Precise measurement of renal filtration and vascular parameters using a two-compartment model for dynamic contrast-enhanced MRI of the kidney gives realistic normal values.
ABSTRACT To model the uptake phase of T(1)-weighted DCE-MRI data in normal kidneys and to demonstrate that the fitted physiological parameters correlate with published normal values.
The model incorporates delay and broadening of the arterial vascular peak as it appears in the capillary bed, two distinct compartments for renal intravascular and extravascular Gd tracer, and uses a small-vessel haematocrit value of 24%. Four physiological parameters can be estimated: regional filtration K ( trans ) (ml min(-1) [ml tissue](-1)), perfusion F (ml min(-1) [100 ml tissue](-1)), blood volume v ( b ) (%) and mean residence time MRT (s). From these are found the filtration fraction (FF; %) and total GFR (ml min(-1)). Fifteen healthy volunteers were imaged twice using oblique coronal slices every 2.5 s to determine the reproducibility.
Using parenchymal ROIs, group mean values for renal biomarkers all agreed with published values: K ( trans ): 0.25; F: 219; v ( b ): 34; MRT: 5.5; FF: 15; GFR: 115. Nominally cortical ROIs consistently underestimated total filtration (by ~50%). Reproducibility was 7-18%. Sensitivity analysis showed that these fitted parameters are most vulnerable to errors in the fixed parameters kidney T(1), flip angle, haematocrit and relaxivity.
These renal biomarkers can potentially measure renal physiology in diagnosis and treatment.
• Dynamic contrast-enhanced magnetic resonance imaging can measure renal function. • Filtration and perfusion values in healthy volunteers agree with published normal values. • Precision measured in healthy volunteers is between 7 and 15%.
Full-textDOI: · Available from: Marica Cutajar, May 30, 2015
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ABSTRACT: To investigate the reproducibility of arterial spin labelling (ASL) and dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) and quantitatively compare these techniques for the measurement of renal blood flow (RBF). Sixteen healthy volunteers were examined on two different occasions. ASL was performed using a multi-TI FAIR labelling scheme with a segmented 3D-GRASE imaging module. DCE MRI was performed using a 3D-FLASH pulse sequence. A Bland-Altman analysis was used to assess repeatability of each technique, and determine the degree of correspondence between the two methods. The overall mean cortical renal blood flow (RBF) of the ASL group was 263 ± 41 ml min(-1) [100 ml tissue](-1), and using DCE MRI was 287 ± 70 ml min(-1) [100 ml tissue](-1). The group coefficient of variation (CVg) was 18 % for ASL and 28 % for DCE-MRI. Repeatability studies showed that ASL was more reproducible than DCE with CVgs of 16 % and 25 % for ASL and DCE respectively. Bland-Altman analysis comparing the two techniques showed a good agreement. The repeated measures analysis shows that the ASL technique has better reproducibility than DCE-MRI. Difference analysis shows no significant difference between the RBF values of the two techniques. • Reliable non-invasive monitoring of renal blood flow is currently clinically unavailable. • Renal arterial spin labelling MRI is robust and repeatable. • Renal dynamic contrast-enhanced MRI is robust and repeatable. • ASL blood flow values are similar to those obtained using DCE-MRI.European Radiology 03/2014; 24(6). DOI:10.1007/s00330-014-3130-0 · 4.34 Impact Factor
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ABSTRACT: This study compared three methods for analyzing DCE-MRI data with a reference region (RR) model: a linear least-square fitting with numerical analysis (LLSQ-N), a nonlinear least-square fitting with numerical analysis (NLSQ-N), and an analytical analysis (NLSQ-A). The accuracy and precision of estimating the pharmacokinetic parameter ratios KR and VR, where KR is defined as a ratio between the two volume transfer constants, K(trans,TOI) and K(trans,RR), and VR is the ratio between the two extracellular extravascular volumes, ve,TOI and ve,RR, were assessed using simulations under various signal-to-noise ratios (SNRs) and temporal resolutions (4, 6, 30, and 60s). When no noise was added, the simulations showed that the mean percent error (MPE) for the estimated KR and VR using the LLSQ-N and NLSQ-N methods ranged from 1.2% to 31.6% with various temporal resolutions while the NLSQ-A method maintained a very high accuracy (<1.0×10(-4) %) regardless of the temporal resolution. The simulation also indicated that the LLSQ-N and NLSQ-N methods appear to underestimate the parameter ratios more than the NLSQ-A method. In addition, seven in vivo DCE-MRI datasets from spontaneously occurring canine brain tumors were analyzed with each method. Results for the in vivo study showed that KR (ranging from 0.63 to 3.11) and VR (ranging from 2.82 to 19.16) for the NLSQ-A method were both higher than results for the other two methods (KR ranging from 0.01 to 1.29 and VR ranging from 1.48 to 19.59). A temporal downsampling experiment showed that the averaged percent error for the NLSQ-A method (8.45%) was lower than the other two methods (22.97% for LLSQ-N and 65.02% for NLSQ-N) for KR, and the averaged percent error for the NLSQ-A method (6.33%) was lower than the other two methods (6.57% for LLSQ-N and 13.66% for NLSQ-N) for VR. Using simulations, we showed that the NLSQ-A method can estimate the ratios of pharmacokinetic parameters more accurately and precisely than the NLSQ-N and LLSQ-N methods over various SNRs and temporal resolutions. All simulations were validated with in vivo DCE MRI data.Magnetic Resonance Imaging 04/2014; 32(7). DOI:10.1016/j.mri.2014.04.007 · 2.02 Impact Factor
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ABSTRACT: Renal plasma flow (RPF) (derived from renal blood flow, RBF) and glomerular filtration rate (GFR) allow the determination of the filtration fraction (FF), which may have a role as a non-invasive renal biomarker. This is a hypothesis-generating pilot study assessing the effect of nephrectomy on renal function in healthy kidney donors. Eight living kidney donors underwent arterial spin labelling (ASL) magnetic resonance imaging (MRI) and GFR measurement prior to and 1 year after nephrectomy. Chromium-51 labelled ethylenediamine tetraacetic acid ((51)Cr-EDTA) with multi-blood sampling was undertaken and GFR calculated. The RBF and GFR obtained were used to calculate FF. All donors showed an increase in single kidney GFR of 24 - 75 %, and all but two showed an increase in FF (-7 to +52 %) after nephrectomy. The increase in RBF, and hence RPF, post-nephrectomy was not as great as the increase in GFR in seven out of eight donors. As with any pilot study, the small number of donors and their relatively narrow age range are potential limiting factors. The ability to measure RBF, and hence RPF, non-invasively, coupled with GFR measurement, allows calculation of FF, a biomarker that might provide a sensitive indicator of loss of renal reserve in potential donors. • Non-invasive MRI measured renal blood flow and calculated renal plasma flow. • Effect of nephrectomy on blood flow and filtration in donors is presented. • Calculated filtration fraction may be a useful new kidney biomarker.European Radiology 02/2015; DOI:10.1007/s00330-015-3594-6 · 4.34 Impact Factor