Radiomics of apparent diffusion coefficient maps to predict histologic grade in squamous cell carcinoma of the oral tongue and floor of mouth: a preliminary study
Radiomics of apparent diffusion coefficient maps to predict histologic grade in squamous cell carcinoma of the oral tongue and floor of mouth: a preliminary study
复制标题
表观扩散系数图的放射组学预测口腔舌和口底鳞状细胞癌的组织学分级：初步研究
DOI：
10.1177/0284185120931683
复制
发表时间：
2020-06-14
期刊：
影响因子：
1.3
通讯作者：
Tao, Xiaofeng
中科院分区：
文献类型：
--
作者：
Ren, Jiliang;Qi, Meng;Tao, Xiaofeng
组织学分级在口腔舌和口底鳞状细胞癌（SCC）的临床决策和预后评估中起着重要作用。目的评价基于表观扩散系数（ADC）的放射组学技术在鉴别口腔舌部低、高级别鳞状细胞癌（SCC）和口腔鳞状细胞癌（FOM）中的价值。材料和方法我们纳入了88例患者（训练队列：n = 59;测试队列：n = 29）的数据，这些患者在治疗前接受了3.0 T磁共振成像扫描仪的弥散加权成像。从ADC图中提取总共526个放射组学特征，以构建具有最小绝对收缩和选择算子逻辑回归的放射组学签名。使用受试者工作特征曲线和曲线下面积（AUC）来评价放射性组学特征的性能。结果选择5个特征构建放射组学特征，用于预测组织学分级。基于ADC的放射组学特征在区分低级别和高级别肿瘤方面表现良好，两个队列的AUC均为0.83。基于训练队列的截止值，放射组学特征在训练和测试队列中分别实现了0.78和0.79的准确度、0.65和0.71的灵敏度以及0.85和0.82的特异性。结论基于ADC的放射组学技术是一种有效的、有前途的无创性方法，可用于预测口腔舌鳞癌和FOM的组织学分级。
Background Histologic grade assessment plays an important part in the clinical decision making and prognostic evaluation of squamous cell carcinoma (SCC) of the oral tongue and floor of mouth (FOM). Purpose To assess the value of apparent diffusion coefficient (ADC)-based radiomics in discriminating between low- and high-grade SCC of the oral tongue and FOM. Material and Methods We included data from 88 patients (training cohort: n = 59; testing cohort: n = 29) who underwent diffusion-weighted imaging with a 3.0-T magnetic resonance imaging scanner before treatment. A total of 526 radiomics features were extracted from ADC maps to construct a radiomics signature with least absolute shrinkage and selection operator logistic regression. Receiver operating characteristic curves and areas under the curve (AUCs) were used to evaluate the performance of radiomic signature. Results Five features were selected to construct the radiomics signature for predicting histologic grade. The ADC-based radiomics signature performed well for discriminating between low- and high-grade tumors, with AUCs of 0.83 in both cohorts. Based on the cut-off value of the training cohort, the radiomics signature achieved accuracies of 0.78 and 0.79, sensitivities of 0.65 and 0.71, and specificities of 0.85 and 0.82 in the training and testing cohorts, respectively. Conclusion ADC-based radiomics can be a useful and promising non-invasive method for predicting histologic grade of SCC of the oral tongue and FOM.