Physics and Imaging in Radiation Oncology (Jan 2022)
A positron emission tomography radiomic signature for distant metastases risk in oropharyngeal cancer patients treated with definitive chemoradiotherapy
Abstract
Background and purpose: Disease recurrence and distant metastases (DM) are major concerns for oropharyngeal cancer (OPC) patients receiving definitive chemo-radiotherapy. Here, we investigated whether pre-treatment primary tumor positron emission tomography (PET) features could predict progression-free survival (PFS) or DM. Methods and materials: Primary tumors were delineated on pre-treatment PET scans for patients treated between 2005 and 2018 using gradient-based segmentation. Radiomic image features were extracted, along with SUV metrics. Features with zero variance and strong correlation to tumor volume, stage, p16 status, age or smoking were excluded. A random forest model was used to identify features associated with PFS. Kaplan-Meier methods, Cox regression and logistic regression with receiver operating characteristics (ROC) and 5-fold cross-validated areas-under-the-curve (CV-AUCs) were used. Results: A total of 114 patients were included. With median follow-up 40 months (range: 3–138 months), 14 patients had local recurrence, 21 had DM and 38 died. Two-year actuarial local control, distant control, PFS and overall survival was 89%, 84%, 70% and 84%, respectively. The wavelet_LHL_GLDZM_LILDE feature slightly improved PFS prediction compared to clinical features alone (CV-AUC 0.73 vs. 0.71). Age > 65 years (HR = 2.64 (95%CI: 1.36–5.2), p = 0.004) and p16-negative disease (HR = 3.38 (95%CI: 1.72–6.66), p < 0.001) were associated with poor PFS. A binary radiomic classifier strongly predicted DM with multivariable HR = 3.27 (95%CI: 1.15–9.31), p = 0.027, specifically for patients with p16-negative disease with 2-year DM-free survival 83% for low-risk vs. 38% for high-risk patients (p = 0.004). Conclusions: A radiomics signature strongly associated with DM risk could provide a tool for improved risk stratification, potentially adding adjuvant immunotherapy for high-risk patients.
