Simulated fine-needle aspiration diagnosis of follicular thyroid nodules by hyperspectral Raman microscopy and chemometric analysis.

SIGNIFICANCE: Follicular thyroid carcinoma carries a substantially poor prognosis due to its unique biological behavior and less favorable outcomes. In particular, fine-needle aspiration (FNA) biopsies, which play a key role in screening thyroid nodules, cannot differentiate benign from malignant follicular neoplasm. AIM: We report on the use of hyperspectral Raman microscopy in combination with chemometric analysis for identifying and classifying single cells obtained from clinical samples of human follicular thyroid neoplasms. APPROACH: We used a method intended to simulate the FNA procedure to obtain single cells from thyroid nodules. A total of 392 hyperspectral Raman images of single cells from follicular thyroid neoplasms were collected. RESULTS: Malignant cells were identified based on their intrinsic Raman spectral signatures with an overall diagnostic accuracy of up to 83.7%. CONCLUSIONS: Our findings indicate that hyperspectral Raman microscopy can potentially be developed into an ancillary test for analyzing single cells from thyroid FNA biopsies to better stratify "indeterminate" nodules and other cytologically challenging cases.

Diagnosing Hirschsprung disease by detecting intestinal ganglion cells using label-free hyperspectral microscopy.

Hirschsprung disease (HD) is a congenital disorder in the distal colon that is characterized by the absence of nerve ganglion cells in the diseased tissue. The primary treatment for HD is surgical intervention with resection of the aganglionic bowel. The accurate identification of the aganglionic segment depends on the histologic evaluation of multiple biopsies to determine the absence of ganglion cells in the tissue, which can be a time-consuming procedure. We investigate the feasibility of using a combination of label-free optical modalities, second harmonic generation (SHG); two-photon excitation autofluorescence (2PAF); and Raman spectroscopy (RS), to accurately locate and identify ganglion cells in murine intestinal tissue without the use of exogenous labels or dyes. We show that the image contrast provided by SHG and 2PAF signals allows for the visualization of the overall tissue morphology and localization of regions that may contain ganglion cells, while RS provides detailed multiplexed molecular information that can be used to accurately identify specific ganglion cells. Support vector machine, principal component analysis and linear discriminant analysis classification models were applied to the hyperspectral Raman data and showed that ganglion cells can be identified with a classification accuracy higher than 95%. Our findings suggest that a near real-time intraoperative histology method can be developed using these three optical modalities together that can aid pathologists and surgeons in rapid, accurate identification of ganglion cells to guide surgical decisions with minimal human intervention.

Raman-based cytopathology: an approach to improve diagnostic accuracy in medullary thyroid carcinoma.

Medullary thyroid carcinoma (MTC) is a rare form of thyroid malignancy that can be diagnostically challenging on fine needle aspiration (FNA) cytology. Ancillary tests such as elevated serum or immunohistochemical positive calcitonin have been helpful, yet they can occasionally provide false positive results. In search for an alternative method to improve diagnostic accuracy (DA), we applied hyperspectral Raman spectroscopy to characterize the biochemical composition of single cells from MTC and compared their spectral information to cells from other types of thyroid nodules. Hyperspectral Raman images of 117 MTC single cells from digested tissue were obtained with a line-scan hyperspectral Raman microscope and compared to 127 benign and 121 classic variant of papillary thyroid carcinoma (CVPTC) cells. When principal component analysis and linear discriminant analysis were used to classify the spectral data, MTC cells were differentiated from benign and CVPTC cells with 97% and 99% DA, respectively. In addition, MTC cells exhibited a prominent Raman peak at 1003 cm-1, whose intensity is 84% and 226% greater on average than that observed in benign and CVPTC cells, respectively. When specifically utilizing only this peak as a spectral marker, MTC cells were separated from benign and CVPTC cells with 87% and 95% DA, respectively. As this peak is linked to phenylalanine, which is known to be associated with calcitonin release in thyroid parafollicular cells, the increased intensity further suggests that this Raman peak could potentially be a new diagnostic marker for MTC. Furthermore, preliminary data from MTC cells (n=21) isolated from a simulated FNA procedure provided similar Raman signatures when compared to single cells from digestion. These results suggest that "Raman-based cytopathology" can be used as an adjunct technique to improve the diagnostic accuracy of FNA cytopathology at a single cell level.