Clinical validation of artificial intelligence-assisted karyotyping on peripheral blood in a cytogenetic diagnostic laboratory

Abstract

G-banded chromosome analysis, also known as G-banded karyotyping, remains a fundamental and irreplaceable diagnostic modality in clinical genetic testing. G-banded karyotypes provide whole genome visualization through chromosome banding patterns at the single-cell resolution for the diagnosis of chromosomal disorders. However, this method is labor-intensive and requires specialized expertise to manually analyze and karyotype metaphase spreads. In recent years, artificial intelligence (AI) algorithms have been utilized to automate karyotyping and assist with chromosome analysis. Despite this progress, there is a scarcity of studies evaluating the utility of artificial intelligence-assisted (AI-assisted) karyotyping analysis in cytogenetics diagnostic laboratories. This study highlights promising applications of AI-assisted karyotyping analysis in a cytogenetics diagnostic laboratory through a combination of a literature review, our data, and experience from a retrospective cohort study. This study also discusses important considerations of the use of AI-assisted karyotyping analysis in a cytogenetic diagnostic laboratory and outlines a two-stage framework for its implementation into clinical workflows. This approach aims to utilize the accuracy and efficiency of AI-assisted karyotyping analysis, potentially benefiting personalized patient care and contributing to advancements in the health system.

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