Could metabolic imaging and artificial intelligence provide a novel path to non-invasive aneuploidy assessments? A certain clinical need

Fabrizzio Horta; Denny Sakkas; William Ledger; Ewa M. Goldys; Robert B. Gilchrist

doi:10.1071/RD24122

REVIEW (Open Access)

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Could metabolic imaging and artificial intelligence provide a novel path to non-invasive aneuploidy assessments? A certain clinical need

Fabrizzio Horta

^A ^B ^C ^D ^* , Denny Sakkas ^E , William Ledger ^A ^D , Ewa M. Goldys ^F and Robert B. Gilchrist ^A

+ Author Affiliations

- Author Affiliations

^A Fertility & Research Centre, Discipline of Women health, School of Clinical Medicine and the Royal Hospital for Women, University of New South Wales, Sydney, NSW, Australia.

^B Dept O&G, Monash University, Melbourne, Vic, Australia.

^C Monash Data Future Institute, Monash University, Melbourne, Vic, Australia.

^D City Fertility, Sydney, NSW, Australia.

^E Boston IVF, IVIRMA, Global Research Alliance, Waltham, MA, USA.

^F Graduate School of Biomedical Engineering, ARC Centre of Excellence for Nanoscale BioPhotonics, University of New South Wales, Sydney, NSW, Australia.

^* Correspondence to: Fabrizzio.Horta@unsw.edu.au

Handling Editor: Ye Yuan

Reproduction, Fertility and Development 37, RD24122 https://doi.org/10.1071/RD24122

Submitted: 6 August 2024 Accepted: 7 January 2025 Published online: 28 January 2025

© 2025 The Author(s) (or their employer(s)). Published by CSIRO Publishing. This is an open access article distributed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND)

Abstract

Pre-implantation genetic testing for aneuploidy (PGT-A) via embryo biopsy helps in embryo selection by assessing embryo ploidy. However, clinical practice needs to consider the invasive nature of embryo biopsy, potential mosaicism, and inaccurate representation of the entire embryo. This creates a significant clinical need for improved diagnostic practices that do not harm embryos or raise treatment costs. Consequently, there has been an increasing focus on developing non-invasive technologies to enhance embryo selection. Such innovations include non-invasive PGT-A, artificial intelligence (AI) algorithms, and non-invasive metabolic imaging. The latter measures cellular metabolism through autofluorescence of metabolic cofactors. Notably, hyperspectral microscopy and fluorescence lifetime imaging microscopy (FLIM) have revealed unique metabolic activity signatures in aneuploid embryos and human fibroblasts. These methods have demonstrated high accuracy in distinguishing between euploid and aneuploid embryos. Thus, this review discusses the clinical challenges associated with PGT-A and emphasizes the need for novel solutions such as metabolic imaging. Additionally, it explores how aneuploidy affects cell behaviour and metabolism, offering an opinion perspective on future research directions in this field of research.

Keywords: aneuploidy, artificial intelligence, embryo quality, infertility, IVF, label free imaging, metabolic imaging, PGT-A.

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