文章：

局部晚期宫颈癌放化疗治疗反应早期预测的纵向FDG-PET影像组学：一项初步研究

Longitudinal FDG-PET Radiomics for Early Prediction of Treatment Response to Chemoradiation in Locally Advanced Cervical Cancer: A Pilot Study

原文发布日期：13 November 2024

DOI: 10.3390/cancers16223813

类型: Article

开放获取: 是

英文摘要：

Objectives: This study aimed to assess the capacity of longitudinal FDG-PET radiomics for early distinguishing between locally advanced cervical cancer (LACC) patients who responded to treatment and those who did not.Methods: FDG-PET scans were obtained before and midway through concurrent chemoradiation for a study cohort of patients with LACC. Radiomics features related to image textures were extracted from the primary tumor volumes and stratified for relevance to treatment response status with the aid of random forest recursive feature elimination. Predictive models based on the k-nearest neighbors time series classifier were developed using the top-selected features to differentiate between responders and non-responders. The performance of the developed models was evaluated using receiver operating characteristic (ROC) curve analysis and n-fold cross-validation.Results: The top radiomics features extracted from scans taken midway through treatment showed significant differences between the two responder groups (p-values < 0.0005). In contrast, those from pretreatment scans did not exhibit significant differences. The AUC of the mean ROC curve for the predictive model based on the top features from pretreatment scans was 0.8529, while it reached 0.9420 for those derived midway through treatment scans.Conclusions: The study highlights the potential of longitudinal FDG-PET radiomics extracted midway through treatment for predicting response to chemoradiation in LACC patients and emphasizes that interim PET scans could be crucial in personalized medicine, ultimately enhancing therapeutic outcomes for LACC.

摘要翻译： 

目的：本研究旨在评估纵向FDG-PET影像组学在早期区分局部晚期宫颈癌（LACC）患者中对治疗有反应与无反应者的能力。 方法：研究队列中的LACC患者在同步放化疗前及治疗中期接受了FDG-PET扫描。从原发肿瘤体积中提取与图像纹理相关的影像组学特征，并借助随机森林递归特征消除法筛选与治疗反应状态相关的特征。基于k近邻时间序列分类器，利用筛选出的最优特征构建预测模型，以区分有反应者和无反应者。通过受试者工作特征（ROC）曲线分析和n折交叉验证评估所构建模型的性能。 结果：从治疗中期扫描中提取的顶级影像组学特征在两个反应组间显示出显著差异（p值 < 0.0005），而治疗前扫描提取的特征则未表现出显著差异。基于治疗前扫描顶级特征构建的预测模型，其平均ROC曲线下面积（AUC）为0.8529，而基于治疗中期扫描特征构建的模型AUC达到0.9420。 结论：本研究强调了治疗中期提取的纵向FDG-PET影像组学在预测LACC患者对放化疗反应方面的潜力，并强调中期PET扫描在个体化医疗中的关键作用，最终有望改善LACC患者的治疗效果。

原文链接：

Longitudinal FDG-PET Radiomics for Early Prediction of Treatment Response to Chemoradiation in Locally Advanced Cervical Cancer: A Pilot Study