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Quantitative CT Imaging for Response Assessment when using Dose Reduction Methods

使用剂量减少方法时用于疗效评估的定量 CT 成像

基本信息

批准号：
9055664
负责人：
MATTHEW S BROWN
金额：
$ 39.39万
依托单位：
UNIVERSITY OF CALIFORNIA LOS ANGELES
依托单位国家：
美国
项目类别：
财政年份：
2014
资助国家：
美国
起止时间：
2014-05-01 至 2018-04-30
项目状态：
已结题

项目摘要

DESCRIPTION (provided by applicant): Despite widespread concerns over radiation dose, CT continues to be widely used for assessing response to therapy in many clinical trials settings. There have been significant developments which allow the reduction of radiation dose from CT, including advances in iterative reconstruction techniques, detector technologies and others that promise significant dose reductions (50-60 percent) to patients, while maintaining clinical image quality. While these technologies should be investigated wherever possible in a clinical environment, their effects on quantitative measures extracted from CT images are unclear and need to be investigated before they are deployed in clinical trials. Simply reducing tube current time product (mAs) will increase image noise, which may increase variability in quantitative measures. Size measures may be affected differently depending on the anatomic region; lung lesions (typically high contrast objects) may be affected differently from liver lesions (typically lower contrast). Peak values measured when contrast enhanced studies are used may also respond to dose reductions differently. In addition, because new iterative reconstruction methods reduce noise, they often also smooth the image somewhat, which may affect size and density (e.g. average HU) measures. Therefore, this application proposes to systematically investigate the effects of radiation dose reduction methods on quantitative metrics used in clinical trials. The goal is to determine how far we can decrease dose under different conditions before we increase variance to unacceptable levels in the context of clinical trials using quantitative measures to assess response to therapy. We have proposed three specific aims to carry out this research. In the first aim, we propose to create a collection of cases that represen a range of low dose acquisition and reconstruction scenarios in specific quantitative imaging tasks. This will be accomplished using a calibrated dose reduction simulation method (noise insertion tool) and then reconstructing images under a wide variety of dose reduction levels and reconstruction methods. The second specific aim will be to extract quantitative Imaging measures from these reconstructed image data sets and analyze variance of quantitative measures across dose levels and reconstruction methods. The third will use the results of the second aim's analysis to evaluate reduced dose imaging effects in a prospective clinical trial. The overall goal is to provide guidance to the QIN, and clinical trials in general, regarding the use of both standardized protocols and the use of dose reduction methods, with the ultimate goal of determining the levels of dose reduction that yield acceptable levels of measurement variance in several assessment tasks/environments.

描述（由申请人提供）：尽管人们普遍担心辐射剂量，但 CT 仍然在许多临床试验环境中广泛用于评估治疗反应。已经取得了显着的进展，可以减少 CT 的辐射剂量，包括迭代重建技术、探测器技术和其他技术的进步，这些技术有望显着减少患者的剂量 (50-60%)，同时保持临床图像质量。虽然这些技术应尽可能在临床环境中进行研究，但它们对从 CT 图像中提取的定量测量的影响尚不清楚，需要在临床试验中部署之前进行研究。简单地减少管电流时间乘积 (mAs) 会增加图像噪声，这可能会增加定量测量的变异性。根据解剖区域的不同，尺寸测量可能会受到不同的影响；肺部病变（通常是高对比度物体）受到的影响可能与肝脏病变（通常是对比度较低）。使用对比增强研究时测量的峰值也可能对剂量减少有不同的反应。此外，由于新的迭代重建方法可以减少噪声，因此它们通常也会对图像进行一定程度的平滑，这可能会影响尺寸和密度（例如平均 HU）测量。因此，本申请提出系统地研究辐射剂量减少方法对临床试验中使用的定量指标的影响。目标是确定在使用定量措施评估治疗反应的临床试验中，在将方差增加到不可接受的水平之前，在不同条件下我们可以减少多少剂量。我们提出了开展这项研究的三个具体目标。在第一个目标中，我们建议创建一个案例集合，代表特定定量成像任务中的一系列低剂量采集和重建场景。这将使用校准的剂量减少模拟方法（噪声插入工具）然后在各种剂量减少水平和重建方法下重建图像来完成。第二个具体目标是从这些重建图像数据集中提取定量成像测量，并分析不同剂量水平和重建方法的定量测量的方差。第三个目标将使用第二个目标的分析结果来评估前瞻性临床试验中减少剂量的成像效果。总体目标是为 QIN 和一般临床试验提供有关标准化方案和剂量减少方法的使用的指导，最终目标是确定在多个评估任务/环境中产生可接受的测量方差水平的剂量减少水平。