Department of Obstetrics and Gynecology, West China Second University Hospital, Sichuan University, Chengdu, China.
Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, Chengdu, China.
J Healthc Eng. 2021 Nov 12;2021:7026098. doi: 10.1155/2021/7026098. eCollection 2021.
The prediction of an additional space for the dose sparing of organs at risk (OAR) in radiotherapy is still difficult. In this pursuit, the present study was envisaged to find out the factors affecting the bladder and rectum dosimetry of cervical cancer. Additionally, the relationship between the dose-volume histogram (DVH) parameters and the geometry and plan dose-volume optimization parameters of the bladder/rectum was established to develop the dose prediction models and guide the planning design for lower OARs dose coverage directly. Thirty volume modulated radiation therapy (VMAT) plans from cervical cancer patients were randomly chosen to build the dose prediction models. The target dose coverage was evaluated. Dose prediction models were established by univariate and multiple linear regression among the dosimetric parameters of the bladder/rectum, the geometry parameters (planning target volume (PTV), volume of bladder/rectum, overlap volume of bladder/rectum (OV), and overlapped volume as a percentage of bladder/rectum volume (OP)), and corresponding plan dose-volume optimization parameters of the nonoverlapping structures (the structure of bladder/rectum outside the PTV (NOS)). Finally, the accuracy of the prediction models was evaluated by tracking = (predicted dose-actual dose)/actual in additional ten VMAT plans. , , and of the bladder and rectum were found to be multiple linearly correlated with the relevant OP and corresponding dose-volume optimization parameters of NOS (regression > 0.99, < 0.001). The variations of these models were less than 0.5% for bladder and rectum. Percentage of bladder and rectum within the PTV and the dose-volume optimization parameters of NOS could be used to predict the dose quantitatively. The parameters of NOS as a limited condition could be used in the plan optimization instead of limiting the dose and volume of the entire OAR traditionally, which made the plan optimization more unified and convenient and strengthened the plan quality and consistency.
预测放疗中危及器官（OAR）的剂量节省的额外空间仍然具有挑战性。在这一追求中，本研究旨在找出影响宫颈癌膀胱和直肠剂量学的因素。此外，还建立了剂量-体积直方图（DVH）参数与膀胱/直肠的几何形状和计划剂量-体积优化参数之间的关系，以开发剂量预测模型，并直接指导较低 OAR 剂量覆盖的计划设计。从宫颈癌患者中随机选择 30 个容积调强放疗（VMAT）计划来建立剂量预测模型。评估了靶区剂量覆盖情况。通过膀胱/直肠的剂量学参数、几何形状参数（计划靶区（PTV）、膀胱/直肠体积、膀胱/直肠重叠体积（OV）和膀胱/直肠体积的重叠百分比（OP））、以及相应的非重叠结构的计划剂量-体积优化参数（PTV 外的膀胱/直肠结构（NOS））之间的单变量和多变量线性回归，建立了剂量预测模型。最后，通过跟踪 = （预测剂量-实际剂量）/实际剂量，在另外 10 个 VMAT 计划中评估了预测模型的准确性。膀胱和直肠的, , 和 与相关的 OP 和相应的 NOS 剂量-体积优化参数呈多线性相关（回归 > 0.99， < 0.001）。这些模型的变化对膀胱和直肠的影响小于 0.5%。膀胱和直肠的 PTV 内百分比和 NOS 的剂量-体积优化参数可用于定量预测剂量。NOS 的参数可以作为一个有限的条件用于计划优化，而不是传统上限制整个 OAR 的剂量和体积，这使得计划优化更加统一和方便，并增强了计划的质量和一致性。
