Radioluminescence dosimetry solution for precision radiation therapy
用于精准放射治疗的放射发光剂量测定解决方案
基本信息
- 批准号:10418642
- 负责人:
- 金额:$ 47万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2018
- 资助国家:美国
- 起止时间:2018-06-01 至 2024-05-31
- 项目状态:已结题
- 来源:
- 关键词:3D PrintAlgorithmsAutomationBiocompatible Coated MaterialsCalibrationCancer PatientCharacteristicsClinicClinicalClinical assessmentsCollaborationsCollimatorCommunitiesComplexConsumptionCountryDataData AnalysesData CollectionDoseElectron BeamEnsureEnvironmentFeedbackFutureHigh-Dose Rate BrachytherapyImageImaging TechniquesIncidenceIndustrializationIntensity-Modulated RadiotherapyLightLinear Accelerator Radiotherapy SystemsMalignant NeoplasmsManualsMeasurementMeasuresMethodsModalityModernizationMonte Carlo MethodNatureOperative Surgical ProceduresOpticsPatientsPerformancePhotonsPositioning AttributeProceduresProcessRadiationRadiation AccidentsRadiation OncologyRadiation therapyResearchRoentgen RaysSafetySeriesSignal TransductionSoftware ToolsSurfaceSystemTechnologyTestingTherapeuticTimeWaterWorkanalytical toolbasecheckpoint therapychemotherapyclinical applicationclinical research siteclinically translatablecostdata acquisitiondesigndigitaldosimetryhuman errorimage guided radiation therapyimaging systemimprovedindexingnovelnovel strategiesoptical imagingpalliationprogramsproton therapyprototypequality assurancereal-time imagesresponsesuccesstherapy developmenttool
项目摘要
Radioluminescence dosimetry solution for precision radiation therapy
Project summary
Radiation therapy (RT) is an important modality for cancer management. Clinically, over 60% of all
cancer patients in the US receive RT each year as therapy or for palliation, or as an adjunct to surgery or
chemotherapy. There is also increased evidence that RT in combination with checkpoint immunotherapy
is highly effective in treating a subset of cancer patients. In practice, however, because of the invisible
nature of X-ray and its complex interaction process with media, how to ensure the geometric and
dosimetric accuracy of incident RT beams presents a significant challenge in precision RT and critically
determines the success of patient treatment. In this project, we form an academic-industrial collaboration
to investigate and create a clinically translatable solution for substantially improved RT quality assurance
(QA) using a radioluminescence imaging technique recently developed at Stanford. On the basis of our
promising preliminary work, we hypothesize that the accuracy, efficacy and cost of geometric and
dosimetric QA measurements of linear accelerators (LINACs) can be substantially improved with the use
of radioluminecsnce imaging strategy. With the proposed research, we anticipate that submillimeter
accuracy in geometric measurements and better than 3% accuracy in dosimetric measurements will be
readily achievable with orders of magnitude less time and effort as compared to current practice, removing
a major workflow bottleneck in clinical QA and reducing potential radiation treatment errors. This
research presents a first-of-its-kind machine QA strategy capable of instantaneously measuring complex
geometric and dosimetric characteristics of LINACs. If successful, the partnership will lead to a much
safer and more efficient radiation oncology practice, and enable patients to truly benefit from modern RT
modalities such as VMAT and IMRT and SBRT. In addition, the proposed strategy is quite general and
the system developed here will also be valuable for QA applications of other treatment modalities, such
as proton therapy and high-dose rate (HDR) brachytherapy.
用于精确放射治疗的放射发光剂量测量解决方案
项目摘要
放射治疗(RT)是癌症管理的重要方式。临床上,超过60%的
美国的癌症患者每年接受RT作为治疗或缓解,或作为手术的辅助手段,
化疗还有越来越多的证据表明,RT与检查点免疫疗法相结合,
对治疗一部分癌症患者非常有效。然而,实际上,由于无形的
X射线的性质及其与介质的复杂相互作用过程,如何保证X射线的几何
入射RT射束的剂量测定精度在精密RT中提出了重大挑战,
决定了患者治疗的成功。在这个项目中,我们形成了一个学术-工业合作
研究并创建一个临床上可翻译的解决方案,以大幅提高RT质量保证
(QA)利用斯坦福大学最近开发的放射发光成像技术。根据我们的
有希望的初步工作,我们假设,准确性,效率和成本的几何和
使用这种方法,可以大大改善直线加速器(LINAC)的剂量测定QA测量
