RecruitingNot ApplicableNCT05896709

A Novel Integrative Non-invasive Embryo Selection Approach for IVF Based on MK-RS Analysis

A Novel Integrative Non-invasive Embryo Selection Approach for in Vitro Fertilization Based on Artificial Intelligence Enhanced Morphokinetic Analysis and Raman Spectra in Spent Culture Media


Sponsor

Chinese University of Hong Kong

Enrollment

176 participants

Start Date

Jul 17, 2023

Study Type

INTERVENTIONAL

Conditions

Summary

During assisted reproductive technology treatment, embryo selection is an important process that may affect the clinical pregnancy rate. Many assisted reproductive technology units over the world have tried different approaches to increase the clinical pregnancy rate. Conventionally, the morphology of the embryo is assessed by the embryologist with naked eyes only. Nowadays, artificial intelligence (AI) has been used to assist in morphological assessment of the embryo. Our pilot study showed that the AI-enhanced morphokinetic (MK) analysis increased the accuracy in embryo selection by \~9%, while the detection rate for abnormal chromosomes in embryo has also been increased by Raman spectroscopy (RS) analysis. The combined MK-RS analysis will be able to complete embryo assessment within 5-6 days after fertilization. This method needs shorter time and is at lower cost when compared to invasive preimplantation genetic testing for aneuploidies (PGT-A). In this study, we have combined the following non-invasive techniques to assist in embryo screening. 1. Using time-lapse imaging (i.e. images of embryo being taken every 10 minutes inside the incubator) with AI)-enhanced MK analysis to assess the entire morphological changes of the embryo. 2. As the embryo releases metabolites during its growth, the spent culture medium will be collected after culture of the embryo and then be used for RS analysis, which is a kind of metabolomics-based non-invasive PGT-A, for screening chromosomal abnormalities of the embryo. This study will include two phases. In Phase I, it is a retrospective part. We will collect data to train the convolutional neural network (CNN)-enhanced MK with RS method on embryo selection, leading to the integrated approach (MK-RS). In Phase II, it is a randomized controlled trial and participants will be randomised into 2 groups. For the experimental group, embryo selection will be based on the MK-RS method, whereas embryo selection for the control group will rely on the traditional embryo assessment results alone. Then we will assess the clinical pregnancy rate and evaluate the efficacy of our approach finally. Patients who receive in vitro fertilisation (IVF)/ intracytoplasmic sperm injection (ICSI) treatment from The Assisted Reproductive Technology (ART) Unit of The Chinese University of Hong Kong, Prince of Wales Hospital will be recruited.


Eligibility

Plain Language Summary

Simplified for easier understanding

This clinical trial is studying MK-RS for people with ivf, reproductive issues, and other related conditions. The study is currently recruiting participants at 1 location.

This summary was AI-generated to explain the trial in plain language. It is not medical advice. Always discuss eligibility with your doctor before enrolling in a clinical trial.

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Interventions

OTHERMK-RS

The embryos are assessed by the AI-enhanced MK analysis together with RS analysis.


Locations(1)

The Chinese University of Hong Kong

Hong Kong, Hong Kong

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NCT05896709


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