Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital at Linkou, 5 Fuhsing St., Guishan, Taoyuan, Taiwan, 33382.
Imaging Core Laboratory, Institute for Radiological Research, Chang Gung Memorial Hospital at Linkou and Chang Gung University, 5 Fuhsing St., Guishan, Taoyuan, Taiwan, 33382.
Eur Radiol. 2019 Feb;29(2):556-565. doi: 10.1007/s00330-018-5651-4. Epub 2018 Jul 26.
To develop and validate a prognostic model of integrating whole-tumour apparent diffusion coefficient (ADC) from pretreatment diffusion-weighted (DW) magnetic resonance (MR) imaging with human papillomavirus (HPV) genotyping in predicting the overall survival (OS) and disease-free survival (DFS) for women with stage IB-IV cervical cancer following concurrent chemoradiotherapy (CCRT).
We retrospectively analysed three prospectively collected cohorts comprising 300 patients with stage IB-IV cervical cancer treated with CCRT in 2007-2014 and filtered 134 female patients who underwent MR imaging at 3.0 T for final analysis (age, 24-92 years; median, 54 years). Univariate and multivariate Cox regression analyses were used to evaluate the whole-tumour ADC histogram parameters, HPV genotyping and relevant clinical variables in predicting OS and DFS. The dataset was randomly split into training (n = 88) and testing (n = 46) datasets for construction and independent bootstrap validation of the models.
The median follow-up time for surviving patients was 69 months (range, 9-126 months). Non-squamous cell type, ADC <0.77 × 10 mm/s, T3-4, M1 stage and high-risk HPV status were selected to generate a model, in which the OS and DFS for the low, intermediate and high-risk groups were significantly stratified (p < 0.0001). The prognostic model improved the prediction significantly compared with the International Federation of Gynaecology and Obstetrics (FIGO) stage for both the training and independent testing datasets (p < 0.0001).
The prognostic model based on integrated clinical and imaging data could be a useful clinical biomarker to predict OS and DFS in patients with stage IB-IV cervical cancer treated with CCRT.
• ADC is the best prognostic factor among ADC parameters in cervical cancer treated with CCRT • A novel prognostic model was built based on histology, ADC , T and M stage and HPV status • The prognostic model outperforms FIGO stage in the survival prediction.
建立并验证一个整合宫颈癌患者术前弥散加权磁共振成像(DW-MRI)全瘤体表观弥散系数(ADC)和人乳头瘤病毒(HPV)基因型的预后模型,以预测同步放化疗(CCRT)后 IB-IV 期宫颈癌患者的总生存(OS)和无病生存(DFS)。
我们回顾性分析了三个前瞻性队列,共纳入 2007 年至 2014 年接受 CCRT 治疗的 300 例 IB-IV 期宫颈癌患者,筛选出最终纳入分析的 134 例女性患者(年龄 24-92 岁,中位年龄 54 岁)。采用单因素和多因素 Cox 回归分析评价全瘤体 ADC 直方图参数、HPV 基因型及相关临床变量在预测 OS 和 DFS 中的作用。数据集被随机分为训练集(n=88)和验证集(n=46),用于模型的构建和独立的自举验证。
存活患者的中位随访时间为 69 个月(9-126 个月)。非鳞癌、ADC<0.77×10 mm/s、T3-4、M1 期和高危型 HPV 状态被纳入模型,低、中、高危组的 OS 和 DFS 差异有统计学意义(p<0.0001)。与国际妇产科联盟(FIGO)分期相比,该预后模型在训练集和验证集均显著提高了预测能力(p<0.0001)。
基于临床和影像数据整合的预后模型可作为预测 CCRT 后 IB-IV 期宫颈癌患者 OS 和 DFS 的有效临床生物标志物。
·ADC 是 CCRT 后宫颈癌患者最佳的预后因素。
·基于组织学、ADC、T 和 M 期及 HPV 状态建立了一个新的预后模型。
·该预后模型在生存预测方面优于 FIGO 分期。