Title |
Shear wave elastography in chronic kidney disease: a pilot experience in native kidneys
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Published in |
BMC Nephrology, July 2015
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DOI | 10.1186/s12882-015-0120-7 |
Pubmed ID | |
Authors |
Anthony E. Samir, Andrew S. Allegretti, Qingli Zhu, Manish Dhyani, Arash Anvari, Dorothy A. Sullivan, Caitlin A. Trottier, Sarah Dougherty, Winfred W. Williams, Jodie L. Babitt, Julia Wenger, Ravi I. Thadhani, Herbert Y. Lin |
Abstract |
There currently is a need for a non-invasive measure of renal fibrosis. We aim to explore whether shear wave elastography (SWE)-derived estimates of tissue stiffness may serve as a non-invasive biomarker that can distinguish normal and abnormal renal parenchymal tissue. Participants with CKD (by estimated GFR) and healthy volunteers underwent SWE. Renal elasticity was estimated as Young's modulus (YM) in kilopascals (kPa). Univariate Wilcoxon rank-sum tests were used. Twenty-five participants with CKD (median GFR 38 mL/min; quartile 1, quartile 3 28, 42) and 20 healthy controls without CKD underwent SWE performed by a single radiologist. CKD was associated with increased median YM (9.40 [5.55, 22.35] vs. 4.40 [3.68, 5.70] kPa; p = 0.002) and higher median intra-subject inter-measurement estimated YM's variability (4.27 [2.89, 9.90] vs. 1.51 [1.21, 2.05] kPa; p < 0.001). SWE-derived estimates of renal stiffness and intra-subject estimated stiffness variability are higher in patients with CKD than in healthy controls. Renal fibrosis is a plausible explanation for the observed difference in YM. Further studies are required to determine the relationship between YM, estimated renal stiffness, and renal fibrosis severity. |
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Unknown | 1 | 100% |
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Members of the public | 1 | 100% |
Mendeley readers
Geographical breakdown
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United States | 1 | <1% |
Unknown | 105 | 99% |
Demographic breakdown
Readers by professional status | Count | As % |
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Researcher | 16 | 15% |
Student > Ph. D. Student | 13 | 12% |
Student > Postgraduate | 12 | 11% |
Student > Master | 12 | 11% |
Student > Doctoral Student | 5 | 5% |
Other | 17 | 16% |
Unknown | 31 | 29% |
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Engineering | 10 | 9% |
Nursing and Health Professions | 3 | 3% |
Materials Science | 3 | 3% |
Neuroscience | 3 | 3% |
Other | 13 | 12% |
Unknown | 40 | 38% |