Hyperspectral Metachip‐Based 3D Spatial Map for Cancer Cell Screening and Quantification
In this paper, compact terahertz (THz) metachips for hyperspectral screening and quantitative evaluation of human cancer cells is reported. This pixelated resonant metachips feature the resonance channel from 1 and 3 THz frequency with a record-high quality factor (up to 230). Through the interactions of various cancer cells of different concentrations, high-dimensional spectral signatures are obtained, which are further transformed into a spatial map for labelling and quantification purposes. The screening of up to 15 cancer cells is experimentally reported, with very high detecting accuracy of 93.33% and with attractive quantitative concentration sensitivity up to 1320 kHz cell mL<sup>-1</sup>. This hyperspectral metachips are low-cost, highly compact, and label-free for fast, high-throughput and high-sensitivity detections and evaluation of human cancer cells. This technology does not require clinical experience, representing an accessible technology for early diagnosis of cancer.
Authors
- Xinyue Liang (ORCID: https://orcid.org/0000-0003-2177-2782)
- Guangwei Hu (ORCID: https://orcid.org/0000-0002-3023-9632)
- Cuong Dang (ORCID: https://orcid.org/0000-0001-6183-4082)
- Yanli Meng (ORCID: https://orcid.org/0000-0003-3497-6602)
- Xiaocong Tang
- Rui Luo (ORCID: https://orcid.org/0009-0001-3711-6643)
- Xumin Ding (ORCID: https://orcid.org/0000-0002-7725-790X)
- Chang‐Yin Ji (ORCID: https://orcid.org/0009-0006-4762-703X)
- Cong Wang (ORCID: https://orcid.org/0000-0002-5297-9586)
- Jian Liu (ORCID: https://orcid.org/0000-0002-2993-9607)
- Qun Wu (ORCID: https://orcid.org/0000-0001-9144-048X)
- Zihan Zhao (ORCID: https://orcid.org/0009-0003-8227-3108)
Institutions
- Shenzhen Institute of Information Technology (CN)
- Nanyang Technological University (SG)
- Harbin Institute of Technology (CN)
- Heilongjiang Academy of Sciences (CN)
Publication Details
- Journal
- Advanced Materials
- Published
- 2024-12-31
- DOI
- https://doi.org/10.1002/adma.202412738
- Citations
- 11
- Primary Topic
- Remote-Sensing Image Classification
- Type
- article
- Field-Weighted Citation Impact
- 3.52
Funders
- National Research Foundation Singapore
- National Natural Science Foundation of China
- National Key Research and Development Program of China