Literature DB >> 34816375

Human Oocyte Morphology and Outcomes of Infertility Treatment: a Systematic Review.

Dmitry Nikiforov1, Marie Louise Grøndahl2, Julius Hreinsson3, Claus Yding Andersen4,5.   

Abstract

Oocyte morphology assessment is easy to implement in any laboratory with possible quality grading prior to fertilization. At present, comprehensive oocyte morphology scoring is not performed as a routine procedure. However, it may augment chances for successful treatment outcomes if a correlation with certain dysmorphisms can be proven. In order to determine a correlation between oocyte morphology and treatment outcome, we performed a systematic search in PubMed and Cochrane Controlled Trials Register following PRISMA guidelines. A total of 52 articles out of 6,755 search results met the inclusion criteria. Dark colour of the cytoplasm (observed with an incidence rate of 7%), homogeneous granularity of the cytoplasm (19%) and ovoid shape of oocytes (7%) appeared to have no influence on treatment outcome. Abnormalities such as refractile bodies (10%), fragmented first polar body (37%), dark zona pellucida (9%), enlarged perivitelline space (18%) and debris in it (21%) are likely to affect the treatment outcome to some extent. Finally, cytoplasmic vacuoles (4%), centrally located cytoplasmic granularity (12%) and clusters of smooth endoplasmic reticulum (4%) negatively impact infertility treatment outcomes. Nonetheless, morphological assessment is informative rather than predictive. Adding oocyte morphology to the artificial intelligence (AI)-driven selection process may improve the precision of the algorithms. Oocyte morphology assessment can be especially useful in oocyte donation cycles, during oocyte freezing for fertility preservation and finally, objective oocyte scoring can be important in cases of very poor treatment outcome as a tool for explanation of results to the patient.
© 2021. Society for Reproductive Investigation.

Entities:  

Keywords:  Assisted reproduction; Human oocyte; Oocyte dysmorphisms; Oocyte morphology; Oocyte quality

Mesh:

Year:  2021        PMID: 34816375     DOI: 10.1007/s43032-021-00723-y

Source DB:  PubMed          Journal:  Reprod Sci        ISSN: 1933-7191            Impact factor:   2.924


  76 in total

1.  Influence of oocytes and spermatozoa on early embryonic development.

Authors:  Andres Salumets; Anne Maria Suikkari; Tonu Möls; Viveca Söderström-Anttila; Timo Tuuri
Journal:  Fertil Steril       Date:  2002-11       Impact factor: 7.329

2.  Optimum number of oocytes for a successful first IVF treatment cycle.

Authors:  M H van der Gaast; M J C Eijkemans; J B van der Net; E J de Boer; C W Burger; F E van Leeuwen; B C J M Fauser; N S Macklon
Journal:  Reprod Biomed Online       Date:  2006-10       Impact factor: 3.828

3.  Oocyte morphology does not affect fertilization rate, embryo quality and implantation rate after intracytoplasmic sperm injection.

Authors:  B Balaban; B Urman; A Sertac; C Alatas; S Aksoy; R Mercan
Journal:  Hum Reprod       Date:  1998-12       Impact factor: 6.918

4.  Oocyte morphology does not correlate with fertilization rate and embryo quality after intracytoplasmic sperm injection.

Authors:  P De Sutter; D Dozortsev; C Qian; M Dhont
Journal:  Hum Reprod       Date:  1996-03       Impact factor: 6.918

5.  Increased risk of preterm birth and low birthweight with very high number of oocytes following IVF: an analysis of 65 868 singleton live birth outcomes.

Authors:  Sesh Kamal Sunkara; Antonio La Marca; Paul T Seed; Yacoub Khalaf
Journal:  Hum Reprod       Date:  2015-04-16       Impact factor: 6.918

6.  Influence of oocyte dysmorphisms on blastocyst formation and quality.

Authors:  Daniela Paes Almeida Ferreira Braga; Amanda S Setti; Rita de Cássia S Figueira; Rogério Bonassi Machado; Assumpto Iaconelli; Edson Borges
Journal:  Fertil Steril       Date:  2013-06-12       Impact factor: 7.329

7.  Significance of metaphase II human oocyte morphology on ICSI outcome.

Authors:  Laura Rienzi; Filippo Mari Ubaldi; Marcello Iacobelli; Maria Giulia Minasi; Stefania Romano; Susanna Ferrero; Fabio Sapienza; Elena Baroni; Katarzyna Litwicka; Ermanno Greco
Journal:  Fertil Steril       Date:  2008-02-04       Impact factor: 7.329

8.  Sperm morphologic features as a prognostic factor in in vitro fertilization.

Authors:  T F Kruger; R Menkveld; F S Stander; C J Lombard; J P Van der Merwe; J A van Zyl; K Smith
Journal:  Fertil Steril       Date:  1986-12       Impact factor: 7.329

9.  Development of deep learning algorithms for predicting blastocyst formation and quality by time-lapse monitoring.

Authors:  Qiuyue Liao; Qi Zhang; Xue Feng; Haibo Huang; Haohao Xu; Baoyuan Tian; Jihao Liu; Qihui Yu; Na Guo; Qun Liu; Bo Huang; Ding Ma; Jihui Ai; Shugong Xu; Kezhen Li
Journal:  Commun Biol       Date:  2021-03-26

10.  Development of an artificial intelligence-based assessment model for prediction of embryo viability using static images captured by optical light microscopy during IVF.

Authors:  M VerMilyea; J M M Hall; S M Diakiw; A Johnston; T Nguyen; D Perugini; A Miller; A Picou; A P Murphy; M Perugini
Journal:  Hum Reprod       Date:  2020-04-28       Impact factor: 6.918

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