New Diagnostic Tool for Thyroid Cancer

August 13, 2019


Naveed Saleh, MD, MS
Hyperspectral Raman microscopy could be developed into a highly sensitive and highly specific objective approach in the analysis of single cells from fine needle aspiration (FNA) biopsies to allow for minimally invasive diagnosis of “indeterminate” thyroid nodules and similarly challenging presentations, according to the results of a study published in Biomedical Optics Express. This new approach could be an accurate ancillary tool for assessing FNA samples to enhance diagnostic cytopathology and circumvent unwarranted surgery.


“Thyroidectomy remains the treatment of choice, although [the] majority of the excised nodules are ultimately benign,” wrote authors led by Marcos A. S. de Oliveira, PhD, Department of Pathology & Laboratory Medicine, University of California Davis, Sacramento. “Hence, a novel approach that can more accurately diagnose and differentiate thyroid nodules would avoid unnecessary surgeries and have a major impact in patient care and management.”


In the current study, researchers used line-scan hyperspectral Raman microscopy, multivariate statistical analyses, principal component analysis, and linear discriminant analysis to assess the multidimensional spectral data with the intent of optimizing group separation and determining the diagnostic accuracy of the Raman spectral signatures in different thyroid nodules. The team identified spectral differences secondary to phenylalanine, tryptophan, lipids, proteins, and nucleic acids in benign and papillary carcinoma cells.

In total, 248 hyperspectral Ramen images of single cells were collected, with 127 from benign thyroid nodules and 121 from classic variant papillary carcinoma nodules. Cells were identified with 97% diagnostic accuracy by means of principal component analysis and linear discriminant analysis. Furthermore, preliminary data of cells derived from follicular adenoma (n = 20), follicular carcinoma (n = 25), and follicular variant of papillary carcinoma (n = 18) nodules suggest the viability of additional discrimination of subtypes.

Raman spectroscopy is a label-free spectroscopic method based on inelastic scattering of light via vibrational modes of chemical bonds. It allows for the identification of intrinsic molecules (eg, amino acids, nucleic acids, protein, and lipids) in cells and tissues. With this technique, subtle differences in chemical composition and structure results in changes in peak intensities or positions in a Raman spectrum. Advantages of this technique include the provision of the following:  1) intrinsic chemical information of the sample without the need for exogenous labels or stains, 2) subcellular spatial resolution if examined with a confocal microscope; and 3) nondestructive and noninvasive diagnostics. Previous research with Raman microscopy has focused on thyroid commercial cell lines and supported the improved diagnosis of thyroid tissues

Between 10 and 30% of thyroid nodules express “indeterminate” cytology per the Bethesda System for Reporting Thyroid Cytopathology. With these cases, it’s impossible for the cytopathologist to gauge whether the nodule is benign or malignant and the patient is faced with the uncertainty of whether surgery is necessary. To date, researchers have developed various genetic based molecular studies to help clinicians manage patients with indeterminate thyroid nodules. Nevertheless, the positive predictive value of these approaches has been suboptimal. Consequently, although most nodules end up being benign and surgery is unnecessary, thyroidectomy remains the treatment of choice.

“Our methodology of converting a hyperspectral image into a single-cell Raman spectrum more accurately captures the chemical composition of the entire cell compared to other studies that acquire a Ramen spectrum of a cell by sampling only an arbitrary fraction of the cell volume,” concluded the authors. “The high reproducibility and diagnostic accuracy of our data may be attributed to our method’s ability to adequately sample the entire cell. Our preliminary results even show excellent discrimination of cells that cannot be distinguished by current cytopathologic FNA analysis.”