Department of Radiology, The Second Affiliated Hospital of Soochow University, Suzhou 215004, China.
Department of Radiology, Suzhou Dushuhu Public Hospital (Soochow University Multi-Disciplinary Polyclinic), Suzhou 215004, China.
Eur J Radiol. 2019 Aug;117:156-163. doi: 10.1016/j.ejrad.2019.06.008. Epub 2019 Jun 17.
To assess the diagnostic accuracy of histogram analysis of diffusion kurtosis imaging (DKI) in breast lesions.
Our institutional review board approved this retrospective study. Seventy-two breast lesions (30 benign and 42 malignant) in 71 patients were histopathologically confirmed. All breast lesions were evaluated by 3.0-T diffusion-weighted imaging (DWI) with 4 b-values of 0, 500, 800, and 2000s/mm and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). Histogram analyses of conventional DWI and DKI were performed using FireVoxel software for whole lesions. The parameters included apparent diffusion coefficient (ADC), diffusivity (D), and kurtosis (K). The metrics of ADC and DKI parameters (D and K) for benign lesions were compared with those for malignant lesions. The effectiveness of the ADC and DKI parameters (D and K) for diagnosing breast lesions was analysed using receiver operating characteristic (ROC) regression models.
For the malignant breast lesions, the mean, median, and 10th/25th/75th percentile values of ADC and D were significantly lower, while the skewness of ADC and D were significantly higher in comparison of the benign lesions(all p < 0.05). The malignant lesions had significantly higher mean, median, and 10th/25th/75th/90th percentile K values than did the benign lesions (all p < 0.05). Within each set of parameters, the 10th percentile ADC (Az = 0.752) and D, (Az = 0.834) coupled with the 75th percentile K (Az = 0.904) were the best metrics for differentiating benign from malignant breast lesions. After comparing the parameters in pairs, the Az for the 75th percentile K was significantly higher than that for the 10th percentile ADC (p = 0.0321) in differentiating benign from malignant breast lesions. When comparing the combination of the 75th percentile K and the 10th percentile D (Az = 0.937) with the 10th percentile D, 75th percentile K and the mean K, a significantly higher Az was observed for the combination than that for the 10th percentile D and the mean K (p = 0.0097 and p = 0.0431, respectively). The diagnostic sensitivity and specificity of the combination of the 75th percentile K and the 10th percentile D were 85.71% and 93.33%, respectively.
Histogram analysis of DKI can accurately reflect the histologic characteristics and heterogeneity and is a reliable method for diagnosing breast lesions.
评估基于体素内不相干运动扩散峰度成像（DKI）的直方图分析在乳腺病变诊断中的准确性。
本研究经机构审查委员会批准，回顾性分析了 71 例患者的 72 个乳腺病变（30 个良性和 42 个恶性）的临床和病理资料。所有患者均行 3.0T 磁共振扩散加权成像（DWI）检查，b 值取 0、500、800 和 2000s/mm，同时行动态对比增强磁共振成像（DCE-MRI）检查。应用 FireVoxel 软件对全病变进行常规 DWI 和 DKI 直方图分析，获得参数包括表观扩散系数（ADC）、弥散系数（D）和峰度（K）。比较良恶性病变的 ADC 值和 DKI 各参数（D 和 K）。采用受试者工作特征（ROC）回归模型分析 ADC 值和 DKI 各参数（D 和 K）诊断乳腺病变的效能。
与良性病变相比，恶性病变的 ADC 值和 D 值的平均值、中位数和 10/25/75 百分位数均明显降低，ADC 值和 D 值的偏度明显升高（均 P<0.05）。恶性病变的 ADC 值和 D 值的平均值、中位数和 10/25/75/90 百分位数均明显高于良性病变（均 P<0.05）。在每一组参数中，10 百分位数 ADC（Az=0.752）和 D（Az=0.834）联合 75 百分位数 K（Az=0.904）是鉴别良恶性乳腺病变的最佳参数。比较两两参数后发现，75 百分位数 K 的 Az 值显著高于 10 百分位数 ADC 的 Az 值（P=0.0321）。比较 75 百分位数 K 和 10 百分位数 D（Az=0.937）与 10 百分位数 D、75 百分位数 K 和平均 K 的联合诊断效能，75 百分位数 K 和 10 百分位数 D 的联合诊断效能明显优于 10 百分位数 D 和平均 K（P=0.0097 和 P=0.0431）。75 百分位数 K 和 10 百分位数 D 的联合诊断敏感度和特异度分别为 85.71%和 93.33%。
DKI 的直方图分析可以准确反映组织学特征和异质性，是一种可靠的诊断乳腺病变的方法。
