Acuidade de mamografia BI-RADS 4 e 5 na predição de malignidade em lesões não palpáveis da mama: correlação com a patologia

• Ano de defesa: 2011
• Autor(a) principal: Ricardo Alcantara da Silva
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Minas Gerais; UFMG
• Palavras-chave em Português: BI-RADS; Histopatologia; Câncer de mama; Mamografia; Neoplasias da mama/patologia; Palpação; Neoplasias da mama; Mama Diagnostico por imagem; Neoplasias da mama/radiografia; Biópsia por agulha; Mama Câncer; Neoplasias da mama/diagnóstico; Mama/anatomia & histologia
• Link de acesso: http://hdl.handle.net/1843/MCGI-8TBNV2

This study was done to evaluate the accuracy of mammography in the diagnosis of non-palpable breast lesions classified as BI-RADS 4 and 5 compared with the histopathology result, used as the "gold standard". The method was applied to 588 cases of breast biopsies with mammograms classified as suspicious (category 4 and 5) from the period of 1999 to 2009. The biopsies were made after marking the image with a metallic wire done with use of mammography and only cases of non-palpable breast lesions were included. The mammograms of these patients were classified according to the fourth edition of BI-RADS, evaluating categories 4 and 5. The correlation was made with mammographic and histopathological examinations of the lesions, evaluating the positive predictive value in each category. The results show 277 (47.1%) cases diagnosed with cancer, of whom 142 (32.9%) cases were Category 4 and 135 (86%) cases were category 5. The positive predictive values (PPV) for categories 4 and 5, and overall were respectively 32.9%, 86% and 47.1%. Mammography alterations more often associated with malignancy were microcalcifications (48.7%). Our results showed that the cases classified as high suspicion of malignancy (category 5) enable foretell malignancy in 86% and cases classified in category 4 in 34%.Concurring with the literature that emphasizes the need for new predictors for category 4.