SavedAdd your journal

Journals / Kocatepe Veteriner Dergisi / 2026 / Cilt: 16 Sayı: 3

Subjective Scoring Method for Evaluation of Uterine Echotexture to Detect Early Pregnancy in Holstein Cows and Heifers

Holstein Irkı İnek ve Düvelerde Uterus Ekotekstürünün Değerlendirilmesi için Yeni Bir Subjektif Skorlama Yöntemi

Kemal Tuna Olğaç(ANKARA UNIVERSITY, ANKARA FACULTY OF VETERINARY MEDICINE)0000-0001-9216-7059
Pages
326–333
Publication Date
2023-09-30
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The gray tone scoring analysis were concluded that the mean of gray tone scoring were not differed significantly in terms of means and two-way interactions between sampling time and pregnancy status (p>0.05).

📌 3 Key Takeaways

🎯
Objective & Hypothesis:In the study, it was aimed to develop a scoring scale, graded from 1 to 5, to identify different gray tones of the ultrasonographic images of uterus, and the pregnancy determination in cows was tried to make by the scoring technique, in the first 20 days after artificial insemination.
📊
Key Findings & Data:Sixty Holstein cows (n:30) and heifers (n:30) were enrolled in the study.
💡
Conclusion & Impact:The gray tone scoring analysis were concluded that the mean of gray tone scoring were not differed significantly in terms of means and two-way interactions between sampling time and pregnancy status (p>0.05).
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:düve · ekotekstür · inek

Abstract

In the study, it was aimed to develop a scoring scale, graded from 1 to 5, to identify different gray tones of the ultrasonographic images of uterus, and the pregnancy determination in cows was tried to make by the scoring technique, in the first 20 days after artificial insemination. Sixty Holstein cows (n:30) and heifers (n:30) were enrolled in the study. For each animal, two ultrasonographic images were taken (totally 1320 images) starting from the day of the artificial insemination (D0) until the 20th day (D20) on every other day. At the same time that images were taken, subjective scoring were made. Then, the images were evaluated to determine mean gray value (MGV) by ImageJ (ImageJ 1.53k; NIH, ABD) software. The obtained data at the end of the evaluations were analyzed in terms of age of animals (cow or heifer), the days of examinations (alternate days between D0 and D20) and the 28th day pregnancy status (pregnant or non-pregnant). Also score rates were given by one experienced and one inexperienced independent operators to determine scoring agreement level in terms of experience on the ultrasonographic examinations. The mean MGV values indicated statistically significant differences only between days of sampling (p<0.05). On the other hand, according to other main effects and interactions were not concluded with statistically significant differences (p>0.05). It has been determined that experienced (Rater 1) and inexperienced (Rater 2) raters have agreement (p<0.001) in poor level (κ=0.15). Moreover, scores of the Rater 1 (0.720) were observed that had higher level correlations than Rater 2 (0,541). The gray tone scoring analysis were concluded that the mean of gray tone scoring were not differed significantly in terms of means and two-way interactions between sampling time and pregnancy status (p>0.05). In conclusion, it has been observed that the 256 different shades of gray which is analyzed by computer assisted image analysis could be identified by human eye in a 5 graded scale. However, the endometrium of the ovulation side uterine horn reflects the same differentiation in the presence or absence of pregnancy, in the first 20 days.

Özet

Çalışmada uterusun ultrasonografik görüntülerinin farklı gri tonlarını belirlemek için 1 ile 5 arasında derecelendirilen bir skorlama skalası geliştirilmesi amaçlanmış ve çalışmada ineklerde tohumlama sonrası ilk 20 gün içinde bu skorlama yöntemi ile gebelik tespitinin gerçekleştirilmesi araştırılmıştır. Çalışmada 60 adet Holstein inek (n:30) ve düve (n:30) kullanıldı. Her bir hayvandan suni tohumlamanın yapıldığı günden başlayarak 20. güne kadar gün aşırı olmak üzere en az iki adet (toplam 1320 adet) ultrasonografik uterus görüntüsü alındı. Subjektif skorlamalar bir deneyimli ve bir deneyimsiz olmak üzere iki bağımsız uygulayıcı tarafından gerçekleştirildi. Aynı görüntüler, ImageJ (ImageJ 1.53k; NIH, ABD) yazılımı ile Ortalama Grilik Değeri (MGV) değerlerinin belirlenmesi açısından analiz edildi. Veriler, hayvanların yaşı (inek veya düve), muayene günleri (D0 - D20) ve 28. gün gebelik durumu (gebe veya gebe değil) açısından değerlendirildi. Ortalama MGV değerleri sadece örnekleme günleri arasında istatistiksel olarak anlamlı farklılıklar gösterdi (p<0,05). Diğer ana etkilere ve etkileşimlere göre elde edilen farklılıklar istatistiksel olarak anlamsız bulundu (p>0,05). Deneyimli (1. skorlayıcı) ve deneyimsiz (2. skorlayıcı) skorlayıcıların uyumlarının zayıf düzeyde (κ=0,15) olduğu belirlendi (p<0,001). Ayrıca, 1. skorlayıcının (0,720) 2. skorlayıcıya göre (0,541) MGV değerleri ile daha yüksek korelasyona sahip olduğu belirlendi. Gri tonu skorlama ile gebelik belirlenmesi analizinde anlamlı bir farklılık bulunmadı (p>0,05). Sonuç olarak, bilgisayar destekli görüntü analizi ile değerlendirilen grinin 256 farklı tonunun (MGV) insan gözü tarafından 5 dereceli bir ölçekte tanımlanabildiği sonucu elde edilmiştir. Ancak gebe olan ve olmayan inek ve düvelerde uterus endometriyumunun ekotekstür yapısının suni tohumlama sonrası ilk 20 gün içinde benzer olduğu gözlemlenmiştir

