PLoS ONE (Jan 2024)

Development and evaluation of a usable blastocyst predictive model using the biomechanical properties of human oocytes.

  • Daniel Meyer,
  • Jonathan Kort,
  • Ching Hung Chen,
  • Huan Zhao,
  • Xiaoling Yi,
  • Shin-Yu Lai,
  • Farn Lu,
  • Wen Jui Yang,
  • I-Chiao Hsieh,
  • Chung-Li Chiang,
  • Wei-Ming Chen,
  • Jack Yu Jen Huang,
  • David Camarillo,
  • Barry Behr

DOI
https://doi.org/10.1371/journal.pone.0299602
Journal volume & issue
Vol. 19, no. 5
p. e0299602

Abstract

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PurposeThe purposes of this study were to determine whether biomechanical properties of mature oocytes could predict usable blastocyst formation better than morphological information or maternal factors, and to demonstrate the safety of the aspiration measurement procedure used to determine the biomechanical properties of oocytes.MethodsA prospective split cohort study was conducted with patients from two IVF clinics who underwent in vitro fertilization. Each patient's oocytes were randomly divided into a measurement group and a control group. The aspiration depth into a micropipette was measured, and the biomechanical properties were derived. Oocyte fertilization, day 3 morphology, and blastocyst development were observed and compared between measured and unmeasured cohorts. A predictive classifier was trained to predict usable blastocyst formation and compared to the predictions of four experienced embryologists.Results68 patients and their corresponding 1252 oocytes were included in the study. In the safety analyses, there was no significant difference between the cohorts for fertilization, while the day 3 and 5 embryo development were not negatively affected. Four embryologists predicted usable blastocyst development based on oocyte morphology with an average accuracy of 44% while the predictive classifier achieved an accuracy of 71%. Retaining the variables necessary for normal fertilization, only data from successfully fertilized oocytes were used, resulting in a classifier an accuracy of 81%.ConclusionsTo date, there is no standard guideline or technique to aid in the selection of oocytes that have a higher likelihood of developing into usable blastocysts, which are chosen for transfer or vitrification. This study provides a comprehensive workflow of extracting biomechanical properties and building a predictive classifier using these properties to predict mature oocytes' developmental potential. The classifier has greater accuracy in predicting the formation of usable blastocysts than the predictions provided by morphological information or maternal factors. The measurement procedure did not negatively affect embryo culture outcomes. While further analysis is necessary, this study shows the potential of using biomechanical properties of oocytes to predict embryo developmental outcomes.