SBIR Phase I: Cloud-based Automated Dose Accumulation for Online Adaptive Radiotherapy
SBIR Phase I: Cloud-based Automated Dose Accumulation for Online Adaptive Radiotherapy
批准号:
1746778
负责人:
Rodney Bosley
金额:
$22.47万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2018
资助国家:
美国
项目状态:
已结题
起止时间:
2018-01-01 至 2018-06-30
中文摘要
这个小型企业创新研究(SBIR)第一阶段项目的更广泛的影响/商业潜力将来自于为放射癌症治疗(自适应放射治疗)开发新型实时云治疗指导软件,这将提高放射治疗的疗效、患者的生活质量,并最终减少患者的再次住院。放射治疗是治疗癌症最常用的方法。放射治疗过程持续数天(5-35天),在此期间,由于患者解剖结构的改变,放射治疗效果可能会降低。该项目使临床医生能够在治疗前获得有关肿瘤和周围正常器官的辐射剂量的信息。该项目的成功结果将使放射肿瘤学家能够计划和提供先进的治疗方法,其中所提供的辐射剂量可以迅速调整以适应当前肿瘤的位置和运动,从而仅包围肿瘤并有效地保留正常组织。该项目的成果还将使偏远诊所的医生能够接受专家的指导,进行在线自适应放射治疗,从而使全球放射治疗进入一个新时代。这个基于云的框架将与大多数图像引导放射治疗设备一起工作。这个小型企业创新研究(SBIR)第一阶段项目将使技术开发能够有效地执行质量保证测试,以确定更准确的辐射剂量,并减少许多癌症肿瘤治疗中的分割数量。癌症周围的软组织在其生理行为上有所不同,这在不考虑的情况下会改变治疗效果。虽然传统的假说认为放射治疗期间更好的肿瘤靶向将产生更好的治疗反应,但患者生存统计数据表明情况并非如此,这表明到目前为止还没有促进准确的治疗指导。这项研究将侧重于开发一个基于云的计算机断层扫描和磁共振图像处理框架,用于快速可变形图像配准和辐射剂量累积估计,并具有量化可变形图像配准性能的自动化方法。这些技术成果可能会促进一个自动化框架,用于准确跟踪患者的解剖结构,计算提供的累积剂量,并近乎实时地报告关键结构的剂量学终点,这将是实现在线自适应放射治疗的关键。
英文摘要
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project will result from the development of novel real-time cloud-based treatment guidance software for radiation cancer treatment (adaptive radiotherapy), which will improve radiation treatment efficacy, patient's quality of life, and ultimately reduce patient re-hospitalizations. Radiotherapy is the most common approach for treating cancer. The radiotherapy treatment procedures happen for multiple days (5-35 days) during which the radiation treatment efficacy may be lowered because of changes in the patient anatomy. This project provides the clinician the ability to obtain information regarding the radiation dose to be delivered to both the tumor as well as the surrounding normal organs before the treatment is delivered. The successful outcome of this project will allow radiation oncologists to plan and deliver advanced treatments where the radiation dose delivered can be quickly modified to suit the current tumor location and motion, to only encompass the tumor and effectively spare normal tissues. The project outcome will also enable physicians at remote clinics to receive guidance from experts to perform online adaptive radiotherapy, enabling a new era of radiotherapy treatment world-wide. The cloud-based framework will work with most image-guided radiotherapy equipment.This Small Business Innovation Research (SBIR) Phase I project will enable development of technology to effectively perform quality assurance tests to determine a more accurate radiation dose and reduce the number of fractions in the treatment of many cancerous tumors. The soft tissue surrounding the cancer varies in its physiological behavior, which alters the treatment efficacy when not accounted for. While a conventional hypothesis would dictate that better tumor targeting during radiotherapy would yield an improved treatment response, patient survival statistics dictate otherwise, indicating that accurate treatment guidance has not been facilitated to date. The research will focus on developing a cloud-based framework of computed tomography and magnetic resonance image processing for fast deformable image registration and radiation dose accumulation estimation, with an automated methodology for quantifying the deformable image registration performance. The technical results may facilitate an automated framework for accurately tracking a patient's anatomy, computing the accumulated dose delivered and reporting dosimetric endpoints for critical structures in near real-time, which will be vital for enabling online adaptive radiotherapy.
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SBIR Phase II: Cloud-based Automated Dose Accumulation for Online Adaptive Radiotherapy
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批准号:1853110
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项目类别:Standard Grant
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资助金额:$75.0万
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财政年份:2019
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负责人:Rodney Bosley
-
依托单位:
国内基金
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