放射性发光成像策略。根据这项研究,我们预计亚毫米波
几何测量的准确度和剂量测定测量的准确度将优于3%,
与目前的做法相比,很容易以数量级更少的时间和精力实现,
这是临床QA和减少潜在放射治疗错误的主要工作流程瓶颈。这
一项研究提出了一种能够即时测量复杂的机器QA策略,
LINAC的几何和剂量学特性。如果成功的话,这种伙伴关系将带来很大的
更安全,更有效的放射肿瘤学实践,使患者真正受益于现代RT
VMAT、IMRT和SBRT等模式。此外,拟议的战略相当笼统,
这里开发的系统对于其他治疗方式的QA应用也是有价值的,例如
如质子治疗和高剂量率(HDR)近距离放射治疗。
项目成果
期刊论文数量(1)
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 }}
Lei Xing其他文献
Lei Xing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('Lei Xing', 18)}}的其他基金
Improving the Safety and Quality of Eye Plaque Brachytherapy by Assembly with Intensity Modulated Loading
通过调强加载组装提高眼斑近距离治疗的安全性和质量
- 批准号:
10579754 - 财政年份:2023
- 资助金额:
$ 47万 - 项目类别:
Development of AI-Augmented quality assurance tools for radiation therapy
开发用于放射治疗的人工智能增强质量保证工具
- 批准号:
10558155 - 财政年份:2023
- 资助金额:
$ 47万 - 项目类别:
Leveraging deep learning for markerless motion management in radiation therapy
利用深度学习进行放射治疗中的无标记运动管理
- 批准号:
10617647 - 财政年份:2021
- 资助金额:
$ 47万 - 项目类别:
Leveraging deep learning for markerless motion management in radiation therapy
利用深度学习进行放射治疗中的无标记运动管理
- 批准号:
10374171 - 财政年份:2021
- 资助金额:
$ 47万 - 项目类别:
Dual Modality X-ray Luminescence CT for in vivo Cancer Imaging
用于体内癌症成像的双模态 X 射线发光 CT
- 批准号:
10530681 - 财政年份:2018
- 资助金额:
$ 47万 - 项目类别:
Radioluminescence dosimetry solution for precision radiation therapy
用于精准放射治疗的放射发光剂量测定解决方案
- 批准号:
10160833 - 财政年份:2018
- 资助金额:
$ 47万 - 项目类别:
Dual Modality X-ray Luminescence CT for in vivo Cancer Imaging
用于体内癌症成像的双模态 X 射线发光 CT
- 批准号:
10089148 - 财政年份:2018
- 资助金额:
$ 47万 - 项目类别:
Dual Modality X-ray Luminescence CT for in vivo Cancer Imaging
用于体内癌症成像的双模态 X 射线发光 CT
- 批准号:
10360435 - 财政年份:2018
- 资助金额:
$ 47万 - 项目类别:
DASSIM-RT and Compressed Sensing-Based Inverse Planning
DASSIM-RT 和基于压缩感知的逆规划
- 批准号:
9269990 - 财政年份:2014
- 资助金额:
$ 47万 - 项目类别:
DASSIM-RT and Compressed Sensing-Based Inverse Planning
DASSIM-RT 和基于压缩感知的逆规划
- 批准号:
8643085 - 财政年份:2014
- 资助金额:
$ 47万 - 项目类别:
相似海外基金
Design Automation Algorithms for High-Speed Integrated Circuits and Microsystems
高速集成电路和微系统的设计自动化算法
- 批准号:
RGPIN-2019-05341 - 财政年份:2022
- 资助金额:
$ 47万 - 项目类别:
Discovery Grants Program - Individual
Design Automation Algorithms for High-Speed Integrated Circuits and Microsystems
高速集成电路和微系统的设计自动化算法
- 批准号:
RGPIN-2019-05341 - 财政年份:2021
- 资助金额:
$ 47万 - 项目类别:
Discovery Grants Program - Individual
Design Automation Algorithms for High-Speed Integrated Circuits and Microsystems
高速集成电路和微系统的设计自动化算法
- 批准号:
RGPIN-2019-05341 - 财政年份:2020
- 资助金额:
$ 47万 - 项目类别:
Discovery Grants Program - Individual
Design Automation Algorithms for High-Speed Integrated Circuits and Microsystems
高速集成电路和微系统的设计自动化算法
- 批准号:
RGPIN-2019-05341 - 财政年份:2019
- 资助金额:
$ 47万 - 项目类别:
Discovery Grants Program - Individual
Design and Implementation of VLSI Design Automation Algorithms for Analog and Mix-signal ICs
模拟和混合信号 IC 的 VLSI 设计自动化算法的设计和实现
- 批准号:
532188-2018 - 财政年份:2018
- 资助金额:
$ 47万 - 项目类别:
University Undergraduate Student Research Awards
Electronic Design Automation Algorithms for Signal Integrity Analysis of High Speed Integrated Circuits
用于高速集成电路信号完整性分析的电子设计自动化算法
- 批准号:
RGPIN-2014-05429 - 财政年份:2018
- 资助金额:
$ 47万 - 项目类别:
Discovery Grants Program - Individual
Electronic Design Automation Algorithms for Signal Integrity Analysis of High Speed Integrated Circuits
用于高速集成电路信号完整性分析的电子设计自动化算法
- 批准号:
RGPIN-2014-05429 - 财政年份:2017
- 资助金额:
$ 47万 - 项目类别:
Discovery Grants Program - Individual
CAREER: Re-thinking Electronic Design Automation Algorithms for Secure Outsourced Integrated Circuit Fabrication
职业:重新思考安全外包集成电路制造的电子设计自动化算法
- 批准号:
1553419 - 财政年份:2016
- 资助金额:
$ 47万 - 项目类别:
Continuing Grant
Electronic Design Automation Algorithms for Signal Integrity Analysis of High Speed Integrated Circuits
用于高速集成电路信号完整性分析的电子设计自动化算法
- 批准号:
RGPIN-2014-05429 - 财政年份:2016
- 资助金额:
$ 47万 - 项目类别:
Discovery Grants Program - Individual
EAPSI: Algorithms for the Design Automation of Microfluidic Laboratories-on-a-chip
EAPSI:微流控片上实验室设计自动化算法
- 批准号:
1515406 - 财政年份:2015
- 资助金额:
$ 47万 - 项目类别:
Fellowship Award














{{item.name}}会员




