Improving the Discrimination of Benign and Malignant Breast MRI Lesions Using the Apparent Diffusion Coefficient

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

Abstract

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.
利用表观扩散系数提高乳腺MRI良恶性病变的鉴别
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。
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