Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, Indiana, USA.
Med Phys. 2022 Feb;49(2):878-890. doi: 10.1002/mp.15405. Epub 2021 Dec 20.
The development of clinically meaningful, objective, and quantitative methods for assessing the performance of ultrasound imaging systems represents a continuing area of interest. One approach has been to image phantoms with randomly distributed spherical voids.
The objectives of this study were: (1) to explore the potential of using relatively high-volume fraction random spherical void (RSV) phantoms as an approach for quantitatively assessing the performance of ultrasound imaging systems; (2) to identify potential metrics that can be used to provide quantitative assessments of images obtained from relatively high-volume fraction RSV phantoms; and (3) to demonstrate changes in the quantitative metrics that can occur as image features are degraded.
A series (10 each) of computer-simulated RSV phantoms with a range of RSV volume fractions (0.05, 0.15, and 0.25) were generated. To determine the number of image planes necessary to provide robust measurements, a series of consecutive planes (ranging from 1 to 150) within each type of simulated phantom were analyzed. The observed circular cross-section radii histogram distributions (representing the intersection of each plane with the local distribution of spherical voids) were compared with the theoretical histogram distribution. Simulated phantom images were produced by adding speckle and degradation of imaging system performance was modeled by averaging 1 to 9 neighboring planes to represent increasing elevation plane thicknesses. Quantification of the performance of the imaging system was determined by measuring the: (1) mean number of circular cross-sections detected per image frame; (2) mean fractional area of circular cross-sections detected per image frame; (3) agreement of observed circular cross-section radii histogram distribution with the theoretical distribution (Chi-square statistic); and (4) contrast and contrast-to-noise ratio as a function of observed circular cross-section radius.
Results suggest that analyses of a sufficient number of image planes (providing over approximately 3000 total circular cross-sectional areas) provides excellent agreement between the observed and theoretical histogram distributions (mean Chi-square < 0.004). For the 0.15 volume fraction series of simulated RSV phantoms, using 150 image plane analyses, phantom images show decreasing mean number of circle cross-sections detected per frame (31.5 ± 0.3, 28.4 ± 0.3, 28.2 ± 0.3, 26.3 ± 0.3, and 25.3 ± 0.3); decreasing mean fractional area of circle cross-sections per frame (0.157 ± 0.002, 0.133 ± 0.001, 0.133 ± 0.001, 0.111 ± 0.001, and 0.108 ± 0.001); and a decreasing agreement with the theoretical histogram distribution of radii (Chi-square values: 0.070 ± 0.004, 0.140 ± 0.005, 0.149 ± 0.007, 0.379 ± 0.011, and 0.518 ± 0.010) for 1, 3, 5, 7, and 9 plane averages, respectively. Contrast and contrast-to-noise measurements as a function of observed circular cross-section radius also demonstrate marked changes with simulated image degradation.
Results of this simulation study suggest that analyses of images obtained from relatively high-density RSV phantoms may offer a promising approach for assessing ultrasound imaging systems. The proposed measurements appear to provide reproducible, robust, quantitative metrics that can be compared with corresponding theoretical values to provide quantifiable, objective metrics of imaging system performance.
开发具有临床意义、客观和定量的超声成像系统性能评估方法一直是人们关注的热点。一种方法是使用随机分布的球形空洞的体模进行成像。
本研究的目的是：（1）探索使用相对高体积分数的随机球形空洞（RSV）体模作为定量评估超声成像系统性能的方法的潜力；（2）确定可用于提供相对高体积分数 RSV 体模图像的定量评估的潜在指标；（3）证明随着图像特征的退化，定量指标可能发生的变化。
生成了一系列（每个 10 个）具有不同 RSV 体积分数（0.05、0.15 和 0.25）的计算机模拟 RSV 体模。为了确定提供可靠测量所需的图像平面数量，分析了每个类型的模拟体模中的一系列连续平面（从 1 到 150）。观察到的圆形横截面半径直方图分布（代表每个平面与局部球形空洞分布的交点）与理论直方图分布进行比较。通过添加散斑来产生模拟体模图像，并通过平均 1 到 9 个相邻平面来模拟成像系统性能的退化，以代表增加的高程平面厚度。通过测量以下内容来确定成像系统的性能：（1）每帧图像检测到的圆形横截面的平均数量；（2）每帧图像检测到的圆形横截面的平均分数区域；（3）观察到的圆形横截面半径直方图分布与理论分布的一致性（卡方统计量）；（4）观察到的圆形横截面半径的对比度和对比噪声比。
结果表明，对足够数量的图像平面（提供大约 3000 个总圆形横截面区域）进行分析可以在观察到的和理论直方图分布之间提供极好的一致性（平均卡方值<0.004）。对于模拟 RSV 体模的 0.15 体积分数系列，使用 150 个图像平面分析，体模图像显示出每帧检测到的圆形横截面数量减少（31.5±0.3、28.4±0.3、28.2±0.3、26.3±0.3 和 25.3±0.3）；每帧检测到的圆形横截面的平均分数区域减少（0.157±0.002、0.133±0.001、0.133±0.001、0.111±0.001 和 0.108±0.001）；与半径理论直方图分布的一致性降低（卡方值分别为 0.070±0.004、0.140±0.005、0.149±0.007、0.379±0.011 和 0.518±0.010），用于 1、3、5、7 和 9 个平面平均值。观察到的圆形横截面半径的对比度和对比噪声比测量值也显示出与模拟图像退化的显著变化。
这项模拟研究的结果表明，对来自相对高密度 RSV 体模的图像进行分析可能是评估超声成像系统的一种很有前途的方法。提出的测量方法似乎提供了可重复、稳健的定量指标，可以与相应的理论值进行比较，从而提供成像系统性能的可量化、客观的指标。
