4.6 Article

Role of perfusion parameters on DCE-MRI and ADC values on DWMRI for invasive ductal carcinoma at 3.0 Tesla

期刊

WORLD JOURNAL OF SURGICAL ONCOLOGY
卷 16, 期 -, 页码 -

出版社

BMC
DOI: 10.1186/s12957-018-1538-8

关键词

Diffusion-weighted MRI; Magnetic resonance imaging; Invasive ductal carcinoma; Breast cancer

资金

  1. Nanjing Medical Science and Technology Development Project - Digital Mammography and Magnetic Resonance Quantitative Imaging Mode in Subclinical Breast Cancer [YKK14181]

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BackgroundThe value of apparent diffusion coefficient (ADC) values and quantitative parameters (Ktrans, Kep, Ve) in detecting prognostic factor at 3.0 Tesla remains unclear, especially in predicting prognosis of breast cancer.MethodsA total of 151 patients with IDC underwent breast DCE-MRI and DWI-MRI at 3.0 Tesla following surgery. The ADC values were acquired with b values of 0 and 1000s/mm(2). The relationship between ADC values or DCE-MRI quantitative parameters and size, histologic grade (HG), lymph node metastasis (LNM), ER, PR, and Ki67 was evaluated. The predictive values of ADC, Ktrans, Kep, and Ve to prognosis of IDC were assessed.ResultsADC value was positively related to size (P=0.04) and HER2 (P=0.046) expression and negatively related to ER (P=0.012) and PR (P<0.001) expression. Ktrans value has positive correlation with size (P<0.001), HG (P<0.001), LNM (P<0.001), HER2 (P=0.007), and Ki67 (P<0.001) expression and negative correlation with ER (P<0.001) and PR (P<0.001) expression. Kep value was positively related to size (P<0.001) and negatively related to ER (P<0.001) and PR (P<0.001) expression. Ve value was negatively related to HER2 expression (P=0.004). The Cox hazard ratio (HR) of ADC, Ktrans, Kep, and Ve values on survival was 5.26 (P=0.093), 1.081 (P=0.002), 1.006 (P=0.941), and 0.883 (P=0.926), respectively.ConclusionsKtrans value was a best predictive indicator of HG, LNM, ER, PR, and Ki67 expression, and ADC value was the best predictive indicator of HER2. Preoperative use of the 3.0 Tesla could provide important information to determine the optimal treatment plan.

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