Better correlation of outcomes with MC dose calculation
结果与 MC 剂量计算具有更好的相关性
基本信息
- 批准号:7244748
- 负责人:
- 金额:$ 23.83万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2005
- 资助国家:美国
- 起止时间:2005-03-01 至 2008-02-28
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
DESCRIPTION (provided by applicant): The clinical utility of the use of more accurate dose calculation algorithms for radiotherapy treatment planning has not yet been shown for many clinical sites. Although increasingly sophisticated and accurate dose calculation methods such as Monte Carlo and convolution/superposition have over the past decade become increasingly available for clinical study, direct study of the usefulness of the more accurate dose distributions obtained with these algorithms in terms of improving clinical patient outcomes has not been performed. In this study, we will use the clinical outcomes from two conformal therapy treatment studies (parotid-sparing in the head/neck and dose escalation for non-small cell lung cancer) to investigate whether dose distributions calculated with the more accurate Monte Carlo method will improve the correlation between the clinical patient outcomes and the calculated dose distributions. Since both clinical complications and local control for the two clinical studies are well-documented, and the full 3-D patient anatomy and treatment information is available for the patients on those protocols, these data provide a unique opportunity to evaluate the potential for clinical improvements due to improved dose calculations with a retrospective study. To accomplish the proposed goal, we must: (a) perform the necessary algorithmic verification against measurements made in phantoms that closely resemble the relevant clinical geometries, and (b) use the validated and accurate calculational method to re-evaluate the dose distributions delivered to patients treated on the conformal therapy trials performed in the head/neck and lung, and determine if the clinical outcomes (complications and local control) are better correlated with the more accurate calculational results than with the original results.
描述(由申请人提供):在许多临床场所尚未显示出使用更准确的剂量计算算法进行放射治疗治疗计划的临床效用。尽管蒙特卡洛和卷积/叠加等日益复杂和准确的剂量计算方法在过去十年中越来越多地用于临床研究,但尚未对通过这些算法获得的更准确的剂量分布在改善临床患者结果方面的有用性进行直接研究。在本研究中,我们将利用两项适形疗法治疗研究(头/颈部腮腺保留和非小细胞肺癌剂量递增)的临床结果来研究使用更准确的蒙特卡罗方法计算的剂量分布是否会改善临床患者结果和计算的剂量分布之间的相关性。由于这两项临床研究的临床并发症和局部控制都有详细记录,并且可以为这些方案中的患者提供完整的 3D 患者解剖结构和治疗信息,因此这些数据提供了一个独特的机会来评估由于回顾性研究改进的剂量计算而带来的临床改善的潜力。为了实现拟议的目标,我们必须:(a)对与相关临床几何形状非常相似的体模中进行的测量进行必要的算法验证,以及(b)使用经过验证的准确计算方法重新评估在头/颈和肺部进行的适形治疗试验中接受治疗的患者的剂量分布,并确定临床结果(并发症和局部控制)是否符合要求。 与原始结果相比,与更准确的计算结果的相关性更好。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
数据更新时间:{{ journalArticles.updateTime }}
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
数据更新时间:{{ journalArticles.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ monograph.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ sciAawards.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ conferencePapers.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ patent.updateTime }}
INDRIN Julian CHETTY其他文献
INDRIN Julian CHETTY的其他文献
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
{{ truncateString('INDRIN Julian CHETTY', 18)}}的其他基金
Better correlation of outcomes with MC dose calculation
结果与 MC 剂量计算具有更好的相关性
- 批准号:
7010103 - 财政年份:2005
- 资助金额:
$ 23.83万 - 项目类别:
Better correlation of outcomes with MC dose calculation
结果与 MC 剂量计算具有更好的相关性
- 批准号:
7189828 - 财政年份:2005
- 资助金额:
$ 23.83万 - 项目类别:
Better correlation of outcomes with MC dose calculation
结果与 MC 剂量计算具有更好的相关性
- 批准号:
6865114 - 财政年份:2005
- 资助金额:
$ 23.83万 - 项目类别:
Better correlation of outcomes with MC dose calculation
结果与 MC 剂量计算具有更好的相关性
- 批准号:
7630775 - 财政年份:2005
- 资助金额:
$ 23.83万 - 项目类别:
相似海外基金
Calculation and the Verification of the maximum electric power of Microbial Fuel Cells by Minimizing the Internal Resistance Using the Mathematical Model
微生物燃料电池内阻最小化最大电功率的数学模型计算与验证
- 批准号:
23K11483 - 财政年份:2023
- 资助金额:
$ 23.83万 - 项目类别:
Grant-in-Aid for Scientific Research (C)
Advancement of mathematical model and visualization method for cognition of relation between micro and macro phenomena
认知微观与宏观现象关系的数学模型和可视化方法的进展
- 批准号:
23K11128 - 财政年份:2023
- 资助金额:
$ 23.83万 - 项目类别:
Grant-in-Aid for Scientific Research (C)
Construction and analysis of a hybrid mathematical model describing the dynamics of bacterial cellular society
描述细菌细胞社会动态的混合数学模型的构建和分析
- 批准号:
23K03208 - 财政年份:2023
- 资助金额:
$ 23.83万 - 项目类别:
Grant-in-Aid for Scientific Research (C)
Mathematical Model-Based Optimization of CRT Response in Ischemia
基于数学模型的缺血 CRT 反应优化
- 批准号:
10734486 - 财政年份:2023
- 资助金额:
$ 23.83万 - 项目类别:
Noncontact Measurement of Multiple Sites of Multiple People Using Array Radar Signal Processing Based on Mathematical Model of Body Displacement
基于人体位移数学模型的阵列雷达信号处理非接触多人多部位测量
- 批准号:
23H01420 - 财政年份:2023
- 资助金额:
$ 23.83万 - 项目类别:
Grant-in-Aid for Scientific Research (B)
A mathematical model of colloidal membrane vesicle formation
胶体膜囊泡形成的数学模型
- 批准号:
567961-2022 - 财政年份:2022
- 资助金额:
$ 23.83万 - 项目类别:
Postgraduate Scholarships - Doctoral
Mathematical model to simulate SARS-CoV-2 infection within-host
模拟宿主内 SARS-CoV-2 感染的数学模型
- 批准号:
EP/W007355/1 - 财政年份:2022
- 资助金额:
$ 23.83万 - 项目类别:
Research Grant
Towards A Mathematical Model For Spacetimes With Multiple Histories
建立具有多重历史的时空数学模型
- 批准号:
577586-2022 - 财政年份:2022
- 资助金额:
$ 23.83万 - 项目类别:
University Undergraduate Student Research Awards
Mathematical model of internal standard selection criteria for accurate quantitative analysis
精确定量分析内标选择标准的数学模型
- 批准号:
22K10604 - 财政年份:2022
- 资助金额:
$ 23.83万 - 项目类别:
Grant-in-Aid for Scientific Research (C)
Mathematical model for quantitatively analysis the pathophysiological characteristics of mouse photoreceptor cell
定量分析小鼠感光细胞病理生理特征的数学模型
- 批准号:
22K20514 - 财政年份:2022
- 资助金额:
$ 23.83万 - 项目类别:
Grant-in-Aid for Research Activity Start-up














{{item.name}}会员




