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Published in: Pediatric Radiology 5/2020

01-05-2020 | Magnetic Resonance Imaging | Original Article

Prospective pediatric study comparing glomerular filtration rate estimates based on motion-robust dynamic contrast-enhanced magnetic resonance imaging and serum creatinine (eGFR) to 99mTc DTPA

Authors: Sila Kurugol, Onur Afacan, Richard S. Lee, Catherine M. Seager, Michael A. Ferguson, Deborah R. Stein, Reid C. Nichols, Monet Dugan, Alto Stemmer, Simon K. Warfield, Jeanne S. Chow

Published in: Pediatric Radiology | Issue 5/2020

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Abstract

Background

Current methods to estimate glomerular filtration rate (GFR) have shortcomings. Estimates based on serum creatinine are known to be inaccurate in the chronically ill and during acute changes in renal function. Gold standard methods such as inulin and 99mTc diethylenetriamine pentaacetic acid (DTPA) require blood or urine sampling and thus can be difficult to perform in children. Motion-robust radial volumetric interpolated breath-hold examination (VIBE) dynamic contrast-enhanced MRI represents a novel tool for estimating GFR that has not been validated in children.

Objective

The purpose of our study was to determine the feasibility and accuracy of GFR measured by motion-robust radial VIBE dynamic contrast-enhanced MRI compared to estimates by serum creatinine (eGFR) and 99mTc DTPA in children.

Materials and methods

We enrolled children, 0–18 years of age, who were undergoing both a contrast-enhanced MRI and nuclear medicine 99mTc DTPA glomerular filtration rate (NM-GFR) within 2 weeks of each other. Enrolled children consented to an additional 6-min dynamic contrast-enhanced MRI scan using the motion-robust high spatiotemporal resolution prototype dynamic radial VIBE sequence (Siemens, Erlangen, Germany) at 3 tesla (T). The images were reconstructed offline with high temporal resolution (~3 s/volume) using compressed sensing image reconstruction including regularization in temporal dimension to improve image quality and reduce streaking artifacts. Images were then automatically post-processed using in-house-developed software. Post-processing steps included automatic segmentation of kidney parenchyma and aorta using convolutional neural network techniques and tracer kinetic model fitting using the Sourbron two-compartment model to calculate the MR-based GFR (MR-GFR). The NM-GFR was compared to MR-GFR and estimated GFR based on serum creatinine (eGFR) using Pearson correlation coefficient and Bland–Altman analysis.

Results

Twenty-one children (7 female, 14 male) were enrolled between February 2017 and May 2018. Data from six of these children were not further analyzed because of deviations from the MRI protocol. Fifteen patients were analyzed (5 female, 10 male; average age 5.9 years); the method was technically feasible in all children. The results showed that the MR-GFR correlated with NM-GFR with a Pearson correlation coefficient (r-value) of 0.98. Bland–Altman analysis (i.e. difference of MR-GFR and NM-GFR versus mean of NM-GFR and MR-GFR) showed a mean difference of −0.32 and reproducibility coefficient of 18 with 95% confidence interval, and the coefficient of variation of 6.7% with values between −19 (−1.96 standard deviation) and 18 (+1.96 standard deviation). In contrast, serum creatinine compared with NM-GFR yielded an r-value of 0.73. Bland–Altman analysis (i.e. difference of eGFR and NM-GFR versus mean of NM-GFR and eGFR) showed a mean difference of 2.9 and reproducibility coefficient of 70 with 95% confidence interval, and the coefficient of variation of 25% with values between −67 (−1.96 standard deviation) and 73 (+1.96 standard deviation).

