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Early Prediction of Corpus Luteum Functionality Using an Imaging Software

The present study aimed to assess the applicability of luteal blood flow data acquired through the use of color Doppler ultrasonography and a post-processing analysis tool (ImageJ) for predicting pregnancy in buffaloes (Bubalus bubalis). The experiment was carried out on 59 multiparous Italian Medit...

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Autores principales: Salzano, Angela, Russo, Marco, Anglani, Giuseppe, Licitra, Francesca, Zullo, Gianluigi, Cotticelli, Alessio, Fatone, Gerardo, Campanile, Giuseppe
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7314946/
https://www.ncbi.nlm.nih.gov/pubmed/32626727
http://dx.doi.org/10.3389/fvets.2020.00299
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author Salzano, Angela
Russo, Marco
Anglani, Giuseppe
Licitra, Francesca
Zullo, Gianluigi
Cotticelli, Alessio
Fatone, Gerardo
Campanile, Giuseppe
author_facet Salzano, Angela
Russo, Marco
Anglani, Giuseppe
Licitra, Francesca
Zullo, Gianluigi
Cotticelli, Alessio
Fatone, Gerardo
Campanile, Giuseppe
author_sort Salzano, Angela
collection PubMed
description The present study aimed to assess the applicability of luteal blood flow data acquired through the use of color Doppler ultrasonography and a post-processing analysis tool (ImageJ) for predicting pregnancy in buffaloes (Bubalus bubalis). The experiment was carried out on 59 multiparous Italian Mediterranean buffaloes that underwent synchronization of estrus and fixed-time artificial insemination (TAI). Corpus luteum features (size: CLS and blood flow: BFA) were taken from Day 5 to 10 after TAI and retrospectively measured with ImageJ. In the same period, blood samples were taken to assess progesterone (P(4)) concentrations. Pregnancy diagnosis was carried out on Day 45 by ultrasound and confirmed on Day 70 post-TAI. Differences in CLS, BFA, and P(4) concentrations from Day 5 to 10 after TAI measured between groups were analyzed by ANOVA repeated measures as were differences within each day of measuring. Buffaloes that established a pregnancy (n = 29; 55%) had larger CLS (2.2 ± 0.1 vs. 1.9 ± 0.1 cm(2); P < 0.01), higher BFA (0.6 ± 0.0 vs. 0.4 ± 0.0 cm(2); P < 0.01), and higher P(4) blood level (1.8 ± 0.1 vs. 1.4 ± 0.1; P < 0.01) during Day 5–10 as compared to not-pregnant buffaloes (n = 22). Throughout the entire period, the first feature that changed between groups was P(4) blood concentration at Day 7 (1.7 ± 0.1 vs. 1.2 ± 0.1; P < 0.05) followed by BFA at Day 8 (0.6 ± 0.0 vs. 0.5 ± 0.0; P < 0.05), respectively, in pregnant and not-pregnant animals. The ROC analyses indicated that P(4) was able to predict pregnancy since Day 5 (P < 0.05) although a more reliable result could be obtained from Day 8 (P < 0.01). At Day 10, it was possible to set a cutoff value for every parameter taken into account. The logistic regression analysis showed that pregnancy was positively influenced by P(4) concentration (odds ratio 534.127; P < 0.01) and BFA (odds ratio 744.893; P < 0.01). In conclusion, the use of color Doppler ultrasonography, together with ImageJ, identified different patterns of BFA between pregnant and not-pregnant buffaloes starting from Day 8 post-TAI.
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spelling pubmed-73149462020-07-02 Early Prediction of Corpus Luteum Functionality Using an Imaging Software Salzano, Angela Russo, Marco Anglani, Giuseppe Licitra, Francesca Zullo, Gianluigi Cotticelli, Alessio Fatone, Gerardo Campanile, Giuseppe Front Vet Sci Veterinary Science The present study aimed to assess the applicability of luteal blood flow data acquired through the use of color Doppler ultrasonography and a post-processing analysis tool (ImageJ) for predicting pregnancy in buffaloes (Bubalus bubalis). The experiment was carried out on 59 multiparous Italian Mediterranean buffaloes that underwent synchronization of estrus and fixed-time artificial insemination (TAI). Corpus luteum features (size: CLS and blood flow: BFA) were taken from Day 5 to 10 after TAI and retrospectively measured with ImageJ. In the same period, blood samples were taken to assess progesterone (P(4)) concentrations. Pregnancy diagnosis was carried out on Day 45 by ultrasound and confirmed on Day 70 post-TAI. Differences in CLS, BFA, and P(4) concentrations from Day 5 to 10 after TAI measured between groups were analyzed by ANOVA repeated measures as were differences within each day of measuring. Buffaloes that established a pregnancy (n = 29; 55%) had larger CLS (2.2 ± 0.1 vs. 1.9 ± 0.1 cm(2); P < 0.01), higher BFA (0.6 ± 0.0 vs. 0.4 ± 0.0 cm(2); P < 0.01), and higher P(4) blood level (1.8 ± 0.1 vs. 1.4 ± 0.1; P < 0.01) during Day 5–10 as compared to not-pregnant buffaloes (n = 22). Throughout the entire period, the first feature that changed between groups was P(4) blood concentration at Day 7 (1.7 ± 0.1 vs. 1.2 ± 0.1; P < 0.05) followed by BFA at Day 8 (0.6 ± 0.0 vs. 0.5 ± 0.0; P < 0.05), respectively, in pregnant and not-pregnant animals. The ROC analyses indicated that P(4) was able to predict pregnancy since Day 5 (P < 0.05) although a more reliable result could be obtained from Day 8 (P < 0.01). At Day 10, it was possible to set a cutoff value for every parameter taken into account. The logistic regression analysis showed that pregnancy was positively influenced by P(4) concentration (odds ratio 534.127; P < 0.01) and BFA (odds ratio 744.893; P < 0.01). In conclusion, the use of color Doppler ultrasonography, together with ImageJ, identified different patterns of BFA between pregnant and not-pregnant buffaloes starting from Day 8 post-TAI. Frontiers Media S.A. 2020-06-18 /pmc/articles/PMC7314946/ /pubmed/32626727 http://dx.doi.org/10.3389/fvets.2020.00299 Text en Copyright © 2020 Salzano, Russo, Anglani, Licitra, Zullo, Cotticelli, Fatone and Campanile. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Veterinary Science
Salzano, Angela
Russo, Marco
Anglani, Giuseppe
Licitra, Francesca
Zullo, Gianluigi
Cotticelli, Alessio
Fatone, Gerardo
Campanile, Giuseppe
Early Prediction of Corpus Luteum Functionality Using an Imaging Software
title Early Prediction of Corpus Luteum Functionality Using an Imaging Software
title_full Early Prediction of Corpus Luteum Functionality Using an Imaging Software
title_fullStr Early Prediction of Corpus Luteum Functionality Using an Imaging Software
title_full_unstemmed Early Prediction of Corpus Luteum Functionality Using an Imaging Software
title_short Early Prediction of Corpus Luteum Functionality Using an Imaging Software
title_sort early prediction of corpus luteum functionality using an imaging software
topic Veterinary Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7314946/
https://www.ncbi.nlm.nih.gov/pubmed/32626727
http://dx.doi.org/10.3389/fvets.2020.00299
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