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Discovery and Validation of a CT-Based Radiomic Signature for Preoperative Prediction of Early Recurrence in Hypopharyngeal Carcinoma
Joint Authors
Li, Wenming
Wei, Dongmin
Wushouer, Aihemaiti
Cao, Shengda
Zhao, Tongtong
Yu, Dexin
Lei, Dapeng
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-08-10
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Abstract EN
Purpose.
In the clinical management of hypopharyngeal squamous cell carcinoma (HSCC), preoperative identification of early recurrence (≤2 years) after curative resection is essential.
Thus, we aimed to develop a CT-based radiomic signature to predict early recurrence in HSCC patients preoperatively.
Methods.
In total, 167 HSCC patients who underwent partial surgery were enrolled in this retrospective study and divided into two groups, i.e., the training cohort (n=133) and the validation cohort (n=34).
Each individual was followed up for at least for 2 years.
Radiomic features were extracted from CT images, and the radiomic signature was built with the least absolute shrinkage and selection operator (LASSO) logistic regression (LR) model.
The associations of preoperative clinical factors with early recurrence were evaluated.
A radiomic signature-combined model was built, and the area under the curve (AUC) was used to explore their performance in discriminating early recurrence.
Results.
Among the 1415 features, 335 of them were selected using the variance threshold method.
Then, the SelectKBest method was further used for the selection of 31 candidate features.
Finally, 11 out of 31 optimal features were identified with the LASSO algorithm.
In the LR classifier, the AUCs of the training and validation sets in discriminating early recurrence were 0.83 (95% CI: 0.76-0.90) (sensitivity 0.8 and specificity 0.83) and 0.83 (95% CI: 0.67-0.99) (sensitivity 0.69 and specificity 0.71), respectively.
Conclusions.
Using the radiomic signature, we developed a radiomic signature to preoperatively predict early recurrence in patients with HSCC, which may serve as a potential noninvasive tool to guide personalized treatment.
American Psychological Association (APA)
Li, Wenming& Wei, Dongmin& Wushouer, Aihemaiti& Cao, Shengda& Zhao, Tongtong& Yu, Dexin…[et al.]. 2020. Discovery and Validation of a CT-Based Radiomic Signature for Preoperative Prediction of Early Recurrence in Hypopharyngeal Carcinoma. BioMed Research International،Vol. 2020, no. 2020, pp.1-8.
https://search.emarefa.net/detail/BIM-1133893
Modern Language Association (MLA)
Li, Wenming…[et al.]. Discovery and Validation of a CT-Based Radiomic Signature for Preoperative Prediction of Early Recurrence in Hypopharyngeal Carcinoma. BioMed Research International No. 2020 (2020), pp.1-8.
https://search.emarefa.net/detail/BIM-1133893
American Medical Association (AMA)
Li, Wenming& Wei, Dongmin& Wushouer, Aihemaiti& Cao, Shengda& Zhao, Tongtong& Yu, Dexin…[et al.]. Discovery and Validation of a CT-Based Radiomic Signature for Preoperative Prediction of Early Recurrence in Hypopharyngeal Carcinoma. BioMed Research International. 2020. Vol. 2020, no. 2020, pp.1-8.
https://search.emarefa.net/detail/BIM-1133893
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1133893