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Pre-Implantation Genetic Testing for Aneuploidy on a Semiconductor Based Next-Generation Sequencing Platform
Published on: August 17, 2022
AI-guided meta-analysis of non-invasive prenatal testing platforms for trisomy 21 screening: comparative evaluation
Alaa Elmetwalli1, Fuad Ameen2, Najwa Magrashi2
1Prince Fahad bin Sultan Chair for Biomedical Research, University of Tabuk, Tabuk, Saudi Arabia. aelmetwalli@ut.edu.sa.
Background:
Trisomy 21 (Down syndrome) remains the most prevalent autosomal aneuploidy, necessitating accurate prenatal diagnosis. While cell-free fetal DNA (cffDNA)-based non-invasive prenatal testing (NIPT) has transformed screening, challenges persist in low fetal fraction cases and confined placental mosaicism. Integrating artificial intelligence (AI), multi-omics, and fetal cell-based approaches represents a paradigm shift toward comprehensive prenatal diagnostics.
Objective:
This AI-assisted meta-analysis evaluates NIPT platforms for Trisomy 21 detection, comparing cffDNA-based, SNP-based, digital PCR, and emerging fetal cell-based approaches.
Methods:
Following PRISMA guidelines, we systematically searched PubMed, Web of Science, and Scopus (2010-2023). Ten high-quality studies were analyzed for diagnostic accuracy metrics across multiple NIPT platforms.
Results:
MPS-based cffDNA NIPT demonstrated pooled sensitivity of 99.3% (95% CI: 98.7-99.7%) and specificity of 99.9% (95% CI: 99.8-100%). Alternative platforms, including fetal cell-based NIPT, showed promising but moderately lower accuracy. AI-driven risk stratification models demonstrated enhanced diagnostic precision in complex cases.
Conclusion:
MPS-based NIPT remains the gold standard for Trisomy 21 screening. Future integration of AI-enhanced fetal cell isolation and multi-omics profiling may expand diagnostic capabilities beyond aneuploidy detection.
