Prognostic Value of Radiomics Analysis of Skeletal Muscle After Radical Irradiation of Esophageal Cancer
Prognostic Value of Radiomics Analysis of Skeletal Muscle After Radical Irradiation of Esophageal Cancer
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DOI：
10.21873/anticanres.16328
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发表时间：
2023-04-01
影响因子：
2
通讯作者：
Sasaki, Ryohei
中科院分区：
文献类型：
--
作者：
Iwashita, Kazuma;Kubota, Hikaru;Sasaki, Ryohei
背景/目的：肌肉减少症是几种肿瘤类型的独立生存预测因子。计算机断层扫描（CT）是身体成分评估的标准测量方法。CT图像的放射组学分析可以精确评估骨骼肌。本研究旨在利用骨骼肌放射组学建立食管癌根治性放疗患者的预后生存模型。患者和方法：我们回顾性地确定了2008年4月至2017年12月期间在我们机构接受根治性放疗的食管癌患者。从第三腰椎水平的轴向预处理CT中提取骨骼肌放射组学。使用机器学习结合最小绝对收缩和选择算子（LASSO）构建预测模型。预测诺模图模型包括具有放射组学特征的临床因素。创建了三种预测模型：临床，放射组学和组合。结果：98例食管癌患者入组本研究。中位观察期为57.5个月（范围=1-98个月）。通过LASSO分析选择了35个放射组学特征，并使用训练和验证数据构建了预测模型。在联合模型中，预测食管癌生存率的准确性、特异性、敏感性和浓度-时间曲线下面积的平均值分别为75%、92%和0.86。临床的C指数，
Background/Aim: Sarcopenia is an independent survival predictor in several tumor types. Computed tomography (CT) is the standard measurement for body composition assessment. Radiomics analysis of CT images allows for the precise evaluation of skeletal muscles. This study aimed to construct a prognostic survival model for patients with esophageal cancer who underwent radical irradiation using skeletal muscle radiomics. Patients and Methods: We retrospectively identified patients with esophageal cancer who underwent radical irradiation at our institution between April 2008 and December 2017. Skeletal muscle radiomics were extracted from an axial pretreatment CT at the third lumbar vertebral level. The prediction model was constructed using machine learning coupled with the least absolute shrinkage and selection operator (LASSO). The predictive nomogram model comprised clinical factors with radiomic features. Three prediction models were created: clinical, radiomics, and combined. Results: Ninety-eight patients with 98 esophageal cancers were enrolled in this study. The median observation period was 57.5 months (range=1-98 months). Thirty-five radiomics features were selected by LASSO analysis, and a prediction model was constructed using training and validation data. The average of the accuracy, specificity, sensitivity, and area under the concentration-time curve for predicting survival in esophageal cancer in the combined model were 75%, 92%, and 0.86, respectively. The C-indices of the clinical,