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Original ArticlesTransplantation
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Magnetic Resonance Elastography to Assess Fibrosis in Kidney Allografts

Anish Kirpalani, Eyesha Hashim, General Leung, Jin K. Kim, Adriana Krizova, Serge Jothy, Maya Deeb, Nan N. Jiang, Lauren Glick, Gevork Mnatzakanian and Darren A. Yuen
CJASN October 2017, 12 (10) 1671-1679; DOI: https://doi.org/10.2215/CJN.01830217
Anish Kirpalani
Departments of *Medical Imaging and
†Li Ka Shing Knowledge Institute and
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Eyesha Hashim
Departments of *Medical Imaging and
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General Leung
Departments of *Medical Imaging and
†Li Ka Shing Knowledge Institute and
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Jin K. Kim
Departments of *Medical Imaging and
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Adriana Krizova
‡Laboratory Medicine and Pathology and
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Serge Jothy
‡Laboratory Medicine and Pathology and
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Maya Deeb
§Division of Nephrology, Department of Medicine, St. Michael’s Hospital and University of Toronto, Toronto, Ontario, Canada; and
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Nan N. Jiang
Departments of *Medical Imaging and
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Lauren Glick
‖Keenan Research Centre for Biomedical Science, St. Michael’s Hospital, Toronto, Ontario, Canada
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Gevork Mnatzakanian
Departments of *Medical Imaging and
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Darren A. Yuen
§Division of Nephrology, Department of Medicine, St. Michael’s Hospital and University of Toronto, Toronto, Ontario, Canada; and
‖Keenan Research Centre for Biomedical Science, St. Michael’s Hospital, Toronto, Ontario, Canada
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Abstract

Background and objectives Fibrosis is a major cause of kidney allograft injury. Currently, the only means of assessing allograft fibrosis is by biopsy, an invasive procedure that samples <1% of the kidney. We examined whether magnetic resonance elastography, an imaging-based measure of organ stiffness, could noninvasively estimate allograft fibrosis and predict progression of allograft dysfunction.

Design, setting, participants, & measurements Kidney allograft recipients >1 year post-transplant undergoing an allograft biopsy first underwent free-breathing, flow-compensated magnetic resonance elastography on a 3.0-T magnetic resonance imaging scanner. Each patient had serial eGFR measurements after the elastography scan for a follow-up period of up to 1 year. The mean stiffness value of the kidney allograft was compared with both the histopathologic Banff fibrosis score and the rate of eGFR change during the follow-up period.

Results Sixteen patients who underwent magnetic resonance elastography and biopsy were studied (mean age: 54±9 years old). Whole-kidney mean stiffness ranged between 3.5 and 7.3 kPa. Whole-kidney stiffness correlated with biopsy-derived Banff fibrosis score (Spearman rho =0.67; P<0.01). Stiffness was heterogeneously distributed within each kidney, providing a possible explanation for the lack of a stronger stiffness-fibrosis correlation. We also found negative correlations between whole-kidney stiffness and both baseline eGFR (Spearman rho =−0.65; P<0.01) and eGFR change over time (Spearman rho =−0.70; P<0.01). Irrespective of the baseline eGFR, increased kidney stiffness was associated with a greater eGFR decline (regression r2=0.48; P=0.03).

Conclusions Given the limitations of allograft biopsy, our pilot study suggests the potential for magnetic resonance elastography as a novel noninvasive measure of whole-allograft fibrosis burden that may predict future changes in kidney function. Future studies exploring the utility and accuracy of magnetic resonance elastography are needed.

  • Received February 15, 2017.
  • Accepted June 26, 2017.
  • Copyright © 2017 by the American Society of Nephrology
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Clinical Journal of the American Society of Nephrology: 12 (10)
Clinical Journal of the American Society of Nephrology
Vol. 12, Issue 10
October 06, 2017
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Magnetic Resonance Elastography to Assess Fibrosis in Kidney Allografts
Anish Kirpalani, Eyesha Hashim, General Leung, Jin K. Kim, Adriana Krizova, Serge Jothy, Maya Deeb, Nan N. Jiang, Lauren Glick, Gevork Mnatzakanian, Darren A. Yuen
CJASN Oct 2017, 12 (10) 1671-1679; DOI: 10.2215/CJN.01830217

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Magnetic Resonance Elastography to Assess Fibrosis in Kidney Allografts
Anish Kirpalani, Eyesha Hashim, General Leung, Jin K. Kim, Adriana Krizova, Serge Jothy, Maya Deeb, Nan N. Jiang, Lauren Glick, Gevork Mnatzakanian, Darren A. Yuen
CJASN Oct 2017, 12 (10) 1671-1679; DOI: 10.2215/CJN.01830217
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