Samavati Navid, Velec Michael, Brock Kristy K
Institute of Biomaterials and Biomedical Engineering, University of Toronto, Toronto, Ontario M5G 2M9, Canada.
Institute of Medical Science, University of Toronto, Toronto, Ontario M5S 1A8, Canada.
Med Phys. 2016 Jan;43(1):233. doi: 10.1118/1.4938412.
Deformable image registration (DIR) plays an important role in dose accumulation, such as incorporating breathing motion into the accumulation of the delivered dose based on daily 4DCBCT images. However, it is not yet well understood how the uncertainties associated with DIR methods affect the dose calculations and resulting clinical metrics. The purpose of this study is to evaluate the impact of DIR uncertainty on the clinical metrics derived from its use in dose accumulation.
A biomechanical model based DIR method and a biomechanical-intensity-based hybrid method, which reduced the average registration error by 1.6 mm, were applied to ten lung cancer patients. A clinically relevant dose parameter [minimum dose to 0.5 cm(3) (Dmin)] was calculated for three dose scenarios using both algorithms. Dose scenarios included static (no breathing motion), predicted (breathing motion at the time of planning), and total accumulated (interfraction breathing motion). The relationship between the dose parameter and a combination of DIR uncertainty metrics, tumor volume, and dose heterogeneity of the plan was investigated.
Depending on the dose heterogeneity, tumor volume, and DIR uncertainty, in over 50% of the patients, differences greater than 1.0 Gy were observed in the Dmin of the tumor in the static dose calculation on exhale phase of the 4DCT. Such differences were due to the errors in propagating the tumor contours from the reference planning 4DCT phase onto a subsequent 4DCT phase using each DIR algorithm and calculating the dose on that phase. The differences in predicted dose were more subtle when breathing motion was modeled explicitly at the time of planning with only one patient exhibiting a greater than 1.0 Gy difference in Dmin. Dmin differences of up to 2.5 Gy were found in the total accumulated delivered dose due to difference in quantifying the interfraction variations. Such dose uncertainties could potentially be clinically significant.
Reductions in average uncertainty in DIR algorithms by 1.6 mm may have a clinically significant impact on the decision-making metrics used in dose planning and dose accumulation assessment.
可变形图像配准（DIR）在剂量累积中起着重要作用，例如将呼吸运动纳入基于每日4D CBCT图像的已交付剂量累积中。然而，与DIR方法相关的不确定性如何影响剂量计算和由此产生的临床指标，目前尚未得到充分理解。本研究的目的是评估DIR不确定性对其在剂量累积中使用所衍生的临床指标的影响。
将基于生物力学模型的DIR方法和基于生物力学-强度的混合方法应用于10例肺癌患者，该混合方法将平均配准误差降低了1.6毫米。使用这两种算法针对三种剂量方案计算了一个临床相关剂量参数[0.5 cm³的最小剂量（Dmin）]。剂量方案包括静态（无呼吸运动）、预测（计划时的呼吸运动）和总累积（分次间呼吸运动）。研究了剂量参数与DIR不确定性指标、肿瘤体积和计划的剂量异质性组合之间的关系。
根据剂量异质性、肿瘤体积和DIR不确定性，在超过50%的患者中，在4DCT呼气期的静态剂量计算中，肿瘤的Dmin观察到大于1.0 Gy的差异。这种差异是由于使用每种DIR算法将肿瘤轮廓从参考计划4DCT阶段传播到后续4DCT阶段并在该阶段计算剂量时的误差所致。当在计划时明确模拟呼吸运动时，预测剂量的差异更为细微，只有一名患者的Dmin差异大于1.0 Gy。由于在量化分次间变化方面存在差异，在总累积交付剂量中发现Dmin差异高达2.5 Gy。这种剂量不确定性可能具有临床意义。
DIR算法平均不确定性降低1.6毫米可能对剂量计划和剂量累积评估中使用的决策指标产生临床显著影响。
