Institute of Radiation Protection, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, 85764, Germany.
Department of Medical Physics, Ludwig-Maximilians-Universität München (LMU Munich), Garching, 85748, Germany.
Med Phys. 2018 Jul;45(7):3391-3403. doi: 10.1002/mp.12984. Epub 2018 Jun 8.
Variance-based sensitivity analysis (SA) is described and applied to the radiation dosimetry model proposed by the Committee on Medical Internal Radiation Dose (MIRD) for the organ-level absorbed dose calculations in nuclear medicine. The uncertainties in the dose coefficients thus calculated are also evaluated.
A Monte Carlo approach was used to compute first-order and total-effect SA indices, which rank the input factors according to their influence on the uncertainty in the output organ doses. These methods were applied to the radiopharmaceutical (S)-4-(3- F-fluoropropyl)-L-glutamic acid ( F-FSPG) as an example. Since F-FSPG has 11 notable source regions, a 22-dimensional model was considered here, where 11 input factors are the time-integrated activity coefficients (TIACs) in the source regions and 11 input factors correspond to the sets of the specific absorbed fractions (SAFs) employed in the dose calculation. The SA was restricted to the foregoing 22 input factors. The distributions of the input factors were built based on TIACs of five individuals to whom the radiopharmaceutical F-FSPG was administered and six anatomical models, representing two reference, two overweight, and two slim individuals. The self-absorption SAFs were mass-scaled to correspond to the reference organ masses.
The estimated relative uncertainties were in the range 10%-30%, with a minimum and a maximum for absorbed dose coefficients for urinary bladder wall and heart wall, respectively. The applied global variance-based SA enabled us to identify the input factors that have the highest influence on the uncertainty in the organ doses. With the applied mass-scaling of the self-absorption SAFs, these factors included the TIACs for absorbed dose coefficients in the source regions and the SAFs from blood as source region for absorbed dose coefficients in highly vascularized target regions. For some combinations of proximal target and source regions, the corresponding cross-fire SAFs were found to have an impact.
Global variance-based SA has been for the first time applied to the MIRD schema for internal dose calculation. Our findings suggest that uncertainties in computed organ doses can be substantially reduced by performing an accurate determination of TIACs in the source regions, accompanied by the estimation of individual source region masses along with the usage of an appropriate blood distribution in a patient's body and, in a few cases, the cross-fire SAFs from proximal source regions.
描述了基于方差的敏感性分析（SA）方法，并将其应用于委员会对医学内照射剂量（MIRD）提出的器官水平吸收剂量计算的辐射剂量模型。还评估了由此计算得出的剂量系数的不确定性。
使用蒙特卡罗方法计算一阶和总效应 SA 指数，根据它们对器官剂量不确定性的影响对输入因素进行排序。将这些方法应用于放射性药物（S）-4-（3-F-氟丙基）-L-谷氨酸（ F-FSPG）作为一个例子。由于 F-FSPG 有 11 个显著的源区，因此在这里考虑了一个 22 维模型，其中 11 个输入因素是源区的时间积分活度系数（TIACs），11 个输入因素对应于剂量计算中使用的一组特定吸收分数（SAFs）。SA 仅限于上述 22 个输入因素。输入因素的分布是基于向五个接受放射性药物 F-FSPG 的个体和六个解剖模型（代表两个参考个体、两个超重个体和两个苗条个体）的 TIACs 构建的。自我吸收 SAFs 被质量缩放以对应于参考器官的质量。
估计的相对不确定度在 10%-30%之间，对于膀胱壁和心壁的吸收剂量系数，分别具有最小值和最大值。应用的全局基于方差的 SA 使我们能够识别对器官剂量不确定性影响最大的输入因素。通过应用自我吸收 SAFs 的质量缩放，这些因素包括源区吸收剂量系数的 TIACs 和作为高血管化靶区吸收剂量系数源区的血液 SAFs。对于一些近端靶区和源区的组合，发现对应的交叉火力 SAFs 有影响。
全局基于方差的 SA 首次应用于内部剂量计算的 MIRD 方案。我们的研究结果表明，通过准确确定源区的 TIACs，同时估计个体源区的质量，并在患者体内使用适当的血液分布，在少数情况下，使用来自近端源区的交叉火力 SAFs，可以大大降低计算得出的器官剂量的不确定性。
