Electrical impedance tomography for non-invasive identification of fatty liver infiltrate in overweight individuals.


Journal

Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288

Informations de publication

Date de publication:
06 10 2021
Historique:
received: 01 06 2021
accepted: 16 09 2021
entrez: 7 10 2021
pubmed: 8 10 2021
medline: 31 12 2021
Statut: epublish

Résumé

Non-alcoholic fatty liver disease (NAFLD) is one of the most common causes of cardiometabolic diseases in overweight individuals. While liver biopsy is the current gold standard to diagnose NAFLD and magnetic resonance imaging (MRI) is a non-invasive alternative still under clinical trials, the former is invasive and the latter costly. We demonstrate electrical impedance tomography (EIT) as a portable method for detecting fatty infiltrate. We enrolled 19 overweight subjects to undergo liver MRI scans, followed by EIT measurements. The MRI images provided the a priori knowledge of the liver boundary conditions for EIT reconstruction, and the multi-echo MRI data quantified liver proton-density fat fraction (PDFF%) to validate fat infiltrate. Using the EIT electrode belts, we circumferentially injected pairwise current to the upper abdomen, followed by acquiring the resulting surface-voltage to reconstruct the liver conductivity. Pearson's correlation analyses compared EIT conductivity or MRI PDFF with body mass index, age, waist circumference, height, and weight variables. We reveal that the correlation between liver EIT conductivity or MRI PDFF with demographics is statistically insignificant, whereas liver EIT conductivity is inversely correlated with MRI PDFF (R = -0.69, p = 0.003, n = 16). As a pilot study, EIT conductivity provides a portable method for operator-independent and cost-effective detection of hepatic steatosis.

Identifiants

pubmed: 34615918
doi: 10.1038/s41598-021-99132-z
pii: 10.1038/s41598-021-99132-z
pmc: PMC8494919
doi:

Substances chimiques

Biomarkers 0

Types de publication

Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, Non-P.H.S.

Langues

eng

Sous-ensembles de citation

IM

Pagination

19859

Subventions

Organisme : BLRD VA
ID : I01 BX004356
Pays : United States
Organisme : NHLBI NIH HHS
ID : R01 HL129727
Pays : United States
Organisme : NHLBI NIH HHS
ID : R01 HL118650
Pays : United States
Organisme : NHLBI NIH HHS
ID : R01 HL111437
Pays : United States
Organisme : CSRD VA
ID : IK2 CX001717
Pays : United States
Organisme : NHLBI NIH HHS
ID : R01 HL083015
Pays : United States

Informations de copyright

© 2021. The Author(s).

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Auteurs

Chih-Chiang Chang (CC)

Department of Bioengineering, UCLA, Los Angeles, CA, USA.
Department of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA.

Zi-Yu Huang (ZY)

Department of Medical Engineering, California Institute of Technology, Pasadena, CA, USA.

Shu-Fu Shih (SF)

Department of Bioengineering, UCLA, Los Angeles, CA, USA.
Department of Radiological Sciences, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA.

Yuan Luo (Y)

Department of Medical Engineering, California Institute of Technology, Pasadena, CA, USA.

Arthur Ko (A)

Department of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA.

Qingyu Cui (Q)

Department of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA.

Jennifer Sumner (J)

Department of Psychology, College of Life Sciences, UCLA, Los Angeles, CA, USA.

Susana Cavallero (S)

Department of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA.

Swarna Das (S)

Department of Bioengineering, UCLA, Los Angeles, CA, USA.

Wei Gao (W)

Department of Medical Engineering, California Institute of Technology, Pasadena, CA, USA.

Janet Sinsheimer (J)

Department of Biostatistics, Fielding School of Public Health, UCLA, Los Angeles, CA, USA.
Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA.
Computational Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA.

Alex Bui (A)

Department of Bioengineering, UCLA, Los Angeles, CA, USA.
Department of Radiological Sciences, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA.

Jonathan P Jacobs (JP)

Department of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA.
Division of Digestive Diseases, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA.
Greater Los Angeles VA Healthcare System, Los Angeles, CA, USA.

Päivi Pajukanta (P)

Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA.
Institute for Precision Health, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA.

Holden Wu (H)

Department of Bioengineering, UCLA, Los Angeles, CA, USA.
Department of Radiological Sciences, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA.

Yu-Chong Tai (YC)

Department of Medical Engineering, California Institute of Technology, Pasadena, CA, USA.

Zhaoping Li (Z)

Department of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA.
Greater Los Angeles VA Healthcare System, Los Angeles, CA, USA.
Center for Human Nutrition, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA.

Tzung K Hsiai (TK)

Department of Bioengineering, UCLA, Los Angeles, CA, USA. Thsiai@mednet.ucla.edu.
Department of Medical Engineering, California Institute of Technology, Pasadena, CA, USA. Thsiai@mednet.ucla.edu.
Department of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA. Thsiai@mednet.ucla.edu.
Greater Los Angeles VA Healthcare System, Los Angeles, CA, USA. Thsiai@mednet.ucla.edu.

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