摘要
Purpose: This study integrated clinical outcomes and radiomics of advanced thoracic esophageal squamous cell carcinoma patients receiving neoadjuvant concurrent chemoradiotherapy (NACCRT) to establish a novel constraint model for predicting radiation pneumonitis (RP). Patients and methods: We conducted a retrospective review for thoracic advanced esophageal cancer patients who received NACCRT. From 2013 to 2018, 89 patients were eligible for review. Staging workup and response evaluation included positron emission tomography/computed tomography (PET/CT) scans and endoscopic ultrasound. Patients received RTwith 48 Gy to gross tumor and 43.2 Gy to elective nodal area in simultaneous integrated boost method divided in 24 fractions. Weekly platinum-based chemotherapy was administered concurrently. Side effects were evaluated using CTCAE v4. Images of 2-fluoro-2-deoxyglucose PET/CT before and after NACCRT were registered to planning CT images to create a region of interest for dosimetry parameters that spatially matched RP-related regions, including V10, V20, V50%, V27, and V30. Correlation between bio-physic parameters and toxicity was used to establish a constraint model for avoiding RP. Results: Among the investigated cohort, clinical downstaging, complete pathological response, and 5-year overall survival rates were 59.6%, 40%, and 34.4%, respectively. Multivariate logistic regression analysis demonstrated that each individual set standardized uptake value ratios (SUVRs), neither pre- nor post-NACCRT, was not predictive. Interestingly, cutoff increments of 6.2% and 8.9% in SUVRs (delta-SUVR) in registered V20 and V27 regions were powerful predictors for acute and chronic RP, respectively. Conclusion: Spatial registration of metabolic and planning CT images with delta-radiomics analysis using fore-and-aft image sets can establish a unique bio-physic prediction model for avoiding RP in esophageal cancer patients receiving NACCRT.
原文 | 英語 |
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頁(從 - 到) | 6439-6451 |
頁數 | 13 |
期刊 | OncoTargets and Therapy |
卷 | 12 |
DOIs | |
出版狀態 | 已出版 - 2019 |
對外發佈 | 是 |
文獻附註
Publisher Copyright:© 2019 Hou et al.