Quantitative dual-energy CT imaging for radiation therapy treatment planning
Quantitative dual-energy CT imaging for radiation therapy treatment planning
批准号:
8105671
负责人:
JEFFREY F WILLIAMSON
金额:
$34.85万
依托单位国家:
美国
项目类别:
财政年份:
2011
资助国家:
美国
项目状态:
已结题
起止时间:
2011-04-01 至 2016-03-31
关键词:
AddressAlgorithmsArchitectureBase CompositionBenchmarkingBiologicalBrachytherapyBreastCancer PatientChargeChestClinicalClinical ResearchClinical TreatmentClinical assessmentsCodeDataData SetDependenceDevelopmentDevicesDiseaseDoseElectron BeamElectron Beam TherapyEnvironmentEquilibriumFemale breastFundingGoalsHead and Neck CancerHead and neck structureHousingImageImaging technologyImplantIntensity-Modulated RadiotherapyKnowledgeLightLungMalignant neoplasm of lungMalignant neoplasm of prostateMapsMeasurementMedicalMethodsModalityModelingNoiseNormal tissue morphologyOrganOutcomePatientsPelvisPerformancePhotonsProcessPropertyProstateProtonsRadiation therapyRelative (related person)ResearchResolutionSamplingScanningSeedsShapesSimulateSliceStructureSystemTechniquesTechnologyTestingTherapeuticTissuesTomography, Computed, ScannersToxic effectUncertaintyVariantWorkX-Ray Computed Tomographyabstractinganalytical toolbasecancer siteclinical practiceclinically significantcost effectivedensitydigitalelectron densityexperiencehigh riskhuman tissueimage reconstructionimprovedin vivoinnovationirradiationmalemalignant breast neoplasmnovelparallel computerparticlepatient populationproton beamprototypereconstructiontherapy outcometooltreatment planningtumor
中文摘要
描述(由申请人提供):用于放射治疗计划的定量双能CT成像6.项目摘要/摘要质子束治疗(PT)和低能量(20-60keV)光子发射近距离放射治疗(LEPBT)是快速发展的方法,具有改善放射治疗临床结果的巨大潜力,因为它们能够将高剂量照射到目标组织,同时保留周围正常组织。这两种方式的剂量传递对辐照组织的原子组成和电子密度都很敏感。对于LEPBT,目前的剂量计算实践忽略了组织的不均匀性,引入了高达2倍的剂量预测误差。对于PT,当前的定量单能量计算机断层成像(QSECT)导致3-6 mm范围的不确定,显著增加邻近器官暴露在高剂量下。推荐的块状组织成分基于大量且基本上未知的患者间和患者内变异性的不充分数据,并且不能为临床治疗计划或评估PT或LEPBT的剂量传递不确定性提供充分的基础。常规的QSECT不能定量研究PT和LEPBT的放射组织特性,因为组织成分和电子密度独立变化。该项目的目标是开发和验证一种新的定量双能量CT(QDECT)成像技术,该技术能够准确地成像放射学特性,并通过评估小样本中组织不均匀的程度和临床意义来展示QDECT的用途。为了实现这些目标,提出了三个具体目标。在具体目标1中,将开发一种新的统计图像重建算法,用于从临床多层CT成像系统输出的双能量螺旋正弦图中重建三维截面图。具体地说,将对交替最小化、正则化的3D重建引擎进行调整和优化,以解决用于近距离治疗和质子束剂量规划的准确组织图成像问题,并实施临床原型。在具体目标2中,将对照实验体模、患者数据和计算基准来验证从实验获得的双能量正弦图重建的QDECT横断面图像。对估计误差的分析将用于集中AM重建算法的优化工作。开发的QDECT过程将被用来研究我们小患者群体中质子阻止能力和光子截面图的大小和可变性。具体目标3将使用现有的治疗计划系统和蒙特卡罗剂量估计代码,研究更准确的针对患者的QDECT横断面分布对头颈部、前列腺癌、乳腺癌和肺癌部位的模拟近距离放射治疗、电子束和质子束治疗计划的剂量学和临床影响。
与公共卫生相关:与兆伏光子强度调制放射治疗(IMRT)等竞争疗法相比,出口剂量自由质子疗法的治疗优势被部分否定,因为需要很大的靶区余量来补偿3-6 mm射程的不确定性。通过将这种范围不确定性降低到1 mm,我们的定量横断面成像项目将使质子治疗高剂量关键结构保留与调强放疗相比具有竞争力,极大地增强其改善临床结果的潜力。对于局部前列腺癌的低能量光子近距离放射治疗(LEPBT)和加速部分乳腺放射治疗,我们的项目将把10%-30%的剂量不确定度降低到5%,使高危疾病的剂量增加而不增加毒性,并实现与其他放射治疗方式的客观比较。
英文摘要
DESCRIPTION (provided by applicant): Quantitative dual-energy CT imaging for radiation therapy treatment planning 6. Project Summary/Abstract Proton-beam therapy (PT) and low-energy (20-60 keV) photon-emitting brachytherapy (LEPBT) are rapidly evolving modalities with high potential for improving radiation therapy clinical outcomes because of their ability to deliver high doses to the target tissue while sparing surrounding normal tissues. Dose delivery from both modalities is sensitive to the atomic composition as well as election density of the irradiated tissues. For LEPBT, current dose-calculation