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Updated: Jan 28, 2026

Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
Published on: May 17, 2019
Correlation Analysis of Breast Cancer DWI Combined with DCE-MRI Imaging Features with Molecular Subtypes and
Congru Yuan1, Feng Jin2, Xiuling Guo2
1Department of Geriatrics, The Affiliated Hospital of Inner Mongolia Medical University, Huhhot, 010110, Inner Mongolia, China.
Abstract:
This study aimed to deeply analyze the application of DWI and DCE-MRI imaging in breast cancer, the correlation between the imaging characteristics of DWI and DCE-MRI and the molecular subtypes and prognostic factors of breast cancer was studied. Firstly, DWI and DCE-MRI scans of all patients before interventional therapy were performed, and relevant information of the subjects was introduced in turn. Secondly, molecular subtypes were determined according to immunohistochemical results and gene amplification. Siemens 3.0 T post-processing workstation was used for image post-processing. The time signal curve (TIC), early enhancement rate (EER) and ADC values were measured, morphological characteristics were recorded, and the correlation between each image feature and molecular subtypes, prognostic factors (tumor size, pathological grade, lymph node metastasis, ER, PR, HER2, Ki67) was analyzed. The results showed that parameters such as ADC value, EER, lobulation sign, burr sign, enhancement way and TIC type were correlated with prognostic factors and molecular subtypes. And Bayesian model discriminant analysis showed that the above imaging parameters couldn't well predict the expression of immunohistochemical factors and molecular subtypes. However, the above characteristics had a good effect on the prediction of pathological grade, with a false diagnosis rate of 9.69%.
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