Conclusion

MR-GFR is a technically feasible and reliable method of measuring GFR when compared to the reference standard, NM-GFR by serum 99mTc DTPA, and MR-GFR is more reliable than estimates based on serum creatinine.
Literature
1.
go back to reference Shemesh O, Golbetz H, Kriss JP, Myers BD (1985) Limitations of creatinine as a filtration marker in glomerulopathic patients. Kidney Int 28:830–838CrossRef Shemesh O, Golbetz H, Kriss JP, Myers BD (1985) Limitations of creatinine as a filtration marker in glomerulopathic patients. Kidney Int 28:830–838CrossRef
2.
go back to reference Schwartz GJ, Work DF (2009) Measurement and estimation of GFR in children and adolescents. Clin J Am Soc Nephrol 4:1832–1843CrossRef Schwartz GJ, Work DF (2009) Measurement and estimation of GFR in children and adolescents. Clin J Am Soc Nephrol 4:1832–1843CrossRef
3.
go back to reference Stevens LA, Levey AS (2009) Measured GFR as a confirmatory test for estimated GFR. J Am Soc Nephrol 20:2305–2313CrossRef Stevens LA, Levey AS (2009) Measured GFR as a confirmatory test for estimated GFR. J Am Soc Nephrol 20:2305–2313CrossRef
4.
go back to reference Kainer G, McIlveen B, Höschl R, Rosenberg AR (1979) Assessment of individual renal function in children using 99mTc-DTPA. Arch Dis Child 54:931–936CrossRef Kainer G, McIlveen B, Höschl R, Rosenberg AR (1979) Assessment of individual renal function in children using 99mTc-DTPA. Arch Dis Child 54:931–936CrossRef
5.
go back to reference Ledneva E, Karie S, Launay-Vacher V et al (2009) Renal safety of gadolinium-based contrast media in patients with chronic renal insufficiency. Radiology 250:618–628CrossRef Ledneva E, Karie S, Launay-Vacher V et al (2009) Renal safety of gadolinium-based contrast media in patients with chronic renal insufficiency. Radiology 250:618–628CrossRef
6.
go back to reference Hackstein N, Heckrodt J, Rau WS (2003) Measurement of single-kidney glomerular filtration rate using a contrast-enhanced dynamic gradient-echo sequence and the Rutland-Patlak plot technique. J Magn Reson Imaging 18:714–725CrossRef Hackstein N, Heckrodt J, Rau WS (2003) Measurement of single-kidney glomerular filtration rate using a contrast-enhanced dynamic gradient-echo sequence and the Rutland-Patlak plot technique. J Magn Reson Imaging 18:714–725CrossRef
7.
go back to reference Annet L, Hermoye L, Peeters F et al (2004) Glomerular filtration rate: assessment with dynamic contrast-enhanced MRI and a cortical-compartment model in the rabbit kidney. J Magn Reson Imaging 20:843–849CrossRef Annet L, Hermoye L, Peeters F et al (2004) Glomerular filtration rate: assessment with dynamic contrast-enhanced MRI and a cortical-compartment model in the rabbit kidney. J Magn Reson Imaging 20:843–849CrossRef
8.
go back to reference Buckley DL, Shurrab AE, Cheung CM et al (2006) Measurement of single kidney function using dynamic contrast-enhanced MRI: comparison of two models in human subjects. J Magn Reson Imaging 24:1117–1123CrossRef Buckley DL, Shurrab AE, Cheung CM et al (2006) Measurement of single kidney function using dynamic contrast-enhanced MRI: comparison of two models in human subjects. J Magn Reson Imaging 24:1117–1123CrossRef
9.
go back to reference Lee VS, Rusinek H, Bokacheva L et al (2007) Renal function measurements from MR renography and a simplified multicompartmental model. Am J Physiol Renal Physiol 292:F1548–F1589CrossRef Lee VS, Rusinek H, Bokacheva L et al (2007) Renal function measurements from MR renography and a simplified multicompartmental model. Am J Physiol Renal Physiol 292:F1548–F1589CrossRef
10.
go back to reference Sourbron SP, Michaely HJ, Reiser MF, Schoenberg SO (2008) MRI-measurement of perfusion and glomerular filtration in the human kidney with a separable compartment model. Investig Radiol 43:40–48CrossRef Sourbron SP, Michaely HJ, Reiser MF, Schoenberg SO (2008) MRI-measurement of perfusion and glomerular filtration in the human kidney with a separable compartment model. Investig Radiol 43:40–48CrossRef
11.
