Non-invasive radiomic biomarkers involve high-throughput extraction of imaging data and may provide important complementary information. We investigated the association between pretreatment nodal radiomic features and clinical outcome for head neck cancer (HNC). After institutional review board approval, patients with lymph node positive head and neck squamous cell carcinoma treated with definitive radiotherapy were retrospectively reviewed. Lymph node delineation for radiation planning was based on computed tomography (CT), and 39 intensity and shape based first order radiomics features were extracted from nodal volumes. Loco-regional control (LRC), disease free survival (DFS) and overall survival (OS) were estimated by a Cox proportional hazard regression univariate analysis (UVA). Association between radiomic features and known p16 status were also analyzed by Wilcoxon rank sum test. A total of 44 patients were identified with a median follow-up of 12 months. Primary sites consisted of oropharynx (n=41) and oral cavity (n=3), 27 (61%) of which 27 (66%) were p16 positive. Median radiation dose was 68 Gy (range 54-70 Gy). The majority of patients received concurrent chemotherapy (n=36, 73%). No radiomic features were associated with p16 status (all p>0.1). The 2-year actuarial LRC, DFS and OS were 84%, 84% and 94%, respectively. On UVA, radiomic features with a trending association to LRC included sphericity (p=0.055), eccentricity (p=0.07), spherical disproportion (p=0.068), convexity (p=0.072), and long-axis dimension (p=0.091), of which, sphericity (p=0.082) and convexity (p=0.072) also showed a trending association with DFS. The radiomics features significantly associated with DFS were surface area [HR 1.02 (95% CI: 1-1.04); p=0.02], long-axis [HR 1.02 (95% CI: 1-1.04); p=0.03], and short-axis dimension [HR 1.09 (95% CI: 1.01-1.18); p=0.04]. Other features with a trending association with DFS were volume (p=0.057), kurtosis (p=0.09), and TGV (p=0.09). No radiomic features predicted for OS on UVA. This study identified certain lymph node radiomic features may be prognostic for DFS in HNC. Further work is required to improve the power and resolution of these features, with the goal towards identifying novel predictive tools to aid in personalized radiotherapy.
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