Abstract

Detection of rare fetal cells (FCs) in the maternal circulation could be used for non-invasive prenatal diagnosis. Considering that FCs in maternal blood are present in extremely low frequency, manual scanning is cumbersome, time-consuming, and unsuitable for clinical applications. As an alternative, we optimized a custom-made classifier for automatic detection of FCs. Using MetaSystems' automated platform, we developed a robust detection algorithm and validated its efficiency on retrieval of rare XY cells in a pure population of XX cells. Slides were scanned for presence of predefined XY cells after fluorescence in situ hybridization (FISH) and primed in situ labeling (PRINS). Retrieval of FCs was also performed on samples from maternal blood. The efficiency of detection of rare XY cells was 88% using FISH (117/133) in comparison with 78% (53/68) with PRINS. FC frequencies per 1 mL of maternal blood ranged from 3 to 6 FCs in normal pregnancies versus 13 to 21 FCs in Down syndrome pregnancies. Automatic scanning was more efficient and consistent than manual scanning for detection of rare FCs and required considerably less operator time. Automatic scanning using FISH is more sensitive than that using PRINS. The study validates automatic scanning retrieval of FCs from maternal blood.

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