ArticleFrontiers in chemistry2021
Detection and Classification of Multi-Type Cells by Using Confocal Raman Spectroscopy.
Article in Frontiers in chemistry, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 14 citations in OpenAlex.
- Predicting targeted- and immunotherapeutic response outcomes in melanoma with single-cell Raman spectroscopy and AI.bioRxiv : the preprint server for biology · 2026Article
- Integrating spatial and chemical information enhances differentiation of non-alcoholic steatohepatitis states in Raman imaging.Scientific reports · 2025Article
- In-line Raman imaging of mixing by herringbone grooves in microfluidic channels.Lab on a chip · 2024Article
- Assessment of Primary Human Liver Cancer Cells by Artificial Intelligence-Assisted Raman Spectroscopy.Cells · 2023Article
- Inflammation and fibrosis in the coal dust-exposed lung described by confocal Raman spectroscopy.PeerJ · 2022Article
Corrections and comments
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Authors and funding
8 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Tumor cells circulating in the peripheral blood are the prime cause of cancer metastasis and death, thus the identification and discrimination of these rare cells are crucial in the diagnostic of cancer. As a label-free detection method without invasion, Raman spectroscopy has already been indicated as a promising method for cell identification. This study uses a confocal Raman spectrometer with 532 nm laser excitation to obtain the Raman spectrum of living cells from the kidney, liver, lung, skin, and breast. Multivariate statistical methods are applied to classify the Raman spectra of these cells. The results validate that these cells can be distinguished from each other. Among the models built to predict unknown cell types, the quadratic discriminant analysis model had the highest accuracy. The demonstrated analysis model, based on the Raman spectrum of cells, is propitious and has great potential in the field of biomedical for classifying circulating tumor cells in the future.
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