Assessing morphokinetic parameters via time lapse microscopy (TLM) to predict euploidy: are aneuploidy risk classification models universal?
Purpose To determine if Aneuploidy Risk Classification Models are predictive of euploidy/aneuploidy amongst IVF facilities. Methods We retrospectively applied key time lapse imaging events of embryos (Campbell et al.[ 5 , 6 ]) to stratify embryos into 3 groups: low, medium and high risk of aneuploid...
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Veröffentlicht in: | Journal of assisted reproduction and genetics 2014-09, Vol.31 (9), p.1231-1242 |
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creator | Kramer, Yael G. Kofinas, Jason D. Melzer, Katherine Noyes, Nicole McCaffrey, Caroline Buldo-Licciardi, Julia McCulloh, David H. Grifo, James A. |
description | Purpose
To determine if Aneuploidy Risk Classification Models are predictive of euploidy/aneuploidy amongst IVF facilities.
Methods
We retrospectively applied key time lapse imaging events of embryos (Campbell et al.[
5
,
6
]) to stratify embryos into 3 groups: low, medium and high risk of aneuploidy. The actual ploidy results (from array comparative genomic hybridization) were compared with expectations [
5
,
6
]. Sources of variability in morphokinetic parameters were determined using Analysis of Variance (ANOVA).
Results
The model failed to segregate euploid embryos from aneuploid embryos cultured at our facility. Further analysis indicated that the variability of embryos among patients was too great to allow selection of euploid embryos based on simple morphokinetic thresholds. Clinical selection of embryos based on morphokinetics alone is unlikely to identify euploid embryos accurately for transfer or yield higher rates of live delivery.
Conclusions
The use of non-invasive morphokinetics is unlikely to discriminate aneuploid from euploid embryos. Further, it does not approach the accuracy of preimplantation genetic screening with array comparative genomic hybridization. |
doi_str_mv | 10.1007/s10815-014-0285-1 |
format | Article |
fullrecord | <record><control><sourceid>proquest_pubme</sourceid><recordid>TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_4156952</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>1561036315</sourcerecordid><originalsourceid>FETCH-LOGICAL-c573t-cddcdd4be3992f6a3730d05fd359aa6ce30c9ced7ee1f8cc1a2a8d94baa7420c3</originalsourceid><addsrcrecordid>eNqNkt9qFTEQxhdRbK0-gDcS8KZerE6S_ZP1olKK2sIRb-p1mJPMnqbd3azJ7oHzDj60WU5bWkEoBJIwv_kmk_my7C2Hjxyg_hQ5KF7mwIschCpz_iw75GUt81pKeJ7OUKocikodZK9ivAaARgn5MjsQRVOJWjWH2Z_TGClGN2xY78N45W_cQJMzbMSAPU0UIts6ZJPriXU4RmK9M8FH48cdO75c_fjAJs_GQNaZidE8dt7Z3WeGgRgOd3cWXLxhpsNUqnUGJ-eHVNBSF9k8uG0qg92X19mLFrtIb273o-zXt6-XZ-f56uf3i7PTVW5Sc1NurE2rWJNsGtFWKGsJFsrWyrJBrAxJMI0hWxPxVhnDUaCyTbFGrAsBRh5lJ3vdcV73ZA0NU8BOj8H1GHbao9OPI4O70hu_1QUvq6YUSeD4ViD43zPFSfcuGuq61LGfo05YpaRQSj4F5SArycuEvv8HvfZzGNJPLBQUcpltovieWqYQA7X37-agF1vovS10soVebKF5ynn3sOH7jDsfJEDsgZhCw4bCg9L_Vf0LJnnHcg</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1560431573</pqid></control><display><type>article</type><title>Assessing morphokinetic parameters via time lapse microscopy (TLM) to predict euploidy: are aneuploidy risk classification models universal?</title><source>MEDLINE</source><source>Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals</source><source>PubMed Central</source><source>SpringerLink Journals - AutoHoldings</source><creator>Kramer, Yael G. ; Kofinas, Jason D. ; Melzer, Katherine ; Noyes, Nicole ; McCaffrey, Caroline ; Buldo-Licciardi, Julia ; McCulloh, David H. ; Grifo, James A.</creator><creatorcontrib>Kramer, Yael G. ; Kofinas, Jason D. ; Melzer, Katherine ; Noyes, Nicole ; McCaffrey, Caroline ; Buldo-Licciardi, Julia ; McCulloh, David H. ; Grifo, James A.</creatorcontrib><description>Purpose
To determine if Aneuploidy Risk Classification Models are predictive of euploidy/aneuploidy amongst IVF facilities.
