| Abstract | The objective of this study was to assess the feasibility of infrared spectroscopy as an alternative means of screening for the diagnosis of thyroid tumors. A total of 89 fine-needle aspirates were obtained from patients with various thyroid disorders. Infrared spectra were recorded from original aspirates as well as from cell pellets obtained after centrifugation. The spectra were analyzed by two different multivariate statistical methods using the clinical data as reference. An unsupervised cluster analysis of cell pellet spectra revealed a good separation of normal cells from tumor cells with an accuracy of 94.7%. When using spectra of the original aspirates, the separation of normal and tumor was only 65.3%. However, by using a supervised methodology, such as the linear discriminant analysis, the partition of the original aspirates into normal and tumor groups was highly successful; the accuracy for the training set was 96.6%, while that for the validation set was as high as 90.2%. These results suggest that this new methodology, after appropriate refinement, has the potential of screening for thyroid tumors from fine-needle aspirate samples. |
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