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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）：尽管对辐射剂量存在广泛的担忧，但CT仍在许多临床试验中广泛用于评估治疗反应。已经有了显著的发展，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，这些技术承诺在保持临床图像质量的同时显著减少患者的剂量（50- 60%）。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。简单地降低管电流时间积（mAs）将增加图像噪声，这可能会增加定量测量的可变性。根据解剖区域，尺寸测量可能受到不同的影响;肺部病变（通常是高对比度对象）可能受到与肝脏病变（通常是高对比度对象）不同的影响。较低的对比度）。使用对比度增强研究时测量的峰值也可能对剂量降低产生不同的反应。此外，由于新的迭代重建方法减少了噪声，它们通常也会在一定程度上平滑图像，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降低方法对临床试验中使用的定量指标的影响。我们的目标是确定在不同条件下，我们可以在多大程度上减少剂量，然后我们增加方差到不可接受的水平，在临床试验的背景下，使用定量措施来评估对治疗的反应。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的病例集。这将使用校准的剂量降低模拟方法（噪声插入工具）完成，然后在各种剂量降低水平和重建方法下重建图像。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，并分析剂量水平和重建方法之间定量测量的方差。第三个将使用第二个目标的分析结果，以评估减少剂量成像效果的前瞻性临床试验。总体目标是为QIN和一般临床试验提供关于使用标准化方案和使用剂量降低方法的指导，最终目标是确定在几个评估任务/环境中产生可接受水平的测量方差的剂量降低水平。