Computational Tools for Adaptive Radiation Therapy
Computational Tools for Adaptive Radiation Therapy
批准号:
8192932
负责人:
Lei Xing
金额:
$23.63万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2009
资助国家:
美国
项目状态:
已结题
起止时间:
2009-07-16 至 2013-06-30
关键词:
AccountingAdverse effectsAlgorithmsAnatomic ModelsAnatomyCancer PatientCancer SurvivorClinicClinicalClinical TrialsComplicationComputational ScienceDataDecision MakingDiseaseDoseEnsureFeedbackFinancial compensationFoundationsGoalsHead and neck structureImageImaging DeviceIndividualIntensity-Modulated RadiotherapyInvestigationLeadLinear Accelerator Radiotherapy SystemsMapsMedicalMedical ImagingMethodsModelingModificationMotionMovementNatureNormal tissue morphologyOrganPatient CarePatientsPerformancePhasePhysiciansPhysicsPhysiologicalPositioning AttributeProbabilityProceduresProcessQuality of lifeRadiationRadiation OncologistRadiation OncologyRadiation therapyRectal CancerResearchResearch InfrastructureResearch PersonnelRetinal ConeSeriesSimulateStructureSystemTechniquesTechnologyTestingTissuesUncertaintyUnited States National Institutes of HealthWorkX-Ray Computed Tomographybasecancer cellcomputerized toolscone-beam computed tomographydigitalelectron densityexperienceimage guided therapyimage registrationimprovedinnovationinterestneoplasticnext generationnovelpopulation basedpublic health relevancereconstructionresponsesimulationsuccesstheoriestooltreatment planningtumor
中文摘要
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英文摘要
DESCRIPTION (provided by applicant): Interfractional patient setup uncertainty and anatomy change are widely recognized as one of the major limiting factors for maximum exploitation of modern radiation therapy techniques, such as intensity modulated radiation therapy (IMRT). Up to this point, almost all research efforts have been focused on reducing the adverse effects of organ movement/deformation by attempting to reposition the patient more accurately. Clinically, IMRT treatment plan optimization and dose delivery are still two decoupled steps, with the geometric uncertainties taking into account by population based margins encompassing the clinical target volume, which significantly compromises the success of radiation therapy. The recent advent of onboard volumetric imaging device provides a valuable tool for us to obtain 3D or even 4D geometric model of the patient in the treatment position and allows adaptive modification of IMRT plan during a course of treatment. The objective of this project is to develop enabling computational tools for image guided adaptive radiation therapy (IGART) and to show the potential clinical impact of the new paradigm of IGART. The underlying hypothesis of this work is that IGART will greatly reduce the uncertainty in beam targeting and provide substantially improved dose distributions required to achieve greater local tumor control while reducing the probability of normal tissue complications. Specific aims of the project are (1) to establish a cone beam CT (CBCT)-based dose reconstruction method for fractional and cumulative dose calculations; (2) to setup a dynamic closed-loop framework of IGART planning; and (3) to demonstrate the potential clinical impact of the proposed IGART. Execution of the project will demonstrate that the IGART is achievable and determine the level of improvement of IGART over the conventional IMRT. Given its significant promise in optimally compensating for interfractional geometric uncertainties as well as dosimetric errors incurred in previous fractions, successful completion of the project should lead to substantial improvement in cancer patient care.
PUBLIC HEALTH RELEVANCE: Currently, a radiation therapy treatment plan is produced based on the patient's anatomical model from planning CT images acquired a few days or even weeks before treatment. Numerous investigations have revealed that there can be significant changes in the patient anatomy from day to day due to patient positioning uncertainties and physiologic and clinical factors. This project is aimed to develop enabling computational tools for a new paradigm of radiation therapy, referred to as image-guided adaptive radiation therapy (IGART), to eliminate the influence of inter-fractional anatomy change. IGART improves current radiation therapy by adaptively adjusting the beam parameters according to volumetric imaging data acquired with the patient in the actual treatment position.
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财政年份:2018
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财政年份:2018
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依托单位:
DASSIM-RT and Compressed Sensing-Based Inverse Planning
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批准号:9269990
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项目类别:
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资助金额:$45.43万
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财政年份:2014
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负责人:Lei Xing
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依托单位:
DASSIM-RT and Compressed Sensing-Based Inverse Planning
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项目类别:
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财政年份:2014
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负责人:Lei Xing
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依托单位:
Computational Tools for Next Generation Volumetric Cone Beam Computed Tomography
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项目类别:
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资助金额:$54.08万
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依托单位:
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项目类别:
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资助金额:$50.7万
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财政年份:2013
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依托单位:
Computational Tools for Next Generation Volumetric Cone Beam Computed Tomography
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项目类别:
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资助金额:$50.19万
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财政年份:2013
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依托单位:
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依托单位:
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负责人:Lei Xing
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依托单位:
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依托单位:
Computational Tools for Adaptive Radiation Therapy
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批准号:7894736
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项目类别:
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资助金额:$24.36万
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财政年份:2009
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负责人:Lei Xing
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依托单位:
Computational Tools for Adaptive Radiation Therapy
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批准号:8300169
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项目类别:
-
资助金额:$23.63万
-
财政年份:2009
-
负责人:Lei Xing
-
依托单位:
Computational Tools for Adaptive Radiation Therapy
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批准号:7728376
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项目类别:
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资助金额:$24.36万
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财政年份:2009
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负责人:Lei Xing
-
依托单位:
海外基金