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Acad Radiol ; 18(6): 716-21, 2011 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-21420333

RESUMO

RATIONALE AND OBJECTIVES: We retrospectively determined if signal enhancement ratio (SER), a quantitative measure of contrast kinetics using volumetric parameters, could reduce the number of biopsy recommendations without decreasing the number of cancers detected when applied to suspicious lesions seen on breast magnetic resonance imaging (MRI). MATERIALS AND METHODS: A retrospective review of Breast Imaging Reporting and Data System (BIRADS) 4 or 5 lesions seen on breast MRI in 2008 that were clinically and mammographically occult yielded a final sample size of 73 lesions in 65 patients. Images were processed with in-house software. Parameters used to predict benignity/malignancy included SER total tumor volume (lesion volume above a 70% initial enhancement level), SER partial tumor volume (volume with "washout" and "plateau" kinetics), SER washout tumor volume, peak SER, and peak percent enhancement. Thresholds were determined to retrospectively discriminate benign from malignant histopathology. Clinical impact was assessed through the reduction in the number of biopsies recommended (by eliminating benign lesions discriminated by SER). RESULTS: Based on the original radiologist interpretations, 73 occult lesions were called suspicious and biopsied with a predictive value of biopsies (PPV(3)) of 18/73 (25%). SER parameters were found to be significantly associated with histopathology (P < .05). Biopsy recommendations could be reduced using SER parameters of SER partial tumor volume (73 to 40), SER total tumor volume (73 to 45), and peak percent enhancement (73 to 55) without removing true positives. CONCLUSION: The adjunctive use of SER parameters may reduce the number of recommended biopsies without reducing the number of cancers detected.


Assuntos
Biópsia , Neoplasias da Mama/diagnóstico , Meios de Contraste/farmacocinética , Gadolínio DTPA/farmacocinética , Imageamento por Ressonância Magnética/métodos , Feminino , Humanos , Interpretação de Imagem Assistida por Computador/métodos , Valor Preditivo dos Testes , Estudos Prospectivos , Estudos Retrospectivos , Sensibilidade e Especificidade
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