RESUMO
Breast magnetic resonance imaging (MRI) has demonstrated increased sensitivity over conventional imaging in identifying and characterizing in situ and invasive, multifocal, and multicentric disease. A histologic diagnosis is required for any enhancing lesion displaying suspicious features, especially in the presence of lower and often variable reported specificity values. Breast MRI findings occult on mammography and ultrasound should undergo an MR-guided biopsy. We retrospectively evaluate our 8 years' experience with this procedure. Our study included 259 lesions in 255 consecutive patients referred for MR-guided breast biopsy. MRI screening of women at a high risk for developing breast cancer accounted for 84 lesions, 54 lesions were detected on MRI staging for multifocal and multicentric disease, and 115 were incidental findings or lesions that presented diagnosis related issues on conventional imaging. Six procedures were cancelled due to lack of visualization. MR-guided breast biopsy was performed for 100 mass and 153 nonmass enhancements. Pathology results were classified into benign (113 lesions), high risk (47 lesions), and malignant (40 ductal carcinoma in situ, 38 invasive ductal carcinoma, 15 invasive lobular carcinoma). Subsequent surgery for high risk and malignant findings revealed an underestimation rate of 34% (16/47) for high risk lesions and of 7.5% for ductal carcinoma in situ (3/40). The overall positive predictive value (PPV) was calculated at 43.1% (33.3% for high-risk women, 70.3% for cancer staging, and 37.4% for incidental/undetermined lesions). The PPV was higher for mass (57%) versus nonmass enhancements (34%). MR-guided breast biopsy proved to be a reliable procedure for the diagnosis and management of occult breast MRI findings, or lesions that preclude biopsy under conventional guidance. The PPV displayed significant variation between patient subgroups, correlating higher values with a higher associated breast cancer prevalence.
Assuntos
Neoplasias da Mama/patologia , Biópsia Guiada por Imagem/métodos , Imageamento por Ressonância Magnética/métodos , Adulto , Idoso , Idoso de 80 Anos ou mais , Carcinoma Intraductal não Infiltrante/patologia , Carcinoma Lobular/patologia , Feminino , Humanos , Pessoa de Meia-Idade , Estudos Retrospectivos , Vácuo , Adulto JovemRESUMO
PURPOSE: To determine the diagnostic performance of Acoustic Radiation Force Impulse (ARFI) Virtual Touch IQ shear wave elastography in the discrimination of benign and malignant breast lesions. MATERIALS AND METHODS: Conventional B-mode and elasticity imaging were used to evaluate 110 breast lesions. Elastographic assessment of breast tissue abnormalities was done using a shear wave based technique, Virtual Touch IQ (VTIQ), implemented on a Siemens Acuson S3000 ultrasound machine. Tissue mechanical properties were interpreted as two-dimensional qualitative and quantitative colour maps displaying relative shear wave velocity. Wave speed measurements in m/s were possible at operator defined regions of interest. The pathologic diagnosis was established on samples obtained by ultrasound guided core biopsy or fine needle aspiration. RESULTS: BIRADS based B-mode evaluation of the 48 benign and 62 malignant lesions achieved 92% sensitivity and 62.5% specificity. Subsequently performed VTIQ elastography relying on visual interpretation of the colour overlay displaying relative shear wave velocities managed similar standalone diagnostic performance with 92% sensitivity and 64.6% specificity. Lesion and surrounding tissue shear wave speed values were calculated and a significant difference was found between the benign and malignant populations (Mann-Whitney U test, p<0.0001). By selecting a lesion cut-off value of 3.31m/s we achieved 80.4% sensitivity and 73% specificity. Applying this threshold only to BIRADS 4a masses, we reached overall levels of 92% sensitivity and 72.9% specificity. CONCLUSION: VTIQ qualitative and quantitative elastography has the potential to further characterise B-mode detected breast lesions, increasing specificity and reducing the number of unnecessary biopsies.
Assuntos
Neoplasias da Mama/diagnóstico por imagem , Técnicas de Imagem por Elasticidade/métodos , Interpretação de Imagem Assistida por Computador/métodos , Palpação/métodos , Ultrassonografia Mamária/métodos , Interface Usuário-Computador , Adulto , Idoso , Feminino , Humanos , Aumento da Imagem/métodos , Pessoa de Meia-Idade , Imagem Multimodal/métodos , Variações Dependentes do Observador , Reprodutibilidade dos Testes , Sensibilidade e Especificidade , TatoRESUMO
BACKGROUND: When any atypical feature is identified on a percutaneous biopsy specimen of a suspicious breast lesion, surgical excision is mandatory, leading to unnecessary surgeries in 70-90% of the cases. The purpose of this study was to develop a model to predict the presence of cancer at surgery that would be applicable to all atypical lesions. METHODS: We collected complete clinical, radiological, and double-reading histological data concerning all patients with a diagnosis of a pure atypical lesion on image-guided biopsy performed at the One-Stop Breast Care Unit between 2004 and 2011. RESULTS: Among the 204 eligible patients, 49 cancers (24%) had been diagnosed at definitive surgery (20 ductal carcinoma in situ, 20 invasive ductal, and 9 invasive lobular carcinoma). The univariate analysis retrieved age (p=0.03), the focus size in mm (p=0.02), the number of biopsy cores (p=0.02), the disappearance of radiological anomalies after biopsy (p=0.05), the mean number of atypical foci (p=0.05) and the percentage of atypical lobules and ducts for lobular neoplasia (p=0.04) as factors associated with cancer at surgery, whereas neither Ki67 nor ALDH1 expression was significantly correlated. The final most informative nomogram comprised information on patient age, the disappearance of radiological anomalies after biopsy and a focus size>15 mm. For the optimal threshold (risk of cancer=21%), sensitivity, specificity, positive predictive value, and negative predictive value were 78, 66, 36, and 90%, respectively. CONCLUSIONS: After validation, this model could help to identify a subset of patients with premalignant disease who could be spared surgery.