Department of Medical Physic,Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.
Radiation Oncology Research Center, Cancer Institute; Department of Medical Physics and Medical Engineering, Faculty of Medicine, Tehran University of Medical Sciences, Tehran, Iran.
J Cancer Res Ther. 2020 Oct-Dec;16(6):1323-1330. doi: 10.4103/jcrt.JCRT_1149_19.
Different dose calculation algorithms (DCAs) predict different dose distributions for the same treatment. Awareness of optimal model parameters is vital for estimating normal tissue complication probability (NTCP) for different algorithms. The aim is to determine the NTCP parameter values for different DCAs in left-sided breast radiotherapy, using the Lyman-Kutcher-Burman (LKB) model.
First, the methodology recommended by International Atomic Energy Agency TEC-DOC 1583 was used to establish the accuracy of dose calculations of different DCAs including: Monte Carlo (MC) and collapsed cone algorithms implemented in Monaco, pencil beam convolution (PBC) and analytical anisotropic algorithm (AAA) implemented in Eclipse, and superposition and Clarkson algorithms implemented in PCRT3D treatment planning systems (TPSs). Then, treatment planning of 15 patients with left-sided breast cancer was performed by the mentioned DCAs and NTCP of the left-lung normal tissue were calculated for each patient individually, using the LKB model. For the PB algorithm, the NTCP parameters were taken from previously published values and new model parameters obtained for each DCA, using the iterative least squares methods.
For all cases and DCAs, NTCP computation with the same model parameters resulted in >15% deviation in NTCP values. The new NTCP model parameters were classified according to the algorithm type. Thus, the discrepancy of NTCP computations was reduced up to 5% after utilizing adjusted model parameters.
This paper confirms that the NTCP values for a given treatment type are different for the different DCAs. Thus, it is essential to introduce appropriate NTCP parameter values according to DCA adopted in TPS, to obtain a more precise estimation of lung NTCP. Hence, new parameter values, classified according to the DCAs, must be determined before introducing NTCP estimation in clinical practice.
不同的剂量计算算法（DCA）对同一治疗方案预测的剂量分布不同。了解最优模型参数对于估计不同算法的正常组织并发症概率（NTCP）至关重要。本研究旨在使用 Lyman-Kutcher-Burman（LKB）模型，确定左乳腺癌放疗中不同 DCA 的 NTCP 参数值。
首先，使用国际原子能机构 TEC-DOC 1583 建议的方法，评估不同 DCA 的剂量计算准确性，包括：Monte Carlo（MC）和在 Monaco 中实现的锥形束算法、在 Eclipse 中实现的笔形束卷积（PBC）和解析各向异性算法（AAA），以及在 PCRT3D 治疗计划系统（TPS）中实现的叠加和 Clarkson 算法。然后，对 15 例左乳腺癌患者进行上述 DCA 治疗计划，并使用 LKB 模型分别为每位患者计算左肺正常组织的 NTCP。对于 PB 算法，NTCP 参数取自先前发表的值，并使用迭代最小二乘法为每个 DCA 获得新的模型参数。
对于所有病例和 DCA，使用相同模型参数进行 NTCP 计算会导致 NTCP 值偏差超过 15%。根据算法类型对新的 NTCP 模型参数进行分类。因此，在使用调整后的模型参数后，NTCP 计算的差异可降低至 5%。
本研究证实，对于给定的治疗类型，不同的 DCA 会导致不同的 NTCP 值。因此，在 TPS 中采用适当的 DCA 引入合适的 NTCP 参数值对于更精确地估计肺 NTCP 非常重要。因此，在临床实践中引入 NTCP 估计之前，必须根据 DCA 确定新的分类参数值。
