Optimized Cone-Beam CT for Image-Guided Radiation Therapy

用于图像引导放射治疗的优化锥束 CT

基本信息

  • 批准号:
    8078958
  • 负责人:
  • 金额:
    $ 36.23万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2007
  • 资助国家:
    美国
  • 起止时间:
    2007-07-27 至 2014-05-31
  • 项目状态:
    已结题

项目摘要

DESCRIPTION (provided by applicant): In radiation therapy (RT), it is essential to deliver a prescribed high radiation dose to a target volume containing malignancy while sparing surrounding normal tissues. This is accomplished by extensive use of imaging throughout the RT process. Computed tomography (CT) is the dominant imaging tool in image- guided radiation therapy (IGRT). Simulator units with cone-beam CT (CBCT) imaging capabilities have become available as part of RT planning systems. Recently, a KV X-ray imager, referred to as the on-board imager, capable of CBCT imaging has also been developed on the linear accelerator (LINAC) treatment system. The on-board imager offers a unique opportunity to yield accurate image representation of the patient before, during, and after treatment sessions. There are two broad classes of RT tasks to which these systems are suited, and each task class has its own set of requirements on image quality, acquisition speed, and patient dose minimization. The first class includes tasks such as those involving CBCT for treatment planning, where the objective is to obtain diagnostic image quality and to identify unknown object in a complex scene. The second class includes tasks such as those using CBCT for localization, where the objective is to recognize differences in position relative to the planning scan and to identify pose of known objects. The goal of the project is to, using the on-board imager as the test-bed platform, capitalize fully on the hardware capabilities and on recent algorithm advances through developing innovative scanning configurations and algorithms to yield accurate and dose-efficient volumetric images in IGRT. The specific aims of the project are: (1) To develop innovative scanning configurations for radiotherapy CBCT imaging; (2) To develop image-reconstruction algorithms for radiotherapy CBCT imaging; (3) To compensate for the physical factors in radiotherapy CBCT imaging; and (4) To evaluate the scanning configurations and algorithms for radiotherapy CBCT imaging. We have recently made significant breakthroughs in CBCT algorithms. Algorithms can be designed for accurate image reconstruction within regions-of-interest (ROI) from CBCT data acquired with X-ray illumination that partially covers the patient and with general scanning configurations. Our strategy for targeted ROI imaging resembles that of the intensity-modulated radiation therapy. It can reduce patient dose and scatter and avoid repeated illumination of critical organs. We believe that our expertise and insights developed and accumulated in our studies in both imaging and radiation therapy have placed us in a unique and strong position to perform and accomplish the proposed research on optimization of CBCT imaging in IGRT successfully and in a timely manner.
描述(由申请人提供):在放射治疗(RT)中,必须向含有恶性肿瘤的目标体积输送规定的高辐射剂量,同时不伤害周围的正常组织。这是通过在整个 RT 过程中广泛使用成像来实现的。计算机断层扫描 (CT) 是图像引导放射治疗 (IGRT) 中的主要成像工具。具有锥束 CT (CBCT) 成像功能的模拟器装置已成为 RT 计划系统的一部分。最近,在直线加速器(LINAC)治疗系统上还开发出了能够进行CBCT成像的KV X射线成像仪,简称机载成像仪。机载成像仪提供了一个独特的机会,可以在治疗之前、期间和之后生成患者的准确图像表示。这些系统适合两大类 RT 任务,每种任务类别对图像质量、采集速度和患者剂量最小化都有自己的一套要求。第一类包括涉及用于治疗计划的 CBCT 的任务,其目标是获得诊断图像质量并识别复杂场景中的未知物体。第二类包括使用 CBCT 进行定位等任务,其目标是识别相对于计划扫描的位置差异并识别已知物体的姿态。该项目的目标是,使用机载成像仪作为测试平台,通过开发创新的扫描配置和算法,充分利用硬件功能和最新的算法进步,在 IGRT 中产生准确且剂量高效的体积图像。该项目的具体目标是:(1)开发用于放射治疗CBCT成像的创新扫描配置; (2) 开发放射治疗CBCT成像的图像重建算法; (3) 补偿放疗CBCT成像中的物理因素; (4) 评估放射治疗 CBCT 成像的扫描配置和算法。我们最近在 CBCT 算法方面取得了重大突破。可以设计算法,以便根据使用部分覆盖患者的 X 射线照明和一般扫描配置获取的 CBCT 数据在感兴趣区域 (ROI) 内进行准确的图像重建。我们的靶向 ROI 成像策略类似于强度调制放射治疗。可以减少患者剂量和分散,避免对重要器官的重复照射。我们相信,我们在成像和放射治疗研究中发展和积累的专业知识和见解使我们处于独特且有利的地位,能够成功、及时地执行和完成 IGRT 中 CBCT 成像优化的拟议研究。

