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Highly Sensitive Terahertz Metasurface Based on Electromagnetically Induced Transparency-Like Resonance in Detection of Skin Cancer Cells

  • Shohreh Nourinovin
  • , Muhammad M. Rahman
  • , Mira Naftaly
  • , Michael P. Philpott
  • , Qammer H. Abbasi
  • , Akram Alomainy
  • Queen Mary University of London
  • National Physical Laboratory
  • University of Glasgow

Research output: Contribution to journalArticlepeer-review

39 Scopus citations

Abstract

Terahertz (THz) metasurfaces based on high Q-factor electromagnetically induced transparency-like (EIT-like) resonances are promising for biological sensing. Despite this potential, they have not often been investigated for practical differentiation between cancerous and healthy cells. The present methodology relies mainly on refractive index sensing, while factors of transmission magnitude and Q-factor offer significant information about the tumors. To address this limitation and improve sensitivity, we fabricated a THz EIT-like metasurface based on asymmetric resonators on an ultra-thin and flexible dielectric substrate. Bright-dark modes coupling at 1.96 THz was experimentally verified, and numerical results and theoretical analysis were presented. An enhanced theoretical sensitivity of 550 GHz/RIU was achieved for a sample with a thickness of 13 μm due to the ultra-thin substrate and novel design. A two-layer skin model was generated whereby keratinocyte cell lines were cultured on a base of collagen. When NEB1-shPTCH (basal cell carcinoma (BCC)) were switched out for NEB1-shCON cell lines (healthy) and when BCC's density was raised from 1 × 105 to 2.5 × 105, a frequency shift of 40 and 20 GHz were observed, respectively. A combined sensing analysis characterizes different cell lines. The findings may open new opportunities for early cancer detection with a fast, less-complicated, and inexpensive method.

Original languageEnglish
Pages (from-to)2180-2188
Number of pages9
JournalIEEE Transactions on Biomedical Engineering
Volume71
Issue number7
DOIs
StatePublished - 1 Jul 2024
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • EIT-like resonance
  • Terahertz
  • early cancer detection
  • metasurface

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