Department of Theriogenology, Faculty of Veterinary Medicine, Mansoura University, Mansoura, Egypt.
Center for Reproductive Biotechnology, Faculty of Veterinary Medicine, Mansoura University, Mansoura, Egypt.
Reprod Domest Anim. 2023 Nov;58(11):1525-1531. doi: 10.1111/rda.14464. Epub 2023 Aug 31.
The objective of this study was to investigate the reliability of corpus luteum and dominant follicles, imaging parameters on the plasma progesterone, and prediction of pregnancy in cows. In total, 48 cows were used in this study and underwent Ovsynch program. Ultrasound imaging of the ovaries was done at the time of PG shots. Corpus luteum diameter (CL_d), area (CL_area), volume (CL_vol), and pixels (CL_PXL), as well as dominant follicle diameter (F_d) and area (F_area), were estimated using the ImageJ program. Blood samples were taken to assess progesterone (P4) concentrations. Pregnancy status was determined at 32 ± 3 days after insemination using an ultrasound "Sonoscape-5 V." Data were analysed using correlation analysis and ROC curves. Plasma P4 concentration showed positive correlation with CL_d (r = .68, p < .01), CL_area (r = .45, p < .01), CL_volume (r = .41, p < .01), and CL_pixels (r = .67, p < .01). The ROC curve indicated that P4 concentrations and CL parameters, especially the CL_pixels, were the best predictors of the pregnancy, among the others that were able to detect pregnancy at the time of PG with the best P4 and CL_pixels cut-off value (4.1 ng/mL and 43.18) and AUC was (0.95 and 0.89); resp. (p < .001). Regarding the other parameters, it was possible to set AUC 0.79, 0.79, and 0.68 for CL_d, area, and volume with a sensitivity of 66.7%, 70.8%, and 66.7% and a specificity of 88.2%, 82.4%, and 70.4% (p < .01), respectively. The AUC for both the follicular diameter and F_area was (0.56) with a sensitivity of 58.33% and 70.8% and a specificity of 62.5% and 50% (p > .05), respectively. In conclusion, CL measurements and progesterone concentrations had the greatest pregnancy prediction in Holstein dairy cows.
本研究旨在探讨黄体和优势卵泡、血浆孕酮的影像学参数以及奶牛妊娠的预测可靠性。本研究共使用了 48 头奶牛，并进行了 Ovsynch 方案。在 PG 注射时进行卵巢超声成像。使用 ImageJ 程序估计黄体直径（CL_d）、面积（CL_area）、体积（CL_vol）和像素（CL_PXL）以及优势卵泡直径（F_d）和面积（F_area）。采集血样以评估孕酮（P4）浓度。在授精后 32 ± 3 天使用超声“Sonoscape-5V”确定妊娠状态。使用相关分析和 ROC 曲线分析数据。血浆 P4 浓度与 CL_d（r =.68，p <.01）、CL_area（r =.45，p <.01）、CL_volume（r =.41，p <.01）和 CL_pixels（r =.67，p <.01）呈正相关。ROC 曲线表明，P4 浓度和 CL 参数，尤其是 CL_pixels，是预测妊娠的最佳指标，其中其他能够在 PG 时检测到妊娠的指标，具有最佳的 P4 和 CL_pixels 截断值（4.1ng/mL 和 43.18）和 AUC（0.95 和 0.89）；分别。关于其他参数，可以设置 AUC 0.79、0.79 和 0.68 用于 CL_d、面积和体积，灵敏度为 66.7%、70.8%和 66.7%，特异性为 88.2%、82.4%和 70.4%（p <.01）。卵泡直径和 F_area 的 AUC 分别为（0.56），灵敏度分别为 58.33%和 70.8%，特异性分别为 62.5%和 50%（p>.05）。综上所述，CL 测量和孕酮浓度对荷斯坦奶牛的妊娠预测具有最大的预测价值。