Methods
We retrospectively applied key time lapse imaging events of embryos (Campbell et al.[
5
,
6
]) to stratify embryos into 3 groups: low, medium and high risk of aneuploidy. The actual ploidy results (from array comparative genomic hybridization) were compared with expectations [
5
,
6
]. Sources of variability in morphokinetic parameters were determined using Analysis of Variance (ANOVA).
Results
The model failed to segregate euploid embryos from aneuploid embryos cultured at our facility. Further analysis indicated that the variability of embryos among patients was too great to allow selection of euploid embryos based on simple morphokinetic thresholds. Clinical selection of embryos based on morphokinetics alone is unlikely to identify euploid embryos accurately for transfer or yield higher rates of live delivery.
Conclusions
The use of non-invasive morphokinetics is unlikely to discriminate aneuploid from euploid embryos. Further, it does not approach the accuracy of preimplantation genetic screening with array comparative genomic hybridization.</description><identifier>ISSN: 1058-0468</identifier><identifier>EISSN: 1573-7330</identifier><identifier>DOI: 10.1007/s10815-014-0285-1</identifier><identifier>PMID: 24962789</identifier><language>eng</language><publisher>Boston: Springer US</publisher><subject>Analysis of Variance ; Aneuploidy ; Biopsy ; Comparative Genomic Hybridization ; Embryo Biology ; Embryonic Development ; Embryos ; Female ; Fertility ; Fertilization in Vitro ; Gynecology ; Human Genetics ; Humans ; Infertility ; Lasers ; Male ; Medicine ; Medicine & Public Health ; Microscopy ; Mineral oils ; Ovaries ; Patients ; Preimplantation Diagnosis - methods ; Reproductive Medicine ; Retrospective Studies ; Sperm ; Time-Lapse Imaging ; Variance analysis</subject><ispartof>Journal of assisted reproduction and genetics, 2014-09, Vol.31 (9), p.1231-1242</ispartof><rights>Springer Science+Business Media New York 2014</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c573t-cddcdd4be3992f6a3730d05fd359aa6ce30c9ced7ee1f8cc1a2a8d94baa7420c3</citedby><cites>FETCH-LOGICAL-c573t-cddcdd4be3992f6a3730d05fd359aa6ce30c9ced7ee1f8cc1a2a8d94baa7420c3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC4156952/pdf/$$EPDF$$P50$$Gpubmedcentral$$H</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC4156952/$$EHTML$$P50$$Gpubmedcentral$$H</linktohtml><link.rule.ids>230,314,723,776,780,881,27903,27904,41467,42536,51297,53769,53771</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/24962789$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Kramer, Yael G.</creatorcontrib><creatorcontrib>Kofinas, Jason D.</creatorcontrib><creatorcontrib>Melzer, Katherine</creatorcontrib><creatorcontrib>Noyes, Nicole</creatorcontrib><creatorcontrib>McCaffrey, Caroline</creatorcontrib><creatorcontrib>Buldo-Licciardi, Julia</creatorcontrib><creatorcontrib>McCulloh, David H.</creatorcontrib><creatorcontrib>Grifo, James A.</creatorcontrib><title>Assessing morphokinetic parameters via time lapse microscopy (TLM) to predict euploidy: are aneuploidy risk classification models universal?</title><title>Journal of assisted reproduction and genetics</title><addtitle>J Assist Reprod Genet</addtitle><addtitle>J Assist Reprod Genet</addtitle><description>Purpose
To determine if Aneuploidy Risk Classification Models are predictive of euploidy/aneuploidy amongst IVF facilities.
Methods
We retrospectively applied key time lapse imaging events of embryos (Campbell et al.[
5
,
6
]) to stratify embryos into 3 groups: low, medium and high risk of aneuploidy. The actual ploidy results (from array comparative genomic hybridization) were compared with expectations [
5
,
6
]. Sources of variability in morphokinetic parameters were determined using Analysis of Variance (ANOVA).
