ArticleArchives of toxicology2021
Inter-laboratory automation of the in vitro micronucleus assay using imaging flow cytometry and deep learning.
Article in Archives of toxicology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed, 35 citations in OpenAlex.
- From Cellular Radiosensitivity to Precision Radiotherapy: Integrating Functional Assays, Genomics, and Clinical Modeling.Cancers · 2026Review
- Micronuclei: origins, assays, mechanisms, diseases and treatments.Signal transduction and targeted therapy · 2026Review
- Deep learning and object detection methods for scoring cell types within the human buccal cell micronucleus and cytome assays for human biomonitoring.Mutagenesis · 2026Review
- Flow Cytometric Determination of Micronucleus Frequency.Methods in molecular biology (Clifton, N.J.) · 2026Article
- Interpretation of in vitro concentration-response data for risk assessment and regulatory decision-making: Report from the 2022 IWGT quantitative analysis expert working group meeting.Environmental and molecular mutagenesis · 2025Review
- Microvascular Health as a Key Determinant of Organismal Aging.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Review
- An efficient cell micronucleus classification network based on multi-layer perception attention mechanism.Scientific reports · 2025Article
- Application of the Buccal Micronucleus Cytome Assay for Genotoxicity Detection in Dogs.Animals : an open access journal from MDPI · 2025Article
- The Fate of Micronuclei.Methods in molecular biology (Clifton, N.J.) · 2025Review
- Liquid Biopsy for Cutaneous Melanoma: Opportunities and Challenges in Detecting and Characterizing Circulating Tumor Cells.Journal of dermato-oncology · 2025Article
- A multi-biomarker micronucleus assay using imaging flow cytometry.Archives of toxicology · 2024Article
- Application of image-recognition techniques to automated micronucleus detection in the in vitro micronucleus assay.Genes and environment : the official journal of the Japanese Environmental Mutagen Society · 2024Article
- Article
- Development of a micronucleus test using the EpiAirway™ organotypic human airway model.Genes and environment : the official journal of the Japanese Environmental Mutagen Society · 2023Article
- Machine learning approach for quantitative biodosimetry of partial-body or total-body radiation exposures by combining radiation-responsive biomarkers.Scientific reports · 2023Article
- Towards AI-driven longevity research: An overview.Frontiers in aging · 2023Review
- CRISPRthripsis: The Risk of CRISPR/Cas9-induced Chromothripsis in Gene Therapy.Stem cells translational medicine · 2022Article
- Detection and Characterization of Circulating Tumor Cells Using Imaging Flow Cytometry-A Perspective Study.Cancers · 2022Article
- Rapid and automatic detection of micronuclei in binucleated lymphocytes image.Scientific reports · 2022Article
- Imaging flow cytometry: a primer.Nature reviews. Methods primers · 2022Article
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Authors and funding
20 authors at 7 institutions in 2 countries.
Funding
Abstract
The in vitro micronucleus assay is a globally significant method for DNA damage quantification used for regulatory compound safety testing in addition to inter-individual monitoring of environmental, lifestyle and occupational factors. However, it relies on time-consuming and user-subjective manual scoring. Here we show that imaging flow cytometry and deep learning image classification represents a capable platform for automated, inter-laboratory operation. Images were captured for the cytokinesis-block micronucleus (CBMN) assay across three laboratories using methyl methanesulphonate (1.25-5.0 μg/mL) and/or carbendazim (0.8-1.6 μg/mL) exposures to TK6 cells. Human-scored image sets were assembled and used to train and test the classification abilities of the "DeepFlow" neural network in both intra- and inter-laboratory contexts. Harnessing image diversity across laboratories yielded a network able to score unseen data from an entirely new laboratory without any user configuration. Image classification accuracies of 98%, 95%, 82% and 85% were achieved for 'mononucleates', 'binucleates', 'mononucleates with MN' and 'binucleates with MN', respectively. Successful classifications of 'trinucleates' (90%) and 'tetranucleates' (88%) in addition to 'other or unscorable' phenotypes (96%) were also achieved. Attempts to classify extremely rare, tri- and tetranucleated cells with micronuclei into their own categories were less successful (≤ 57%). Benchmark dose analyses of human or automatically scored micronucleus frequency data yielded quantitation of the same equipotent concentration regardless of scoring method. We conclude that this automated approach offers significant potential to broaden the practical utility of the CBMN method across industry, research and clinical domains. We share our strategy using openly-accessible frameworks.
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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 OpenQuestion graph.