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Advanced CT Strategies for Image Quality Improvement and Dose Reduction

Advanced CT Strategies for Image Quality Improvement and Dose Reduction
提高图像质量和减少剂量的先进 CT 策略
批准号:
RGPIN-2019-06445
负责人:
Jaffray, David
金额:
$5.21万
依托单位:
依托单位国家:
加拿大
项目类别:
Discovery Grants Program - Individual
财政年份:
2019
资助国家:
加拿大
项目状态:
已结题
起止时间:
2019-01-01 至 2020-12-31

项目摘要

项目成果

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中文摘要
翻译
X射线计算机断层扫描(CT)产生身体的详细图像,是医疗保健中的关键工具。这些系统应用于医学的各个方面,从癌症筛查到评估损伤,再到指导治疗,如放射治疗和手术。** 然而,通过更好地利用基本物理学来提高图像质量并最大限度地减少对患者的辐射剂量,有很大的机会增强CT技术。该研究计划建立在X射线成像方法和系统开发方面20多年的经验基础上,以开发利用计算方法,机电一体化和纳米技术进步的下一代CT方法。本研究主要集中在两个方面:**1。通过使用基于物理的模型来校正不需要的X射线散射,从而提高图像质量 *2。使用一种名为“通量场调制CT”(FFMCT)的新方法降低与CT成像相关的风险。** 简而言之,CT的工作原理是从发射器发送一束X射线,穿过患者到达探测器。信号的变化取决于两者之间的情况,例如,骨骼比肌肉阻挡更多的X射线。然而,一些X射线是分散的,并没有沿着一条直线穿过病人。这些散射的X射线对图像质量具有显著影响,由于照射的组织体积和缺乏拒绝方法,这在锥形束CT(CBCT)中加剧。通过蒙特卡罗(MC)模拟对散射物理基础进行精确建模,使我们能够更好地理解和校正散射,从而改善图像和患者剂量管理。我们最近使模拟更有效,更快,这是将其纳入临床成像系统所需的第一步。该项目将改进模拟的建模和准确性,并将工作扩展到具有类似挑战的其他成像模式,如正电子发射断层扫描(PET)。**FFMCT是在我的实验室开发的,它有可能通过根据成像任务的目标改变CT扫描仪的操作来改变CT技术。它涉及在图像采集期间动态调整X射线注量模式,以便针对特定感兴趣区域调整图像质量和剂量。FFMCT可以减少对不感兴趣的敏感组织(例如,肺部筛查中的乳腺组织)的剂量,从而降低暴露风险,同时确保或改善现有CT图像质量。新的基于纳米技术的X射线发射器将使我们能够开发一种具有多个可编程源的新型FFMCT原型;这种方法还将利用我实验室正在推进的基于物理的模型。
英文摘要
X-ray computed tomography (CT) produces detailed images of the body and is a critical tool in health care. These systems are employed in every facet of medicine from cancer screening to assessing injuries to guiding treatments such as radiotherapy and surgery. ******However, there is significant opportunity enhance CT technology by better exploiting the underlying physics to improve image quality and minimize the radiation dose to patients. This program of research builds upon over 20 years of experience in X-ray imaging methods and system development to develop next-generation CT methods that leverage advances in computational methods, mechatronics, and nanotechnology. The research focuses on two major topics:***1. Improving image quality by using physics-based models to correct for unwanted X-ray scatter***2. Lowering the risk associated with CT imaging using a novel approach called fluence-field modulated CT (FFMCT). ******In brief, CT works by sending a beam of X-rays from an emitter through the patient to a detector. The signal changes depending on what's in-between the two, e.g. with bone blocking more X-rays than muscle. However, some X-rays are scattered and didn't follow a straight line through the patient. These scattered X-rays have a significant effect on image quality, which is exacerbated in cone beam CT (CBCT) due to the volume of tissue irradiated and lack of a rejection method. Accurate modeling of the physics underlying scatter with Monte Carlo (MC) simulations allows us to better understand and correct for scatter, leading to improved images and patient dose management. We recently made the simulations more efficient and faster, a first step needed to incorporate them in clinical imaging systems. This project will improve the modelling and accuracy of the simulations, and extend the work to other imaging modalities with similar challenges such as positron emission tomography (PET). ******FFMCT was developed in my laboratory and has the potential to transform CT technology by changing the operation of the CT scanner depending on the objective of the imaging task. It involves dynamically adjusting the X-ray fluence pattern during image acquisition so that the image quality and dose are adjusted for specific regions-of-interest. FFMCT can reduce dose to sensitive tissues not of interest (e.g. breast tissue in lung screening)and as a result lower the exposure risk while assuring or improving upon existing CT image quality. New nanotechnology-based X-ray emitters will let us develop a novel FFMCT prototype with multiple programmable sources; this approach will also leverage the physics-based models being advanced in my lab.
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Advanced Strategies for Image Quality Improvement and Dose Reduction in CT
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    RGPIN-2014-05017
  • 项目类别:
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  • 资助金额:
    $2.62万
  • 财政年份:
    2018
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Advanced Strategies for Image Quality Improvement and Dose Reduction in CT
  • 批准号:
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  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
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  • 财政年份:
    2017
  • 负责人:
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Advanced Strategies for Image Quality Improvement and Dose Reduction in CT
  • 批准号:
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  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $2.62万
  • 财政年份:
    2016
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