Nomograms Combining Clinical and Imaging Parameters to Predict Recurrence and Disease-free Survival After Concurrent Chemoradiotherapy in Patients With Locally Advanced Cervical Cancer

医学 列线图 盒内非相干运动 宫颈癌 放化疗 无线电技术 逻辑回归 比例危险模型 肿瘤科 头颈部癌 多元分析 放射治疗 内科学 放射科 核医学 磁共振弥散成像 癌症 磁共振成像
作者
Yu Zhang,Long Liu,Kaiyue Zhang,Rixin Su,Haodong Jia,Liting Qian,Jiangning Dong
出处
期刊:Academic Radiology [Elsevier BV]
卷期号:30 (3): 499-508 被引量:26
标识
DOI:10.1016/j.acra.2022.08.002
摘要

To investigate the value of nomograms based on clinical prognostic factors (CPF), intravoxel incoherent motion diffusion weighted imaging (IVIM-DWI) and MRI-derived radiomics in predicting recurrence and disease-free survival (DFS) after concurrent chemoradiotherapy (CCRT) for locally advanced cervical cancer (LACC).Retrospective analysis of data from 115 patients with ⅠB-ⅣA cervical cancer who underwent CCRT and had been followed up consistently. All patients were randomized 2:1 into training and validation groups. Pre-treatment IVIM-DWI parameters (ADC-value, D-value, D*-value and f-value) and pre- and post-treatment three-dimensional radiomics parameters (from axial T2WI) of primary lesions were measured. The LASSO algorithm and Logistic regression analysis were used to filter texture features and calculate radiomics score (Rad-score). Multivariate Logistic and Cox regression analysis was used to construct nomograms to predict recurrence and DFS for patients with LACC after CCRT respectively, with internal and external validation.External beam radiotherapy dose, f-value, pre-treatment and post-treatment Rad-score were independent prognostic factors for recurrence and DFS in patients with cervical cancer, forming Model1 and Model2, with OR values of 0.480, 1.318, 3.071, 3.200 and HR values of 0.322, 3.372, 5.138, 7.204. The area under the curve (AUC) of Model1 for predicting recurrence of cervical cancer was 0.977, with internal and external validation C-indexes of 0.977 and 0.962. The AUC for Model2 predicting disease-free survival (DFS) at 1, 3, and 5 years was 0.895, 0.888 and 0.916 respectively, with internal and external C-indexes of 0.860 and 0.892. The decision curves analysis and clinical impact curves further indicate the high predictive efficiency and stability of nomograms.The nomograms based on clinical, IVIM-DWI and radiomics parameters have high clinical value in predicting recurrence and DFS of patients with LACC after CCRT and can provide a reference for prognostic assessment and individualized treatment of cervical cancer patients.
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