Literature DB >> 34935650

Reliable Assessment of Swine Renal Fibrosis Using Quantitative Magnetization Transfer Imaging.

Kai Jiang1, Christopher M Ferguson1, Roger C Grimm2, Xiangyang Zhu1, James F Glockner2, Lilach O Lerman1.   

Abstract

OBJECTIVES: Quantitative magnetization transfer (qMT) is useful for measurement of murine renal fibrosis at high and ultrahigh field strengths. However, its utility at clinical field strengths and in human-like kidneys remains unknown. We tested the hypothesis that qMT would successfully detect fibrosis in swine kidneys with unilateral renal artery stenosis (RAS) at 3.0 T.
METHODS: The qMT protocol is composed of MT scans with variable flip angles and offset frequencies, and of B0, B1, and T1 mapping. Pigs were scanned 10 weeks after RAS or control. A 2-pool model was used to fit the bound pool fraction f of the renal cortex (CO) and outer medulla (OM). Then qMT-derived f in 5 normal and 10 RAS pigs was compared with histological fibrosis determined using Masson's trichrome staining and to renal perfusion assessed with computed tomography.
RESULTS: The qMT 2-pool model provided accurate fittings of data collected on swine kidneys. Stenotic kidneys showed significantly elevated f in both the CO (9.8% ± 2.7% vs 6.4% ± 0.9%, P = 0.002) and OM (7.6% ± 2.2% vs 4.7% ± 1.1%, P = 0.002), as compared with normal kidneys. Histology-measured renal fibrosis and qMT-derived f correlated directly in both the cortex (Pearson correlation coefficient r = 0.93, P < 0.001) and OM (r = 0.84, P = 0.002), and inversely with stenotic kidney perfusion (r = 0.85, P = 0.002).
CONCLUSIONS: This study demonstrates the feasibility of qMT for measuring fibrosis in human-like swine kidneys, and the association between tissue macromolecule content and renal perfusion. Therefore, qMT may be useful as a tool for noninvasive assessment of renal fibrosis in subjects with RAS at clinical field strengths.
Copyright © 2021 Wolters Kluwer Health, Inc. All rights reserved.

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Year:  2022        PMID: 34935650      PMCID: PMC8986560          DOI: 10.1097/RLI.0000000000000843

Source DB:  PubMed          Journal:  Invest Radiol        ISSN: 0020-9996            Impact factor:   6.016


  44 in total

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Authors:  Robert G Bryant; Jean-Pierre Korb
Journal:  Magn Reson Imaging       Date:  2005-02       Impact factor: 2.546

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Authors:  Kai Jiang; Hui Tang; Prasanna K Mishra; Slobodan I Macura; Lilach O Lerman
Journal:  Magn Reson Imaging       Date:  2019-08-20       Impact factor: 2.546

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Authors:  Valerij G Kiselev; Gregor Körzdörfer; Peter Gall
Journal:  Invest Radiol       Date:  2021-01       Impact factor: 6.016

5.  Assessment of renal artery stenosis using intravoxel incoherent motion diffusion-weighted magnetic resonance imaging analysis.

Authors:  Behzad Ebrahimi; Naveen Rihal; John R Woollard; James D Krier; Alfonso Eirin; Lilach O Lerman
Journal:  Invest Radiol       Date:  2014-10       Impact factor: 6.016

6.  Cortical microvascular remodeling in the stenotic kidney: role of increased oxidative stress.

Authors:  Xiang-Yang Zhu; Alejandro R Chade; Martin Rodriguez-Porcel; Michael D Bentley; Erik L Ritman; Amir Lerman; Lilach O Lerman
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7.  Distinct renal injury in early atherosclerosis and renovascular disease.

Authors:  Alejandro R Chade; Martin Rodriguez-Porcel; Joseph P Grande; James D Krier; Amir Lerman; J Carlos Romero; Claudio Napoli; Lilach O Lerman
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8.  Magnetization Transfer Imaging Predicts Porcine Kidney Recovery After Revascularization of Renal Artery Stenosis.

Authors:  Mohsen Afarideh; Kai Jiang; Christopher M Ferguson; John R Woollard; James F Glockner; Lilach O Lerman
Journal:  Invest Radiol       Date:  2021-02-01       Impact factor: 10.065

9.  Precise estimate of fundamental in-vivo MT parameters in human brain in clinically feasible times.

Authors:  A Ramani; C Dalton; D H Miller; P S Tofts; G J Barker
Journal:  Magn Reson Imaging       Date:  2002-12       Impact factor: 2.546

10.  Quantitative Magnetization Transfer Detects Renal Fibrosis in Murine Kidneys With Renal Artery Stenosis.

Authors:  Kai Jiang; Yiyuan Fang; Christopher M Ferguson; Hui Tang; Prasanna K Mishra; Slobodan I Macura; Lilach O Lerman
Journal:  J Magn Reson Imaging       Date:  2020-09-17       Impact factor: 4.813

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