Li Xue, Li Chunmei, Hua Bin, Jiang Lei, Chen Min
Department of Radiology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, No. 1 Da Hua Road, Dong Dan, Beijing 100730, PR China; Graduate School of Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, PR China.
Breast Center, Department of Thyroid-Breast-Hernia Surgery, Department of General Surgery, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, PR China.
Magn Reson Imaging. 2025 Apr;117:110323. doi: 10.1016/j.mri.2025.110323. Epub 2025 Jan 4.
This study aimed to evaluate the diagnostic efficacy of time-dependent diffusion magnetic resonance imaging (td-dMRI) and dynamic contrast-enhanced MRI (DCE-MRI)-based kinetic heterogeneity in differentiating suspicious breast lesions (categorised as Breast Imaging Reporting and Data System 4 or 5).
This prospective study included 51 females with suspicious breast lesions who underwent preoperative breast MRI, including DCE-MRI and td-dMRI. Six kinetic parameters, namely peak, persistent, plateau, washout component, predominant curve type, and heterogeneity, were extracted from the DCE series using MATLAB and SPM software. The td-dMRI data were analysed using the JOINT model to obtain five microstructural parameters and apparent diffusion coefficient at 50 ms (ADC). Chi-square or Fisher's exact test and the Mann-Whitney U test were used to compare these parameters between benign and malignant breast lesions. Univariate and multivariate logistic regression analyses with forward stepwise covariate selection were performed to identify significant clinical and radiologic variables. Differential diagnostic performance was evaluated using receiver operating characteristic curves and logistic regression analyses.
For td-dMRI-derived parameters, the values of f and cellularity were significantly higher in malignant breast lesions compared to benign lesions (P = 0.001 and P<0.001, respectively), while ADC was significantly lower in malignant lesions (P = 0.001). In the kinetic heterogeneity analysis, the washout component was higher in malignant lesions compared to benign lesions (P = 0.003). When combining significant td-dMRI and kinetic heterogeneity parameters, the area under the curve (AUC) value was 0.875, with an accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of 82.69 %, 86.11 %, 75.00 %, 88.57 %, and 70.59 %, respectively. Notably, margin and kinetic pattern emerged as independent predictors of malignant breast lesions (P = 0.019 and 0.006, respectively). Furthermore, incorporating these two clinical-radiologic characteristics further enhanced diagnostic accuracy, yielding an AUC of 0.969, with accuracy, sensitivity, specificity, PPV, and NPV improving to 90.38 %, 86.11 %, 100 %, 100 %, and 76.19 %, respectively.
Kinetic heterogeneity- and td-dMRI-derived parameters are potentially non-invasive biomarkers for distinguishing suspicious breast lesions.
本研究旨在评估基于时间依赖扩散磁共振成像（td-dMRI）和动态对比增强磁共振成像（DCE-MRI）的动力学异质性在鉴别可疑乳腺病变（分类为乳腺影像报告和数据系统4类或5类）中的诊断效能。
这项前瞻性研究纳入了51例患有可疑乳腺病变的女性，她们在术前接受了乳腺MRI检查，包括DCE-MRI和td-dMRI。使用MATLAB和SPM软件从DCE序列中提取六个动力学参数，即峰值、持续期、平台期、廓清成分、主要曲线类型和异质性。使用JOINT模型分析td-dMRI数据，以获得五个微观结构参数和50毫秒时的表观扩散系数（ADC）。采用卡方检验或Fisher精确检验以及Mann-Whitney U检验比较良性和恶性乳腺病变之间的这些参数。进行单因素和多因素逻辑回归分析，并采用向前逐步协变量选择来确定显著的临床和放射学变量。使用受试者工作特征曲线和逻辑回归分析评估鉴别诊断性能。
对于td-dMRI衍生参数，与良性病变相比，恶性乳腺病变的f值和细胞密度值显著更高（分别为P = 0.001和P<0.001），而恶性病变的ADC显著更低（P = 0.001）。在动力学异质性分析中，与良性病变相比，恶性病变的廓清成分更高（P = 0.003）。当结合显著的td-dMRI和动力学异质性参数时，曲线下面积（AUC）值为0.875，准确性、敏感性、特异性、阳性预测值（PPV）和阴性预测值（NPV）分别为82.69%、86.11%、75.00%、88.57%和70.59%。值得注意的是，边缘和动力学模式成为恶性乳腺病变的独立预测因素（分别为P = 0.019和0.006）。此外，纳入这两个临床放射学特征进一步提高了诊断准确性，AUC为0.969，准确性、敏感性、特异性、PPV和NPV分别提高到90.38%、86.11%、100%、100%和76.19%。
动力学异质性和td-dMRI衍生参数可能是鉴别可疑乳腺病变的无创生物标志物。
