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Non-Invasive Electrical Impedance Tomography for Multi-Scale Detection of Liver Fat Content

Luo, Yuan and Abiri, Parinaz and Zhang, Shell and Chang, Chih-Chiang and Kaboodrangi, Amir H. and Li, Rongsong and Sahib, Ashish K. and Bui, Alex and Kumar, Rajesh and Woo, Mary and Li, Zhaoping and Packard, René R. Sevag and Tai, Yu-Chong and Hsiai, Tzung K. (2018) Non-Invasive Electrical Impedance Tomography for Multi-Scale Detection of Liver Fat Content. Theranostics, 8 (6). pp. 1636-1647. ISSN 1838-7640. PMCID PMC5858172. https://resolver.caltech.edu/CaltechAUTHORS:20180222-083518129

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Abstract

Introduction: Obesity is associated with an increased risk of nonalcoholic fatty liver disease (NAFLD). While Magnetic Resonance Imaging (MRI) is a non-invasive gold standard to detect fatty liver, we demonstrate a low-cost and portable electrical impedance tomography (EIT) approach with circumferential abdominal electrodes for liver conductivity measurements. Methods and Results: A finite element model (FEM) was established to simulate decremental liver conductivity in response to incremental liver lipid content. To validate the FEM simulation, we performed EIT imaging on an ex vivo porcine liver in a non-conductive tank with 32 circumferentially-embedded electrodes, demonstrating a high-resolution output given a priori information on location and geometry. To further examine EIT capacity in fatty liver detection, we performed EIT measurements in age- and gender-matched New Zealand White rabbits (3 on normal, 3 on high-fat diets). Liver conductivity values were significantly distinct following the high-fat diet (p = 0.003 vs. normal diet, n=3), accompanied by histopathological evidence of hepatic fat accumulation. We further assessed EIT imaging in human subjects with MRI quantification for fat volume fraction based on Dixon procedures, demonstrating average liver conductivity of 0.331 S/m for subjects with low Body-Mass Index (BMI < 25 kg/m²) and 0.286 S/m for high BMI (> 25 kg/m²). Conclusion: We provide both the theoretical and experimental framework for a multi-scale EIT strategy to detect liver lipid content. Our preliminary studies pave the way to enhance the spatial resolution of EIT as a marker for fatty liver disease and metabolic syndrome.


Item Type:Article
Related URLs:
URLURL TypeDescription
https://doi.org/10.7150/thno.22233DOIArticle
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5858172/PubMed CentralArticle
ORCID:
AuthorORCID
Packard, René R. Sevag0000-0002-8520-5843
Tai, Yu-Chong0000-0001-8529-106X
Hsiai, Tzung K.0000-0003-1734-0792
Additional Information:© 2018 Ivyspring International Publisher. This is an open access article distributed under the terms of the Creative Commons Attribution (CC BY-NC) license (https://creativecommons.org/licenses/by-nc/4.0/). Received 2017-8-4; Accepted 2017-12-1; Published 2018-2-8. This study was supported by NIH R01HL083015 (T.K.H.), R01HL118650 (T.K.H.), R01HL111437 (T.K.H.), U54 EB0220002 (T.K.H., A.B.), R01NR014669 (M.W. and R.K.), American Heart Association 16SDG30910007 (R.R.S.P.), UCLA MSTP program (P.A.), and UCLA David Geffen Scholarship (P.A.). The authors have declared that no competing interest exists.
Funders:
Funding AgencyGrant Number
NIHR01HL083015
NIHR01HL118650
NIHR01HL111437
NIHU54 EB0220002
NIHR01NR014669
American Heart Association16SDG30910007
UCLA-Caltech Medical Scientist Training ProgramUNSPECIFIED
Subject Keywords:Fatty Liver, Nonalcoholic Fatty Liver Disease, Electrical Impedance Tomography, Fat Volume Fraction
Issue or Number:6
PubMed Central ID:PMC5858172
Record Number:CaltechAUTHORS:20180222-083518129
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20180222-083518129
Official Citation:Luo Y, Abiri P, Zhang S, Chang CC, Kaboodrangi AH, Li R, Sahib AK, Bui A, Kumar R, Woo M, Li Z, Packard RRS, Tai YC, Hsiai TK. Non-Invasive Electrical Impedance Tomography for Multi-Scale Detection of Liver Fat Content. Theranostics 2018; 8(6):1636-1647. doi:10.7150/thno.22233. Available from http://www.thno.org/v08p1636.htm
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:84917
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:22 Feb 2018 18:00
Last Modified:26 Nov 2019 00:03

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