Three-Dimensional Impedance Tomographic Mapping of Metabolically Active Endolumen
Abstract
Real-time detection of vulnerable atherosclerotic lesions, characterized by a high content of oxidized low-density lipoprotein (oxLDL)-laden macrophages or foam cells, remains an unmet clinical need. While fractional flow reserve (FFR)-guided revascularization in angiographically intermediate stenoses is utilized to assess hemodynamic significance, in vivo detection of oxLDL-rich plaques may provide a new paradigm for treating metabolically unstable lesions. Herein, we have demonstrated endoluminal mapping of lipid-laden lesions using 3-D electrical impedance spectroscopy-derived impedance tomography (EIT) in a pre-clinical swine model. We performed surgical banding of the right carotid arteries of Yucatan mini-pigs, followed by 16 weeks of high-fat diet, to promote the development of lipid-rich lesions. We implemented an intravascular sensor combining an FFR pressure transducer with a 6-point micro-electrode array for electrical impedance spectroscopy (EIS) measurements. 3-D EIT mapping was achieved using an EIS-based reconstruction algorithm. We demonstrated that EIT mapping corresponds to endoluminal histology for oxLDL-laden lesions. We further used computational models to theoretically predict and validate EIS measurements. Thus, our 3-D EIS-derived EIT provides in vivo detection of metabolically active plaques with the goal of guiding optimal intravascular intervention.
Additional Information
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. This version posted September 25, 2020. We appreciate Chadi Nahal for sorting the histological data. Funding: 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.). Author contributions: PA, YL, and ZYH designed and performed the experiments, and they wrote the manuscript. PA also contributed to data integration and revision. YL also fabricated the device and performed the data analysis. ZYH further performed the computational modeling. MR contributed to the 3-D histology for modeling and simulation of deployment. SDV helped with the planning and deployment of sensors to the pre-clinical model. QC helped with the illustrations. RRSP helped with the planning of pre-clinical studies, imaging, and connecting with CV path for histology. RE and PB helped with the clinical correlation and manuscript revision. YCT supervised the microfabrication of the catheter-based sensors and data analyses. TKH conceived, implemented, and supported the project, and he revised the manuscript. Competing interests: none.Attached Files
Submitted - 2020.09.24.312025v1.full.pdf
Supplemental Material - media-1.pdf
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Additional details
- Eprint ID
- 105581
- Resolver ID
- CaltechAUTHORS:20200928-103350812
- NIH
- R01HL111437
- NIH
- R01HL118650
- NIH
- R01HL149808
- NIH Predoctoral Fellowship
- GM008042
- UCLA
- Created
-
2020-09-28Created from EPrint's datestamp field
- Updated
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2021-11-16Created from EPrint's last_modified field