practice ignores tissue inhomogeneity, introducing dose-prediction errors as large as a factor of 2. For PT, current quantitative single-energy computed tomography imaging (QSECT) leads to 3-6 mm range uncertainties that significantly increases exposure of adjacent organs to high doses. Recommended bulk tissue compositions are based upon inadequate data with large and essentially unknown patient-to-patient and intrapatient variability and cannot provide an adequate basis either for clinical treatment planning or assessing dose delivery uncertainty in PT or LEPBT. Conventional QSECT is inadequate for quantitative study of PT and LEPBT radiological tissue properties because tissue composition and electron density vary independently. The goal of this project is to develop and validate a novel quantitative dual-energy CT (QDECT) imaging technology able to accurately image the radiological properties and to demonstrate QDECT utility by assessing the magnitude and clinical significance of tissue inhomogeneities in a small patient sample. To achieve these goals, three specific aims are proposed. In Specific Aim 1, a novel statistical image reconstruction algorithm will be developed for reconstructing 3D cross-section maps derived from dual energy spiral sinograms exported from a clinical multi-slice CT imaging system. Specifically, an alternating minimization regularized, 3D reconstruction engine will be adapted and optimized to the problems of accurate tissue-map imaging for brachytherapy and proton-beam dose planning and a clinical prototype implemented. In Specific Aim 2, QDECT cross-section images reconstructed from experimentally-acquired dual-energy sinograms will be validated against experimental phantom, patient data, and computational benchmarks. Analysis of estimation errors will be used to focus AM reconstruction algorithm optimization efforts above. The developed QDECT process will be used to study the magnitude and variability of proton stopping-power and photon-cross section maps in our small patient population. Specific Aim 3 will study the dosimetric and clinical impact of more accurate patient-specific QDECT cross-section distributions on simulated brachytherapy, electron-beam and proton-beam treatment plans in head and neck, prostate, breast, and lung cancer sites using available treatment-planning systems and Monte Carlo dose-estimation codes.
PUBLIC HEALTH RELEVANCE: The therapeutic advantage of exit-dose free proton-therapy over competing modalities such as megavoltage photon intensity-modulated radiation therapy (IMRT) is partially negated because of the large target volume margins needed to compensate for 3-6 mm range uncertainties. By reducing such range uncertainties to 1 mm, our quantitative cross-section imaging project will make proton-therapy high dose critical structure sparing competitive with IMRT, greatly enhancing its potential for improving clinical outcomes. For low-energy photon brachytherapy (LEPBT) of localized prostate cancer and accelerated partial breast irradiation, our project will reduce 10%-30% dose uncertainties to 5%, enabling dose escalation in higher risk disease without increasing toxicity and objective comparison with other radiation therapy modalities to be realized.
