The Value of Blooming Sign on MRI in Distinguishing Malignancy from Benign Small Breast Masses and Its Radiologic-pathologic Correlation Analysis
10.13471/j.cnki.j.sun.yat-sen.univ（med.sci）.20211227.001
- VernacularTitle:MRI敷霜征鉴别乳腺良恶性小肿块的价值及其病理组织学分析
- Author:
Chan LAI
1
;
Zhuang-sheng LIU
1
;
Ru-qiong LI
1
;
Ke-ming LIANG
1
;
Wan-sheng LONG
1
;
Hai-cheng LI
2
;
Zhong-xin NIE
1
Author Information
1. Department of Radiology， Jiangmen Central Hospital//The Affiliated Jiangmen Hospital of Sun Yat-sen University， Jiangmen 529070， China
2. Department of Pathology， Jiangmen Central Hospital//The Affiliated Jiangmen Hospital of Sun Yat-sen University， Jiangmen 529070， China
- Publication Type:Journal Article
- Keywords:
magnetic resonance imaging;
blooming sign;
small breast masses;
benign and malignant;
histopathology
- From:
Journal of Sun Yat-sen University(Medical Sciences)
2022;43(2):321-330
- CountryChina
- Language:Chinese
-
Abstract:
ObjectiveTo determine the value of MRI blooming sign in differentiating benign and malignant small breast masses and investigate its radiologic-pathologic correlation. MethodsThis retrospective study included 554 small breast masses （291 malignant and 263 benign） which were ≤ 2 cm and validated by pathology analysis between June 2016 and September 2020. All 554 patients underwent breast MRI. The clinical characteristics and MR features were analyzed. Univariate and multivariate regression analysis were performed to identify the independent risk factors of breast cancer. Two diagnostic models were constructed based on independent risk factors （model 1 included blooming sign and model 2 didn’t）. ROC curve was used to evaluate the diagnostic performances of the two models. The histological changes of peritumoral tissues in all small masses were analyzed. ResultsThe blooming sign was positive in 199 cases （68.4%） of the malignant masses and 25 cases （9.5%） of the benign ones （P＜0.05）. Univariate and multivariate regression analysis showed that age， lesion diameter， margin， ADC value， time signal intensity curve type and blooming sign were independent risk factors for breast cancer. Odds ratio were 1.065， 4.515， 2.811， 0.013， 3.487 and 13.894， respectively. Their corresponding 95%CI were （1.034， 1.097）， （2.368， 8.608）， （1.954， 4.045）， （0.004， 0.049）， （2.087， 5.826） and （7.026， 27.477）， respectively. The diagnostic performance of model 1 （blooming sign included） was better than that of model 2 （blooming sign not included； AUC： 0.938 vs 0.897， P < 0.05）. Histopathological analysis showed that the blooming sign was related to peritumoral lymphocyte infiltration and vascular proliferation. ConclusionsMRI blooming sign is helpful for distinguishing breast cancer from benign masses. The correlated histopathological basis may be peritumoral lymphocyte infiltration and neovascularization.
