课题基金 / 基金详情

Image Guided Intergrated Active Breath Hold Radiotherapy

Image Guided Intergrated Active Breath Hold Radiotherapy
图像引导综合主动屏气放疗
批准号:
7102043
负责人:
Geoffrey D Hugo
金额:
$19.95万
依托单位国家:
美国
项目类别:
财政年份:
2006
资助国家:
美国
项目状态:
已结题
起止时间:
2006-06-01 至 2010-04-30

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中文摘要
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英文摘要
DESCRIPTION (provided by applicant): Control of the primary tumor is a major goal of radiotherapy for cancer. Escalating the dose delivered to the tumor provides a method to improve local control. For lung cancer patients in particular, respiratory-induced organ motion has impeded safe dose escalation. Methods to compensate for this motion or to immobilize the tumor have been developed in recent years. However, these new technologies have not been applied in concert with reduced margins that would enable dose escalation due to the lack of data characterizing uncertainty in respiratory-induced organ motion. It is critical to characterize the uncertainties associated with tumor immobilization to enable the use of appropriate margins. It is our hypothesis that the combination of image guidance techniques and integrated active breath hold radiotherapy will enable characterization and reduction of the geometric uncertainties due to respiratory-induced organ motion. Active breathing control (ABC) has been shown to be a safe and effective means of tumor immobilization for breast cancer patients which allows for the reduction of the dose to normal tissue structures such as the heart and lungs. For lung cancer patients, however, the ABC technique must be adapted to increase compliance for patients with pulmonary compliance issues. Furthermore, the integration of image guidance techniques with ABC radiotherapy enables the characterization and reduction of daily setup variation and immobilization uncertainty. The specific aims of this project are to (1) Measure the random and systematic uncertainties of tumor immobilization for integrated active breath hold radiotherapy. (2) Evaluate a model image-guidance strategy with respect to the presence of these uncertainties and to design a treatment margin to compensate for these uncertainties. (3) Quantify residual setup error in a small population of patients.
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