Diagnosis of luteal and follicular ovarian cysts in dairy cows by sector scan ultrasonography.
Sixty-seven ultrasonograms of ovarian cysts (cysts) from 35 cows were used to evaluate sector scan ultrasonography as a means for differentiating luteal cysts from follicular cysts. Initial diagnosis of cysts was made by ovarian palpation per rectum during weekly herd visits. The ovaries of each cow were then examined by ultrasonography. Ultrasonograms of cysts > 25 mm in diameter were diagnosed as either luteinized or follicular cysts and were recorded on video tape for evaluation by a second clinician. Serum progesterone concentrations at the time of examination were determined by radioimmunoassay and were used to classify luteal (> 0.5 ng/ml) or follicular (</= 0.5 ng/ml) cysts. Mean serum progesterone concentrations were 1.41 +/- 0.14 ng/ml for cows diagnosed as having luteal cysts (n = 49) and 0.40 +/- 0.13 ng/ml for cows with follicular cysts (n = 18). Sensitivity of ultrasonography for correct diagnosis of luteinized cysts was 91.5%, however, specificity was only 70.0%. Sensitivity (93.1 versus 88.9%) and specificity (75.0 versus 68.8%) were similar for cystic cows that received treatment (either gonadotropin-releasing hormone, GnRH, or prostaglandin F(2)alpha, PGF) 7 d prior to examination (n = 33) compared with cows that received no previous treatment (n = 34). Agreement between the two clinicians when diagnosing type of cyst was 80.6% (Kappa=0.5). Agreement between the two clinicians' diagnoses as well as with the progesterone classification was higher for luteal cysts (92.6%) than for follicular cysts (75.0%). Results of this study suggest that, based on serum progesterone, luteal and follicular cysts can be differentiated by means of sector scan ultrasonography; however, sector scan ultrasonography is more effective for diagnosing luteinized cysts.
Farin
P W
PW
Department of Veterinary Medicine and Surgery University of Missouri-Columbia, Columbia, MO 65211 USA.
Youngquist
R S
RS
Parfet
J R
JR
Garverick
H A
HA