Optimized IMRT Incorporating Beam Delivery

优化的 IMRT 结合射束传输

基本信息

批准号：
7071695
负责人：
JEFFREY Vincent SIEBERS
金额：
$ 26.07万
依托单位：
VIRGINIA COMMONWEALTH UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2003
资助国家：
美国
起止时间：
2003-07-01 至 2007-06-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/7071695
关键词：
behavioral /social science research tag clinical research health care quality health services research tag human data human tissue mathematical model medical records method development neoplasm /cancer radiation therapy outcomes research patient care management patient care planning patient safety /medical error radiation therapy dosage statistics /biometry

项目摘要

DESCRIPTION (provided by applicant): Intensity Modulated Radiation Therapy (IMRT) seeks to deliver highly conformal tumorcidal doses to selected target volumes while conformably avoiding nearby normal tissues and critical structures. IMRT assumes that the optimized planned doses can be precisely and accurately delivered to the patient and that the final plan is optimal relative to the desired treatment objectives. Yet, current IMRT planning systems use simplified fast dose calculations during plan optimization and divides optimization and plan delivery into separate processes. The simplified dose computations can result in dose prediction errors (DPEs), which are differences between actual and computed doses, of 10% or more, while optimization with algorithms that have DPEs and the transformation from optimized to deliverable parameter spaces lead to optimization convergence errors (OCEs). OCEs prevent the true optimal plan from being found and can result in critical structure doses that are as much as 20% greater than necessary. Since dose differences of 3%-5% can produce clinically detectable changes in response, DPEs and OCEs may significantly impact clinical outcome. The goals of this project are: (1) To develop accurate IMRT dose-calculation methods that reduce DPEs to clinically insignificant levels. Monte Carlo (MC) methods will be used to evaluate the sources and clinical impacts of DPEs caused by patient heterogeneities, incident fluence prediction, and patient set-up errors and to identify and develop methods to reduce IMRT dose-calculation errors to less than 2% for all patient cases. (2) To develop optimization processes that reduces OCEs to clinically insignificant levels. This will be achieved by incorporating algorithms, identified in goal 1, that accurately model radiation transport through the multi-leaf collimator and the patient into the IMRT optimization process. Such deliverable optimization will allow each intensity-modulated beam to partially compensate for the limitations of other beams and may result in significantly reduced doses to critical Istructures for the same planning target volume dose. (3) To improve the computational efficiency of accurate Ideliverable-optimization processes developed in goal 2 to make them clinically practical without compromising plan laccuracy or optimality. This will allow accurate, deliverable optimized plans to be used for routine clinical IMRT, Iwhere previously it was not practical due to the excessive calculation time required. The long-term objectives of' this project are to develop rapid, accurate IMRT dose calculation and optimization} methods that result in minimal dose prediction and optimization convergence errors, to use these more accurate IRMT to accumulate more reliable dose-response data, and to improve patient outcomes through more conformal.

描述（由申请人提供）：强度调节放射治疗（IMRT）试图向选定的靶标体积提供高度的形成型肿瘤剂量，同时避免附近的正常组织和关键结构。 IMRT假设可以精确，准确地将优化的计划剂量交付给患者，并且最终计划相对于所需的治疗目标是最佳的。但是，当前的IMRT计划系统在计划优化期间使用简化的快速剂量计算，并将优化和计划交付分为单独的过程。简化的剂量计算可能会导致剂量预测误差（DPE），这些错误是实际剂量和计算剂量之间的差异，分别为10％或更多，而使用具有DPE的算法以及从优化参数空间转换为优化的算法会导致优化融合误差（OCES）。 OCES防止找到真正的最佳计划，并可能导致临界结构剂量比必要大20％。由于3％-5％的剂量差异可以在反应中产生可检测到的可检测到的变化，因此DPE和OCE可能会显着影响临床结果。该项目的目标是：（1）开发准确的IMRT剂量计量方法，以将DPE降低到临床上不重要的水平。蒙特卡洛（MC）方法将用于评估由患者异质性，事件通知预测和患者设置错误引起的DPE的来源和临床影响，并确定和开发和开发方法，以将IMRT剂量分解错误降低到所有患者病例的不足2％。（2）开发优化过程，将OCE降低到临床上微不足道的水平。这将通过合并目标1中确定的算法来实现，从而准确地将辐射通过多叶准准直仪和患者建模为IMRT优化过程。这种可交付的优化将使每个强度调节的光束可以部分补偿其他梁的局限性，并可能导致相同计划目标体积剂量的关键西部剂量显着降低剂量。（3）提高目标2中开发的准确iDelable优化过程的计算效率，以使其在临床上实用，而不会损害计划的裸露性或最佳性。这将允许准确，可交付的优化计划用于常规的临床IMRT，由于所需的计算时间过多，因此以前不可行。 “该项目的长期目标是开发快速，准确的IMRT剂量计算和优化}方法，从而导致剂量预测和优化收敛误差最少，以使用这些更准确的IRMT来积累更可靠的剂量 - 反应数据，并通过更多的唯一形象来改善患者的结果。

项目成果

期刊论文数量（19）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

The effect of statistical noise on IMRT plan quality and convergence for MC-based and MC-correction-based optimized treatment plans.

DOI：
10.1088/1742-6596/102/1/012020
发表时间：
2008-04
期刊：
Journal of physics. Conference series
影响因子：
0
作者：
J. Siebers
通讯作者：
J. Siebers

Performance of a hybrid MC dose algorithm for IMRT optimization dose evaluation.

DOI：
10.1118/1.2745236
发表时间：
2007-07
期刊：
Medical physics
影响因子：
3.8
作者：
J. Siebers;I. Kawrakow;Viswanathan Ramakrishnan
通讯作者：
J. Siebers;I. Kawrakow;Viswanathan Ramakrishnan

Comparison of two methods to compute the absorbed dose to water for photon beams.

计算光子束对水的吸收剂量的两种方法的比较。

DOI：
10.1088/0031-9155/52/19/n02
发表时间：
2007
期刊：
Physics in medicine and biology
影响因子：
3.5
作者：
Gardner,JosephK;Siebers,JeffreyV;Kawrakow,Iwan
通讯作者：
Kawrakow,Iwan

Analytic IMRT dose calculations utilizing Monte Carlo to predict MLC fluence modulation.

利用蒙特卡罗分析 IMRT 剂量计算来预测 MLC 注量调节。

DOI：
10.1118/1.2178449
发表时间：
2006
期刊：
Medical physics
影响因子：
3.8
作者：
Mihaylov,IB;Lerma,FA;Wu,Y;Siebers,JV
通讯作者：
Siebers,JV

Monte Carlo-based dosimetry of head-and-neck patients treated with SIB-IMRT.

对接受 SIB-IMRT 治疗的头颈患者进行基于蒙特卡罗的剂量测定。

DOI：
10.1016/j.ijrobp.2005.09.049
发表时间：
2006
期刊：
International journal of radiation oncology, biology, physics.
影响因子：
0
作者：
Sakthi,Nirmal;Keall,Paul;Mihaylov,Ivaylo;Wu,Qiuwen;Wu,Yan;Williamson,JeffreyF;Schmidt-Ullrich,Rupert;Siebers,JeffreyV
通讯作者：
Siebers,JeffreyV