Li Chunli, Yin Jiandong
Department of Radiology, Shengjing Hospital of China Medical University, Shenyang, China.
Department of Biomedical Engineering, School of Fundamental Sciences, China Medical University, Shenyang, China.
Front Oncol. 2021 May 10;11:671354. doi: 10.3389/fonc.2021.671354. eCollection 2021.
To develop and validate a radiomics nomogram based on T2-weighted imaging (T2WI) and apparent diffusion coefficient (ADC) features for the preoperative prediction of lymph node (LN) metastasis in rectal cancer patients.
One hundred and sixty-two patients with rectal cancer confirmed by pathology were retrospectively analyzed, who underwent T2WI and DWI sequences. The data sets were divided into training (n = 97) and validation (n = 65) cohorts. For each case, a total of 2,752 radiomic features were extracted from T2WI, and ADC images derived from diffusion-weighted imaging. A two-sample -test was used for prefiltering. The least absolute shrinkage selection operator method was used for feature selection. Three radiomics scores (rad-scores) (rad-score 1 for T2WI, rad-score 2 for ADC, and rad-score 3 for the combination of both) were calculated using the support vector machine classifier. Multivariable logistic regression analysis was then used to construct a radiomics nomogram combining rad-score 3 and independent risk factors. The performances of three rad-scores and the nomogram were evaluated using the area under the receiver operating characteristic curve (AUC). Decision curve analysis (DCA) was used to assess the clinical usefulness of the radiomics nomogram.
The AUCs of the rad-score 1 and rad-score 2 were 0.805, 0.749 and 0.828, 0.770 in the training and validation cohorts, respectively. The rad-score 3 achieved an AUC of 0.879 in the training cohort and an AUC of 0.822 in the validation cohort. The radiomics nomogram, incorporating the rad-score 3, age, and LN size, showed good discrimination with the AUC of 0.937 for the training cohort and 0.884 for the validation cohort. DCA confirmed that the radiomics nomogram had clinical utility.
The radiomics nomogram, incorporating rad-score based on features from the T2WI and ADC images, and clinical factors, has favorable predictive performance for preoperative prediction of LN metastasis in patients with rectal cancer.
基于T2加权成像(T2WI)和表观扩散系数(ADC)特征开发并验证一种影像组学列线图,用于术前预测直肠癌患者的淋巴结(LN)转移。
回顾性分析162例经病理确诊的直肠癌患者,这些患者均接受了T2WI和DWI序列检查。数据集被分为训练组(n = 97)和验证组(n = 65)。对于每例患者,从T2WI以及扩散加权成像衍生的ADC图像中总共提取2752个影像组学特征。采用双样本t检验进行预筛选。使用最小绝对收缩选择算子方法进行特征选择。使用支持向量机分类器计算三个影像组学评分(rad评分)(T2WI的rad评分1、ADC的rad评分2以及两者组合的rad评分3)。然后使用多变量逻辑回归分析构建一个结合rad评分3和独立危险因素的影像组学列线图。使用受试者操作特征曲线(ROC)下面积(AUC)评估三个rad评分和列线图的性能。采用决策曲线分析(DCA)评估影像组学列线图的临床实用性。
训练组和验证组中,rad评分1的AUC分别为0.805、0.749,rad评分2的AUC分别为0.828、0.770。rad评分3在训练组中的AUC为0.879,在验证组中的AUC为0.822。纳入rad评分3、年龄和LN大小的影像组学列线图显示出良好的区分能力,训练组的AUC为0.937,验证组的AUC为0.884。DCA证实影像组学列线图具有临床实用性。
结合基于T2WI和ADC图像特征的rad评分以及临床因素的影像组学列线图,对直肠癌患者术前LN转移具有良好的预测性能。