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Thyroid lesions categories iii and IV: malignancy detection by computer analysis of nuclear images

Grant number: 16/14988-6
Support type:Scholarships in Brazil - Scientific Initiation
Effective date (Start): November 01, 2016
Effective date (End): October 31, 2018
Field of knowledge:Health Sciences - Medicine - Pathological Anatomy and Clinical Pathology
Principal researcher:Gláucia Maria Ferreira da Silva Mazeto
Grantee:Danilo Takeshi Abe Jaune
Home Institution: Faculdade de Medicina (FMB). Universidade Estadual Paulista (UNESP). Campus de Botucatu. Botucatu , SP, Brazil


Although thyroid cancer is the most common endocrine neoplasia, its incidence is reduced. The differentiated thyroid carcinoma (DTC) corresponds to 90% of all thyroid carcinomas and is mainly represented by papillary (PC) and follicular carcinomas (FC) subtypes. According to the Bethesda System, the fine-needle aspiration (FNA) of thyroid nodules may be specified in six classes. As the risk of malignancy in classes III and IV is still unclear, there are divergences about which conduct to be used. Therefore, the computer analysis of certain nuclear parameters of follicular cells may show a better identification of malignancy in these two classes. Objectives: To evaluate nuclear parameters, using computerized image analysis, in cytological material obtained from thyroid nodules cytologically diagnosed in categories III and IV, and relate them with the final histological diagnose. Methodology: It will be studied cytological material from thyroid nodules, obtained from FNA between 2009 and 2015 in the Botucatu Clinics Hospital, and diagnosed as III and IV categories according to Bethesda System. Follicular nuclei will be analyzed by a software named Image J, that will consider morphometric and textural parameters. Eventually, it will be observed if these nuclear parameters are able to predict the lesion malignancy, according to the final histological diagnose.

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Scientific publications
(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)
HAYASHI, CAROLINE Y.; JAUNE, DANILO T. A.; OLIVEIRA, CRISTIANO C.; COELHO, BARBARA P.; MIOT, HELIO A.; MARQUES, MARIANGELA E. A.; TAGLIARINI, JOSE VICENTE; CASTILHO, EMANUEL C.; SOARES, CARLOS S. P.; OLIVEIRA, FLAVIA R. K.; SOARES, PAULA; MAZETO, GLAUCIA M. F. S. Indeterminate thyroid cytology: detecting malignancy using analysis of nuclear images. ENDOCRINE CONNECTIONS, v. 10, n. 7, p. 707-714, JUL 2021. Web of Science Citations: 0.

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