首页> 外文期刊>Frontiers in Oncology >A Computed Tomography-Based Radiomic Prognostic Marker of Advanced High-Grade Serous Ovarian Cancer Recurrence: A Multicenter Study
【24h】

A Computed Tomography-Based Radiomic Prognostic Marker of Advanced High-Grade Serous Ovarian Cancer Recurrence: A Multicenter Study

机译:基于计算的断层摄影基于高级浆液卵巢癌复发的基于射碎基于辐射预后标志性:多中心研究

获取原文
获取外文期刊封面目录资料

摘要

Objectives: We used radiomic analysis to establish a radiomic signature based on preoperative contrast enhanced computed tomography (CT) and explore its effectiveness as a novel recurrence risk prognostic marker for advanced high-grade serous ovarian cancer (HGSOC). Methods: This study had a retrospective multicenter (two hospitals in China) design and a radiomic analysis was performed using contrast enhanced CT in advanced HGSOC (FIGO stage III or IV) patients. We used a minimum 18-month follow-up period for all patients (median 38.8 months, range 18.8–81.8 months). All patients were divided into three cohorts according to the timing of their surgery and hospital stay: training cohort (TC) and internal validation cohort (IVC) were from one hospital, and independent external validation cohort (IEVC) was from another hospital. A total of 620 3-D radiomic features were extracted and a Lasso-Cox regression was used for feature dimension reduction and determination of radiomic signature. Finally, we combined the radiomic signature with seven common clinical variables to develop a novel nomogram using a multivariable Cox proportional hazards model. Results: A final 142 advanced HGSOC patients were enrolled. Patients were successfully divided into two groups with statistically significant differences based on radiomic signature, consisting of four radiomic features (log-rank test P = 0.001, &0.001, &0.001 for TC, IVC, and IEVC, respectively). The discrimination accuracies of radiomic signature for predicting recurrence risk within 18 months were 82.4% (95% CI, 77.8–87.0%), 77.3% (95% CI, 74.4–80.2%), and 79.7% (95% CI, 73.8–85.6%) for TC, IVC, and IEVC, respectively. Further, the discrimination accuracies of radiomic signature for predicting recurrence risk within 3 years were 83.4% (95% CI, 77.3–89.6%), 82.0% (95% CI, 78.9–85.1%), and 70.0% (95% CI, 63.6–76.4%) for TC, IVC, and IEVC, respectively. Finally, the accuracy of radiomic nomogram for predicting 18-month and 3-year recurrence risks were 84.1% (95% CI, 80.5–87.7%) and 88.9% (95% CI, 85.8–92.5%), respectively. Conclusions: Radiomic signature and radiomic nomogram may be low-cost, non-invasive means for successfully predicting risk for postoperative advanced HGSOC recurrence before or during the perioperative period. Radiomic signature is a potential prognostic marker that may allow for individualized evaluation of patients with advanced HGSOC.
机译:目的:我们使用射线分析来建立基于术前对比增强的计算断层扫描(CT)的辐射瘤签名,并探讨其作为先进高级浆液癌(HGSOC)的新型复发性风险预后标志物的有效性。方法:本研究有一个回顾性多中心(中国的两家医院)设计,使用对比度增强CT在高级HGSOC(FIGO第III期或IV)患者中进行射线分析。我们使用所有患者的最低18个月的随访时间(中位数38.8个月,范围为18.8-81.8个月)。所有患者根据手术和住院时间的时间分为三个队列:培训队列(TC)和内部验证队列(IVC)来自一家医院,独立的外部验证队列(IEVC)来自另一家医院。提取了总共620个3-D射线瘤特征,使用洛索-COX回归进行特征尺寸减少和射出物签名的测定。最后,我们将零域签名与七个常见的临床变量相结合,以使用多变量的Cox比例危险模型开发一种新颖的录音图。结果:最终142名先进的HGSOC患者注册。患者成功分为两组,基于含有四个射出物特征的辐射症状,分别具有统计学上显着的差异(分别为逻辑秩检测P = 0.001,& 0.001,对于TC,IVC和IEVC,分别用于TC,IVC和IEVC)。在18个月内预测复发风险的偏射签名的辨别准确性为82.4%(95%CI,77.8-87.0%),77.3%(95%CI,74.4-80.2%)和79.7%(95%CI,73.8-分别为TC,IVC和IEVC的85.6%。此外,在3年内预测复发风险的辐射素签名的判别精度为83.4%(95%CI,77.3-89.6%),82.0%(95%CI,78.9-85.1%)和70.0%(95%CI,分别为TC,IVC和IEVC的63.6-76.4%。最后,用于预测18个月和3年复发风险的射出物质图表的准确性分别为84.1%(95%CI,80.5-87.7%)和88.9%(95%CI,85.8-92.5%)。结论:射致签名和射线图标可能是低成本,非侵入性手段,用于成功预测术后期间或期间术后术后高级HGSOC复发的风险。辐射素签名是一种潜在的预后标记,可允许对高级HGSOC患者的个体化评估。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号