基于T2加权成像的影像组学特征和临床特征模型在早期宫颈鳞状细胞癌深间质浸润中的诊断价值

The Value of Model Based on Radiomics Features of T2-weighted Imaging and Clinical Feature in Diagnosing the Depth of Stromal Invasion of Cervical Squamous Cell Carcinoma

  • 摘要:
      目的  初步探讨基于T2加权成像(T2-weighted imaging, T2WI)的影像组学特征联合患者临床特征构建的模型对早期宫颈鳞状细胞癌深间质浸润(deep stromal invasion, DSI)的诊断价值。
      方法  回顾性纳入2017年1月至2021年2月在北京协和医院行根治性子宫切除术的早期宫颈鳞状细胞癌患者,并按8∶2的比例随机分为训练集和验证集。收集训练集患者的术前临床特征和矢状位T2WI图像影像组学特征资料,经筛选、特征降维后,采用Logistic回归分析法建立早期宫颈癌DSI诊断模型,包括临床特征模型、影像组学模型和临床-影像组学模型。基于验证集数据,采用受试者工作特征(receiver operating characteristic, ROC)曲线对上述模型的性能进行验证。
      结果  共168例符合纳入和排除标准的早期宫颈鳞状细胞癌患者入选本研究。其中训练集135例,验证集33例;经组织病理学证实为浅间质浸润的患者72例,DSI患者96例。共筛选出患者年龄、术前鳞状细胞癌抗原水平、国际妇产科联盟分期3个临床特征和4个影像组学特征用于模型构建。ROC曲线分析显示,临床特征模型、影像组学模型和临床-影像组学模型诊断早期宫颈鳞状细胞癌DSI的曲线下面积分别为0.797(95% CI: 0.623~0.971)、0.793(95% CI: 0.633~0.954)和0.820(95% CI: 0.665~0.974),且以临床-影像组学模型的诊断效能最高,其灵敏度、特异度和准确度分别为85.7%(95% CI: 49.8%~100%)、73.7%(95% CI: 57.9%~100%)和78.8%(95% CI: 69.7%~93.9%)。
      结论  基于T2WI图像的影像组学特征联合临床特征构建的临床-影像组学模型可作为一种无创的术前检查手段高效判断早期宫颈鳞状细胞癌间质浸润深度。

     

    Abstract:
      Objective  To investigate the prediction value of a clinical-radiomics model based on T2- weighted imaging (T2WI) and clinical features for diagnosing deep stromal invasion (DSI) in patients with early-stage cervical squamous cell carcinoma.
      Methods  Patients with early-stage cervical squamous cell carcinoma that underwent radical hysterectomy in Peking Union Medical College Hospital from January 2017 to February 2021 were retrospectively included and randomly divided into the training set and the validation set with the the ratio of 8∶2. The preoperative clinical features and the radiomics features of sagittal T2WI images were obtained. After selection of key features, a radiomics model, a clinical model, and a clinical-radiomics model for diagnosing DSI in early-stage cervical squamous cell carcinoma were developed by Logistic regression based on the training set. The performance of different models was compared by the receiver operating characteristic (ROC) curve in the validation set.
      Results  A total of 168 patients with early-stage cervical squamous cell carcinoma that met the inclusion and exclusion criteria were included in this study. They were randomly divided into the training set (n=135) and the validation set (n=33), in which 72 cases had histopathologically confirmed superficial stromal invasion and 96 cases had DSI. Four radiomics features and three clinical parameters (age, Federation International of Gynecology and Obstetrics stage, and preoperative squamous cell carcinoma antigen levels) were selected and used to develop models. In the validation set, the clinical-radiomics model showed better diagnostic performance with the area under the curve (AUC) of 0.820 (95% CI: 0.665-0.974) than the clinical modelAUC: 0.797(95% CI: 0.623-0.971) and the radiomics modelAUC: 0.793(95% CI: 0.633-0.954).The sensitivity, specificity, and accuracy of the clinical-radiomics model were 85.7%(95% CI: 49.8%-100%), 73.7%(95% CI: 57.9%-100%), and 78.8%(95% CI: 69.7%-93.9%), respectively.
      Conclusion  Radiomics features based on T2WI images combined with clinical features can be used as a noninvasive preoperative method to determine the depth of stromal invasion in early-stage cervical squamous cell carcinoma.

     

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