Clinical Physics Laboratory, Radboud University Medical Centre, Nijmegen, The Netherlands.
Anim Reprod Sci. 2011 Aug;127(1-2):7-15. doi: 10.1016/j.anireprosci.2011.07.006. Epub 2011 Jul 23.
In recent years, several attempts have been made to evaluate the activity of a corpus luteum by determining its sonographic echo texture. In all of these studies the values of the echo texture parameters depended on the type and settings of the ultrasound machine. Therefore, the aim of the study was to investigate if a quantitative analysis of ultrasound (US) images of the corpus luteum (CL) after calibration of the ultrasound machine enables the assessment of the peripheral plasma progesterone (P4) level. Ten Holstein Friesian cows were examined daily at Days 4 to 8, 10 to 16, and -5 to -1 (Day 1=ovulation) of the estrous cycle. B-mode sonography of the corpora lutea was performed and blood samples were taken for plasma P4 analysis. US images were calibrated and analyzed using a software package (CAUS) developed by the authors. In addition to the area of the CL (Total Area, TotA; Tissue Area interactive, TisAi; Tissue Area Automatic, TisAa), the following US parameters were calculated from the gray level histogram and from the size of the speckles: Mean, Standard Deviation (SD) and Signal-to-Noise Ratio (SNR=Mean/SD) of echo levels, Residual Attenuation (ResAtt), Axial and Lateral speckle size (Ax and Lat, respectively). The inter-individual variability of the P4 level was expressed by the coefficient of variability (CV), averaged over all days. It appeared that the CV of the absolute P4 was high (0.65) and the P4 relative to that at Day 4 and at Day 16 was of comparable magnitude. Correlations of US parameters with P4 were highest for the P4 relative to Day 16 (P4_rel_D16). This relative P4 measure was then used for further analysis. The correlations of P4_rel_D16 with TotA, TisAa (CL area after automatic segmentation of tissue) and ResAtt were found the highest (R=0.68, 0.74, and -0.42, respectively). Multiple linear regression analysis, incorporating all US parameters revealed the formula: P4_rel_D16(pred)=-0.315+0.225TisAa-0.023ResAtt, and a goodness of fit: R(2)=0.59 (p<0.001). This formula was then used to "predict" for each image the P4_rel_D16 from the estimated US parameters. A high correlation of the predicted with the measured P4_rel_D16 was found: R=0.77. Classification of images using the predicted P4_rel_D16 to be in the range >0.80 (corresponding to 0.95 times the average_P4_rel_D16 measured during the "static" phase of the luteal cycle) by ROC analysis was correctly made in 88% of cases. In conclusion the quantitative analysis of calibrated ultrasound images may yield a good prediction of cyclic changes of P4 levels and has potential for predicting the phase in the estrous cycle of a cow.
近年来，人们尝试通过确定黄体的超声回声纹理来评估黄体的活性。在所有这些研究中，回声纹理参数的值取决于超声仪器的类型和设置。因此，本研究的目的是探讨在对超声仪器进行校准后，对黄体的超声（US）图像进行定量分析是否能够评估外周血浆孕酮（P4）水平。10 头荷斯坦弗里生奶牛在发情周期的第 4-8 天、第 10-16 天和第-5 天至第-1 天（第 1 天=排卵）每天进行检查。对黄体进行 B 型超声检查，并采集血样进行血浆 P4 分析。使用作者开发的软件包（CAUS）对 US 图像进行校准和分析。除了黄体的面积（总面积，TotA；组织面积交互，TisAi；组织面积自动，TisAa）外，还从灰度直方图和斑点的大小计算以下 US 参数：回声水平的均值、标准差（SD）和信噪比（SNR=Mean/SD）、残余衰减（ResAtt）、轴向和侧向斑点大小（分别为 Ax 和 Lat）。P4 水平的个体间变异性用变异系数（CV）表示，即所有天数的平均值。结果表明，P4 的绝对变异系数（CV）较高（0.65），而与第 4 天和第 16 天相比的 P4 则具有相似的幅度。与 P4 相关性最高的是与第 16 天（P4_rel_D16）相关的 US 参数。然后使用此相对 P4 测量值进行进一步分析。与 P4_rel_D16 相关性最高的是 TotA、TisAa（组织自动分割后的黄体面积）和 ResAtt（R=0.68、0.74 和-0.42）。包含所有 US 参数的多元线性回归分析揭示了以下公式：P4_rel_D16（pred）=-0.315+0.225TisAa-0.023ResAtt，拟合度：R（2）=0.59（p<0.001）。然后，使用此公式根据估计的 US 参数“预测”每个图像的 P4_rel_D16。发现预测的 P4_rel_D16 与测量的 P4_rel_D16 之间存在高度相关性：R=0.77。使用预测的 P4_rel_D16 通过 ROC 分析将图像分类为范围>0.80（对应于黄体周期“静态”阶段测量的平均 P4_rel_D16 的 0.95 倍），正确分类了 88%的病例。总之，校准后的超声图像的定量分析可以很好地预测 P4 水平的周期性变化，并有可能预测奶牛发情周期的阶段。
