A high efficiency imager for real-time lung cancer monitoring during radiotherapy

用于放射治疗过程中实时肺癌监测的高效成像仪

• 批准号: 8917151
• 负责人: Ross I. Berbeco
• 金额: $ 76.06万
• 依托单位: DANA-FARBER CANCER INST
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-01 至 2019-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8917151
• 关键词: Anatomy; Cancer Patient; Clinic; Clinical; Collaborations; Computer software; Dana-Farber Cancer Institute; Data; Development; Dose; Ensure; Eye; Fiber; Geometry; Goals; Health; Image; Imaging Device; Imaging Techniques; Intensity-Modulated Radiotherapy; Internet; Lung; Lung Neoplasms; Malignant neoplasm of lung; Marketing; Measurement; Medical; Methods; Modeling; Monitor; Motion; Nature; Noise; Online Systems; Patients; Radiation; Radiation therapy; Recording of previous events; Research; Research Personnel; Respiration; System; Testing; Time; Translations; Validation; Work; base; cancer imaging; clinical application; cost; design; imaging modality; improved; meetings; novel; photon-counting detector; pre-clinical; research clinical testing; research study; tool; tumor

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.

描述（由申请人提供）：在放射治疗期间对肺部肿瘤进行直接治疗成像以确保正确的放射靶向是一个尚未解决的挑战。我们建议使用束眼视图（BEV）成像和高效成像仪来克服这一障碍，以实时自动定位肺部肿瘤。该项目的目标是设计、验证和临床部署新型高效成像仪。我们将首先确定强大的 BEV 成像所需的规格。为实现这一目标而设计的新型成像仪将使用新的蒙特卡罗平台进行。闪烁体的组成、像素化和多层堆叠将得到优化，新的成像仪将在放射治疗诊所全面部署之前得到验证。除了实时肺肿瘤定位的直接临床益处外，我们预计该项目还将加速先进的应用，例如 肿瘤追踪、递送剂量积累和适应性放射治疗。蒙特卡罗平台还将加快该项目之外其他医疗应用新型成像仪的开发。因此，该项目的影响远远超出了直接的临床收益，而临床收益本身就是巨大的。