Sub-Region Based Radiomics Analysis for Survival Prediction in Oesophageal Tumours Treated by Definitive Concurrent Chemoradiotherapy

Authors

Congying Xie, Wenzhou Medical University
Pengfei Yang, Zhejiang University School of Medicine
Xuebang Zhang, Wenzhou Medical University
Lei Xu, Zhejiang University School of Medicine
Xiaoju Wang, Hangzhou Cancer Hospital
Xiadong Li, Zhejiang University School of Medicine
Luhan Zhang, Zhejiang University School of Medicine
Ruifei Xie, Hangzhou Cancer Hospital
Ling Yang, Hangzhou Cancer Hospital
Zhao Jing, Hangzhou Cancer Hospital
Hongfang Zhang, Hangzhou Cancer Hospital
Lingyu Ding, Hangzhou Cancer Hospital
Yu Kuang, University of Nevada, Las VegasFollow
Tianye Niu, Zhejiang University School of MedicineFollow
Shixiu Wu, Chinese Academy of Medical Sciences and Peking Union Medical CollegeFollow

Document Type

Article

Publication Date

5-23-2019

Publication Title

EBioMedicine

Publisher

Elsevier

First page number:

1

Last page number:

9

Abstract

Background: Evaluating clinical outcome prior to concurrent chemoradiotherapy remains challenging for oesophageal squamous cell carcinoma (OSCC) as traditional prognostic markers are assessed at the completion of treatment. Herein, we investigated the potential of using sub-region radiomics as a novel tumour biomarker in predicting overall survival of OSCC patients treated by concurrent chemoradiotherapy. Methods: Independent patient cohorts from two hospitals were included for training (n = 87) and validation (n = 46). Radiomics features were extracted from sub-regions clustered from patients' tumour regions using K-means method. The LASSO regression for ‘Cox’ method was used for feature selection. The survival prediction model was constructed based on the sub-region radiomics features using the Cox proportional hazards model. The clinical and biological significance of radiomics features were assessed by correlation analysis of clinical characteristics and copy number alterations(CNAs) in the validation dataset. Finding: The overall survival prediction model combining with seven sub-regional radiomics features was constructed. The C-indexes of the proposed model were 0.729 (0.656–0.801, 95% CI) and 0.705 (0.628–0.782, 95%CI) in the training and validation cohorts, respectively. The 3-year survival receiver operating characteristic (ROC) curve showed an area under the ROC curve of 0.811 (0.670–0.952, 95%CI) in training and 0.805 (0.638–0.973, 95%CI) in validation. The correlation analysis showed a significant correlation between radiomics features and CNAs. Interpretation: The proposed sub-regional radiomics model could predict the overall survival risk for patients with OSCC treated by definitive concurrent chemoradiotherapy.

Keywords

Oesophageal cancer; Radiomics; Prognostic model; Radiation therapy; Imaging

Disciplines

Digestive System Diseases | Environmental Public Health | Health and Medical Physics | Medical Toxicology | Oncology | Radiation Medicine

File Format

pdf

File Size

1.789 KB

Language

English

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 License.

Repository Citation

Xie, C., Yang, P., Zhang, X., Xu, L., Wang, X., Li, X., Zhang, L., Xie, R., Yang, L., Jing, Z., Zhang, H., Ding, L., Kuang, Y., Niu, T., Wu, S. (2019). Sub-Region Based Radiomics Analysis for Survival Prediction in Oesophageal Tumours Treated by Definitive Concurrent Chemoradiotherapy. EBioMedicine 1-9. Elsevier.
http://dx.doi.org/10.1016/j.ebiom.2019.05.023