Rapid, label-free diagnosis of thyroid cancer using SHG imaging

Thyroid cancer has emerged as one of the most prevalent malignant endocrine tumors worldwide. Although fine-needle aspiration cytology (FNAC) is commonly used in clinical diagnosis, its accuracy heavily depends on the clinician's expertise and subjective pathological interpretation, increasing the risk of misdiagnosis or oversight. In this study, second-harmonic generation (SHG) imaging was employed to visualize and quantitatively assess collagen fibers in thyroid tissues. A collagen scoring system was constructed using least absolute shrinkage and selection operator (LASSO) regression. The findings demonstrate that collagen fibers provide strong discriminatory power for distinguishing thyroid cancer from normal tissue.