🔖

Cite This Article

Olğaç, K. T. (2023). Subjective Scoring Method for Evaluation of Uterine Echotexture to Detect Early Pregnancy in Holstein Cows and Heifers. Kocatepe Veteriner Dergisi, Cilt: 16 Sayı: 3, 326–333. https://doi.org/10.30607/kvj.1319566

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (25)

  1. Abdalla, H., Salem, S. E., Elsohaby, I., & Swelum, A. A. (2021). Likelihood of pregnancy in cows identified with different amounts of anechoic intrauterine fluid at the time of insemination. Animal Reproduction Science, 226, 106688.
  2. Camela, E. S., Nociti, R. P., Santos, V. J., Macente, B. I., Murawski, M., Vicente, W. R., Bartlewski, P. M., & Oliveira, M. E. F. (2019). Changes in testicular size, echotexture, and arterial blood flow associated with the attainment of puberty in Dorper rams raised in a subtropical climate. Reproduction in Domestic Animals, 54, 131-137.
  3. Cengiz, M., Çolak, A., Hayırlı, A., & Cannazik, O. (2017). Optical density changes in ultrasonographic images of the endometrium and corpus luteum in pregnant and cyclic cows. Turkish Journal of Veterinary and Animal Science, 41, 18-24.
  4. Cengiz, M., Kanca, H., Salar, S., Bastan, A., Kucukaslan, I., Alkan, H., Karakas, K., Yuksel, O., & Hayırlı H. (2014). Endometrial echotexture parameters in Turkish Saanen Goats (Akkeci) during oestrus and early pregnancy. Animal Reproduction Science, 146, 27-33.
  5. Dietrich, C. F., Wehrmann, T., Zeuzem, S., Braden, B., Caspary, W. F., & Lembcke, B. (1999). Analysis of hepatic echo patterns in chronic hepatitis C. Ultraschall in der Medizin 20(1), 9-14.
  6. Giordano, J. O., Thomas, M. J., Catucuamba, G., Curler, M. D., Wijma, R., Stangaferro, M. L., & Masello, M. (2016). Effect of extending the interval from Presynch to initiation of Ovsynch in a Presynch-Ovsynch protocol on fertility of timed artificial insemination services in lactating dairy cows. Journal of Dairy Science, 99(1), 746-757.
  7. Gordon, M. B., Dinn, N., & Rajamahendran, R. (2010). Effects of presynchronization and postinsemination treatments on pregnancy rates to a timed breeding Ovsynch protocol in dairy cows and heifers. Canadian Journal of Animal Science, 90(1), 35-44.
  8. Holm, D. E., Nielen, M., Jorritsma, R., Irons, P. C., & Thompson, P. N. (2015). Evaluation of pre-breeding reproductive tract scoring as a predictor of long term reproductive performance in beef heifers. Preventive Veterinary Medicine, 118, 56–63.
  9. Kauffold, J., von dem Bussche, B., Failing, K., Wehrend, A., & Wendt, M. (2010). Use of B-mode ultrasound and grey-scale analysis to study uterine echogenicity in the pig. Journal of Reproduction and Development, 56, 444-448.
  10. Lee, S. H., Lee, S. H., Chan, V. W., Lee, J. O., & Kim, H. I. (2011). Echotexture and correlated histologic analysis of peripheral nerves important in regional anesthesia. Regional Anesthesia & Pain Medicine, 36(4), 382-386. Martinoli, C., Derchi, L. E., Pastorino, C., Bertolotto, M., & Silvestri, E. (1993). Analysis of echotexture of tendons with US. Radiology, 186(3), 839-843.
  11. McCue, P. M., Scoggin, C. F., & Lindhom, A. R. G. (2011). Estrus. In: Equine Reproduction. (McKinnon, A. O., E. L. Squires, W. E. Vaala, D. D. Varner, Eds.), WilleyBlackwell, Oxford, UK, pp. 1716-1727.
