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Beyond the Nucleus: Cytoplasmic Dominance in Follicular Thyroid Carcinoma Detection Using Single-Cell Raman Imaging

Aurelien Pelissier1,2, Kosuke Hashimoto3,4, Kentaro Mochizuki3

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Raman spectroscopy can differentiate follicular thyroid carcinoma (FTC) from normal thyroid (NT) cells by analyzing cytoplasmic biochemical changes. Cytoplasmic analysis achieved 84% accuracy, outperforming nuclear analysis for FTC diagnosis.

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Area of Science:

  • Endocrine Oncology
  • Cytopathology
  • Biochemical Analysis

Background:

  • Follicular thyroid carcinoma (FTC) diagnosis is challenging due to subtle morphological indicators.
  • Nuclear abnormalities are typical cancer indicators, but FTC shows cytoplasmic features like carotenoids and lipid droplets as more relevant.
  • Raman spectroscopy detects biochemical changes, often preceding morphological alterations in cancer detection.

Purpose of the Study:

  • To investigate the spatial origin of diagnostic signals in FTC versus normal thyroid (NT) cells using single-cell Raman imaging.
  • To assess the independent contributions of the nucleus and cytoplasm to Raman-based cytopathology for FTC.
  • To evaluate the diagnostic accuracy and transferability of Raman spectroscopy for FTC detection.

Main Methods:

  • Single-cell Raman imaging was employed to analyze both nuclear and cytoplasmic regions of FTC and NT cells.
  • Cells were analyzed under coculture conditions across two cell lines from different donors.
  • Classification models were built using spectral data from nucleus and cytoplasm separately.

Main Results:

  • Raman spectra from the cytoplasmic region distinguished FTC from NT cells with 84% accuracy.
  • Classification based on nuclear spectra yielded only 53% accuracy.
  • Results were consistent across cell lines, donors, and multiple devices, demonstrating robustness.

Conclusions:

  • Cytoplasmic biochemical alterations are more significant for FTC detection than nuclear changes.
  • Raman spectroscopy, particularly focusing on the cytoplasm, shows high potential for improving FTC cytological diagnosis.
  • This approach provides valuable organelle-dependent information, complementing traditional methods and showing device transferability.