背景:为了比较划分的扩散加权模型,体素内不相干运动(IVIM)和限制性光谱成像(RSI),表征乳腺病变和正常纤维腺体组织。
方法:这项前瞻性研究纳入了152例患者,这些患者有157个组织病理学证实的乳腺病变(41个良性和116个恶性)。所有患者均接受全方案术前乳腺MRI检查,包括多b值DWI序列。从单指数模型(ADC)导出的扩散参数,IVIM型号(Dt,Dp,f),和RSI模型(C1,C2,C3,C1C2,F1,F2,F3,F1F2)进行定量测量,然后在恶性病变之间进行比较,良性病变和正常纤维腺体组织使用Kruskal-Wallis试验。Mann-WhitneyU检验用于成对比较。采用Logistic回归分析建立诊断模型。使用5倍交叉验证进行ROC分析,计算并比较平均AUC值,以评估每个参数或模型的辨别能力。
结果:几乎所有的定量扩散参数在区分恶性乳腺病变与良性病变(C2除外)和正常纤维腺体组织(所有参数)方面均存在显着差异(所有P<0.0167)。在良性病变和正常纤维腺体组织的比较方面,从IVIM导出的参数(Dp,f)和RSI(C1、C2、C1C2、F1、F2、F3)均有显著性差异(均P<0.005)。使用单个参数时,RSI衍生的参数F1,C1C2和C2值在恶性与恶性比较中产生了最高的AUC。良性,恶性vs.正常组织和良性vs.正常组织(AUC分别为0.871、0.982和0.863)。此外,联合诊断模型(IVIM+RSI)对成对鉴别结果的诊断效能最高(AUC分别为0.893,0.991和0.928).
结论:与双指数IVIM模型相比,来自三室RSI模型的定量参数有望作为乳腺病变鉴别诊断的影像学指标。此外,IVIM和RSI联合模型在表征乳腺病变方面取得了优异的诊断性能.
BACKGROUND: To compare the compartmentalized diffusion-weighted models, intravoxel incoherent motion (IVIM) and restriction spectrum imaging (RSI), in characterizing breast lesions and normal fibroglandular tissue.
METHODS: This prospective study enrolled 152 patients with 157 histopathologically verified breast lesions (41 benign and 116 malignant). All patients underwent a full-protocol preoperative breast MRI, including a multi-b-value DWI sequence. The diffusion parameters derived from the mono-exponential model (ADC), IVIM model (Dt, Dp, f), and RSI model (C1, C2, C3, C1C2, F1, F2, F3, F1F2) were quantitatively measured and then compared among malignant lesions, benign lesions and normal fibroglandular tissues using Kruskal-Wallis test. The Mann-Whitney U-test was used for the pairwise comparisons. Diagnostic models were built by logistic regression analysis. The ROC analysis was performed using five-fold cross-validation and the mean AUC values were calculated and compared to evaluate the discriminative ability of each parameter or model.
RESULTS: Almost all quantitative diffusion parameters showed significant differences in distinguishing malignant breast lesions from both benign lesions (other than C2) and normal fibroglandular tissue (all parameters) (all P < 0.0167). In terms of the comparisons of benign lesions and normal fibroglandular tissues, the parameters derived from IVIM (Dp, f) and RSI (C1, C2, C1C2, F1, F2, F3) showed significant differences (all P < 0.005). When using individual parameters, RSI-derived parameters-F1, C1C2, and C2 values yielded the highest AUCs for the comparisons of malignant vs. benign, malignant vs. normal tissue and benign vs. normal tissue (AUCs = 0.871, 0.982, and 0.863, respectively). Furthermore, the combined diagnostic model (IVIM + RSI) exhibited the highest diagnostic efficacy for the pairwise discriminations (AUCs = 0.893, 0.991, and 0.928, respectively).
CONCLUSIONS: Quantitative parameters derived from the three-compartment RSI model have great promise as imaging indicators for the differential diagnosis of breast lesions compared with the bi-exponential IVIM model. Additionally, the combined model of IVIM and RSI achieves superior diagnostic performance in characterizing breast lesions.