|Table of Contents|

Value of dynamic contrast-enhanced magnetic resonance image-based model in predicting low expression of HER-2 in breast cancer tissues

Journal Of Modern Oncology[ISSN:1672-4992/CN:61-1415/R]

Issue:
2024 06
Page:
1110-1114
Research Field:
Publishing date:

Info

Title:
Value of dynamic contrast-enhanced magnetic resonance image-based model in predicting low expression of HER-2 in breast cancer tissues
Author(s):
ZHENG Lu1; TANG Tong1; ZHAO Ru2; WANG Zhitao3; SUN Chenyu1; CHEN Xiao1
1.Department of Thyroid and Breast Surgery;2.Department of Radiology;3.Department of Hematology,the Second Affiliated Hospital of Anhui Medical University,Anhui Hefei 230601,China.
Keywords:
breast cancer; HER-2; DCE-MRI; radiomics
PACS:
R737.9
DOI:
10.3969/j.issn.1672-4992.2024.06.022
Abstract:
Objective:To used dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) based imaging omics model to predict the possibility and value of early low expression of HER-2 in breast cancer patients.Methods: Clinical and pathological data of 294 female patients of breast cancer with breast invasive ductal carcinoma confirmed by puncture or surgical pathology were collected.Regions of interest (ROI) were mapped and features extracted from the original MRI image data，and relevant features were screened out by Mann-Whitney U.LASSO regression was used for feature selection，10-fold cross-validation modeling was used，and receiver operator curve (ROC) analysis model was used to evaluate the model performance.Results:After 10-fold cross-validation Linear SVC modeling,the average accuracy was 79.6%,the validation of sensitivity was 73.7% and the validation of specificity was 85.6%,and the average AUC of ROC analysis was 0.87.The diagnostic efficiency of the replacement dataset after 1 000 replacement tests was compared with the original dataset,and the average accuracy,sensitivity and specificity were all less than 0.05,the difference was statistically significant.The model established after cross-validation could classify HER-2 positive and HER-2 low expression in breast cancer patients,and the classification efficiency of the model was higher than the chance level.Conclusion:DCE-MRI imaging model can help predict the low expression of HER-2 receptor in breast cancer,and has a good predictive efficiency,which will provide a new way for clinical diagnosis of non-invasive HER-2 status.

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Memo

Memo:
National Natural Science Foundation of China(No.82200225）；国家自然科学基金（编号：82200225）;中国乳腺肿瘤青年学者科研项目-吴阶平基金(编号:320.6750.2021-10-25);安徽省高等教育人文社会科学重点项目（编号：2021xskc043）;安徽医科大学校科研基金联合资助项目(编号：2018xkj038)
Last Update: 1900-01-01