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Utility of Tissue Classification in Invasive Ductal Carcinoma using Dynamic Magnetic Resonance Imaging of the Mammary Gland
OBJECTIVES: In Japan, invasive ductal carcinomas, which account for 75% of breast cancer cases, are sub-classified as solid, tubule-forming, scirrhous, and other types based on the histopathological findings. Although time-intensity curve (TIC) analysis of magnetic resonance (MR) images has shown di...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Scientific Scholar
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7881501/ https://www.ncbi.nlm.nih.gov/pubmed/33598361 http://dx.doi.org/10.25259/JCIS_173_2020 |
Sumario: | OBJECTIVES: In Japan, invasive ductal carcinomas, which account for 75% of breast cancer cases, are sub-classified as solid, tubule-forming, scirrhous, and other types based on the histopathological findings. Although time-intensity curve (TIC) analysis of magnetic resonance (MR) images has shown diagnostic ability in differentiating benign and malignant tumors, its ability to diagnose different tumor tissue types has not yet been achieved. In this study, we report a histological classification of invasive ductal carcinoma using the TIC analysis of dynamic MR images of the mammary gland. MATERIAL AND METHODS: A total of 312 invasive ductal carcinomas were analyzed, and each tissue type that indicated malignancy in the washout parts of the tumors was classified and characterized using the TIC. RESULTS: The tissue was classified, and the results were then compared to the pathohistological diagnosis. Using this method, the accuracy of tissue classification by quantitative analysis of TIC-MR images was 86.9% (271/312), which was higher than that obtained by ultrasonography 68.9% (215/312). CONCLUSION: This method is effective for classifying tissue types in invasive ductal carcinoma. |
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