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动态增强磁共振成像与扩散加权成像组学联合对微小乳腺癌病灶的诊断价值

Value of dynamic contrast-enhanced magnetic resonance imaging combined with diffusion weighted imaging radiomics in diagnosis of small breast cancer lesions

    摘要
  • 摘要:
    目的 探讨动态增强磁共振成像(DCE-MRI)与扩散加权成像(DWI)组学联合对微小乳腺癌病灶(最大径 < 2 cm)的诊断价值。
    方法 选取经手术病理证实的110例患者的119个乳腺病灶(最大径 < 2 cm), 根据不同入组时间分为训练集(62例患者67个病灶)和测试集(48例患者52个病灶)。比较良恶性病灶各影像学参数; 基于术前DCE-MRI、DWI序列，以梯度提升决策树(GBDT)算法建立影像组学模型，预测测试集病灶良恶性; 绘制受试者工作特征(ROC)曲线，分析并比较GBDT模型与放射科医师基于3种方式评估的诊断效能。
    结果 良性病灶的速率常数(Kep)、容量转移常数(Ktrans)、最小表观扩散系数(ADCmin)、平均表观扩散系数(ADCmean)高于恶性病灶, 血管外细胞外间隙容积比(Ve)低于恶性病灶，差异有统计学意义(P < 0.05)。训练集病灶最大径、恶性病灶检出情况、良性病灶检出情况与测试集比较，差异无统计学意义(P＞0.05)。ROC曲线显示, GBDT模型鉴别诊断最大径 < 2 cm乳腺癌的曲线下面积(AUC)为0.945, 与放射科医师基于DCE-MRI联合DWI诊断的AUC(0.923)比较，差异无统计学意义(P＞0.05), 但大于放射科医师基于DCE-MRI、DWI单独诊断的AUC(0.845、0.851), 差异有统计学意义(P < 0.05); GBDT模型最佳截断点对应的敏感度、特异度、准确度分别为0.91、0.94、0.93, 放射科医师基于DCE-MRI联合DWI诊断则分别为0.94、0.81、0.86, 差异无统计学意义(P＞0.05)。
    结论 基于DCE-MRI与DWI组学联合的GBDT模型对微小乳腺癌病灶具有较高的诊断价值，且与经验丰富的放射科医师基于DCE-MRI联合DWI评估的诊断效能相近。

     

    Abstract:
    Objective To investigate the value of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) combined with diffusion weighted imaging (DWI) in diagnosis of small breast cancer lesions (maximum diameter < 2 cm).
    Methods A total of 110 patients with 119 breast lesions (maximum diameter < 2 cm) confirmed by surgical pathology were selected. According to different inclusion time, the subjects were assigned to a training set (62 patients with 67 lesions) and a test set (48 patients with 52 lesions). The imaging parameters of benign and malignant lesions were comparatively analyzed. A radiomics model was established by gradient boosting decision tree (GBDT) based on preoperative DCE-MRI and DWI sequences to predict benign and malignant lesions in the test set. The receiver operating characteristic (ROC) curve was drawn to analyze and compare the diagnostic efficacy of GBDT model and three methods of radiologists.
    Results Flux rate constant (Kep), transfer constant (Ktrans), minimum apparent diffusion coefficient (ADCmin), mean apparent diffusion coefficient (ADCmean) of benign lesions were higher than those of malignant lesions, while extravascular extracellular volume fraction (Ve) was lower than that of malignant lesions (P < 0.05). The maximum diameter of lesions, detected rates of malignant and benign lesions in the training set were similar to those in the test set (P > 0.05). ROC curve showed that the area under the ROC curve (AUC) of GBDT model in the diagnosis of breast cancer smaller than 2 cm was 0.945, which showed no significant difference compared with 0.923 by combined diagnosis of DCE-MRI and DWI (P > 0.05), and was larger than 0.845, 0.851 by DCE-MRI and DWI alone (P < 0.05). The sensitivity, specificity and accuracy of the best cut-off value of GBDT model were 0.91, 0.94 and 0.93, respectively, which showed no significant difference compared with 0.94, 0.81 and 0.86 of DCE-MRI combined with DWI radiomics by radiologists (P > 0.05).
    Conclusion DCE-MRI combined with DWI radiomics has higher value in the diagnosis of breast cancer lesions smaller than 2 cm when combining with GBDT model, and the diagnostic results are consistent with those from experienced radiologists based on DCE-MRI combined with DWI.

     

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