Hou Tien-Chi, Dai Kun-Yao, Wu Ming-Che, Hua Kai-Lung, Tai Hung-Chi, Huang Wen-Chien, Chen Yu-Jen
Department of Radiation Oncology, Mackay Memorial Hospital, Taipei, Taiwan.
Department of Nuclear Medicine, Mackay Memorial Hospital, Taipei, Taiwan.
Onco Targets Ther. 2019 Aug 13;12:6439-6451. doi: 10.2147/OTT.S205803. eCollection 2019.
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).
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 RT with 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 V, V, V, V, and V. Correlation between bio-physic parameters and toxicity was used to establish a constraint model for avoiding RP.
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 V and V regions were powerful predictors for acute and chronic RP, respectively.
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.
本研究整合了接受新辅助同步放化疗（NACCRT）的晚期胸段食管鳞状细胞癌患者的临床结局和放射组学，以建立一种预测放射性肺炎（RP）的新型约束模型。
我们对接受NACCRT的胸段晚期食管癌患者进行了回顾性研究。2013年至2018年期间，89例患者符合研究标准。分期检查和疗效评估包括正电子发射断层扫描/计算机断层扫描（PET/CT）和内镜超声检查。患者采用同步整合加量法接受放疗，肿瘤靶区剂量为48 Gy，共24次分割，选择性淋巴结区剂量为43.2 Gy。同时每周给予铂类化疗。使用CTCAE v4评估副作用。将NACCRT前后的2-氟-2-脱氧葡萄糖PET/CT图像与计划CT图像进行配准，以创建与RP相关区域在空间上匹配的剂量学参数感兴趣区，包括V、V、V、V和V。利用生物物理参数与毒性之间的相关性建立避免RP的约束模型。
在研究队列中，临床降期、完全病理缓解和5年总生存率分别为59.6%、40%和34.4%。多因素逻辑回归分析表明，无论NACCRT前后，单个标准化摄取值比率（SUVRs）均无预测价值。有趣的是，配准的V和V区域中SUVRs（Δ-SUVR）分别增加6.2%和8.9%是急性和慢性RP的有力预测指标。
通过前后图像集进行代谢和计划CT图像的空间配准及Δ-放射组学分析，可以为接受NACCRT的食管癌患者建立一种独特的生物物理预测模型以避免RP。
