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  • Author: Glaucia M.f.s Mazeto x
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Open access

Flávia O Valentim, Bárbara P Coelho, Hélio A Miot, Caroline Y Hayashi, Danilo T A Jaune, Cristiano C Oliveira, Mariângela E A Marques, José Vicente Tagliarini, Emanuel C Castilho, Paula Soares, and Gláucia M F S Mazeto

Background

Computerized image analysis seems to represent a promising diagnostic possibility for thyroid tumors. Our aim was to evaluate the discriminatory diagnostic efficiency of computerized image analysis of cell nuclei from histological materials of follicular tumors.

Methods

We studied paraffin-embedded materials from 42 follicular adenomas (FA), 47 follicular variants of papillary carcinomas (FVPC) and 20 follicular carcinomas (FC) by the software ImageJ. Based on the nuclear morphometry and chromatin texture, the samples were classified as FA, FC or FVPC using the Classification and Regression Trees method.

Results

We observed high diagnostic sensitivity and specificity rates (FVPC: 89.4% and 100%; FC: 95.0% and 92.1%; FA: 90.5 and 95.5%, respectively). When the tumors were compared by pairs (FC vs FA, FVPC vs FA), 100% of the cases were classified correctly.

Conclusion

The computerized image analysis of nuclear features showed to be a useful diagnostic support tool for the histological differentiation between follicular adenomas, follicular variants of papillary carcinomas and follicular carcinomas.

Open access

Caroline Y. Hayashi, Danilo T. A. Jaune, Cristiano C. Oliveira, Bárbara P. Coelho, Hélio A. Miot, Mariângela E. A. Marques, José Vicente Tagliarini, Emanuel C. Castilho, Carlos Sp Soares, Flavia Rk Oliveira, Paula Soares, and Glaucia M.f.s Mazeto

Background: Thyroid nodules diagnosed as “Atypia of Undetermined Significance/Follicular Lesion of Undetermined Significance” (AUS/FLUS) or “Follicular Neoplasm/Suspected Follicular Neoplasm” (FN/SFN)”, according to Bethesda's classification, represent a challenge in clinical practice. Computerized analysis of nuclear images (CANI) could be a useful tool for these cases. Our aim was to evaluate the ability of CANI to correctly classify AUS/FLUS and FN/SFN thyroid nodules for malignancy.

Methods: We studied 101 nodules cytologically classified as AUS/FLUS (n=68) or FN/SFN (n=33) from 97 thyroidectomy patients. Slides with cytological material were submitted to manual selection and analysis of the follicular cell nuclei for morphometric and texture parameters using ImageJ software. The histologically benign and malignant lesions were compared for such parameters which were then evaluated for the capacity to predict malignancy using the Classification and Regression Trees Gini model. The Intraclass Coefficient of Correlation was used to evaluate method reproducibility.

Results: In AUS/FLUS nodule analysis, the benign and malignant nodules differed for Entropy (p<0.05), while the FN/SFN nodules differed for Fractal analysis, coefficient of variation (CV) of roughness, and CV-Entropy (p<0.05). Considering the AUS/FLUS and FN/SFN nodules separately, it correctly classified 90.0% and 100.0% malignant nodules, with a correct global classification of 94.1% and 97%, respectively. We observed that reproducibility was substantially or nearly complete (0.61-0.93) in 10 of the 12 nuclear parameters evaluated.

Conclusion: CANI demonstrated an high capacity for correctly classifying AUS/FLUS and FN/SFN thyroid nodules for malignancy. This could be a useful method to help increase diagnostic accuracy in the indeterminate thyroid cytology.

Open access

Rui M B Maciel, Cleber P Camacho, Lígia V M Assumpção, Natassia E Bufalo, André L Carvalho, Gisah A de Carvalho, Luciana A Castroneves, Francisco M de Castro Jr, Lucieli Ceolin, Janete M Cerutti, Rossana Corbo, Tânia M B L Ferraz, Carla V Ferreira, M Inez C França, Henrique C R Galvão, Fausto Germano-Neto, Hans Graf, Alexander A L Jorge, Ilda S Kunii, Márcio W Lauria, Vera L G Leal, Susan C Lindsey, Delmar M Lourenço Jr, Léa M Z Maciel, Patrícia K R Magalhães, João R M Martins, M Cecília Martins-Costa, Gláucia M F S Mazeto, Anelise I Impellizzeri, Célia R Nogueira, Edenir I Palmero, Cencita H C N Pessoa, Bibiana Prada, Débora R Siqueira, Maria Sharmila A Sousa, Rodrigo A Toledo, Flávia O F Valente, Fernanda Vaisman, Laura S Ward, Shana S Weber, Rita V Weiss, Ji H Yang, Magnus R Dias-da-Silva, Ana O Hoff, Sergio P A Toledo, and Ana L Maia

Multiple endocrine neoplasia type 2 (MEN2) is an autosomal dominant genetic disease caused by RET gene germline mutations that is characterized by medullary thyroid carcinoma (MTC) associated with other endocrine tumors. Several reports have demonstrated that the RET mutation profile may vary according to the geographical area. In this study, we collected clinical and molecular data from 554 patients with surgically confirmed MTC from 176 families with MEN2 in 18 different Brazilian centers to compare the type and prevalence of RET mutations with those from other countries. The most frequent mutations, classified by the number of families affected, occur in codon 634, exon 11 (76 families), followed by codon 918, exon 16 (34 families: 26 with M918T and 8 with M918V) and codon 804, exon 14 (22 families: 15 with V804M and 7 with V804L). When compared with other major published series from Europe, there are several similarities and some differences. While the mutations in codons C618, C620, C630, E768 and S891 present a similar prevalence, some mutations have a lower prevalence in Brazil, and others are found mainly in Brazil (G533C and M918V). These results reflect the singular proportion of European, Amerindian and African ancestries in the Brazilian mosaic genome.