放射治疗正在从基于 CT 的计划转向 MRI 引导的计划，特别是对于软组织解剖学。这一新工作流程的一个重要要求是从 MRI 生成合成 CT (sCT)，以实现治疗剂量计算。因此，自动确定 CT 亨斯菲尔德单位 (HU) 不确定性可接受范围以避免剂量分布错误的方法是实现安全仅 MRI 放射治疗的关键一步。这项工作分析了 CT 扫描中引入的控制误差对前列腺癌患者的辐射剂量的影响。计算了 Spearman 相关系数，并按照 Morris 筛选方法进行了全局敏感性分析。这允许根据不同误差因素对等中心剂量的影响对不同误差因素进行分类。膀胱中的 sCT HU 估计误差似乎是影响最小的因素，并且 sCT 质量评估不应仅关注辐射目标周围的器官，因为其他软组织的误差可能会显着影响目标体积中的剂量。该方法将基于剂量和强度的指标联系起来，是定义准确剂量计划的 HU 不确定性可接受阈值的第一步。© 2023。作者。

Radiation therapy is moving from CT based to MRI guided planning, particularly for soft tissue anatomy. An important requirement of this new workflow is the generation of synthetic-CT (sCT) from MRI to enable treatment dose calculations. Automatic methods to determine the acceptable range of CT Hounsfield Unit (HU) uncertainties to avoid dose distribution errors is thus a key step toward safe MRI-only radiotherapy. This work has analysed the effects of controlled errors introduced in CT scans on the delivered radiation dose for prostate cancer patients. Spearman correlation coefficient has been computed, and a global sensitivity analysis performed following the Morris screening method. This allows the classification of different error factors according to their impact on the dose at the isocentre. sCT HU estimation errors in the bladder appeared to be the least influential factor, and sCT quality assessment should not only focus on organs surrounding the radiation target, as errors in other soft tissue may significantly impact the dose in the target volume. This methodology links dose and intensity-based metrics, and is the first step to define a threshold of acceptability of HU uncertainties for accurate dose planning.© 2023. The Author(s).