To quantify deformable image registration errors in IGRT

量化 IGRT 中的可变形图像配准误差

• 批准号: 8677763
• 负责人: Hualiang Zhong
• 金额: $ 28.6万
• 依托单位: HENRY FORD HEALTH SYSTEM
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-07-01 至 2016-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8677763
• 关键词: 4D Imaging; Accounting; Agreement; Algorithms; Biological; Cancer Patient; Caring; Clinic; Computer Simulation; Cone; Data Set; Devices; Dose; Elasticity; Electromagnetics; Ensure; Feedback; Goals; Image; Investigation; Malignant neoplasm of lung; Malignant neoplasm of prostate; Manuals; Maps; Measurement; Mechanics; Methods; Modeling; Monte Carlo Method; Organ; Patients; Procedures; Process; Radiation therapy; Recipe; Simulate; System; Techniques; Therapeutic; Time; Tissues; X-Ray Computed Tomography; base; cohort; cone-beam computed tomography; design; image registration; improved; indexing; novel; novel strategies; population based; process optimization; reconstruction; research study; simulation; theories; tool; tool development; treatment planning; tumor; vector

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.

描述（由申请人提供）：本研究的目的是开发一种新颖的系统方法来识别图像引导放射治疗中的变形图像配准（DIR）错误和相关剂量测定结果。 DIR 和剂量重建过程的准确性对于确定给予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余量，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精确靶向的限制因素。在这种情况下，无论是在线还是离线，应用自适应校正，图​​像配准和剂量重建过程的准确性对于评估递送到肿瘤和周围健康组织的实际剂量变得至关重要。该应用的长期目标是确保每个患者的治疗计划都能够适当调整，以考虑 DIR 位移和剂量相关误差，以提高靶向准确性并提供健康组织的最佳保护。为了实现本提案的目标，我们将：（1a）开发一种基于不平衡力和能量概念的新颖的基于弹性的模型，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图进行剂量重建，并量化患者图像数据集上产生的剂量测定误差； (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，通过结合基于量化 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，并根据对一大组回顾性治疗的前列腺癌和肺癌患者的每日锥形束 CT (CBCT) 图像与模拟 CT 图像的配准，制定裕度配方来解释 DVF 相关的剂量误差。

项目成果

4-Dimensional computed tomography-based ventilation and compliance images for quantification of radiation-induced changes in pulmonary function.

基于 4 维计算机断层扫描的通气和顺应性图像，用于量化辐射引起的肺功能变化。

• DOI: 10.1111/1754-9485.12881
• 发表时间: 2019
• 期刊: Journal of medical imaging and radiation oncology
• 影响因子: 1.6
• 作者: Sharifi,Hoda;Brown,Stephen;McDonald,GaryC;Chetty,IndrinJ;Zhong,Hualiang
• 通讯作者: Zhong,Hualiang

Kinetic modeling of tumor regression incorporating the concept of cancer stem-like cells for patients with locally advanced lung cancer.

针对局部晚期肺癌患者，结合癌症干细胞样细胞概念的肿瘤消退动力学模型。

• DOI: 10.1186/s12976-018-0096-7
• 发表时间: 2018
• 期刊: Theoretical biology & medical modelling
• 作者: Zhong,Hualiang;Brown,Stephen;Devpura,Suneetha;Li,XAllen;Chetty,IndrinJ
• 通讯作者: Chetty,IndrinJ

Generation of a novel phase-space-based cylindrical dose kernel for IMRT optimization.

• DOI: 10.1118/1.3700403
• 发表时间: 2012-05
• 期刊: Medical physics
• 影响因子: 3.8
• 作者: H. Zhong;I. Chetty

An assessment of PTV margin based on actual accumulated dose for prostate cancer radiotherapy.

基于前列腺癌放疗实际累积剂量的 PTV 裕度评估。

• DOI: 10.1088/0031-9155/58/21/7733
• 发表时间: 2013
• 期刊: Physics in medicine and biology
• 影响因子: 3.5
• 作者: Wen,Ning;Kumarasiri,Akila;Nurushev,Teamour;Burmeister,Jay;Xing,Lei;Liu,Dezhi;Glide-Hurst,Carri;Kim,Jinkoo;Zhong,Hualiang;Movsas,Benjamin;Chetty,IndrinJ
• 通讯作者: Chetty,IndrinJ

Evaluation of the deformation and corresponding dosimetric implications in prostate cancer treatment.

• DOI: 10.1088/0031-9155/57/17/5361
• 发表时间: 2012-09-07
• 期刊: Physics in medicine and biology
• 影响因子: 3.5
• 作者: Wen N;Glide-Hurst C;Nurushev T;Xing L;Kim J;Zhong H;Liu D;Liu M;Burmeister J;Movsas B;Chetty IJ
• 通讯作者: Chetty IJ