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Quantitative dual-energy CT imaging for radiation therapy treatment planning
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批准号:8628785
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项目类别:
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资助金额:$30.26万
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财政年份:2011
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负责人:JEFFREY F WILLIAMSON
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依托单位:
Quantitative dual-energy CT imaging for radiation therapy treatment planning
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批准号:8444300
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项目类别:
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资助金额:$30.6万
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财政年份:2011
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负责人:JEFFREY F WILLIAMSON
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依托单位:
Software Engineering, Treatment Planning, and QA
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批准号:7806515
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项目类别:
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资助金额:$51.09万
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财政年份:2007
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负责人:JEFFREY F WILLIAMSON
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依托单位:
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批准号:8256663
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项目类别:
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资助金额:$28.6万
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财政年份:2007
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负责人:JEFFREY F WILLIAMSON
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依托单位:
Software Engineering, Treatment Planning, and QA
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批准号:8256665
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资助金额:$50.13万
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财政年份:2007
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负责人:JEFFREY F WILLIAMSON
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依托单位:
Biostatistics, Outcomes Modeling, Clinical Design, and Administration
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批准号:8074388
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项目类别:
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资助金额:$28.29万
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财政年份:2007
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负责人:JEFFREY F WILLIAMSON
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依托单位:
Software Engineering, Treatment Planning, and QA
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批准号:8074387
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项目类别:
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资助金额:$51.73万
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财政年份:2007
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负责人:JEFFREY F WILLIAMSON
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依托单位:
Biostatistics, Outcomes Modeling, Clinical Design, and Administration
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批准号:7806516
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项目类别:
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资助金额:$31.17万
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财政年份:2007
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负责人:JEFFREY F WILLIAMSON
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依托单位:
Biostatistics, Outcomes Modeling, Clinical Design, and Administration
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批准号:8256666
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项目类别:
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资助金额:$23.23万
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财政年份:2007
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负责人:JEFFREY F WILLIAMSON
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依托单位:
Image-guided IMRT and Brachytherapy for Pelvic Tumors
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批准号:8074385
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项目类别:
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资助金额:$30.64万
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财政年份:2007
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负责人:JEFFREY F WILLIAMSON
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依托单位:
Image-Guided Adaptive Radiotherapy
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批准号:7806517
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项目类别:
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资助金额:$209.86万
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财政年份:2007
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负责人:JEFFREY F WILLIAMSON
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依托单位:
Image-Guided Adaptive Radiotherapy
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批准号:7615073
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项目类别:
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资助金额:$214.42万
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财政年份:2007
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负责人:JEFFREY F WILLIAMSON
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依托单位:
Image-Guided Adaptive Radiotherapy
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批准号:8074389
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项目类别:
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资助金额:$196.06万
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财政年份:2007
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负责人:JEFFREY F WILLIAMSON
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依托单位:
Image-guided IMRT and Brachytherapy for Pelvic Tumors
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批准号:7806513
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项目类别:
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资助金额:$37.07万
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财政年份:2007
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负责人:JEFFREY F WILLIAMSON
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依托单位:
Image-Guided Adaptive Radiotherapy
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批准号:7185331
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项目类别:
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资助金额:$208.36万
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财政年份:2007
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负责人:JEFFREY F WILLIAMSON
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依托单位:
Biostatistics, Outcomes Modeling, Clinical Design, and Administration
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批准号:7214976
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项目类别:
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资助金额:$24.29万
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财政年份:2006
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负责人:JEFFREY F WILLIAMSON
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依托单位:
Image-guided IMRT and Brachytherapy for Pelvic Tumors
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批准号:7214973
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项目类别:
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资助金额:$41.2万
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财政年份:2006
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负责人:JEFFREY F WILLIAMSON
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依托单位:
Software Engineering, Treatment Planning, and QA
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批准号:7214975
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项目类别:
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资助金额:$41.85万
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财政年份:2006
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负责人:JEFFREY F WILLIAMSON
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依托单位:
ARTIFACT-FREE CT IMAGING FOR RADIOTHERAPY PLANNING
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批准号:7013587
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项目类别:
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资助金额:$27.78万
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财政年份:1998
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负责人:JEFFREY F WILLIAMSON
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依托单位:
ARTIFACT-FREE CT IMAGING FOR RADIOTHERAPY PLANNING
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批准号:6857156
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项目类别:
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资助金额:$28.61万
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财政年份:1998
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负责人:JEFFREY F WILLIAMSON
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依托单位:
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