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Usefulness of Evaluation of Nuclear Color by Visible-Microscopic Spectroscopy for Objective Differentiation between Non-Cancer and Cancer Cells Prepared Using Liquid-Based Cytology

Abstract

Haruhiko Yoshioka, Keita Hoshiai, Toshiya Nakamura, Kayo Horie, Kiyotada Washiya and Jun Watanabe

Objective: The aims of this study were to investigate the usefulness of color evaluation of the nuclear region using visible-microscopic spectroscopy (Vis-MS) and to clarify whether it can serve as an index to distinguish cancer cells in liquid-based cytology (LBC). Vis-MS is a spectral analysis technique widely used for absorption and fluorometric analyses in the analytical chemistry field. Vis-MS has been applied to histological diagnosis, but only a few studies on its application to cytology have been performed, and no investigations have been performed for LBC, which is expected to become widely used in Japan.
Study design:
Using culture cell lines of non-cancer cells and cancer cells, transmittance at 530 nm (maximum absorption wavelength of eosin), 580 nm (hematoxylin), and 630 nm (light green), and 530 nm/580 nm and 630 nm/580 nm transmittance ratios were analyzed.
Results: Two variances of the transmittance at 580 nm and 630 nm/580 nm transmittance ratio were finally extracted as effective items after applying forward and backward variance selection and investigation of multicollinearity. The odds ratios of 580 nm transmittance and 630 nm/580 nm transmittance ratio were 0.48 and 0.72, respectively. The cancer cell discrimination predictive value determined using the logistic regression equation was 98.0%, being favorable.
Conclusion: It was suggested that Vis-MS is useful to evaluate the color of the nuclear region and serves as a cancer cell discrimination index for LBC. We are planning to apply Vis-MS to clinical materials and develop nuclear color evaluation using Vis-MS into an objective index for cases in which cancer cell judgment is difficult.

Isenção de responsabilidade: Este resumo foi traduzido usando ferramentas de inteligência artificial e ainda não foi revisado ou verificado

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