A high efficiency imager for real-time lung cancer monitoring during radiotherapy
A high efficiency imager for real-time lung cancer monitoring during radiotherapy
批准号:
8917151
负责人:
Ross I. Berbeco
金额:
$76.06万
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:
2014-09-01 至 2019-08-31
关键词:
AnatomyCancer PatientClinicClinicalCollaborationsComputer softwareDana-Farber Cancer InstituteDataDevelopmentDoseEnsureEyeFiberGeometryGoalsHealthImageImaging DeviceImaging TechniquesIntensity-Modulated RadiotherapyInternetLungLung NeoplasmsMalignant neoplasm of lungMarketingMeasurementMedicalMethodsModelingMonitorMotionNatureNoiseOnline SystemsPatientsRadiationRadiation therapyRecording of previous eventsResearchResearch PersonnelRespirationSystemTestingTimeTranslationsValidationWorkbasecancer imagingclinical applicationcostdesignimaging modalityimprovedmeetingsnovelphoton-counting detectorpre-clinicalresearch clinical testingresearch studytooltumor
中文摘要
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英文摘要
DESCRIPTION (provided by applicant): Direct in-treatment imaging of lung tumors during radiation therapy to ensure proper radiation targeting is an unsolved challenge. We propose to overcome this obstacle using beam's-eye-view (BEV) imaging with a high efficiency imager to automatically localize lung tumors in real-time. The project goal is to design, validate and clinically deploy the new high efficiency imager. We will first determine the specifications necessary for robust BEV imaging. The design of the novel imager to meet this goal will be performed using a new Monte Carlo platform. Scintillator composition, pixelation and stacking of multiple layers will be optimized and the new imager will be validated prior to full scale deployment in a radiation therapy clinic. In addition to the immediate clinical benefits of real-tie lung tumor localization, we anticipate that this project will accelerate advanced applications like
tumor tracking, delivered dose accumulation and adaptive radiation therapy. The Monte Carlo platform will also hasten the development of novel imagers for other medical applications beyond this project. Therefore the impact of the project extends far beyond the immediate clinical gain, which is in itself substantial.
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Cross-Training Core (ROBIN-NEST)
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财政年份:2012
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财政年份:2012
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依托单位:
Lung Sparing for SBRT with beam's-eye-view images and real time tumor tracking
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批准号:8298131
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项目类别:
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资助金额:$19.71万
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财政年份:2011
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Lung Sparing for SBRT with beam's-eye-view images and real time tumor tracking
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依托单位:
海外基金