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

Abstract

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