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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...

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Autores principales: Miyazaki, Yoshiaki, Tabata, Nobuyuki, Kubo, Yuichiro, Shinozaki, Kenji
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Scientific Scholar 2021
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
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author Miyazaki, Yoshiaki
Tabata, Nobuyuki
Kubo, Yuichiro
Shinozaki, Kenji
author_facet Miyazaki, Yoshiaki
Tabata, Nobuyuki
Kubo, Yuichiro
Shinozaki, Kenji
author_sort Miyazaki, Yoshiaki
collection PubMed
description 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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spelling pubmed-78815012021-02-16 Utility of Tissue Classification in Invasive Ductal Carcinoma using Dynamic Magnetic Resonance Imaging of the Mammary Gland Miyazaki, Yoshiaki Tabata, Nobuyuki Kubo, Yuichiro Shinozaki, Kenji J Clin Imaging Sci Original Research 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. Scientific Scholar 2021-01-18 /pmc/articles/PMC7881501/ /pubmed/33598361 http://dx.doi.org/10.25259/JCIS_173_2020 Text en © 2020 Published by Scientific Scholar on behalf of Journal of Clinical Imaging Science https://creativecommons.org/licenses/by-nc-sa/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-Share Alike 4.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as the author is credited and the new creations are licensed under the identical terms.
spellingShingle Original Research
Miyazaki, Yoshiaki
Tabata, Nobuyuki
Kubo, Yuichiro
Shinozaki, Kenji
Utility of Tissue Classification in Invasive Ductal Carcinoma using Dynamic Magnetic Resonance Imaging of the Mammary Gland
title Utility of Tissue Classification in Invasive Ductal Carcinoma using Dynamic Magnetic Resonance Imaging of the Mammary Gland
title_full Utility of Tissue Classification in Invasive Ductal Carcinoma using Dynamic Magnetic Resonance Imaging of the Mammary Gland
title_fullStr Utility of Tissue Classification in Invasive Ductal Carcinoma using Dynamic Magnetic Resonance Imaging of the Mammary Gland
title_full_unstemmed Utility of Tissue Classification in Invasive Ductal Carcinoma using Dynamic Magnetic Resonance Imaging of the Mammary Gland
title_short Utility of Tissue Classification in Invasive Ductal Carcinoma using Dynamic Magnetic Resonance Imaging of the Mammary Gland
title_sort utility of tissue classification in invasive ductal carcinoma using dynamic magnetic resonance imaging of the mammary gland
topic Original Research
url 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
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