DASSIM-RT and Compressed Sensing-Based Inverse Planning
DASSIM-RT and Compressed Sensing-Based Inverse Planning
批准号:
9269990
负责人:
Lei Xing
金额:
$45.43万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2014
资助国家:
美国
项目状态:
已结题
起止时间:
2014-06-01 至 2019-05-31
关键词:
AddressAlgorithmsCancer PatientClinicalCollimatorComplexDevelopmentDisciplineDoseDose-RateEquilibriumFoundationsFutureGenerationsGoalsIntensity-Modulated RadiotherapyInvestigationKnowledgeLeadMalignant NeoplasmsMapsModernizationMotionMusPatient CarePatientsPatternPerformancePhysiciansPlanning TechniquesPrincipal InvestigatorProblem SolvingProcessProtocols documentationRadiation OncologyRadiation Therapy Oncology GroupResearchResearch PersonnelRotationSamplingSchemeSeriesShapesSystemTechniquesTechnologyTestingTherapeuticTimeTimeLineTissuesTreatment outcomeVariantbasecancer therapycase controlclinical translationcostdesigndigitalimprovedinnovationmeetingsnovelprogramspublic health relevancetooltreatment planningtumor
中文摘要
描述(申请人提供):本项目的目标是建立一种新的密集角度采样和稀疏强度调制放射治疗(DASSIM-RT)范例。在该方案中,通过使用压缩传感(CS)技术,有效地消除了入射强度调制光束的冗余或可有可无的调制。通过这种方式节省的传输时间被用于增加角度采样,以改善剂量一致性。通过平衡角度采样和强度调制,DASSIM-RT使我们能够充分利用现代数字直线加速器的技术能力,产生可高效传输的高度共形剂量分布。具体地说,我们将1)建立基于压缩感知(CS)的反向治疗规划框架;2)研究一种称为DASSIM-RT的新型治疗方案;3)通过一系列幻影病例和先前治疗的患者来展示DASSIM-RT的优势。DASSIM-RT代表了一种真正最佳的RT方案,具有不折中的角度采样(包括非共面光束)、光束强度调制以及可能的特定场能量和准直器角度。如果成功,该项目将使我们能够克服现有治疗方案的许多限制,以满足放射肿瘤学中尚未满足的高度适形剂量分布的临床需求。
英文摘要
DESCRIPTION (provided by applicant): The goal of this project is to establish a novel paradigm of dense angularly sampled and sparse intensity- modulated radiation therapy (DASSIM-RT). In this scheme, the redundant or dispensable modulation of the incident intensity-modulated beams is removed effectively by using a compressed sensing (CS) technique. The delivery time saved in this way is used to increase the angular sampling for improved dose conformality. By balancing the angular sampling and intensity modulation, DASSIM-RT enables us to fully utilize the technical capabilities of modern digital linacs to produce highly conformal dose distributions that can be delivered efficiently. Specifically, we wil 1) set up a compressed sensing (CS)-based framework for inverse treatment planning; 2) investigate a new type of treatment scheme termed DASSIM-RT; and 3) show the advantage of DASSIM-RT through a series of phantom cases and previously treated patients. DASSIM-RT represents a truly optimal RT scheme with uncompromised angular sampling (including non-coplanar beams), beam intensity modulation, and possible field-specific energy and collimator angle. If successful, the project will allow us to overcome many of the limitations of existing treatment schemes to meet the unmet clinical demand for highly conformal dose distributions in radiation oncology.
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