Preoperative prediction of cervical cancer survival using a high-resolution MRI-based radiomics nomogram

被引:2
作者
Li, Jia [1 ]
Zhou, Hao [2 ]
Lu, Xiaofei [1 ]
Wang, Yiren [3 ]
Pang, Haowen [4 ]
Cesar, Daniel [5 ]
Liu, Aiai [1 ]
Zhou, Ping [1 ]
机构
[1] Southwest Med Univ, Dept Radiol, Affiliated Hosp, Luzhou, Peoples R China
[2] Sichuan Univ, West China Hosp, West China Sch Nursing, Dept Cardiol, Chengdu, Peoples R China
[3] Southwest Med Univ, Sch Nursing, Luzhou, Peoples R China
[4] Southwest Med Univ, Affiliated Hosp, Dept Oncol, Luzhou, Peoples R China
[5] Natl Canc Inst, Dept Gynecol Oncol, Rio De Janeiro, Brazil
关键词
Cervical cancer; Prediction; Nomogram; Magnetic resonance imaging (MRI); DISEASE-FREE SURVIVAL; INVASION; BREAST;
D O I
10.1186/s12880-023-01111-5
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
BackgroundCervical cancer patients receiving radiotherapy and chemotherapy require accurate survival prediction methods. The objective of this study was to develop a prognostic analysis model based on a radiomics score to predict overall survival (OS) in cervical cancer patients.MethodsPredictive models were developed using data from 62 cervical cancer patients who underwent radical hysterectomy between June 2020 and June 2021. Radiological features were extracted from T2-weighted (T2W), T1-weighted (T1W), and diffusion-weighted (DW) magnetic resonance images prior to treatment. We obtained the radiomics score (rad-score) using least absolute shrinkage and selection operator (LASSO) regression and Cox's proportional hazard model. We divided the patients into low- and high-risk groups according to the critical rad-score value, and generated a nomogram incorporating radiological features. We evaluated the model's prediction performance using area under the receiver operating characteristic (ROC) curve (AUC) and classified the participants into high- and low-risk groups based on radiological characteristics.ResultsThe 62 patients were divided into high-risk (n = 43) and low-risk (n = 19) groups based on the rad-score. Four feature parameters were selected via dimensionality reduction, and the scores were calculated after modeling. The AUC values of ROC curves for prediction of 3- and 5-year OS using the model were 0.84 and 0.93, respectively.ConclusionOur nomogram incorporating a combination of radiological features demonstrated good performance in predicting cervical cancer OS. This study highlights the potential of radiomics analysis in improving survival prediction for cervical cancer patients. However, further studies on a larger scale and external validation cohorts are necessary to validate its potential clinical utility.
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页数:10
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