To quantify deformable image registration errors in IGRT

描述（由申请人提供）：本研究的目的是开发一种新的系统性方法，以识别图像引导放射治疗中的变形图像配准（RDR）错误和相关剂量测定后果。剂量重建和剂量重建过程的准确性对于确定输送给患者的剂量是否与计划的剂量分布一致至关重要。随着我们开始减少计划裕度，基于日常成像提供的保证，以及实时靶向设备（例如电磁信标）的引入，肿瘤（和周围器官）变形的影响可能成为肿瘤准确靶向的限制因素。在这样的情况下，并且无论应用在线还是离线自适应校正，图像配准和剂量重建过程的准确性在评估递送到肿瘤和周围健康组织的实际剂量时变得至关重要。本申请的长期目标是确保每名患者的治疗计划都经过适当调整，以考虑放射性位移和剂量相关误差，提高靶向准确性并提供健康组织的最佳保留。（1a）建立一种基于不平衡力和能量概念的新的弹性模型，以量化可变形图像配准中的位移矢量场（DVF）误差，并根据可变形体模中的测量结果验证结果;（1b）将该方法应用于先前使用每日CBCT成像治疗的前列腺癌和肺癌患者的大量图像数据集;（2）使用三线性剂量插值和基于蒙特卡罗的能量映射进行剂量重建，并量化患者图像数据集上的剂量测定误差;（3）开发补偿基于DVF的位移误差的剂量误差的方法;（3a）使用优化过程开发剂量重建系统，以通过结合基于量化的基于DVF的剂量误差的反馈来最小化剂量误差;（3b）将剂量测定误差量化为计划裕度的函数，并制定裕度配方以说明DVF-基于每日锥形束CT（CBCT）图像与模拟CT图像配准的相关剂量误差，用于回顾性治疗的一大组前列腺癌和肺癌患者。

DESCRIPTION (provided by applicant): The purpose of this study is to develop a novel and systematic method to identify deformable image registration (DIR) errors and related dosimetric consequences in image-guided radiotherapy. The accuracy of the DIR and dose reconstruction process is central to determining whether or not the dose delivered to the patient is in agreement with the planned dose distribution. As we begin to reduce planning margins, based on the assurance afforded by daily imaging, and the introduction of real-time targeting devices (e.g. electromagnetic beacons), the impact of tumor (and surrounding organ) deformation may become a limiting factor in accurate targeting of the tumor. Under such circumstances, and regardless of whether on-line or off- line, adaptive corrections are applied, the accuracy of the image registration and dose reconstruction process becomes critical in evaluating the actual dose delivered to the tumor and surrounding healthy tissues. The long-term objective of this application is to ensure that each patient's treatment plan is properly adapted to account for DIR displacement and dose-related errors, to improve targeting accuracy and provide optimal sparing of healthy tissues. To accomplish the goals of this proposal, we will: (1a) Develop a novel elasticity-based model, founded on the concepts of unbalanced forces and energies, to quantify displacement vector field (DVF) errors in deformable image registration, and verify the results against measurements in a deformable phantom; (1b) Apply the method to a large number image datasets of prostate and lung cancer patients previously treated using daily CBCT imaging; (2) Perform dose reconstruction using tri-linear dose interpolation and Monte Carlo-based energy mapping and quantify the resulting dosimetric errors on the patient image datasets; (3) Develop methods to compensate for dose errors from DVF-based displacement errors; (3a) Develop a dose reconstruction system using an optimization process to minimize errors in the dose by incorporating feedback based on the quantified DVF-based dose errors; (3b) Quantify the dosimetric errors as a function of planning margin and develop a margin recipe to account for DVF-related dose errors based on registrations of daily cone-beam CT (CBCT) images with simulation CT images for a large group of prostate and lung cancer patients treated retrospectively.