Automation and Control of Embryo Trophectoderm Cell Biopsy at the Blastocyst Stage.

Abstract

Objective: This study aims to develop and validate a vision-based automation framework for performing trophectoderm (TE) cell biopsy on mouse embryos.

Method: The proposed framework leverages widely available tools in research laboratories and In-Vitro fertilization (IVF) clinics, combined with computer vision and image-based control algorithms. A computer vision system first estimates the embryo's orientation to enable precise reorientation for zona pellucida (ZP) laser perforation. A vision-feedback control system then guides the embryo to the targeted perforation location and determines optimal laser parameters for ZP perforation. A vision-guided vacuum system aspirates the TE cells, with a multi-pulse laser ensuring their separation.

Results: Experimental validation using mouse blastocyst embryos demonstrated the feasibility and reliability of the proposed automation method. The vision-based approach achieved accurate orientation, controlled ZP perforation, and successful isolation of TE cells, effectively replicating manual biopsy techniques performed by skilled embryologists.

Conclusion: The study presents a robust framework for automating embryo TE biopsy, reducing variability, and enhancing procedural precision. Integrating computer vision and control algorithms allows for consistent and reproducible results.

Significance: By utilizing existing infrastructure, the proposed method offers a cost-effective and scalable solution for single-cell research and IVF clinics, advancing genetic testing and reproductive medicine.