Correlations between apparent diffusion coefficient in diffusion?weighted magnetic resonance imaging and molecular subtypes of invasive breast cancer masses.
- Author:
Liu-Tong SHANG
1
;
Jia-Fei YANG
;
Jing LU
;
Ting-Ting WANG
;
Ying ZHOU
;
Xin-Bo XING
;
Xin-Kun WANG
;
Shu-Hui YANG
;
Ming-Yan HU
Author Information
- Publication Type:Journal Article
- From: Journal of Southern Medical University 2017;37(10):1410-1414
- CountryChina
- Language:Chinese
-
Abstract:
OBJECTIVETo study the correlation of apparent diffusion coefficient (ADC) measured by diffusion-weighted magnetic resonance imaging (MRI) with the molecular subtypes and biological prognostic factors of invasive breast cancer masses.
METHODSBreast MRI data (including dynamic enhanced and diffusion-weighted imaging) were collected from 64 patients with pathologically confirmed invasive breast cancer masses (a total of 69 lesions). The mean ADC values of the lesions were calculated and their correlations were analyzed with the 5 molecular subtypes of invasive breast cancer and the biological prognostic factors including estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor 2 (HER2), and Ki-67 index.
RESULTSThe ADC values did not differ significantly among the 5 molecular subtypes of invasive breast cancer masses (P>0.05) or among lesions with different ER, PR, or HER2 status (P>0.05). The mean ADC values were significantly higher in Ki-67-positive lesions than in the negative lesions (P=0.023 and negatively correlated with the expressions of Ki-67 (r=-0.249).
CONCLUSIONADC value can not be used to identify the molecular subtypes of invasive breast cancer masses or to evaluate the biological prognosis of the lesions, but its correlation with Ki-67 expression may help in prognostic evaluation and guiding clinical therapy of the tumors.