Dataset Information

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

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.

SUBMITTER: Luo Y

PROVIDER: S-EPMC5858172 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

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

Luo Yuan Y Abiri Parinaz P Zhang Shell S Chang Chih-Chiang CC Kaboodrangi Amir H AH Li Rongsong R Sahib Ashish K AK Bui Alex A Kumar Rajesh R Woo Mary M Li Zhaoping Z Packard René R Sevag RRS Tai Yu-Chong YC Hsiai Tzung K TK

Theranostics 20180208 6

<b>Introduction:</b> 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. <b>Methods and Results:</b> A finite element model (FEM) was established to simulate decremental liver conductivity in response to ...[more]

PMID: 29556346

Similar Datasets

Project description:ObjectivesObesity and its distribution pattern are important factors for the prediction of the onset of diabetes in humans. Since several mouse models are suitable to study the pathophysiology of type 2 diabetes the aim was to validate a novel computed tomograph model (Aloka-Hitachi LCT-200) for the quantification of visceral, subcutaneous, brown and intrahepatic fat depots in mice.MethodsDifferent lean and obese mouse models (C57BL/6, B6.V-Lep(ob), NZO) were used to determine the most adequate scanning parameters for the detection of the different fat depots. The data were compared with those obtained after preparation and weighing the fat depots. Liver fat content was determined by biochemical analysis.ResultsThe correlations between weights of fat tissues on scale and weights determined by CT were significant for subcutaneous (r(2) = 0.995), visceral (r(2) = 0.990) and total white adipose tissue (r(2) = 0.992). Moreover, scans in the abdominal region, between lumbar vertebrae L4 to L5 correlated with whole-body fat distribution allowing experimenters to reduce scanning time and animal exposure to radiation and anesthesia. Test-retest reliability and measurements conducted by different experimenters showed a high reproducibility in the obtained results. Intrahepatic fat content estimated by CT was linearly related to biochemical analysis (r(2) = 0.915). Furthermore, brown fat mass correlated well with weighted brown fat depots (r(2) = 0.952). In addition, short-term cold-expose (4 °C, 4 hours) led to alterations in brown adipose tissue attributed to a reduction in triglyceride content that can be visualized as an increase in Hounsfield units by CT imaging.ConclusionThe 3D imaging of fat by CT provides reliable results in the quantification of total, visceral, subcutaneous, brown and intrahepatic fat in mice. This non-invasive method allows the conduction of longitudinal studies of obesity in mice and therefore enables experimenters to investigate the onset of complex diseases such as diabetes and obesity.

Dataset Information

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

Publications

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

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets