filtration rates per unit volume of tissue. These kinetic rates multiplied by the cortical and medullary volumes (determined from segmented images) give the renal plasma flow (RPF) and GFR for the entire kidney.Accurate segmentation of contrast-enhanced MRR data remains a difficult task. Dynamic 3D MR images of the abdomen suffer from partial-volume and respiratory-motion artifacts and have a relatively low signal-to-noise ratio (SNR). Other sources of error include signal nonuniformity and wraparound artifacts. The presence of cysts and renal masses, and reduced...

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confidence: 99%

Performance of an automated segmentation algorithm for 3D MR renography

Rusinek

Boykov

Kaur

et al. 2007

Magnetic Resonance in Med

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“…Dynamic contrast enhanced MRI is a promising noninvasive method for imaging renal perfusion and function (1)(2)(3)(4)(5), since it avoids the use of ionizing radiation and combines high temporal and spatial resolution. Moreover, Gd-DTPA is very well tolerated, not nephrotoxic, and has properties comparable to the radioisotopic 99mTc-DTPA (6,7).…”

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confidence: 99%

“…Experiments with a rabbit model (1) have shown that Gd-DTPA enhanced bolus tracking and a deconvolution analysis of ROI signals permit quantitative measures of perfusion and filtration, independent of the effect of the shape and size of the bolus. On the other hand, results obtained with an intravascular contrast agent have shown that a pixel-by-pixel approach to perfusion quantification can be a useful tool for distinguishing normality from renal artery stenosis in dogs as well as humans (2,3).…”

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confidence: 99%

Quantification of renal perfusion and function on a voxel‐by‐voxel basis: A feasibility study

Dujardin

Sourbron

Luypaert

et al. 2005

Magnetic Resonance in Med

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The feasibility of a voxel-by-voxel deconvolution analysis of T 1 -weighted DCE data in the human kidney and its potential for obtaining quantification of perfusion and filtration was investigated. Measurements were performed on 14 normal humans and 1 transplant at 1.5 T using a Turboflash sequence. Signal time-courses were converted to tracer concentrations and deconvolved with an aorta AIF. Parametric maps of relative renal blood flow (rRBF), relative renal volume of distribution (rRVD), relative mean transit time (rMTT), and whole cortex extraction fraction (E) were obtained from the impulse response functions. For the normals average cortical rRBF, rRVD, rMTT, and E were 1.6 mL/min/mL (SD 0.8), 0.4 mL/mL (SD 0.1), 17s (SD 7), and 22.6% (SD 6.1), respectively. A gradual voxelwise rRBF increase is found from the center of two infarction zones toward the edges. Voxel IRFs showed more detail on the nefron substructure than ROI IRFs. In conclusion, quantitative voxelwise perfusion mapping based on deconvolved T 1 -DCE renal data is feasible, but absolute quantification requires inflow correction. rRBF maps and quantitative values are sufficiently sensitive to detect perfusion abnormality in pathologic areas, but further research is necessary to separate perfusion from extraction and to characterize the different compartments of the nephron on the ( Key words: renal; T-weighted; perfusion; deconvolution; quantificationDynamic contrast enhanced MRI is a promising noninvasive method for imaging renal perfusion and function (1-5), since it avoids the use of ionizing radiation and combines high temporal and spatial resolution. Moreover, Gd-DTPA is very well tolerated, not nephrotoxic, and has properties comparable to the radioisotopic 99mTc-DTPA (6,7). Tissue perfusion imaging with dynamic Gd-DTPA enhanced MRI therefore offers the potential for obtaining important information about organ viability, anatomy, and function in the normal as well as in the compromised kidney.Experiments with a rabbit model (1) have shown that Gd-DTPA enhanced bolus tracking and a deconvolution analysis of ROI signals permit quantitative measures of perfusion and filtration, independent of the effect of the shape and size of the bolus. On the other hand, results obtained with an intravascular contrast agent have shown that a pixel-by-pixel approach to perfusion quantification can be a useful tool for distinguishing normality from renal artery stenosis in dogs as well as humans (2,3).In this study we investigate the combination of both approaches: a pixel-by-pixel deconvolution analysis in the human kidney, using Gd-DTPA enhanced bolus tracking. We investigate the quality of the resulting parametric maps, evaluate to what extent they represent perfusion and extraction, and assess the potential of the technique for obtaining reliable quantification of renal blood flow and a measure of filtration. We also investigate the possibility of obtaining other parameters like the tracers' volume of distribution and mean transit time. Our first results...

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“…Whole kidney GFR was estimated from the calculated tubular flow per mL and assuming a cortical volume of 70.4 cm 3 in adolescent healthy pigs (26,27).…”

Section: Postprocessingmentioning

confidence: 99%

Comparison of Gd‐DTPA and Gd‐BOPTA for studying renal perfusion and filtration

Notohamiprodjo

Pedersen

Gläser

et al. 2011

Magnetic Resonance Imaging

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Purpose: To measure the systematic error in perfusion and filtration parameters derived from magnetic resonance (MR) renography caused by protein binding of MR contrast agents. Materials and Methods:Eight healthy Danish Landrace pigs were examined with dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). In four pigs a bolus of gadopentetate-dimeglumine (Gd-DTPA; no protein binding) was injected, followed by gadobenate-dimeglumine (Gd-BOPTA; 10% protein binding). The order was reversed in the other four pigs. A two-compartment filtration model was generalized to allow for protein binding and fitted to whole-cortex region of interest (ROI) curves. Single-kidney plasma flow and volume, tubular flow (or GFR), and tubular transit time of both agents were compared. Results:The data show a strong systematic underestimation (P < 0.001) in GFR by Gd-BOPTA (33 6 7.2%), and no significant differences (P > 0.05) in plasma flow (2.2 6 18%), plasma volume (À1.7 6 7.8%) and tubular transit time (3.1 6 7.2%). The order of injection had no significant effect. Conclusion:Theory and experiments agree that perfusion parameters of both agents are comparable, whereas GFR is underestimated with Gd-BOPTA due to the dependence of relaxivity on protein content. Hence, GFR cannot be measured with protein-bound contrast agents, but the proposed dual-agent protocol may produce new functional indices measuring protein filtration.

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Calculation of the renal perfusion and glomerular filtration rate from the renal impulse response obtained with MRI

Cited by 52 publications

References 37 publications

Performance of an automated segmentation algorithm for 3D MR renography

Performance of an automated segmentation algorithm for 3D MR renography

Quantification of renal perfusion and function on a voxel‐by‐voxel basis: A feasibility study

Comparison of Gd‐DTPA and Gd‐BOPTA for studying renal perfusion and filtration

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