Pérez Haas Y, Ludwig R, Dal Bello R, Tanadini-Lang S, Unkelbach J
Department of Radiation Oncology, University Hospital of Zurich, Zurich, Switzerland.
Phys Med Biol. 2023 Jan 19;68(3). doi: 10.1088/1361-6560/acafd4.
. Fractionated radiotherapy typically delivers the same dose in each fraction. Adaptive fractionation (AF) is an approach to exploit inter-fraction motion by increasing the dose on days when the distance of tumor and dose-limiting organs at risk (OAR) is large and decreasing the dose on unfavorable days. We develop an AF algorithm and evaluate the concept for patients with abdominal tumors previously treated at the MR-linac in 5 fractions.. Given daily adapted treatment plans, inter-fractional changes are quantified by sparing factorsdefined as the OAR-to-tumor dose ratio. The key problem of AF is to decide on the dose to deliver in fraction, givenand the dose delivered in previous fractions, but not knowing futures. Optimal doses that maximize the expected biologically effective dose in the tumor (BED) while staying below a maximum OAR BEDconstraint are computed using dynamic programming, assuming a normal distribution overwith mean and variance estimated from previously observed patient-specifics. The algorithm is evaluated for 16 MR-linac patients in whom tumor dose was compromised due to proximity of bowel, stomach, or duodenum.. In 14 out of the 16 patients, AF increased the tumor BEDcompared to the reference treatment that delivers the same OAR dose in each fraction. However, in 11 of these 14 patients, the increase in BEDwas below 1 Gy. Two patients with large sparing factor variation had a benefit of more than 10 Gy BEDincrease. For one patient, AF led to a 5 Gy BEDdecrease due to an unfavorable order of sparing factors.. On average, AF provided only a small increase in tumor BED. However, AF may yield substantial benefits for individual patients with large variations in the geometry.
分次放疗通常在每个分次中给予相同剂量。自适应分次放疗(AF)是一种通过在肿瘤与危及器官(OAR)距离较大的日子增加剂量,在不利日子减少剂量来利用分次间运动的方法。我们开发了一种AF算法,并对先前在MR直线加速器上分5次治疗的腹部肿瘤患者的这一概念进行了评估。给定每日适应性治疗计划,分次间变化通过定义为OAR与肿瘤剂量比的 sparing 因子进行量化。AF的关键问题是,在已知先前分次所给予剂量但不知道未来情况的前提下,决定本次分次要给予的剂量。假设根据先前观察到的患者特定数据估计的均值和方差服从正态分布,使用动态规划计算在保持低于最大OAR生物等效剂量(BED)约束的同时使肿瘤中预期生物等效剂量(BED)最大化的最佳剂量。对16例因肠道(肠)、胃或十二指肠接近而导致肿瘤剂量受限的MR直线加速器患者的该算法进行了评估。在这16例患者中的14例中,与每次分次给予相同OAR剂量的参考治疗相比,AF增加了肿瘤BED。然而在这14例患者中的11例中,BED的增加低于1 Gy。两名 sparing 因子变化较大的患者BED增加超过10 Gy。对于一名患者,由于 sparing 因子的不利顺序,AF导致BED降低了5 Gy。平均而言,AF仅使肿瘤BED有小幅增加。然而,AF可能会给几何形状变化较大的个体患者带来显著益处。