Bio-physic constraint model using spatial registration of delta 18F-fluorodeoxyglucose positron emission tomography/computed tomography images for predicting radiation pneumonitis in esophageal squamous cell carcinoma patients receiving neoadjuvant chemoradiation

Tien Chi Hou, Kun Yao Dai, Ming Che Wu, Kai Lung Hua, Hung Chi Tai, Wen Chien Huang*, Yu Jen Chen

*此作品的通信作者

研究成果: 期刊稿件文章同行評審

6 引文 斯高帕斯(Scopus)

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
頁(從 - 到)6439-6451
頁數13
期刊OncoTargets and Therapy
12
DOIs
出版狀態已出版 - 2019
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Publisher Copyright:
© 2019 Hou et al.

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