Kim Sun Mo, Haider Masoom A, Jaffray David A, Yeung Ivan W T
Radiation Medicine Program, Princess Margaret Hospital/University Health Network, Toronto, Ontario M5G 2M9, Canada.
Department of Medical Imaging, Sunnybrook Health Sciences Centre, Toronto, Ontario M4N 3M5, Canada and Department of Medical Imaging, University of Toronto, Toronto, Ontario M5G 2M9, Canada.
Med Phys. 2016 Jan;43(1):388. doi: 10.1118/1.4937600.
A previously proposed method to reduce radiation dose to patient in dynamic contrast-enhanced (DCE) CT is enhanced by principal component analysis (PCA) filtering which improves the signal-to-noise ratio (SNR) of time-concentration curves in the DCE-CT study. The efficacy of the combined method to maintain the accuracy of kinetic parameter estimates at low temporal resolution is investigated with pixel-by-pixel kinetic analysis of DCE-CT data.
The method is based on DCE-CT scanning performed with low temporal resolution to reduce the radiation dose to the patient. The arterial input function (AIF) with high temporal resolution can be generated with a coarsely sampled AIF through a previously published method of AIF estimation. To increase the SNR of time-concentration curves (tissue curves), first, a region-of-interest is segmented into squares composed of 3 × 3 pixels in size. Subsequently, the PCA filtering combined with a fraction of residual information criterion is applied to all the segmented squares for further improvement of their SNRs. The proposed method was applied to each DCE-CT data set of a cohort of 14 patients at varying levels of down-sampling. The kinetic analyses using the modified Tofts' model and singular value decomposition method, then, were carried out for each of the down-sampling schemes between the intervals from 2 to 15 s. The results were compared with analyses done with the measured data in high temporal resolution (i.e., original scanning frequency) as the reference.
The patients' AIFs were estimated to high accuracy based on the 11 orthonormal bases of arterial impulse responses established in the previous paper. In addition, noise in the images was effectively reduced by using five principal components of the tissue curves for filtering. Kinetic analyses using the proposed method showed superior results compared to those with down-sampling alone; they were able to maintain the accuracy in the quantitative histogram parameters of volume transfer constant [standard deviation (SD), 98th percentile, and range], rate constant (SD), blood volume fraction (mean, SD, 98th percentile, and range), and blood flow (mean, SD, median, 98th percentile, and range) for sampling intervals between 10 and 15 s.
The proposed method of PCA filtering combined with the AIF estimation technique allows low frequency scanning for DCE-CT study to reduce patient radiation dose. The results indicate that the method is useful in pixel-by-pixel kinetic analysis of DCE-CT data for patients with cervical cancer.
一种先前提出的在动态对比增强（DCE）CT中减少患者辐射剂量的方法通过主成分分析（PCA）滤波得到了改进，该滤波提高了DCE-CT研究中时间-浓度曲线的信噪比（SNR）。通过对DCE-CT数据进行逐像素动力学分析，研究了该组合方法在低时间分辨率下保持动力学参数估计准确性的有效性。
该方法基于以低时间分辨率进行的DCE-CT扫描，以减少患者的辐射剂量。通过先前发表的动脉输入函数（AIF）估计方法，可以利用粗略采样的AIF生成具有高时间分辨率的AIF。为了提高时间-浓度曲线（组织曲线）的SNR，首先，将感兴趣区域分割成大小为3×3像素的正方形。随后，将PCA滤波与部分残余信息准则相结合，应用于所有分割后的正方形，以进一步提高其SNR。将所提出的方法应用于14名患者队列的每个DCE-CT数据集，进行不同程度的下采样。然后，在2至15秒的时间间隔内，对每个下采样方案使用改进的Tofts模型和奇异值分解方法进行动力学分析。将结果与以高时间分辨率（即原始扫描频率）的测量数据作为参考进行的分析进行比较。
基于先前论文中建立的11个动脉脉冲响应的正交基，对患者的AIF进行了高精度估计。此外，通过使用组织曲线的五个主成分进行滤波，有效降低了图像中的噪声。与仅进行下采样的方法相比，使用所提出方法进行的动力学分析显示出更好的结果；对于10至15秒的采样间隔，它们能够保持体积转移常数[标准差（SD）、第98百分位数和范围]、速率常数（SD）、血容量分数（平均值、SD、第98百分位数和范围）以及血流量（平均值、SD、中位数、第98百分位数和范围）的定量直方图参数的准确性。
所提出的PCA滤波与AIF估计技术相结合的方法允许在DCE-CT研究中进行低频扫描，以减少患者的辐射剂量。结果表明，该方法在宫颈癌患者的DCE-CT数据逐像素动力学分析中是有用的。
