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J Cancer Res Ther ; 12(2): 744-50, 2016.
Artículo en Inglés | MEDLINE | ID: mdl-27461644

RESUMEN

PURPOSE: The present meta-analysis investigated the clinical value of apparent diffusion coefficient (ADC) values in diffusion-weighted imaging (DWI) for differential diagnosis of ductal carcinoma in situ (DCIS) and infiltrating ductal carcinoma (IDC). MATERIALS AND METHODS: Electronic databases searches were employed to identify relevant scientific literature, and the search results were screened to selected high-quality studies for this meta-analysis. Methodological quality of the enrolled studies was evaluated by quality evaluation of diagnostic accuracy studies (QUADAS). Summary odds ratios (ORs) and its corresponding 95% confidence interval (95% CI) were calculated for DCIS versus IDC category of ADC value using Z test. RESULTS: Our meta-analysis contained a combined total of 1,097 subjects (928 patients with IDC and 169 patients with DCIS) from 9 relevant high-quality cohort studies. Pooled ORs demonstrated that ADC value in IDC patients was significantly lower than DCIS patients. Subgroup analysis stratified by ethnicity indicated a higher ADC value in DCIS patients compared to IDC, in Asian population, but not in Caucasians. Magnetic resonance imaging (MRI) machine type-stratified analysis revealed that the ADC value of DWI obtained from both non- General Electric Company (GE) 1.5T and GE 1.5T machines were highly reliable in the differential diagnosis of DCIS and IDC. CONCLUSION: Our meta-analysis provides evidence that ADC values in DWI accurately conveys the differences in tumor architecture between IDC and DCIS, which has high clinical value in differentiatal diagnosis of IDC and DCIS. This may lead to improved BC prediction and treatment.


Asunto(s)
Carcinoma de Mama in situ/diagnóstico , Neoplasias de la Mama/diagnóstico , Carcinoma Ductal de Mama/diagnóstico , Imagen de Difusión por Resonancia Magnética/métodos , Diagnóstico Diferencial , Femenino , Humanos , Oportunidad Relativa , Sesgo de Publicación , Sensibilidad y Especificidad
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