Next-generation liquidbiopsy detects nano-sized signs of breastcancer in early-stage patients USC
Blood specimens are collected, processed, and plated onto slides, and undergo immunofluorescent staining.Slides are scanned, acquired images are segmented, cellular features are extracted using R and EBImage software, dimensionality reduction analysis is applied to the cells.Data processing pipeline allows for rare cell detection, filtering, and classification, and DAPI- event separation for curation of final report. Created with BioRender.com.
Finally, the frequency of rare events for each category was reported as the concentration of rare cells per ml , calculated by measuring the total number of nucleated cells per two slides, estimated using DAPI-stained nuclei count, against the total complete blood count of the received sample.. For our morphometric analysis, we utilized the extracted features to further analyze the identified rare cells.
For the model, we tested random forest, logistic regression, and naïve bayes algorithms using Python 3 (Python Software Foundation,
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