Kim Minsun, Kotas Jakob, Rockhill Jason, Phillips Mark
Department of Radiation Oncology, University of Washington, Seattle, WA 98195, USA.
Department of Mathematics, University of Portland, Portland, OR 97203, USA.
Cancers (Basel). 2017 May 13;9(5):51. doi: 10.3390/cancers9050051.
This study investigates the feasibility of personalizing radiotherapy prescription schemes (treatment margins and fractional doses) for glioblastoma (GBM) patients and their potential benefits using a proliferation and invasion (PI) glioma model on phantoms. We propose a strategy to personalize radiotherapy prescription schemes by simulating the proliferation and invasion of the tumor in 2D according to the PI glioma model. We demonstrate the strategy and its potential benefits by presenting virtual cases, where the standard and personalized prescriptions were applied to the tumor. Standard prescription was assumed to deliver 46 Gy in 23 fractions to the initial, gross tumor volume (GTV₁) plus a 2 cm margin and an additional 14 Gy in 7 fractions to the boost GTV₂ plus a 2 cm margin. The virtual cases include the tumors with a moving velocity of 0.029 (slow-move), 0.079 (average-move), and 0.13 (fast-move) mm/day for the gross tumor volume (GTV) with a radius of 1 (small) and 2 (large) cm. For each tumor size and velocity, the margin around GTV₁ and GTV₂ was varied between 0-6 cm and 1-3 cm, respectively. Equivalent uniform dose (EUD) to normal brain was constrained to the EUD value obtained by using the standard prescription. Various linear dose policies, where the fractional dose is linearly decreasing, constant, or increasing, were investigated to estimate the temporal effect of the radiation dose on tumor cell-kills. The goal was to find the combination of margins for GTV₁ and GTV₂ and a linear dose policy, which minimize the tumor cell-surviving fraction (SF) under a normal tissue constraint. The efficacy of a personalized prescription was evaluated by tumor EUD and the estimated survival time. The personalized prescription for the slow-move tumors was to use 3.0-3.5 cm margins for GTV₁, and a 1.5 cm margin for GTV₂. For the average- and fast-move tumors, it was optimal to use a 6.0 cm margin for GTV₁ and then 1.5-3.0 cm margins for GTV₂, suggesting a course of whole brain therapy followed by a boost to a smaller volume. It was more effective to deliver the boost sequentially using a linearly decreasing fractional dose for all tumors. Personalized prescriptions led to surviving fractions of 0.001-0.465% compared to the standard prescription, and increased the tumor EUDs by 25.3-49.3% and estimated survival times by 7.6-22.2 months. Personalizing treatment margins based on the measured proliferative capacity of GBM tumor cells can potentially lead to significant improvements in tumor cell kill and related clinical outcomes.
本研究使用增殖与侵袭(PI)胶质瘤模型在体模上研究了为胶质母细胞瘤(GBM)患者个性化放疗处方方案(治疗边界和分次剂量)的可行性及其潜在益处。我们提出了一种根据PI胶质瘤模型在二维中模拟肿瘤增殖与侵袭来个性化放疗处方方案的策略。我们通过展示虚拟病例来论证该策略及其潜在益处,在这些虚拟病例中,将标准处方和个性化处方应用于肿瘤。假设标准处方是对初始大体肿瘤体积(GTV₁)给予46 Gy分23次照射,外加2 cm边界,对增强GTV₂给予额外14 Gy分7次照射,外加2 cm边界。虚拟病例包括大体肿瘤体积(GTV)半径为1(小)和2(大)cm、移动速度分别为0.029(慢速移动)、0.079(平均移动)和0.13(快速移动)mm/天的肿瘤。对于每种肿瘤大小和速度,GTV₁和GTV₂周围的边界分别在0 - 6 cm和1 - 3 cm之间变化。正常脑的等效均匀剂量(EUD)被限制在使用标准处方获得的EUD值。研究了各种线性剂量策略,即分次剂量线性递减、恒定或递增,以估计辐射剂量对肿瘤细胞杀伤的时间效应。目标是找到GTV₁和GTV₂的边界组合以及一种线性剂量策略,在正常组织限制下使肿瘤细胞存活分数(SF)最小化。通过肿瘤EUD和估计的生存时间评估个性化处方的疗效。慢速移动肿瘤的个性化处方是GTV₁使用3.0 - 3.5 cm边界,GTV₂使用1.5 cm边界。对于平均移动和快速移动肿瘤,GTV₁使用6.0 cm边界然后GTV₂使用1.5 - 3.0 cm边界是最优的,这表明先进行全脑治疗然后对较小体积进行增强照射。对所有肿瘤使用线性递减分次剂量顺序给予增强照射更有效。与标准处方相比,个性化处方导致存活分数为0.001 - 0.465%,并使肿瘤EUD增加25.3 - 49.3%,估计生存时间增加7.6 - 22.2个月。基于测量的GBM肿瘤细胞增殖能力个性化治疗边界可能会显著改善肿瘤细胞杀伤及相关临床结果。