首页> 外文学位 >Absolute quantification of pharmaco-kinetic parameters in dynamic contrast enhanced magnetic resonance imaging.
【24h】

Absolute quantification of pharmaco-kinetic parameters in dynamic contrast enhanced magnetic resonance imaging.

机译:动态对比增强磁共振成像中药代动力学参数的绝对定量。

获取原文
获取原文并翻译 | 示例

摘要

We present a method for absolutely quantifying pharmacokinetic parameters in dynamic contrast-enhanced (DCE)-MRI. This method, known as alternating minimization with model (AMM), involves jointly estimating the arterial input function (AIF) and pharmacokinetic parameters from a characteristic set of measured tissue concentration curves. By blindly estimating the AIF, problems associated with AIF measurement in pharmacokinetic modeling, such as signal saturation, flow and partial volume effects, and small arterial lumens can be ignored. The blind estimation method described here introduces a novel functional form for the AIF, which serves to simplify the estimation process and reduce the deleterious effects of noise on the deconvolution process. Computer simulations were undertaken to assess the performance of the estimation process as a function of the input tissue curves. A confidence metric for the estimation quality, based on a linear combination of the SNR and diversity of the input curves, is presented. This confidence metric is then used to allow for localizing the region from which input curves are drawn. Local blood supply to any particular region can then be blindly estimated, along with some measure of confidence for that estimation. Methods for evaluating the utility of the blind estimation algorithm on clinical data are presented, along with preliminary results on quantifying tissue parameters in soft-tissue sarcomas.;The AMM method is applied to in vivo data from both cardiac perfusion and breast cancer scans. The cardiac scans were conducted using a dual-bolus protocol, which provides a measure of truth for the AIF. Twenty data sets were processed with this method, and pharmacokinetic parameter values derived from the blind AIF were compared with those derived from the dual-bolus measured AIF. For seventeen of the twenty datasets there were no statistically significant differences in Ktrans estimates. The cardiac AMM method presented here provides a way to quantify perfusion of myocardial tissue with a single injection of contrast agent and without a special pulse sequence. The resulting parameters are similar to those given by the dual bolus method. The breast cancer scans were processed with the AMM method and the results were compared to an analysis done with the semiquantitative DCE-MRI scans. The effects of the temporal sampling rate of the data on the AMM method are examined. The ability of the AMM-derived parameters to distinguish benign and malignant tumors is compared to more conventional methods.
机译:我们提出了一种在动态对比增强(DCE)-MRI中绝对定量药代动力学参数的方法。这种方法称为模型交替最小化(AMM),涉及从一组测量的组织浓度曲线的特征集中共同估计动脉输入功能(AIF)和药代动力学参数。通过盲目估计AIF,可以忽略与药物动力学模型中AIF测量相关的问题,例如信号饱和度,流量和部分体积效应以及小动脉腔。这里描述的盲估计方法为AIF引入了一种新颖的函数形式,该函数形式可以简化估计过程并减少噪声对反卷积过程的有害影响。进行计算机模拟以评估估计过程的性能,作为输入组织曲线的函数。提出了基于SNR和输入曲线的多样性的线性组合的估计质量的置信度。然后使用此置信度度量来定位从中绘制输入曲线的区域。然后可以盲目估计到任何特定区域的局部血液供应,以及对该估计值的某种置信度。提出了评估盲估计算法对临床数据效用的方法,以及量化软组织肉瘤组织参数的初步结果。AMM方法应用于心脏灌注和乳腺癌扫描的体内数据。使用双重推注方案进行心脏扫描,该方案可提供AIF的真实程度。用此方法处理了20个数据集,并将盲AIF所得的药代动力学参数值与双推注AIF所得的药代动力学参数值进行了比较。在20个数据集中的17个数据集中,Ktrans估算值没有统计学上的显着差异。此处介绍的心脏AMM方法提供了一种方法,可以通过单次注射造影剂而无特殊脉冲序列来量化心肌组织的灌注。结果参数与双重推注方法给出的参数相似。使用AMM方法处理乳腺癌扫描,并将结果与​​使用半定量DCE-MRI扫描进行的分析进行比较。研究了数据的时间采样率对AMM方法的影响。将AMM衍生的参数区分良性和恶性肿瘤的能力与更常规的方法进行了比较。

著录项

  • 作者

    Fluckiger, Jacob U.;

  • 作者单位

    The University of Utah.;

  • 授予单位 The University of Utah.;
  • 学科 Engineering Biomedical.;Health Sciences Radiology.
  • 学位 Ph.D.
  • 年度 2011
  • 页码 103 p.
  • 总页数 103
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

  • 入库时间 2022-08-17 11:44:42

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号