项目成果

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XIAOCHUAN PAN其他文献

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{{ truncateString('XIAOCHUAN PAN', 18)}}的其他基金

Algorithm-Enabled Auto-Calibrating Quantitative Dual-Energy CT
支持算法的自动校准定量双能 CT
  • 批准号:
    10448987
  • 财政年份:
    2022
  • 资助金额:
    $ 36.23万
  • 项目类别:
Advanced iterative image reconstruction for digital breast tomosynthesis - Resubmission 01
用于数字乳腺断层合成的高级迭代图像重建 - 重新提交 01
  • 批准号:
    9978584
  • 财政年份:
    2018
  • 资助金额:
    $ 36.23万
  • 项目类别:
Advanced iterative image reconstruction for digital breast tomosynthesis - Resubmission 01
用于数字乳腺断层合成的高级迭代图像重建 - 重新提交 01
  • 批准号:
    10224861
  • 财政年份:
    2018
  • 资助金额:
    $ 36.23万
  • 项目类别:
36th Annual International Conference of the IEEE Engineering in Medicine and Biol
第 36 届 IEEE 医学和生物工程国际年会
  • 批准号:
    8720474
  • 财政年份:
    2014
  • 资助金额:
    $ 36.23万
  • 项目类别:
Digital Specimen Tomosynthesis for Volumetric Imaging of Lumpectomy Specimens
用于肿瘤切除标本体积成像的数字标本断层合成
  • 批准号:
    9085109
  • 财政年份:
    2014
  • 资助金额:
    $ 36.23万
  • 项目类别:
Development of Advanced C-arm Cone-Beam CT for the Treatment of Liver Cancer
先进C型臂锥束CT治疗肝癌的开发
  • 批准号:
    9305887
  • 财政年份:
    2014
  • 资助金额:
    $ 36.23万
  • 项目类别:
Digital Specimen Tomosynthesis for Volumetric Imaging of Lumpectomy Specimens
用于肿瘤切除标本体积成像的数字标本断层合成
  • 批准号:
    8766676
  • 财政年份:
    2014
  • 资助金额:
    $ 36.23万
  • 项目类别:
Development of Advanced C-arm Cone-Beam CT for the Treatment of Liver Cancer
先进C型臂锥束CT治疗肝癌的开发
  • 批准号:
    8616609
  • 财政年份:
    2014
  • 资助金额:
    $ 36.23万
  • 项目类别:
International Symposium on Biomedical Imaging: from Nano to Macro 2011 (ISBI2011)
生物医学成像国际研讨会:从纳米到宏观2011 (ISBI2011)
  • 批准号:
    8133639
  • 财政年份:
    2011
  • 资助金额:
    $ 36.23万
  • 项目类别:
31st Annual International Conference of IEEE Engineeering in Medicine and Biology
第 31 届 IEEE 医学和生物学工程国际会议
  • 批准号:
    7744371
  • 财政年份:
    2009
  • 资助金额:
    $ 36.23万
  • 项目类别:

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