Abstract
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.
Highlights
The incidence of hypopharyngeal squamous cell carcinoma (HSCC), one of the common head and neck squamous cell carcinomas, is relatively low among all human cancers
A previous clinical analysis revealed that several clinical characteristics might affect the prognosis of HSCC patients, and these characteristics include smoking, drinking, tumor size, T stage, lymph node metastasis, and resection margin [5]
Radiomics are recognized as a promising tool to improve predictive accuracy of the diagnosis and prognosis through quantifying phenotypic characteristics on medical imaging and the use of automated algorithms [16, 17]
Summary
The incidence of hypopharyngeal squamous cell carcinoma (HSCC), one of the common head and neck squamous cell carcinomas, is relatively low among all human cancers. In China and Eastern Europe, the incidence of HSCC is relatively high due to diet habits, tobacco, and alcohol use. In the Western countries, clinicians tend to choose less expensive conservative treatment (radiotherapy and chemotherapy) due to its low incidence [1], while in China, HSCC patients typically receive comprehensive treatment with surgery [2]. A previous clinical analysis revealed that several clinical characteristics might affect the prognosis of HSCC patients, and these characteristics include smoking, drinking, tumor size, T stage, lymph node metastasis, and resection margin [5]. Some molecular markers were found in head and neck tumors, but these markers still did not achieve a relatively high specificity and sensitivity. It is necessary to further explore other prognostic markers for better individualized
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