Department of Physics, University of Zurich, Zurich, Switzerland; Division of Radiation Oncology, Small Animal Department, Vetsuisse Faculty, University of Zurich, Zurich, Switzerland.
Department of Physics, University of Zurich, Zurich, Switzerland; Radiotherapie Hirslanden AG, Rain 34, Aarau, Switzerland.
Phys Med. 2024 Mar;119:103317. doi: 10.1016/j.ejmp.2024.103317. Epub 2024 Mar 1.
Classical radiation protocols are guided by physical dose delivered homogeneously over the target. Protocols are chosen to keep normal tissue complication probability (NTCP) at an acceptable level. Organs at risk (OAR) adjacent to the target volume could lead to underdosage of the tumor and a decrease of tumor control probability (TCP). The intent of our study was to explore a biology-based dose escalation: by keeping NTCP for OAR constant, radiation dose was to be maximized, allowing to result in heterogeneous dose distributions.
We used computed tomography datasets of 25 dogs with brain tumors, previously treated with 10x4 Gy (40 Gy to PTV D). We generated 3 plans for each patient: A) original treatment plan with homogeneous dose distribution, B) heterogeneous dose distribution with strict adherence to the same NTCPs as in A), and C) heterogeneous dose distribution with adherence to NTCP <5%. For plan comparison, TCPs and TCP equivalent doses (homogenous target dose which results in the same TCP) were calculated. To enable the use of the generalized equivalent uniform dose (gEUD) metric of the tumor target in plan optimization, the calculated TCP values were used to obtain the volume effect parameter a.
As intended, NTCPs for all OARs did not differ from plan A) to B). In plan C), however, NTCPs were significantly higher for brain (mean 2.5% (SD±1.9, 95%CI: 1.7,3.3), p<0.001), optic chiasm (mean 2.0% (SD±2.2, 95%CI: 1.0,2.8), p=0.010) compared to plan A), but no significant increase was found for the brainstem. For 24 of 25 of the evaluated patients, the heterogenous plans B) and C) led to an increase in target dose and projected increase in TCP compared to the homogenous plan A). Furthermore, the distribution of the projected individual TCP values as a function of the dose was found to be in good agreement with the population TCP model.
Our study is a first step towards risk-adaptive radiation dose optimization. This strategy utilizes a biologic objective function based on TCP and NTCP instead of an objective function based on physical dose constraints.
经典的放射治疗方案是基于均匀分布于靶区的物理剂量进行指导。方案的选择旨在将正常组织并发症概率（NTCP）保持在可接受的水平。与靶区相邻的危及器官（OAR）可能导致肿瘤剂量不足和肿瘤控制概率（TCP）下降。我们的研究目的是探索一种基于生物学的剂量递增：通过保持 OAR 的 NTCP 不变，最大限度地增加放射剂量，从而实现不均匀的剂量分布。
我们使用了 25 只患有脑肿瘤的狗的计算机断层扫描数据集，这些狗之前接受了 10x4 Gy（40 Gy 至 PTV D）的治疗。我们为每个患者生成了 3 个计划：A）原始治疗计划，剂量均匀分布；B）严格遵循与 A 相同的 NTCP 的不均匀剂量分布；C）遵循 NTCP<5%的不均匀剂量分布。为了进行计划比较，计算了 TCP 和 TCP 等效剂量（导致相同 TCP 的均匀靶区剂量）。为了能够在肿瘤靶区的计划优化中使用广义等效均匀剂量（gEUD）度量，使用计算出的 TCP 值获得体积效应参数 a。
如预期的那样，所有 OAR 的 NTCP 与计划 A）至 B）没有差异。然而，在计划 C）中，与计划 A）相比，脑（平均 2.5%（SD±1.9，95%CI：1.7，3.3），p<0.001）和视交叉（平均 2.0%（SD±2.2，95%CI：1.0，2.8），p=0.010）的 NTCP 显著升高，但脑干没有显著增加。在评估的 25 名患者中的 24 名中，与均匀计划 A）相比，不均匀计划 B）和 C）导致靶区剂量增加和预测 TCP 增加。此外，作为剂量函数的预测个体 TCP 值的分布与群体 TCP 模型吻合良好。
我们的研究是朝着风险适应放射治疗剂量优化迈出的第一步。该策略利用基于 TCP 和 NTCP 的生物学目标函数，而不是基于物理剂量约束的目标函数。
