Tsougos Ioannis, Bakosis Michael, Tsivaka Dimitra, Athanassiou Evangelos, Fezoulidis Ioannis, Arvanitis Dimitrios, Vassiou Katerina
Department of Medical Physics, Medical School, University of Thessaly, Biopolis, Larissa, Greece.
Department of Medical Physics, Medical School, University of Thessaly, Biopolis, Larissa, Greece.
Clin Imaging. 2019 Jan-Feb;53:25-31. doi: 10.1016/j.clinimag.2018.10.002. Epub 2018 Oct 3.
Conventional breast magnetic resonance imaging (MRI), including dynamic contrast-enhanced MR mammography, may lead to ambiguous diagnosis and unnecessary biopsies.
To investigate the contribution of quantitative diffusion tensor imaging (DTI) in the discrimination between benign and malignant breast lesions at 3 T MRI.
The study included a total of 86 lesions (44 benign and 42 malignant) in 58 women (34 with malignant lesions, 23 with benign lesions and 1 with both types of lesions). All patients were examined on a 3 T MRI scanner. Fractional Anisotropy (FA), Mean Diffusivity (MD), Apparent Diffusion Coefficient (ADC), as well as eigenvalues (λ, λ, λ) were calculated and compared between benign and malignant lesions using two different software packages (GE Functool and ExploreDTI).
Malignant lesions exhibited significantly lower ADC values compared to benign ones (ADC = 1.06 × 10 mm/s, ADC = 1.54 × 10 mm/s, p-value < 0.0001). FA measurements in carcinomas indicated slightly higher values than those in benign lesions (FA = 0.20 ± 0.07, FA = 0.15 ± 0.05, p-value = 0.0003). Eigenvalues λ, λ, λ, showed significantly lower values in malignant tumors compared to benign lesions and normal breast tissue. ROC curve analysis of ADC and DTI metrics demonstrated that ADC provides high diagnostic performance (AUC = 0.944) while, MD and λ showed best discriminative results (AUC = 0.906) for the differentiation of malignant and benign lesions in contrast to other DTI parameters.
The addition of eigenvalue analysis improves DTI's ability to differentiate between benign and malignant breast lesions.
传统的乳腺磁共振成像（MRI），包括动态对比增强磁共振乳腺造影，可能导致诊断不明确和不必要的活检。
探讨定量扩散张量成像（DTI）在3T MRI鉴别乳腺良恶性病变中的作用。
本研究共纳入58名女性的86个病变（44个良性病变和42个恶性病变）（34名患有恶性病变，23名患有良性病变，1名患有两种类型的病变）。所有患者均在3T MRI扫描仪上进行检查。使用两种不同的软件包（GE Functool和ExploreDTI）计算并比较了良性和恶性病变之间的分数各向异性（FA）、平均扩散率（MD）、表观扩散系数（ADC）以及特征值（λ1、λ2、λ3）。
与良性病变相比，恶性病变的ADC值显著更低（ADC = 1.06×10⁻³mm²/s，ADC = 1.54×10⁻³mm²/s，p值<0.0001）。癌灶的FA测量值略高于良性病变（FA = 0.20±0.07，FA = 0.15±0.05，p值 = 0.0003）。与良性病变和正常乳腺组织相比，恶性肿瘤的特征值λ1、λ2、λ3显著更低。ADC和DTI指标的ROC曲线分析表明，ADC具有较高的诊断性能（AUC = 0.944），而与其他DTI参数相比，MD和λ1在鉴别恶性和良性病变方面显示出最佳的判别结果（AUC = 0.906）。
添加特征值分析可提高DTI鉴别乳腺良恶性病变的能力。