go back to reference Zhang JL, Rusinek H, Bokacheva L et al (2008) Functional assessment of the kidney from magnetic resonance and computed tomography renography: impulse retention approach to a multicompartment model. Magn Reson Med 59:278–288CrossRef Zhang JL, Rusinek H, Bokacheva L et al (2008) Functional assessment of the kidney from magnetic resonance and computed tomography renography: impulse retention approach to a multicompartment model. Magn Reson Med 59:278–288CrossRef
12.
go back to reference Bokacheva L, Rusinek H, Zhang JL et al (2009) Estimates of glomerular filtration rate from MR renography and tracer kinetic models. J Magn Reson Imaging 29:371–382CrossRef Bokacheva L, Rusinek H, Zhang JL et al (2009) Estimates of glomerular filtration rate from MR renography and tracer kinetic models. J Magn Reson Imaging 29:371–382CrossRef
13.
go back to reference Tofts PS, Cutajar M, Mendichovszky IA et al (2012) 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. Eur Radiol 22:1320–1330CrossRef Tofts PS, Cutajar M, Mendichovszky IA et al (2012) 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. Eur Radiol 22:1320–1330CrossRef
14.
go back to reference Chandarana H, Block TK, Rosenkrantz AB et al (2011) Free-breathing radial 3D fat-suppressed T1-weighted gradient echo sequence: a viable alternative for contrast-enhanced liver imaging in patients unable to suspend respiration. Investig Radiol 46:648–653CrossRef Chandarana H, Block TK, Rosenkrantz AB et al (2011) Free-breathing radial 3D fat-suppressed T1-weighted gradient echo sequence: a viable alternative for contrast-enhanced liver imaging in patients unable to suspend respiration. Investig Radiol 46:648–653CrossRef
15.
go back to reference Kurugol S (2017) Reliable estimation of kidney filtration rate with DCE-MRI using motion-robust high spatiotemporal resolution radial VIBE. In: Proceedings of the International Society of Magnetic Resonance Medicine, Wiley, Hoboken Kurugol S (2017) Reliable estimation of kidney filtration rate with DCE-MRI using motion-robust high spatiotemporal resolution radial VIBE. In: Proceedings of the International Society of Magnetic Resonance Medicine, Wiley, Hoboken
17.
go back to reference Feng L, Grimm R, Block KT et al (2013) Golden-angle radial sparse parallel MRI: combination of compressed sensing, parallel imaging, and golden-angle radial sampling for fast and flexible dynamic volumetric MRI. Magn Reson Med 72:707–717CrossRef Feng L, Grimm R, Block KT et al (2013) Golden-angle radial sparse parallel MRI: combination of compressed sensing, parallel imaging, and golden-angle radial sampling for fast and flexible dynamic volumetric MRI. Magn Reson Med 72:707–717CrossRef
18.
go back to reference Haghighi M, Warfield SK, Kurugol S (2018) Automatic renal segmentation in DCE-MRI using convolutional neural networks. In: Proceedings of the International Symposium on Biomedical Imaging, IEEE, Piscataway, pp 1534–1537 Haghighi M, Warfield SK, Kurugol S (2018) Automatic renal segmentation in DCE-MRI using convolutional neural networks. In: Proceedings of the International Symposium on Biomedical Imaging, IEEE, Piscataway, pp 1534–1537
20.
go back to reference Li X, Bolan PJ, Ugurbil K, Metzger GJ (2015) Measuring renal tissue relaxation times at 7 T. NMR Biomed 28:63–69PubMed Li X, Bolan PJ, Ugurbil K, Metzger GJ (2015) Measuring renal tissue relaxation times at 7 T. NMR Biomed 28:63–69PubMed
21.
go back to reference Lu H, Clingman C, Golay X, Van Zijl PC (2004) Determining the longitudinal relaxation time (T1) of blood at 3.0 tesla. Magn Reson Med 52:679–682CrossRef Lu H, Clingman C, Golay X, Van Zijl PC (2004) Determining the longitudinal relaxation time (T1) of blood at 3.0 tesla. Magn Reson Med 52:679–682CrossRef
22.
go back to reference Chen Y, Lee GR, Aandal G et al (2016) Rapid volumetric T1 mapping of the abdomen using three-dimensional through-time spiral GRAPPA. Magn Reson Med 75:1457–1465CrossRef Chen Y, Lee GR, Aandal G et al (2016) Rapid volumetric T1 mapping of the abdomen using three-dimensional through-time spiral GRAPPA. Magn Reson Med 75:1457–1465CrossRef
23.
go back to reference Eikefjord E, Andersen E, Hodneland E et al (2017) Dynamic contrast-enhanced MRI measurement of renal function in healthy participants. Acta Radiol 58:748–757CrossRef Eikefjord E, Andersen E, Hodneland E et al (2017) Dynamic contrast-enhanced MRI measurement of renal function in healthy participants. Acta Radiol 58:748–757CrossRef
