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Time-lapse technology for embryo culture and selection
Culturing of human embryos in optimal conditions is crucial for a successful in vitro fertilisation (IVF) programme. In addition, the capacity to assess and rank embryos correctly for quality will allow for transfer of the potentially ‘best’ embryo first, thereby shortening the time to pregnancy, al...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Taylor & Francis
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7720962/ https://www.ncbi.nlm.nih.gov/pubmed/32096675 http://dx.doi.org/10.1080/03009734.2020.1728444 |
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author | Lundin, Kersti Park, Hannah |
author_facet | Lundin, Kersti Park, Hannah |
author_sort | Lundin, Kersti |
collection | PubMed |
description | Culturing of human embryos in optimal conditions is crucial for a successful in vitro fertilisation (IVF) programme. In addition, the capacity to assess and rank embryos correctly for quality will allow for transfer of the potentially ‘best’ embryo first, thereby shortening the time to pregnancy, although not improving cumulative pregnancy and live birth rates. It will also encourage and facilitate the implementation of single embryo transfers, thereby increasing safety for mother and offspring. Time-lapse technology introduces the concept of stable culture conditions, in connection with the possibility of continuous viewing and documenting of the embryo throughout development. However, so far, even when embryo quality scoring is based on large datasets, or when using the time-lapse technology, the morphokinetic scores are still mainly based on subjective and intermittent annotations of morphology and timings. Also, the construction of powerful algorithms for widespread use is hampered by large variations in culture conditions between individual IVF laboratories. New methodology, involving machine learning, where every image from the time-lapse documentation is analysed by a computer programme, looking for patterns that link to outcome, may in the future provide a more accurate and non-biased embryo selection. |
format | Online Article Text |
id | pubmed-7720962 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Taylor & Francis |
record_format | MEDLINE/PubMed |
spelling | pubmed-77209622020-12-10 Time-lapse technology for embryo culture and selection Lundin, Kersti Park, Hannah Ups J Med Sci Review Articles Culturing of human embryos in optimal conditions is crucial for a successful in vitro fertilisation (IVF) programme. In addition, the capacity to assess and rank embryos correctly for quality will allow for transfer of the potentially ‘best’ embryo first, thereby shortening the time to pregnancy, although not improving cumulative pregnancy and live birth rates. It will also encourage and facilitate the implementation of single embryo transfers, thereby increasing safety for mother and offspring. Time-lapse technology introduces the concept of stable culture conditions, in connection with the possibility of continuous viewing and documenting of the embryo throughout development. However, so far, even when embryo quality scoring is based on large datasets, or when using the time-lapse technology, the morphokinetic scores are still mainly based on subjective and intermittent annotations of morphology and timings. Also, the construction of powerful algorithms for widespread use is hampered by large variations in culture conditions between individual IVF laboratories. New methodology, involving machine learning, where every image from the time-lapse documentation is analysed by a computer programme, looking for patterns that link to outcome, may in the future provide a more accurate and non-biased embryo selection. Taylor & Francis 2020-02-25 /pmc/articles/PMC7720962/ /pubmed/32096675 http://dx.doi.org/10.1080/03009734.2020.1728444 Text en © 2020 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Review Articles Lundin, Kersti Park, Hannah Time-lapse technology for embryo culture and selection |
title | Time-lapse technology for embryo culture and selection |
title_full | Time-lapse technology for embryo culture and selection |
title_fullStr | Time-lapse technology for embryo culture and selection |
title_full_unstemmed | Time-lapse technology for embryo culture and selection |
title_short | Time-lapse technology for embryo culture and selection |
title_sort | time-lapse technology for embryo culture and selection |
topic | Review Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7720962/ https://www.ncbi.nlm.nih.gov/pubmed/32096675 http://dx.doi.org/10.1080/03009734.2020.1728444 |
work_keys_str_mv | AT lundinkersti timelapsetechnologyforembryocultureandselection AT parkhannah timelapsetechnologyforembryocultureandselection |