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

Dmitry Nikiforov*, Marie Louise Grøndahl, Julius Hreinsson, Claus Yding Andersen

*Corresponding author for this work
29 Citations (Scopus)

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.

Original languageEnglish
JournalReproductive sciences (Thousand Oaks, Calif.)
Volume29
Issue number10
Pages (from-to)2768-2785
Number of pages18
ISSN1933-7191
DOIs
Publication statusPublished - Oct 2022

Keywords

  • Artificial Intelligence
  • Humans
  • Infertility
  • Oocyte Donation
  • Oocytes
  • Zona Pellucida
  • Oocyte dysmorphisms
  • Human oocyte
  • Oocyte morphology
  • Assisted reproduction
  • Oocyte quality

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