24.
go back to reference Vivier P-H, Storey P, Rusinek H et al (2011) Kidney function: glomerular filtration rate measurement with MR renography in patients with cirrhosis. Radiology 259:462–470CrossRef Vivier P-H, Storey P, Rusinek H et al (2011) Kidney function: glomerular filtration rate measurement with MR renography in patients with cirrhosis. Radiology 259:462–470CrossRef
25.
go back to reference Kang SK, Huang WC, Wong S et al (2013) Dynamic contrast-enhanced magnetic resonance imaging measurement of renal function in patients undergoing partial nephrectomy: preliminary experience. Investig Radiol 48:687–692CrossRef Kang SK, Huang WC, Wong S et al (2013) Dynamic contrast-enhanced magnetic resonance imaging measurement of renal function in patients undergoing partial nephrectomy: preliminary experience. Investig Radiol 48:687–692CrossRef
26.
go back to reference Tipirneni-Sajja A, Loeffler RB, Oesingmann N et al (2016) Measurement of glomerular filtration rate by dynamic contrast-enhanced magnetic resonance imaging using a subject-specific two-compartment model. Physiol Rep 4 Tipirneni-Sajja A, Loeffler RB, Oesingmann N et al (2016) Measurement of glomerular filtration rate by dynamic contrast-enhanced magnetic resonance imaging using a subject-specific two-compartment model. Physiol Rep 4
27.
go back to reference Taton B, De La Faille R, Asselineau J et al (2019) A prospective comparison of dynamic contrast-enhanced MRI and 51Cr-EDTA clearance for glomerular filtration rate measurement in 42 kidney transplant recipients. Eur J Radiol 117:209–215CrossRef Taton B, De La Faille R, Asselineau J et al (2019) A prospective comparison of dynamic contrast-enhanced MRI and 51Cr-EDTA clearance for glomerular filtration rate measurement in 42 kidney transplant recipients. Eur J Radiol 117:209–215CrossRef
28.
go back to reference Lim SW, Chrysochou C, Buckley DL et al (2013) Prediction and assessment of responses to renal artery revascularization with dynamic contrast-enhanced magnetic resonance imaging: a pilot study. Am J Physiol Renal Physiol 305:F672–F678CrossRef Lim SW, Chrysochou C, Buckley DL et al (2013) Prediction and assessment of responses to renal artery revascularization with dynamic contrast-enhanced magnetic resonance imaging: a pilot study. Am J Physiol Renal Physiol 305:F672–F678CrossRef
29.
go back to reference Eikefjord E, Andersen E, Hodneland E et al (2016) Quantification of single-kidney function and volume in living kidney donors using dynamic contrast-enhanced MRI. AJR Am J Roentgenol 207:1022–1030CrossRef Eikefjord E, Andersen E, Hodneland E et al (2016) Quantification of single-kidney function and volume in living kidney donors using dynamic contrast-enhanced MRI. AJR Am J Roentgenol 207:1022–1030CrossRef
30.
go back to reference Kwatra NS, Meany HJ, Ghelani SJ et al (2017) Glomerular hyperfiltration in children with cancer: prevalence and a hypothesis. Pediatr Radiol 47:221–226CrossRef Kwatra NS, Meany HJ, Ghelani SJ et al (2017) Glomerular hyperfiltration in children with cancer: prevalence and a hypothesis. Pediatr Radiol 47:221–226CrossRef
31.
go back to reference Frush DP, Donnelly LF, Rosen NS (2003) Computed tomography and radiation risks: what pediatric health care providers should know. Pediatrics 112:951–957CrossRef Frush DP, Donnelly LF, Rosen NS (2003) Computed tomography and radiation risks: what pediatric health care providers should know. Pediatrics 112:951–957CrossRef
Metadata
Title
Prospective pediatric study comparing glomerular filtration rate estimates based on motion-robust dynamic contrast-enhanced magnetic resonance imaging and serum creatinine (eGFR) to 99mTc DTPA
Authors
Sila Kurugol
Onur Afacan
Richard S. Lee
Catherine M. Seager
Michael A. Ferguson
Deborah R. Stein
Reid C. Nichols
Monet Dugan
Alto Stemmer
Simon K. Warfield
Jeanne S. Chow
Publication date
01-05-2020
Publisher
Springer Berlin Heidelberg
Published in
Pediatric Radiology / Issue 5/2020
Print ISSN: 0301-0449
Electronic ISSN: 1432-1998
DOI
https://doi.org/10.1007/s00247-020-04617-0

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