DCE-MRI Performance in Triple Negative Breast Cancers: Comparison with Non-Triple Negative Breast Cancers

Author:

Yin Guobing1ORCID,Chen Hang1ORCID,Min Yu1,Xiang Ke1,Chen Jialin1

Affiliation:

1. Department of Breast and Thyroid Surgery, The Second Affiliated Hospital of Chongqing Medical University, No.74, Linjiang Rd, Yuzhong Dist, Chongqing 404100, P.R. China

Abstract

Background: Triple negative breast cancers are considered the worst prognosis in breast cancer. Dynamic contrast enhanced magnetic resonance imaging has been widely used in the diagnosis of breast cancer since it is more sensitive to breast cancer. However, few studies report the MRI characteristics of triple negative breast cancers. Objective: The study aimed to evaluate the imaging finding in triple negative breast cancers compared with non-TNBC and attempt to predict it. Method: 223 patients with a preoperative diagnosis of breast cancer were enrolled in the study. Dynamic contrast enhanced magnetic resonance imaging was performed before being diagnosed with breast cancer, and histopathological assessment was confirmed after biopsy or operation. The patients were divided into 2 groups based on immunohistochemistry, namely the triple negative breast cancers or non-triple negative breast cancers. Results: The 2 groups demonstrated significant differences regarding the tumor size, margin, outline, burr sign, enhancement, inverted nipple(P<0.05). A multivariate logistic regression analysis was performed to further validate the association of these features, however, only margin [odds ratio (OR), 0.038; 95% confidence interval (CI), 0.014-0.100; <0.001], outline [odds ratio (OR), 0.039; 95% confidence interval (CI), 0.008-0.200; <0.001], burr sign [odds ratio (OR), 2.786; 95% confidence interval (CI), 1.225-6.333; 0.014], and enhancement [odds ratio (OR), 0.131; 95% confidence interval (CI), 0.037-0.457; P=0.001] were associated with TNBC. Conclusion: The results indicated that the specific dynamic contrast enhanced magnetic resonance imaging features can predict pathological results, with a consequent prognostic value.

Publisher

Bentham Science Publishers Ltd.

Subject

Radiology, Nuclear Medicine and imaging

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