TY - JOUR
T1 - Integrating Tumor and Nodal Imaging Characteristics at Baseline and Mid-Treatment Computed Tomography Scans to Predict Distant Metastasis in Oropharyngeal Cancer Treated With Concurrent Chemoradiotherapy
AU - Wu, Jia
AU - Gensheimer, Micheal F.
AU - Zhang, Nasha
AU - Han, Fei
AU - Liang, Rachel
AU - Qian, Yushen
AU - Zhang, Carrie
AU - Fischbein, Nancy
AU - Pollom, Erqi L.
AU - Beadle, Beth
AU - Le, Quynh Thu
AU - Li, Ruijiang
N1 - Publisher Copyright:
© 2019 Elsevier Inc.
PY - 2019/7/15
Y1 - 2019/7/15
N2 - Purpose: Prognostic biomarkers of disease relapse are needed for risk-adaptive therapy of oropharyngeal cancer (OPC). This work aims to identify an imaging signature to predict distant metastasis in OPC. Methods and Materials: This single-institution retrospective study included 140 patients treated with definitive concurrent chemoradiotherapy, for whom both pre- and midtreatment contrast-enhanced computed tomography (CT) scans were available. Patients were divided into separate training and testing cohorts. Forty-five quantitative image features were extracted to characterize tumor and involved lymph nodes at both time points. By incorporating both imaging and clinicopathological features, a random survival forest (RSF) model was built to predict distant metastasis–free survival (DMFS). The model was optimized via repeated cross-validation in the training cohort and then independently validated in the testing cohort. Results: The most important features for predicting DMFS were the maximum distance among nodes, maximum distance between tumor and nodes at mid-treatment, and pretreatment tumor sphericity. In the testing cohort, the RSF model achieved good discriminability for DMFS (C-index = 0.73, P = .008), and further divided patients into 2 risk groups with different 2-year DMFS rates: 96.7% versus 67.6%. Similar trends were observed for patients with p16+ tumors and smoking ≤10 pack-years. The RSF model based on pretreatment CT features alone achieved lower performance (concordance index = 0.68, P = .03). Conclusions: Integrating tumor and nodal imaging characteristics at baseline and mid-treatment CT allows prediction of distant metastasis in OPC. The proposed imaging signature requires prospective validation and, if successful, may help identify high-risk human papillomavirus-positive patients who should not be considered for deintensification therapy.
AB - Purpose: Prognostic biomarkers of disease relapse are needed for risk-adaptive therapy of oropharyngeal cancer (OPC). This work aims to identify an imaging signature to predict distant metastasis in OPC. Methods and Materials: This single-institution retrospective study included 140 patients treated with definitive concurrent chemoradiotherapy, for whom both pre- and midtreatment contrast-enhanced computed tomography (CT) scans were available. Patients were divided into separate training and testing cohorts. Forty-five quantitative image features were extracted to characterize tumor and involved lymph nodes at both time points. By incorporating both imaging and clinicopathological features, a random survival forest (RSF) model was built to predict distant metastasis–free survival (DMFS). The model was optimized via repeated cross-validation in the training cohort and then independently validated in the testing cohort. Results: The most important features for predicting DMFS were the maximum distance among nodes, maximum distance between tumor and nodes at mid-treatment, and pretreatment tumor sphericity. In the testing cohort, the RSF model achieved good discriminability for DMFS (C-index = 0.73, P = .008), and further divided patients into 2 risk groups with different 2-year DMFS rates: 96.7% versus 67.6%. Similar trends were observed for patients with p16+ tumors and smoking ≤10 pack-years. The RSF model based on pretreatment CT features alone achieved lower performance (concordance index = 0.68, P = .03). Conclusions: Integrating tumor and nodal imaging characteristics at baseline and mid-treatment CT allows prediction of distant metastasis in OPC. The proposed imaging signature requires prospective validation and, if successful, may help identify high-risk human papillomavirus-positive patients who should not be considered for deintensification therapy.
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U2 - 10.1016/j.ijrobp.2019.03.036
DO - 10.1016/j.ijrobp.2019.03.036
M3 - Article
C2 - 30940529
AN - SCOPUS:85065012205
SN - 0360-3016
VL - 104
SP - 942
EP - 952
JO - International Journal of Radiation Oncology Biology Physics
JF - International Journal of Radiation Oncology Biology Physics
IS - 4
ER -