Cargando…

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

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 circumferen...

Descripción completa

Detalles Bibliográficos
Autores principales: Luo, Yuan, Abiri, Parinaz, Zhang, Shell, Chang, Chih-Chiang, Kaboodrangi, Amir H., Li, Rongsong, Sahib, Ashish K., Bui, Alex, Kumar, Rajesh, Woo, Mary, Li, Zhaoping, Packard, René R. Sevag, Tai, Yu-Chong, Hsiai, Tzung K.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Ivyspring International Publisher 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5858172/
https://www.ncbi.nlm.nih.gov/pubmed/29556346
http://dx.doi.org/10.7150/thno.22233
_version_ 1783307605092859904
author Luo, Yuan
Abiri, Parinaz
Zhang, Shell
Chang, Chih-Chiang
Kaboodrangi, Amir H.
Li, Rongsong
Sahib, Ashish K.
Bui, Alex
Kumar, Rajesh
Woo, Mary
Li, Zhaoping
Packard, René R. Sevag
Tai, Yu-Chong
Hsiai, Tzung K.
author_facet Luo, Yuan
Abiri, Parinaz
Zhang, Shell
Chang, Chih-Chiang
Kaboodrangi, Amir H.
Li, Rongsong
Sahib, Ashish K.
Bui, Alex
Kumar, Rajesh
Woo, Mary
Li, Zhaoping
Packard, René R. Sevag
Tai, Yu-Chong
Hsiai, Tzung K.
author_sort Luo, Yuan
collection PubMed
description 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.
format Online
Article
Text
id pubmed-5858172
institution National Center for Biotechnology Information
language English
publishDate 2018
publisher Ivyspring International Publisher
record_format MEDLINE/PubMed
spelling pubmed-58581722018-03-19 Non-Invasive Electrical Impedance Tomography for Multi-Scale Detection of Liver Fat Content Luo, Yuan Abiri, Parinaz Zhang, Shell Chang, Chih-Chiang Kaboodrangi, Amir H. Li, Rongsong Sahib, Ashish K. Bui, Alex Kumar, Rajesh Woo, Mary Li, Zhaoping Packard, René R. Sevag Tai, Yu-Chong Hsiai, Tzung K. Theranostics Research Paper 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. Ivyspring International Publisher 2018-02-08 /pmc/articles/PMC5858172/ /pubmed/29556346 http://dx.doi.org/10.7150/thno.22233 Text en © 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/). See http://ivyspring.com/terms for full terms and conditions.
spellingShingle Research Paper
Luo, Yuan
Abiri, Parinaz
Zhang, Shell
Chang, Chih-Chiang
Kaboodrangi, Amir H.
Li, Rongsong
Sahib, Ashish K.
Bui, Alex
Kumar, Rajesh
Woo, Mary
Li, Zhaoping
Packard, René R. Sevag
Tai, Yu-Chong
Hsiai, Tzung K.
Non-Invasive Electrical Impedance Tomography for Multi-Scale Detection of Liver Fat Content
title Non-Invasive Electrical Impedance Tomography for Multi-Scale Detection of Liver Fat Content
title_full Non-Invasive Electrical Impedance Tomography for Multi-Scale Detection of Liver Fat Content
title_fullStr Non-Invasive Electrical Impedance Tomography for Multi-Scale Detection of Liver Fat Content
title_full_unstemmed Non-Invasive Electrical Impedance Tomography for Multi-Scale Detection of Liver Fat Content
title_short Non-Invasive Electrical Impedance Tomography for Multi-Scale Detection of Liver Fat Content
title_sort non-invasive electrical impedance tomography for multi-scale detection of liver fat content
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5858172/
https://www.ncbi.nlm.nih.gov/pubmed/29556346
http://dx.doi.org/10.7150/thno.22233
work_keys_str_mv AT luoyuan noninvasiveelectricalimpedancetomographyformultiscaledetectionofliverfatcontent
AT abiriparinaz noninvasiveelectricalimpedancetomographyformultiscaledetectionofliverfatcontent
AT zhangshell noninvasiveelectricalimpedancetomographyformultiscaledetectionofliverfatcontent
AT changchihchiang noninvasiveelectricalimpedancetomographyformultiscaledetectionofliverfatcontent
AT kaboodrangiamirh noninvasiveelectricalimpedancetomographyformultiscaledetectionofliverfatcontent
AT lirongsong noninvasiveelectricalimpedancetomographyformultiscaledetectionofliverfatcontent
AT sahibashishk noninvasiveelectricalimpedancetomographyformultiscaledetectionofliverfatcontent
AT buialex noninvasiveelectricalimpedancetomographyformultiscaledetectionofliverfatcontent
AT kumarrajesh noninvasiveelectricalimpedancetomographyformultiscaledetectionofliverfatcontent
AT woomary noninvasiveelectricalimpedancetomographyformultiscaledetectionofliverfatcontent
AT lizhaoping noninvasiveelectricalimpedancetomographyformultiscaledetectionofliverfatcontent
AT packardrenersevag noninvasiveelectricalimpedancetomographyformultiscaledetectionofliverfatcontent
AT taiyuchong noninvasiveelectricalimpedancetomographyformultiscaledetectionofliverfatcontent
AT hsiaitzungk noninvasiveelectricalimpedancetomographyformultiscaledetectionofliverfatcontent