TY - JOUR
T1 - A positron emission tomography radiomic signature for distant metastases risk in oropharyngeal cancer patients treated with definitive chemoradiotherapy
AU - Brodin, N. Patrik
AU - Velten, Christian
AU - Lubin, Jonathan
AU - Eichler, Jeremy
AU - Zhu, Shaoyu
AU - Saha, Sneha
AU - Guha, Chandan
AU - Kalnicki, Shalom
AU - Tomé, Wolfgang A.
AU - Garg, Madhur K.
AU - Kabarriti, Rafi
N1 - Publisher Copyright:
© 2022 The Author(s)
PY - 2022/1
Y1 - 2022/1
N2 - 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.
AB - 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.
KW - Oropharyngeal cancer
KW - Positron emission tomography
KW - Radiomics
KW - Risk stratification
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U2 - 10.1016/j.phro.2022.02.005
DO - 10.1016/j.phro.2022.02.005
M3 - Article
AN - SCOPUS:85124943337
SN - 2405-6316
VL - 21
SP - 72
EP - 77
JO - Physics and Imaging in Radiation Oncology
JF - Physics and Imaging in Radiation Oncology
ER -
