Differentiating between normal and cancerous thyroid tissue using quantitative Second Harmonic Generation microscopy

Orhun O. Davarci; Raksha Raghunathan; Hong Zhao; Stephen T. C. Wong

doi:10.1117/12.3049431

21 October 2024 Differentiating between normal and cancerous thyroid tissue using quantitative Second Harmonic Generation microscopy

Orhun O. Davarci, Raksha Raghunathan, Hong Zhao, Stephen T. C. Wong

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Proceedings Volume 13186, SPIE Translational Biophotonics + Additive Manufacturing for Photonics 2024; 131861V (2024) https://doi.org/10.1117/12.3049431
Event: SPIE Translational Biophotonics + Additive Manufacturing for Photonics, 2024, Houston, Texas, United States

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Abstract

Significant challenges such as a high proportion of indeterminate results, inadequate sampling, and false positives remain prevalent in the diagnosis of thyroid cancer when using fine needle aspiration biopsy or core needle biopsy. Second harmonic generation (SHG) imaging is a label-free, nonlinear optical imaging method that selectively uses fibrillar collagen arrangement to provide endogenous contrast. We investigated applications of SHG-specific feature extraction methods such as anisotropy, and more broadly applied gray-level co-occurrence matrices to generate quantitative metrics that describe either the structural or physical properties of the imaged thyroid samples. The features differed significantly between thyroid cancer and normal thyroid samples, thus independently possessing the capability to differentiate between cancerous and normal thyroid tissue.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

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Orhun O. Davarci, Raksha Raghunathan, Hong Zhao, and Stephen T. C. Wong "Differentiating between normal and cancerous thyroid tissue using quantitative Second Harmonic Generation microscopy", Proc. SPIE 13186, SPIE Translational Biophotonics + Additive Manufacturing for Photonics 2024, 131861V (21 October 2024); https://doi.org/10.1117/12.3049431

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