Carles Montserrat, Fechter Tobias, Radicioni Gianluca, Schimek-Jasch Tanja, Adebahr Sonja, Zamboglou Constantinos, Nicolay Nils H, Martí-Bonmatí Luis, Nestle Ursula, Grosu Anca L, Baltas Dimos, Mix Michael, Gkika Eleni
Department of Radiation Oncology, Division of Medical Physics, University Medical Center Freiburg, Faculty of Medicine, 79106 Freiburg, Germany.
German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Partner Site Freiburg of the German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany.
Cancers (Basel). 2021 Feb 15;13(4):814. doi: 10.3390/cancers13040814.
The aim of this study is to identify clinically relevant image feature (IF) changes during chemoradiation and evaluate their efficacy in predicting treatment response. Patients with non-small-cell lung cancer (NSCLC) were enrolled in two prospective trials (STRIPE, PET-Plan). We evaluated 48 patients who underwent static (3D) and retrospectively-respiratory-gated 4D PET/CT scans before treatment and a 3D scan during or after treatment. Our proposed method rejects IF changes due to intrinsic variability. The IF variability observed across 4D PET is employed as a patient individualized normalization factor to emphasize statistically relevant IF changes during treatment. Predictions of overall survival (OS), local recurrence (LR) and distant metastasis (DM) were evaluated. From 135 IFs, only 17 satisfied the required criteria of being normally distributed across 4D PET and robust between 3D and 4D images. Changes during treatment in the area-under-the-curve of the cumulative standard-uptake-value histogram (δ) within primary tumor discriminated (AUC = 0.87, Specificity = 0.78) patients with and without LR. The resulted prognostic model was validated with a different segmentation method (AUC = 0.83) and in a different patient cohort (AUC = 0.63). The quantification of tumor FDG heterogeneity by δ during chemoradiation correlated with the incidence of local recurrence and might be recommended for monitoring treatment response in patients with NSCLC.
本研究的目的是识别放化疗期间临床上相关的图像特征（IF）变化，并评估其预测治疗反应的效能。非小细胞肺癌（NSCLC）患者被纳入两项前瞻性试验（STRIPE、PET-Plan）。我们评估了48例患者，这些患者在治疗前接受了静态（3D）和回顾性呼吸门控4D PET/CT扫描，并在治疗期间或治疗后进行了一次3D扫描。我们提出的方法可排除因内在变异性导致的IF变化。将4D PET中观察到的IF变异性用作患者个体化的归一化因子，以强调治疗期间具有统计学意义的IF变化。评估总生存期（OS）、局部复发（LR）和远处转移（DM）的预测情况。在135个IF中，只有17个满足在4D PET中呈正态分布且在3D和4D图像之间具有稳健性的所需标准。原发肿瘤内累积标准摄取值直方图（δ）曲线下面积在治疗期间的变化区分了有无LR的患者（AUC = 0.87，特异性 = 0.78）。所得的预后模型在采用不同分割方法时得到验证（AUC = 0.83），并在不同患者队列中得到验证（AUC = 0.63）。放化疗期间通过δ对肿瘤FDG异质性进行量化与局部复发发生率相关，可能推荐用于监测NSCLC患者的治疗反应。
