Publications by authors named "Tatiana L Poloz"

The cytological diagnosis of Hürthle cell (oncocytic) thyroid tumors by means of fine-needle aspiration biopsy represents a challenge, as Hürthle cell polymorphism and atypia alone are not indications of malignancy. In our recent work, an original diagnostic algorithm was proposed, which identified and typed malignant thyroid tumors by analyzing the molecular markers of cytological preparations. The aim of the present study was to assess the effectiveness of this algorithm at detecting Hürthle cell thyroid tumors in clinical samples used for cytological examination.

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Fine needle aspiration cytology (FNAC) is currently the method of choice for malignancy prediction in thyroid nodules. Nevertheless, in some cases the interpretation of FNAC results may be problematic due to limitations of the method. The expression level of some microRNAs changes with the development of thyroid tumors, and its quantitation can be used to refine the FNAC results.

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Background: The postoperative typing of thyroid lesions, which is instrumental in adequate patient treatment, is currently based on histologic examination. However, it depends on pathologist's qualification and can be difficult in some cases. Numerous studies have shown that molecular markers such as microRNAs and somatic mutations may be useful to assist in these cases, but no consensus exists on the set of markers that is optimal for that purpose.

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Objective: To analyze smears of 197 thyroid follicular tumors (adenoma and carcinoma).

Study Design: Several types of artificial neural networks (ANN) of various designs were used for diagnosis of thyroid follicular tumors. The typical complex of cytologic features, some nuclear morphometric parameters (area, perimeter, shape factor) and density features of chromatin texture (mean value and SD of gray levels) were defined for each tumor.

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