Clinical Research Papers:
Prediction of low-risk breast cancer using quantitative DCE-MRI and its pathological basis
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Tingting Xu1,*, Lin Zhang1,*, Hong Xu1, Sifeng Kang1, Yali Xu1, Xiaoyu Luo1, Ting Hua1 and Guangyu Tang1
1Department of Radiology, Tenth People’s Hospital, Tongji University School of Medicine, Shanghai, 200072, China
*These authors contributed equally to this work
Guangyu Tang, email: [email protected]
Keywords: dynamic contrast enhanced magnetic resonance imaging, low-risk breast cancer, apparent diffusion coefficient, quantitative parameters, pathological basis
Received: April 03, 2017 Accepted: July 26, 2017 Published: November 01, 2017
Purpose: This study aimed to evaluate the difference of mass in dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) characteristics between low-risk and non-low-risk breast cancers and to explore the possible pathological basis.
Materials and Methods: Approval from the institutional review board and informed consent were acquired for this study. The MR images of 104 patients with pathologically proven breast cancer (104 lesions) were prospectively analyzed. All of included patients were Chinese woman. The DCE-MRI morphologic findings, apparent diffusion coefficient (ADC) values, quantitative DCE-MRI parameters, and pathological biomarkers between the two subtypes of breast cancer were compared. The quantitative DCE-MRI parameters and ADC values were added to the morphologic features in multivariate models to evaluate diagnostic performance in predicting low-risk breast cancer. The values were further subjected to the receiver operating characteristic (ROC) curve analysis.
Results: Low-risk tumors showed significantly lower Ktrans and Kep values (t = 2.065, P = 0.043 and t = 3.548, P = 0.001, respectively) and higher ADC value (t = 4.713, P = 0.000) than non-low-risk breast cancers. Our results revealed no significant differences in clinic data and conventional imaging findings between the two breast cancer subtypes. Adding the quantitative DCE-MRI parameters and ADC values to conventional MRI improved the diagnostic performance of MRI: The area under the ROC improved from 0.63 to 0.91. Low-risk breast cancers showed significantly lower matrix metalloproteinase (MMP)-2 expression (P = 0.000), lower MMP-9 expression (P = 0.001), and lower microvessel density (MVD) values (P = 0.008) compared with non-low-risk breast cancers. Ktrans and Kep values were positively correlated with pathological biomarkers. The ADC value showed a significant inverse correlation with pathological biomarkers.
Conclusions: The prediction parameter using Ktrans, Kep, and ADC obtained on DCE-MRI and diffusion-weighted imaging could facilitate the identification of low-risk breast cancers. Decreased biological factors, including MVD, vascular endothelial growth factor, MMP-2, and MMP-9, may explain the possible pathological basis.
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