  12. McKinnon, A. O., & Carnevale, E. M. (1993). Ultrasonography. In: Equine Reproduction. (McKinnon, A.O., J. L. Voss, Eds.), Lea & Febiger, Malvern, Pennsylvania, pp. 211-220.
  13. Mee, J. F., Buckley, F., Ryan, D., & Dillon, P. (2009). Pre-breeding ovaro-uterine ultrasonography and its relationship with first service pregnancy rate in seasonal-calving dairy herds. Reproduction in Domestic Animals, 44, 331–337.
  14. Pierson, R. A., & Adams, G. P. (1995). Computer-assisted image analysis, diagnostic ultrasonography and ovulation induction: strange bedfellows. Theriogenology, 43(1), 105-112. Pierson, R. A., & Ginther, O. J. (1984). Ultrasonography for detection of pregnancy and study of embryonic development in heifers. Theriogenology, 22, 225–233.
  15. Ribadu, A. Y., & Nakao, T. (1999). Bovine reproductive ultrasonography: a review. Journal of Reproduction and Development, 45(1), 13-28.
  16. Samper, J. C. (2010). A review of a practitioner's perspective on endometrial edema. Pferdehelkunde 26, 14-18.
  17. Sarwal, A., Parry, S. M., Berry, M. J., Hsu, F. C., Lewis, M. T., Justus, N. W., Morris, P. E., Denehy, L., Berney, S., Dhar, S., & Cartwright, M. S. (2015). Interobserver reliability of quantitative muscle sonographic analysis in the critically ill population. Journal of Ultrasound in Medicine, 34(7), 1191-1200.
  18. Schmauder, S., Weber, F., Kiossis, E., & Bollwein H. (2008). Cyclic changes in endometrial echotexture of cows using a computer-assisted program for the analysis of first-and second-order grey level statistics of B-Mode ultrasound images. Animal Reproduction Science, 106, 153-161.
  19. Scully, S., Butler, S. T., Kelly, A. K., Evans, A. C. O., Lonergan, P., & Crowe, M. A. (2014). Early pregnancy diagnosis on days 18 to 21 postinsemination using high-resolution imaging in lactating dairy cows. Journal of Dairy Science, 97, 3542-3557.
  20. Scully, S., Evans, A., Carter, F., Duffy, P., Lonergan, P., & Crowe, M. (2015). Ultrasound monitoring of blood flow and echotexture of the corpus luteum and uterus during early pregnancy of beef heifers. Theriogenology, 83, 449-458.
  21. Souza, A. H., Silva, E. P., Cunha, A. P., Gumen, A., Ayres, H., Brusveen, D. J., Guenther, J. N., & Wiltbank, M. C. (2011). Ultrasonographic evaluation of endometrial thickness near timed AI as a predictor of fertility in high-producing dairy cows. Theriogenology, 75, 722–733.
  22. Stevenson, J. L., Rodrigues, J. A., Braga, F. A., Bitente, S., Dalton, J. C., Santos, J. E., & Chebel, R. C. (2008). Effect of breeding protocols and reproductive tract score on reproductive performance of dairy heifers and economic outcome of breeding programs. Journal of Dairy Science, 91, 3424–3438.
  23. Themistokleous, K. S., Sakellariou, N., & Kiossis, E. (2022). A deep learning algorithm predicts milk yield and production stage of dairy cows utilizing ultrasound echotexture analysis of the mammary gland. Computers and Electronics in Agriculture, 198, 106992.
  24. Vasconcelos, J. L. M., Sartori, R., Oliveira, H.N., Guenther, J. G., & Wiltbank, M. C. (2001). Reduction in size of the ovulatory follicle reduces subsequent luteal size and pregnancy rate. Theriogenology, 56, 307-314. Vollmerhaus, B. (1958). Die zyklischen Veranderungen des Endometriums beim Rind. Deutsche tierärztliche Wochenschrift, 65, 461–465.
  25. Zagzebski, J. A. (1996). Essentials of ultrasound physics. Mosby, St. Louis