ArticleScientific reports2023
Label-free liquid biopsy through the identification of tumor cells by machine learning-powered tomographic phase imaging flow cytometry.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
23 citing papers in PubMed, 51 citations in OpenAlex.
- Hyper-dimensional computing for enhanced label-free particle analysis in a flow-based optical detection system.Scientific reports · 2026Article
- AI-integrated microfluidics for drug screening: From single cell to organ-on-a-chip.Acta pharmaceutica Sinica. B · 2026Review
- Review
- Digital Holographic Microscopy for Phenotypic Profiling of Adherent Cells.Methods in molecular biology (Clifton, N.J.) · 2026Article
- Automated Analysis of Liquid Biopsy Using Deep Learning: Detecting Circulating Tumor Cells and Cancer-Associated Fibroblasts.Methods in molecular biology (Clifton, N.J.) · 2026Article
- Circulating tumor cell detection in cancer patients using in-flow deep learning holography.Npj biosensing · 2026Article
- Lightweight CNN efficiently discriminates ovarian cancer cells from a tumor microenvironment via holographic imaging flow cytometry.Biomedical optics express · 2025Article
- Lightweight and precise cell classification based on holographic tomography-derived refractive index point cloud.Journal of biomedical optics · 2025Article
- From genotype to phenotype: decoding mutations in blasts by holo-tomographic flow cytometry.Light, science & applications · 2025Article
- Review
- Multifaceted Approaches in Epithelial Cell Adhesion Molecule-Mediated Circulating Tumor Cell Isolation.Molecules (Basel, Switzerland) · 2025Review
- Morphological and Optical Profiling of Melanocytes and SK-MEL-28 Melanoma Cells Via Digital Holographic Microscopy and Quantitative Phase Imaging.Advanced biology · 2025Article
- Label-free imaging flow cytometry for cell classification based directly on multiple off-axis holographic projections.Journal of biomedical optics · 2025Article
- Liquid biopsy in cancer diagnosis and prognosis: a paradigm shift in precision oncology.Frontiers in molecular biosciences · 2025Review
- Enhanced Detection of Gastrointestinal Malignancies using Machine Learning-Optimized Liquid Biopsy: A Mini Review.Current cancer drug targets · 2025Review
- Three-dimensional isotropic imaging of live suspension cells enabled by droplet microvortices.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Quantitative phase imaging techniques for measuring scattering properties of cells and tissues: a review-part I.Journal of biomedical optics · 2024Review
- All-optical dual module platform for motility-based functional scrutiny of microencapsulated probiotic bacteria.Biomedical optics express · 2024Article
- Dissemination of Circulating Tumor Cells in Breast and Prostate Cancer: Implications for Early Detection.Endocrinology · 2024Review
- Narrative review: precision medicine applications in neuroblastoma-current status and future prospects.Translational pediatrics · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
14 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Image-based identification of circulating tumor cells in microfluidic cytometry condition is one of the most challenging perspectives in the Liquid Biopsy scenario. Here we show a machine learning-powered tomographic phase imaging flow cytometry system capable to provide high-throughput 3D phase-contrast tomograms of each single cell. In fact, we show that discrimination of tumor cells against white blood cells is potentially achievable with the aid of artificial intelligence in a label-free flow-cyto-tomography method. We propose a hierarchical machine learning decision-maker, working on a set of features calculated from the 3D tomograms of the cells' refractive index. We prove that 3D morphological features are adequately distinctive to identify tumor cells versus the white blood cell background in the first stage and, moreover, in recognizing the tumor type at the second decision step. Proof-of-concept experiments are shown, in which two different tumor cell lines, namely neuroblastoma cancer cells and ovarian cancer cells, are used against monocytes. The reported results allow claiming the identification of tumor cells with a success rate higher than 97% and with an accuracy over 97% in discriminating between the two cancer cell types, thus opening in a near future the route to a new Liquid Biopsy tool for detecting and classifying circulating tumor cells in blood by stain-free method.
Indexed as
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.