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Published March 1, 2022 | Published + Supplemental Material
Journal Article Open

3-Dimensional electrical impedance spectroscopy for in situ endoluminal mapping of metabolically active plaques

Abstract

Electrical impedance spectroscopy (EIS) has been recognized to characterize oxidized low-density lipoprotein (oxLDL) in the metabolically active plaque. However, intravascular deployment of 3-D EIS-derived electrical impedance tomography (EIT) for endoluminal mapping of oxLDL-laden arterial walls remains an unmet clinical challenge. To this end, we designed the 6-point microelectrode arrays that were circumferentially configurated onto the balloon catheter for 15 intravascular EIS permutations. In parallel, we created the metabolically active plaques by performing partial ligation of right carotid artery in Yorkshire mini-pigs (n = 6 males), followed by demonstrating the plaque progression at baseline, 8 weeks, and 16 weeks of high-fat diet via computed tomography (CT) angiogram. Next, we deployed the 3-D EIS sensors to the right and left carotid arteries, and we demonstrated 3-D EIS mapping of metabolically active endolumen in the right but not left carotid arteries as evidenced by the positive E06 immunostaining for oxLDL-laden regions. By considering electrical conductivity (σ) and permittivity (ε) properties of collagen, lipid, and smooth muscle presence in the arterial wall, we further validated the 3-D EIS-derived EIT by reconstructing the histology of right and left carotid arteries for the finite element modeling of the oxLDL-laden endolumen, and we accurately predicted 3-D EIS mapping. Thus, we establish the capability of 3-D EIS-derived EIT to detect oxLDL-laden arterial walls with translational implication to predict metabolically active plaques prone to acute coronary syndromes or stroke.

Additional Information

© 2021 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Received 21 September 2021, Revised 17 November 2021, Accepted 23 November 2021, Available online 29 November 2021. We appreciate Chadi Nahal for sorting the histological data. This project was supported by NIH R01HL111437 (T.K.H.), R01HL118650 (T.K.H.), R01HL149808 (T.K.H.), NIGMS GM008042 (PA) and UCLA David Geffen Scholarship (P.A.). CRediT authorship contribution statement: Parinaz Abiri: Conceptualization, Methodology, Writing – original draft. Yuan Luo: Conceptualization, Methodology, Writing – original draft. Zi-Yu Huang: Conceptualization, Methodology, Writing – original draft. Qingyu Cui: Visualization, Writing – review & editing, Validation. Sandra Duarte-Vogel: Investigation. Mehrdad Roustaei: Visualization, Investigation. Chih-Chiang Chang: Writing – review & editing. Xiao Xiao: Visualization, Writing – review & editing. Rene Packard: Writing – review & editing. Susana Cavallero: Resources, Writing – review & editing. Ramin Ebrahimi: Writing – review & editing. Peyman Benharash: Writing – review & editing. Jun Chen: Writing – review & editing. Yu-Chong Tai: Supervision, Writing – review & editing. Tzung K. Hsiai: Funding acquisition, Project administration, Supervision, Writing – review & editing. The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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Published - 1-s2.0-S0925400521017202-main.pdf

Supplemental Material - 1-s2.0-S0925400521017202-mmc1.pdf

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Additional details

Created:
August 22, 2023
Modified:
October 23, 2023