Corpus luteum blood flow evaluation on Day 21 to improve the management of embryo recipient herds

The aim of the present study was to use blood flow evaluation of the CL at 14 days after embryo transfer to detect nonpregnant animals and optimize the management of bovine recipients. The estrous cycle was synchronized in 165 recipients, and the day of expected ovulation was considered to be Day 0. Embryo transfer was performed 7 days later, on Day 7. On Day 21, pregnancy was diagnosed on the basis of blood flow evaluation of the CL (DG21-predictive diagnostic). To validate this methodology, visual scores for blood flow were compared to objective data extracted from CL ultrasound images recorded in the Doppler mode. The size was also evaluated using recorded images of the CL in the B mode. Blood samples were also collected for further analysis of the progesterone (P4) concentration. The diagnosis of pregnancy was confirmed at 35 days after estrus (DG35-definitive diagnostic). The DG21 showed that 55.2% (90 of 163) of the animals were presumptively pregnant, and this value was higher (P < 0.04) than that obtained at DG35 (43.6%, 71 of 163). The predictive diagnostic achieved moderate specificity (79.3%) for the detection of pregnancy, but most importantly, high sensitivity (100%) for the detection of nonpregnant recipients. The overall accuracy of the diagnosis was 88.3%. The P4 concentrations were different (P < 0.02) and correlated with each visual score assigned for the CL size. Visual scores for CL blood flow were also efficient (P < 0.0001) to distinguish animals with different levels of P4; however, P4 concentrations were higher for scores 1 and 2 (high and regular blood flow, respectively) than those for score 3 (low blood flow). This technique showed high sensitivity and facilitated the early detection of nonpregnant animals. The DG21 would allow about 793% of nonpregnant animals to be resynchronized 9 to 14 days earlier, when compared to conventional management based on pregnancy diagnosis at Days 30 to 35. (C) 2015 Elsevier Inc. All rights reserved.