利用表观扩散系数提高乳腺MRI良恶性病变的鉴别

D. McClymont, A. Mehnert, A. Trakic, S. Crozier, D. Kennedy
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引用次数: 1

摘要

本文探讨了表观扩散系数(ADC)在乳腺磁共振成像(MRI)中对良恶性病变鉴别中的应用价值。特别提出了一种在动态对比增强(DCE) MRI数据中自动选择高强度肿瘤体素并在相应的扩散加权(DW) MRI数据中评估其平均ADC的方法。将该方法应用于常规临床实践中获得的10组乳腺MRI数据集。结果表明,相对信号增加(DCE-MRI)与表观扩散系数(DW-MRI)相结合的识别效果优于单独使用任何一种特征。结果还表明,以一致的方式获取DWMRI数据很重要,即在获取DCE-MRI数据之前或之后。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Improving the Discrimination of Benign and Malignant Breast MRI Lesions Using the Apparent Diffusion Coefficient
This paper presents an investigation of the apparent diffusion coefficient (ADC) for improving the discrimination of benign and malignant lesions in breast magnetic resonance imaging (MRI). In particular a method is presented for automatically selecting hyper intense tumour voxels in dynamic contrast enhanced (DCE) MRI data and evaluating their average ADC in the corresponding diffusion-weighted (DW) MRI data. The method was applied to ten breast MRI datasets obtained from routine clinical practice. The results demonstrate that the combination of the relative signal increase (DCE-MRI) with the apparent diffusion coefficient (DW-MRI) leads to better discrimination than with either feature alone. The results also suggest that it is important to acquire the DWMRI data in a consistent fashion, i.e. either before or after the acquisition of the DCE-MRI data.
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