Results
The model failed to segregate euploid embryos from aneuploid embryos cultured at our facility. Further analysis indicated that the variability of embryos among patients was too great to allow selection of euploid embryos based on simple morphokinetic thresholds. Clinical selection of embryos based on morphokinetics alone is unlikely to identify euploid embryos accurately for transfer or yield higher rates of live delivery.
Conclusions
The use of non-invasive morphokinetics is unlikely to discriminate aneuploid from euploid embryos. Further, it does not approach the accuracy of preimplantation genetic screening with array comparative genomic hybridization.</description><subject>Analysis of Variance</subject><subject>Aneuploidy</subject><subject>Biopsy</subject><subject>Comparative Genomic Hybridization</subject><subject>Embryo Biology</subject><subject>Embryonic Development</subject><subject>Embryos</subject><subject>Female</subject><subject>Fertility</subject><subject>Fertilization in Vitro</subject><subject>Gynecology</subject><subject>Human Genetics</subject><subject>Humans</subject><subject>Infertility</subject><subject>Lasers</subject><subject>Male</subject><subject>Medicine</subject><subject>Medicine & Public Health</subject><subject>Microscopy</subject><subject>Mineral oils</subject><subject>Ovaries</subject><subject>Patients</subject><subject>Preimplantation Diagnosis - methods</subject><subject>Reproductive Medicine</subject><subject>Retrospective Studies</subject><subject>Sperm</subject><subject>Time-Lapse Imaging</subject><subject>Variance analysis</subject><issn>1058-0468</issn><issn>1573-7330</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2014</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNqNkt9qFTEQxhdRbK0-gDcS8KZerE6S_ZP1olKK2sIRb-p1mJPMnqbd3azJ7oHzDj60WU5bWkEoBJIwv_kmk_my7C2Hjxyg_hQ5KF7mwIschCpz_iw75GUt81pKeJ7OUKocikodZK9ivAaARgn5MjsQRVOJWjWH2Z_TGClGN2xY78N45W_cQJMzbMSAPU0UIts6ZJPriXU4RmK9M8FH48cdO75c_fjAJs_GQNaZidE8dt7Z3WeGgRgOd3cWXLxhpsNUqnUGJ-eHVNBSF9k8uG0qg92X19mLFrtIb273o-zXt6-XZ-f56uf3i7PTVW5Sc1NurE2rWJNsGtFWKGsJFsrWyrJBrAxJMI0hWxPxVhnDUaCyTbFGrAsBRh5lJ3vdcV73ZA0NU8BOj8H1GHbao9OPI4O70hu_1QUvq6YUSeD4ViD43zPFSfcuGuq61LGfo05YpaRQSj4F5SArycuEvv8HvfZzGNJPLBQUcpltovieWqYQA7X37-agF1vovS10soVebKF5ynn3sOH7jDsfJEDsgZhCw4bCg9L_Vf0LJnnHcg</recordid><startdate>20140901</startdate><enddate>20140901</enddate><creator>Kramer, Yael G.</creator><creator>Kofinas, Jason D.</creator><creator>Melzer, Katherine</creator><creator>Noyes, Nicole</creator><creator>McCaffrey, Caroline</creator><creator>Buldo-Licciardi, Julia</creator><creator>McCulloh, David H.</creator><creator>Grifo, James A.</creator><general>Springer US</general><general>Springer Nature B.V</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8C1</scope><scope>8FD</scope><scope>8FE</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>LK8</scope><scope>M0S</scope><scope>M1P</scope><scope>M7P</scope><scope>P64</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>RC3</scope><scope>7X8</scope><scope>5PM</scope></search><sort><creationdate>20140901</creationdate><title>Assessing morphokinetic parameters via time lapse microscopy (TLM) to predict euploidy: are aneuploidy risk classification models universal?</title><author>Kramer, Yael G. ; Kofinas, Jason D. ; Melzer, Katherine ; Noyes, Nicole ; McCaffrey, Caroline ; Buldo-Licciardi, Julia ; McCulloh, David H. ; Grifo, James A.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c573t-cddcdd4be3992f6a3730d05fd359aa6ce30c9ced7ee1f8cc1a2a8d94baa7420c3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2014</creationdate><topic>Analysis of Variance</topic><topic>Aneuploidy</topic><topic>Biopsy</topic><topic>Comparative Genomic Hybridization</topic><topic>Embryo Biology</topic><topic>Embryonic Development</topic><topic>Embryos</topic><topic>Female</topic><topic>Fertility</topic><topic>Fertilization in Vitro</topic><topic>Gynecology</topic><topic>Human Genetics</topic><topic>Humans</topic><topic>Infertility</topic><topic>Lasers</topic><topic>Male</topic><topic>Medicine</topic><topic>Medicine & Public Health</topic><topic>Microscopy</topic><topic>Mineral oils</topic><topic>Ovaries</topic><topic>Patients</topic><topic>Preimplantation Diagnosis - methods</topic><topic>Reproductive Medicine</topic><topic>Retrospective Studies</topic><topic>Sperm</topic><topic>Time-Lapse Imaging</topic><topic>Variance analysis</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Kramer, Yael G.