Prediction of different expression status of human epidermal growth factor receptor 2 in breast cancer based on multi-parameter MRI habitat imaging
10.3760/cma.j.cn112149-20240228-00091
- VernacularTitle:多参数MRI栖息地影像预测乳腺癌人表皮生长因子受体2不同表达状态的研究
- Author:
Zhiheng LI
1
;
Xiaoyan CHEN
;
Xiaolei ZHANG
;
Han ZHOU
;
Yao FU
;
Renhua WU
;
Yan LIN
Author Information
1. 汕头大学医学院第二附属医院影像科，汕头 515041
- Keywords:
Breast neoplasms;
Magnetic resonance imaging;
Habitat imaging;
Human epidermal growth factor receptor 2
- From:
Chinese Journal of Radiology
2024;58(9):909-915
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To investigate the value of multi-parameter MRI habitat imaging in differentiating human epidermal growth factor receptor 2 (HER2) expression in breast cancer.Methods:This study was cross-sectional. A retrospective analysis was conducted on the clinical and imaging data of 86 cases of primary invasive breast cancer confirmed by pathology at the Second Affiliated Hospital of Shantou University from August 2018 to July 2023. All patients were female, aged 33 to 74 (51±10) years. All patients underwent breast MRI examinations, including T 1WI, T 2WI, diffusion-weighted imaging and dynamic contrast-enhanced MRI. The fuzzy C-means clustering algorithm was applied to cluster analysis of the volume ratio of the extracellular extravascular space (V e), the rate constant (K ep), the volume transfer constant (K trans), and the apparent diffusion coefficient (ADC) for all lesions. Different habitat subregions were segmented based on breast cancer. Blood perfusion of the lesion was quantified through mean values of K trans and K ep, and cell proliferation was evaluated by the mean values of ADC and V e in each subregion. Additionally, the percentage of each subregion′s volume in relation to the total lesion volume was calculated. The Mann-Whitney U test was used to compare the differences in the volume percentages of various habitat subregions between different HER2 expression status. The diagnostic performance of statistically significant parameters in determining HER2 status was evaluated using receiver operating characteristic curves and the area under the curve (AUC). Results:Among the 86 patients with invasive breast cancer, 27 were HER2 positive and 59 were HER2 negative. Among the HER2 negative patients, 37 had low and 22 had zero HER2 expression. The volume percentages of habitat subregions 1, 2, and 3 showed statistically significant differences between HER2 positive and HER2 negative patients ( Z=2.90, P=0.004; Z=-2.04, P=0.042; Z=-2.19, P=0.029), with AUC values of 0.696, 0.638, and 0.648, respectively, for predicting HER2 positive expression. The volume percentage of habitat subregion 2 showed a statistically significant difference between low and zero HER2 expression patients ( Z=2.85, P=0.004), with an AUC value of 0.724 for predicting low versus zero HER2 expression. Conclusions:The volume percentage of habitat subregion 1 effectively distinguishes HER2 status, and the volume percentage of habitat subregion 2 effectively distinguishes between low and zero HER2 expression patients. It has significant clinical implications for identifying potential candidates for HER2-targeted therapy.
