Current issues in the diagnosis of ductal carcinoma in situ: A radiopathological correlation

• Autores: Calderón N., Juan Manuel, Febles, Gustavo
• Formato: artículo
• Fecha de Publicación: 2017
• Institución: Universidad de San Martín de Porres
• Repositorio: Horizonte médico
• Lenguaje: español
• OAI Identifier: oai:horizontemedico.usmp.edu.pe:article/564
• Enlace del recurso: https://www.horizontemedico.usmp.edu.pe/index.php/horizontemed/article/view/564
• Nivel de acceso: acceso abierto
• Materia: Carcinoma ductal in situ; Microcalcificaciones; Mamografía; Resonancia magnética; Patología; Ductal carcinoma in situ; Microcalcifications; Mammography; Magnetic resonance imaging; Pathology

Ductal carcinoma in situ (DCIS) falls into a heterogeneous group of tumors, whose diagnosis has increased with the use of mammography as screening method. The Van Nuys Prognostic Index, mainly based on histological nuclear grade and presence of necrosis, is the most reproducible histopathological classification system. The most common abnormality observed during a mammography are microcalcifications, which coexist with other lesions such as masses and architectural distortion, and represent low-grade lesions. The initial diagnosis should be performed by anamnesis and a detailed physical examination to help determine the morphostructural characteristics of the lesion. Then an imaging and dynamic approach should be achieved by magnetic resonance imaging (MRI) complemented by immunohistochemistry to characterize the tumor. The presence of morphological segmental distribution is typical of malignancy (DCIS). The kinetics of the lesions using a dynamic MRI varies, with the washout and late enhancement pattern being pathognomonic for DCIS. However, the dynamic pattern seems to be correlated with mammographic findings. Multidetector CT and MRI findings may be useful in combination with breast MRI for preoperative mapping. Nevertheless, there are complementary techniques such as spectroscopy and weighted diffusion that improve the specificity of the MRI and are useful in predicting response to adjuvant chemotherapy. These future applications will improve the ability for early diagnosis and treatment options.