4.6 Article

Differentiation of malignant and benign breast lesions: Added value of the qualitative analysis of breast lesions on diffusion weighted imaging (DWI) using readout segmented echo-planar imaging at 3.0 T

期刊

PLOS ONE
卷 12, 期 3, 页码 -

出版社

PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pone.0174681

关键词

-

资金

  1. Korean Health Technology R&D Project, Ministry of Health & Welfare, Republic of Korea [HI14C1731]

向作者/读者索取更多资源

Objective To determine the added value of qualitative analysis as an adjunct to quantitative analysis for the discrimination of benign and malignant lesions in patients with breast cancer using diffusion-weighted imaging (DWI) with readout-segmented echo-planar imaging (rs-EPI). Methods A total of 99 patients with 144 lesions were reviewed from our prospectively collected database. DWI data were obtained using rs-EPI acquired at 3.0 T. The diagnostic performances of DWI in the qualitative, quantitative, and combination analyses were compared with that of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). Additionally, the effect of lesion size on the diagnostic performance of the DWI combination analysis was evaluated. Results The strongest indicators of malignancy on DWI were a heterogeneous pattern (P = 0.005) and an apparent diffusion coefficient (ADC) value <1.0 x 10-3 mm2/sec (P = 0.002). The area under the curve (AUC) values for the qualitative analysis, quantitative analysis, and combination analysis on DWI were 0.732 (95% CI, 0.651-0.803), 0.780 (95% CI, 0.7030.846), and 0.826 (95% CI, 0.754-0.885), respectively (P<0.0001). The AUC for the combination analysis on DWI was superior to that for DCE-MRI alone (0.651, P = 0.003) but inferior to that for DCE-MRI plus the ADC value (0.883, P = 0.03). For the DWI combination analysis, the sensitivity was significantly lower in the size <1 cm group than in the size >1 cm group (80% vs. 95.6%, P = 0.034). Conclusions Qualitative analysis of tumor morphology was diagnostically applicable on DWI using rsEPI. This qualitative analysis adds value to quantitative analyses for lesion characterization in patients with breast cancer.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.6
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据