Ehler Eric D, Tomé Wolfgang A
Department of Medical Physics, University of Wisconsin - Madison, WI, USA.
Radiother Oncol. 2008 Sep;88(3):319-25. doi: 10.1016/j.radonc.2008.07.004. Epub 2008 Aug 12.
To compare 4D-dose distributions for IMRT planning on three data sets: a single 4D-CT phase, a 4D-CT phase with a density override to the tumor motion envelope (TME) volume, and the average intensity projection (AIP).
Eight planning cases were considered. IMRT inverse planning optimization was performed on each of the three data set types, for each case considered. The plans were then applied to all ten phases of the associated 4D-CT data set. The dose to the GTV in each breathing phase was compared to the TME dose from the optimized dose distribution, as well as the GTV dose determined from a model-based deformable registration algorithm.
IMRT optimization on a single 3D data set resulted in a greater equivalent uniform dose (EUD) to the GTV when applied to a 4D-CT data set than the EUD for the TME in the optimized plan. The difference was up to 5.5Gy in one case. For all cases and planning techniques considered, a maximum difference of 0.3Gy in the NTDmean to the healthy lung throughout the breathing cycle was found.
For tumors located in the periphery of the lung, optimization on the AIP image resulted in a more uniform GTV dose throughout the breathing cycle. Averages in GTV EUD and healthy lung NTDmean taken over all the breathing phases were found to be in agreement with the dose effect parameters obtained from model-based deformable registration algorithms. All planning methods yielded GTV EUD values that were larger than the prescribed dose when the full 4D data set was considered.
比较在三个数据集上进行调强放射治疗(IMRT)计划的4D剂量分布:单个4D-CT时相、对肿瘤运动包络(TME)体积进行密度覆盖的4D-CT时相以及平均强度投影(AIP)。
考虑了8个计划病例。对每种类型的三个数据集分别针对每个考虑的病例进行IMRT逆向计划优化。然后将计划应用于相关4D-CT数据集的所有十个时相。将每个呼吸时相的大体肿瘤体积(GTV)剂量与优化剂量分布中的TME剂量以及通过基于模型的可变形配准算法确定的GTV剂量进行比较。
当将单个3D数据集上的IMRT优化应用于4D-CT数据集时,与优化计划中TME的等效均匀剂量(EUD)相比,GTV的EUD更高。在一个病例中差异高达5.5Gy。对于所有考虑的病例和计划技术,在整个呼吸周期中健康肺的归一化总剂量(NTDmean)的最大差异为0.3Gy。
对于位于肺周边的肿瘤,在AIP图像上进行优化可在整个呼吸周期中产生更均匀的GTV剂量。发现在所有呼吸时相上GTV的EUD平均值和健康肺的NTDmean与通过基于模型的可变形配准算法获得的剂量效应参数一致。当考虑完整的4D数据集时,所有计划方法产生的GTV EUD值均大于规定剂量。