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）：尽管对放射剂量提出了广泛关注，但在许多临床试验环境中，CT仍在广泛地用于评估对治疗的反应。有很大的发展，可以减少CT的辐射剂量，包括迭代重建技术的进步，检测器技术和其他承诺对患者进行显着剂量减少（50-60％）的其他方面的进步，同时保持临床图像质量。尽管应在临床环境中尽可能研究这些技术，但它们对从CT图像提取的定量措施的影响尚不清楚，需要在将其部署在临床试验中之前进行研究。简单地减少管电流时间产品（MAS）将增加图像噪声，这可能会增加定量测量的变异性。根据解剖区域的不同，大小测量的影响可能会有所不同。肺部病变（通常为高对比对象）可能与肝病变化不同（通常较低对比度）。当使用对比度增强研究时，测量的峰值也可能对降低剂量的降低有所不同。此外，由于新的迭代重建方法降低了噪声，因此它们通常也会在某种程度上平滑图像，这可能会影响大小和密度（例如平均HU）度量。因此，该应用建议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。目的是确定在不同条件下可以减少剂量的多远，然后在临床试验的背景下，使用定量措施将差异提高到不可接受的水平，以评估对治疗的反应。我们提出了三个具体目标来进行这项研究。在第一个目的中，我们建议创建一系列案例，这些案例代表特定定量成像任务中的一系列低剂量获取和重建方案。这将使用校准的剂量还原模拟方法（噪声插入工具）来完成，然后在各种剂量降低水平和重建方法下重建图像。第二个具体目的是从这些重建的图像数据集中提取定量成像度量，并分析跨剂量水平和重建方法的定量度量方差。第三个将使用第二个目标分析的结果来评估一项前瞻性临床试验中的减少剂量成像效应。总体目的是为使用标准化方案和使用减少剂量的方法提供QIN和临床试验的指导，并最终确定剂量降低的水平，以在多种评估任务/环境中获得可接受的测量差异水平。