Cai Weixing, Dhou Salam, Cifter Fulya, Myronakis Marios, Hurwitz Martina H, Williams Christopher L, Berbeco Ross I, Seco Joao, Lewis John H
Brigham and Women's Hospital, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA, 02115, USA.
Phys Med Biol. 2016 Jan 21;61(2):554-68. doi: 10.1088/0031-9155/61/2/554. Epub 2015 Dec 18.
The purpose of this research is to develop a 4DCBCT-based dose assessment method for calculating actual delivered dose for patients with significant respiratory motion or anatomical changes during the course of SBRT. To address the limitation of 4DCT-based dose assessment, we propose to calculate the delivered dose using time-varying ('fluoroscopic') 3D patient images generated from a 4DCBCT-based motion model. The method includes four steps: (1) before each treatment, 4DCBCT data is acquired with the patient in treatment position, based on which a patient-specific motion model is created using a principal components analysis algorithm. (2) During treatment, 2D time-varying kV projection images are continuously acquired, from which time-varying 'fluoroscopic' 3D images of the patient are reconstructed using the motion model. (3) Lateral truncation artifacts are corrected using planning 4DCT images. (4) The 3D dose distribution is computed for each timepoint in the set of 3D fluoroscopic images, from which the total effective 3D delivered dose is calculated by accumulating deformed dose distributions. This approach is validated using six modified XCAT phantoms with lung tumors and different respiratory motions derived from patient data. The estimated doses are compared to that calculated using ground-truth XCAT phantoms. For each XCAT phantom, the calculated delivered tumor dose values generally follow the same trend as that of the ground truth and at most timepoints the difference is less than 5%. For the overall delivered dose, the normalized error of calculated 3D dose distribution is generally less than 3% and the tumor D95 error is less than 1.5%. XCAT phantom studies indicate the potential of the proposed method to accurately estimate 3D tumor dose distributions for SBRT lung treatment based on 4DCBCT imaging and motion modeling. Further research is necessary to investigate its performance for clinical patient data.
本研究的目的是开发一种基于4D CBCT的剂量评估方法,用于计算在立体定向体部放疗(SBRT)过程中存在显著呼吸运动或解剖结构变化的患者的实际 delivered dose。为了解决基于4DCT的剂量评估的局限性,我们建议使用从基于4D CBCT的运动模型生成的随时间变化(“透视”)的3D患者图像来计算delivered dose。该方法包括四个步骤:(1)在每次治疗前,在治疗位置采集患者的4D CBCT数据,并基于此使用主成分分析算法创建患者特异性运动模型。(2)在治疗过程中,连续采集2D随时间变化的kV投影图像,并使用运动模型重建患者随时间变化的“透视”3D图像。(3)使用计划4DCT图像校正横向截断伪影。(4)计算3D透视图像集中每个时间点的3D剂量分布,并通过累积变形剂量分布来计算总有效3D delivered dose。使用六个带有肺部肿瘤且具有源自患者数据的不同呼吸运动的改良XCAT体模对该方法进行了验证。将估计剂量与使用真实XCAT体模计算的剂量进行比较。对于每个XCAT体模,计算得到的delivered肿瘤剂量值通常与真实值遵循相同的趋势,并且在大多数时间点差异小于5%。对于总体delivered dose,计算得到的3D剂量分布的归一化误差通常小于3%,肿瘤D95误差小于1.5%。XCAT体模研究表明了所提出方法基于4D CBCT成像和运动建模准确估计SBRT肺部治疗的3D肿瘤剂量分布的潜力。有必要进行进一步研究以调查其对临床患者数据的性能。