Affordable Access

Access to the full text

Utility of Tissue Classification in Invasive Ductal Carcinoma using Dynamic Magnetic Resonance Imaging of the Mammary Gland

Authors
  • Miyazaki, Yoshiaki1
  • Tabata, Nobuyuki2
  • Kubo, Yuichiro3
  • Shinozaki, Kenji4
  • 1 Department of Radiological Technology, National Cancer Center, Tokyo , (Japan)
  • 2 Department of Radiology, National Hospital Organization Kyushu Medical Center, Fukuoka , (Japan)
  • 3 Department of Clinical Radiology, Kyushu University Hospital, Fukuoka , (Japan)
  • 4 Department of Radiology, National Hospital Organization Kyushu Cancer Center, Fukuoka , (Japan)
Type
Published Article
Journal
Journal of Clinical Imaging Science
Publisher
Scientific Scholar
Publication Date
Jan 18, 2021
Volume
11
Identifiers
DOI: 10.25259/JCIS_173_2020
PMID: 33598361
PMCID: PMC7881501
Source
PubMed Central
Keywords
Disciplines
  • Original Research
License
Green

Abstract

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.

Report this publication

Statistics

Seen <100 times