Four-Dimensional Monte Carlo Dose Calculation
Four-Dimensional Monte Carlo Dose Calculation
批准号:
7394459
负责人:
HARALD PAGANETTI
金额:
$24.97万
依托单位国家:
美国
项目类别:
财政年份:
2005
资助国家:
美国
项目状态:
已结题
起止时间:
2005-07-01 至 2010-04-30
关键词:
AbdomenAccountingAddressAdoptedAffectAlgorithmsAnatomyAreaBlurBreathingChestClassificationClinicalCodeCollimatorColorComplexComputersConditionDataData SetDependencyDepositionDepthDoseDose-RateEventExtravasationEyeFailureFour-dimensionalGoalsHeadImageIndividualLeadLeftLightLungMalignant neoplasm of lungMapsMeasurementMethodsMicroscopicModalityModelingMonte Carlo MethodMotionNumbersOrganPatientsPatternPersonal SatisfactionPhasePhotonsPlant LeavesPositioning AttributeProbabilityProceduresProcessPropertyProtonsPublishingRadiation therapyRandomizedRecording of previous eventsRelative (related person)ReportingResolutionRespirationRotationRunningSafetyScanningSignal TransductionSimulateSiteSlideSpeedStagingStatistical ModelsStructureStructure of parenchyma of lungSystemTechniquesThoracic NeoplasmsTimeTime StudyTissuesTongueTranslatingTumor VolumeVariantWaterWorkattenuationbasecancer therapydensityexperienceheart motionimage registrationimaging Segmentationinnovationneurosurgerynovelprogramsproton beamsimulationsizetooltreatment planningtumortwo-dimensional
中文摘要
描述(由申请人提供):为了研究随时间变化的几何形状中的剂量学效应,通常将单个三维(3D)计算的结果添加或统计组合。如果几何结构复杂,如果设想高时间分辨率(例如考虑剂量率),或者如果微观体积位移作为时间的函数未知,则这是很麻烦的。此外,研究双动力系统来研究随时间变化的光束传递(多叶准直器中的移动叶片)对运动目标(器官运动或变形)中的剂量沉积的影响是困难的。在这里,需要4D而不是多个3D计算。蒙特卡罗(MC)模拟被认为是最准确的剂量计算工具,并且可能在密度变化较大的领域产生最大的影响,例如肺癌治疗。有趣的是,这也是器官运动对剂量分布影响最大的区域。MC方法适合于高精度研究运动的剂量学效应。然而,到目前为止,与分析剂量计算技术一样,在模拟过程中无法修改几何信息。这限制了应用程序的多个3D,而不是真正的4D。利用面向对象的c++编程技术,提出了真正的四维MC剂量计算方法。在连续改变光束配置和器官几何形状的同时,计算患者体内的局部剂量沉积。在模拟过程中,根据叶片测序文件,MLC叶片的位置会发生变化。基于可变形图像配准,在剂量计算过程中,我们将根据患者CT跟踪微观区域。4D剂量计算将允许使用基于临床经验或患者特定4D CT信息的预设移动模式。基于治疗头部变化和患者呼吸方式研究随时间变化的几何形状和双动力系统中任何时间尺度的相互作用的能力,将MC剂量计算提升到一个新的水平,达到4D治疗模拟的水平。
英文摘要
DESCRIPTION (provided by applicant): To study dosimetric effects in time-dependent geometries the results of individual three-dimensional (3D) calculations are usually added or statistically combined. This is cumbersome if the geometry is complex, if high time resolution is envisaged (e.g. considering dose rate), or if the microscopic volume displacement as a function of time is not known. Furthermore, it is difficult to study double-dynamic systems to investigate the influence of time-dependent beam delivery (moving leafs in a multi-leaf collimator) on the dose deposition in a moving target (organ motion or deformation). Here, 4D instead of multiple 3D calculations are required. Monte Carlo (MC) simulations are believed to be the most accurate tool for dose calculation and wiII presumably have the biggest impact in areas of large density variations, e.g. for lung cancer treatments. Interestingly, this is also the area where we might expect the biggest impact of organ motion on the dose distribution. The MC method is well suited to study dosimetric effects of motion with high accuracy. However, until now, like for analytical dose calculation techniques, the geometric information cannot be modified during the simulation. This limits applications to multiple 3D instead of true 4D. In taking advantage of objejctoriented C++ programming techniques we are proposing true 4D MC dose calculation. Local dose deposition in the patient will be calculated while beam configuration and organ geometry are changed continuously MLC leaf positions will be changing during the simulation according to leaf sequencing files. Based on deformable image registration we will track microscopic areas based on the patient's CT during the dose calculation. 4D dose calculation will allow the usage of a preset moving pattern based on clinical experience or patient specific 4D CT information. The capability of studying time dependent geometries and the interplay in double-dynamic systems for any time scale based on treatment head variations and patient's breathing pattern will take MC dose calculation to a new level, to the level of 4D treatment simulation.
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海外基金