</creatorcontrib><creatorcontrib>Kofinas, Jason D.</creatorcontrib><creatorcontrib>Melzer, Katherine</creatorcontrib><creatorcontrib>Noyes, Nicole</creatorcontrib><creatorcontrib>McCaffrey, Caroline</creatorcontrib><creatorcontrib>Buldo-Licciardi, Julia</creatorcontrib><creatorcontrib>McCulloh, David H.</creatorcontrib><creatorcontrib>Grifo, James A.</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Public Health Database</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>ProQuest Biological Science Collection</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Biological Science Database</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Journal of assisted reproduction and genetics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Kramer, Yael G.</au><au>Kofinas, Jason D.</au><au>Melzer, Katherine</au><au>Noyes, Nicole</au><au>McCaffrey, Caroline</au><au>Buldo-Licciardi, Julia</au><au>McCulloh, David H.</au><au>Grifo, James A.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Assessing morphokinetic parameters via time lapse microscopy (TLM) to predict euploidy: are aneuploidy risk classification models universal?</atitle><jtitle>Journal of assisted reproduction and genetics</jtitle><stitle>J Assist Reprod Genet</stitle><addtitle>J Assist Reprod Genet</addtitle><date>2014-09-01</date><risdate>2014</risdate><volume>31</volume><issue>9</issue><spage>1231</spage><epage>1242</epage><pages>1231-1242</pages><issn>1058-0468</issn><eissn>1573-7330</eissn><abstract>Purpose
To determine if Aneuploidy Risk Classification Models are predictive of euploidy/aneuploidy amongst IVF facilities.
Methods
We retrospectively applied key time lapse imaging events of embryos (Campbell et al.[
5
,
6
]) to stratify embryos into 3 groups: low, medium and high risk of aneuploidy. The actual ploidy results (from array comparative genomic hybridization) were compared with expectations [
5
,
6
]. Sources of variability in morphokinetic parameters were determined using Analysis of Variance (ANOVA).
Results
The model failed to segregate euploid embryos from aneuploid embryos cultured at our facility. Further analysis indicated that the variability of embryos among patients was too great to allow selection of euploid embryos based on simple morphokinetic thresholds. Clinical selection of embryos based on morphokinetics alone is unlikely to identify euploid embryos accurately for transfer or yield higher rates of live delivery.
Conclusions
The use of non-invasive morphokinetics is unlikely to discriminate aneuploid from euploid embryos. Further, it does not approach the accuracy of preimplantation genetic screening with array comparative genomic hybridization.</abstract><cop>Boston</cop><pub>Springer US</pub><pmid>24962789</pmid><doi>10.1007/s10815-014-0285-1</doi><tpages>12</tpages><oa>free_for_read</oa></addata></record> |
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source | MEDLINE; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; PubMed Central; SpringerLink Journals - AutoHoldings |
subjects | Analysis of Variance Aneuploidy Biopsy Comparative Genomic Hybridization Embryo Biology Embryonic Development Embryos Female Fertility Fertilization in Vitro Gynecology Human Genetics Humans Infertility Lasers Male Medicine Medicine & Public Health Microscopy Mineral oils Ovaries Patients Preimplantation Diagnosis - methods Reproductive Medicine Retrospective Studies Sperm Time-Lapse Imaging Variance analysis |
title | Assessing morphokinetic parameters via time lapse microscopy (TLM) to predict euploidy: are aneuploidy risk classification models universal? |
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