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[Study of Cervical Exfoliated Cell's DNA Quantitative Analysis Based on Multi-Spectral Imaging Technology].

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    Guang Pu Xue Yu Guang Pu Fen Xi = Guang Pu
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    This study combines two cervical cancer screening methods using a novel multi-spectral imaging system. The developed absorbance unmixing model accurately quantifies DNA, enhancing early cancer detection.

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    Area of Science:

    • Biomedical Engineering
    • Cytopathology
    • Optical Imaging

    Background:

    • Conventional cervical cancer screening relies on The Bethesda System (TBS) classification and DNA quantitative analysis.
    • Simultaneously applying both methods on a single slide using multiple staining techniques is challenging due to potential absorbance interference from non-DNA materials.

    Purpose of the Study:

    • To develop a method for simultaneously performing TBS classification and cellular DNA quantitative analysis on a single cervical cell slide.
    • To overcome the interference of non-DNA material absorbance in multiple staining techniques for accurate DNA quantification.

    Main Methods:

    • A multi-spectral imaging system was developed to capture absorbance data.
    • An absorbance unmixing model using multiple linear regression was established to isolate DNA absorbance.
    • The model was validated by comparing calculated DNA absorbance with measured values and analyzing DNA index confidence intervals.

    Main Results:

    • The absorbance unmixing model demonstrated no statistically significant difference (p < 0.01) between calculated and measured DNA absorbance.
    • Actual application showed no overlap between the DNA index confidence interval of tetraploid cells and the cancer cell judging interval (99% confidence level).

    Conclusions:

    • The developed method accurately quantifies DNA in multiple-stained cervical cells, verifying the feasibility of combining TBS and DNA analysis.
    • This approach offers a promising tool for the early diagnosis of cervical cancer and potentially other cancers, with significant market potential.