English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Background: Diagnostic accuracy of the standard of care fine-needle aspiration cytology (FNAC) remains a significant problem in thyroid oncology. Therefore, a robust and accurate method for reducing uncertainty of cytopathological evaluation would be invaluable. Methods: In this double-blind study, we employed fluorescence emission and quantitative fluorescence polarization (Fpol) confocal imaging for sorting thyroid cells into benign/malignant categories. Samples were collected from malignant tumors, benign nodules, and normal thyroid epithelial tissues. Results: A total of 32 samples, including 12 from cytologically indeterminate categories, were stained using aqueous methylene blue (MB) solution, imaged, and analyzed. Fluorescence emission images yielded diagnostically relevant information on cytomorphology. Significantly higher MB Fpol was measured in thyroid cancer as compared to benign and normal cells. The results obtained from 12 indeterminate samples revealed that MB Fpol accurately differentiated benign and malignant thyroid nodules. Conclusions: The developed imaging approach holds the potential to provide an accurate and objective biomarker for thyroid cancer, improve diagnostic accuracy of cytopathology, and decrease the number of lobectomy and near-total thyroidectomy procedures.

Fluorescence Polarization Imaging of Methylene Blue Facilitates Quantitative Detection of Thyroid Cancer in Single Cells