Polan Daniel F, Feng Mary, Lawrence Theodore S, Ten Haken Randall K, Brock Kristy K
Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan.
Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan; Department of Radiation Oncology, University of California, San Francisco, California.
Int J Radiat Oncol Biol Phys. 2017 Nov 15;99(4):1004-1012. doi: 10.1016/j.ijrobp.2017.06.2455. Epub 2017 Jun 27.
Understanding anatomic and functional changes in the liver resulting from radiation therapy is fundamental to the improvement of normal tissue complication probability models needed to advance personalized medicine. The ability to link pretreatment and posttreatment imaging is often compromised by significant dose-dependent volumetric changes within the liver that are currently not accounted for in deformable image registration (DIR) techniques. This study investigated using delivered dose, in combination with other patient factors, to biomechanically model longitudinal changes in liver anatomy for follow-up care and re-treatment planning.
Population models describing the relationship between dose and hepatic volume response were produced using retrospective data from 33 patients treated with focal radiation therapy. A DIR technique was improved by implementing additional boundary conditions associated with the dose-volume response in series with a previously developed biomechanical DIR algorithm. Evaluation of this DIR technique was performed on computed tomography imaging from 7 patients by comparing the model-predicted volumetric change within the liver with the observed change, tracking vessel bifurcations within the liver through the deformation process, and then determining target registration error between the predicted and identified posttreatment bifurcation points.
Evaluation of the proposed DIR technique showed that all lobes were volumetrically deformed to within the respective contour variability of each lobe. The average target registration error achieved was 7.3 mm (2.8 mm left-right and anterior-posterior and 5.1 mm superior-inferior), with the superior-inferior component within the average limiting slice thickness (6.0 mm). This represented a significant improvement (P<.01, Wilcoxon test) over the application of the previously published biomechanical DIR algorithm (10.9 mm).
This study demonstrates the feasibility of implementing dose-driven volumetric response in deformable registration, enabling improved accuracy of modeling liver anatomy changes, which could allow for improved dose accumulation, particularly for patients who require additional liver radiation therapy.
了解放射治疗引起的肝脏解剖和功能变化是改进推进个性化医疗所需的正常组织并发症概率模型的基础。肝脏内显著的剂量依赖性体积变化常常会影响治疗前和治疗后成像的关联能力，而目前的可变形图像配准（DIR）技术并未考虑这些变化。本研究探讨结合已交付剂量和其他患者因素，对肝脏解剖结构的纵向变化进行生物力学建模，以用于后续护理和再治疗计划。
利用33例接受局部放射治疗患者的回顾性数据，建立了描述剂量与肝脏体积反应之间关系的群体模型。通过将与剂量-体积反应相关的附加边界条件与先前开发的生物力学DIR算法串联实施，对DIR技术进行了改进。对7例患者的计算机断层扫描成像进行了该DIR技术的评估，方法是将模型预测的肝脏体积变化与观察到的变化进行比较，在变形过程中跟踪肝脏内的血管分支，然后确定预测的和识别出的治疗后分支点之间的目标配准误差。
对所提出的DIR技术的评估表明，所有肝叶的体积变形均在各肝叶各自的轮廓变化范围内。实现的平均目标配准误差为7.3毫米（左右方向和前后方向为2.8毫米，上下方向为5.1毫米），上下方向的误差在平均极限切片厚度（6.0毫米）范围内。与先前发表的生物力学DIR算法（10.9毫米）相比，这有显著改善（P<0.01，Wilcoxon检验）。
本研究证明了在可变形配准中实施剂量驱动的体积反应的可行性，提高了肝脏解剖结构变化建模的准确性，这有助于改进剂量累积，特别是对于需要额外肝脏放射治疗的患者。
