ArticleComputational and structural biotechnology journal2021
DeepFoci: Deep learning-based algorithm for fast automatic analysis of DNA double-strand break ionizing radiation-induced foci.
Article in Computational and structural biotechnology journal, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- AI-based methods for the assessment of DNA damage and repair mechanisms.Frontiers in systems biology · 2026Review
- Review
- From survival of irradiated mice to modern molecular insights: a seventy-year journey in radiobiology at the institute of biophysics, Czech academy of sciences.European biophysics journal : EBJ · 2025Review
- Role of Oxidative Stress Signaling, Nrf2, on Survival and Stemness of Human Adipose-Derived Stem Cells Exposed to X-rays, Protons and Carbon Ions.Antioxidants (Basel, Switzerland) · 2024Article
- Multiwell-based G0-PCC assay for radiation biodosimetry.Scientific reports · 2024Article
- Condensed Matter Systems Exposed to Radiation: Multiscale Theory, Simulations, and Experiment.Chemical reviews · 2024Review
- Article
- Artificial Intelligence in Andrology: From Semen Analysis to Image Diagnostics.The world journal of men's health · 2024Review
- Spatial-Temporal Genome Regulation in Stress-Response and Cell-Fate Change.International journal of molecular sciences · 2023Review
- Advanced image-free analysis of the nano-organization of chromatin and other biomolecules by Single Molecule Localization Microscopy (SMLM).Computational and structural biotechnology journal · 2023Article
- HARLEY mitigates user bias and facilitates efficient quantification and co-localization analyses of foci in yeast fluorescence images.Scientific reports · 2022Article
- A deep learning model (FociRad) for automated detection of γ-H2AX foci and radiation dose estimation.Scientific reports · 2022Article
- Incorporation of Low Concentrations of Gold Nanoparticles: Complex Effects on Radiation Response and Fate of Cancer Cells.Pharmaceutics · 2022Article
- DNA double-strand break repair in cancer: A path to achieving precision medicine.International review of cell and molecular biology · 2021Review
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Authors and funding
7 authors.
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Abstract
DNA double-strand breaks (DSBs), marked by ionizing radiation-induced (repair) foci (IRIFs), are the most serious DNA lesions and are dangerous to human health. IRIF quantification based on confocal microscopy represents the most sensitive and gold-standard method in radiation biodosimetry and allows research on DSB induction and repair at the molecular and single-cell levels. In this study, we introduce DeepFoci - a deep learning-based fully automatic method for IRIF counting and morphometric analysis. DeepFoci is designed to work with 3D multichannel data (trained for 53BP1 and γH2AX) and uses U-Net for nucleus segmentation and IRIF detection, together with maximally stable extremal region-based IRIF segmentation. The proposed method was trained and tested on challenging datasets consisting of mixtures of nonirradiated and irradiated cells of different types and IRIF characteristics - permanent cell lines (NHDFs, U-87) and primary cell cultures prepared from tumors and adjacent normal tissues of head and neck cancer patients. The cells were dosed with 0.5-8 Gy γ-rays and fixed at multiple (0-24 h) postirradiation times. Under all circumstances, DeepFoci quantified the number of IRIFs with the highest accuracy among current advanced algorithms. Moreover, while the detection error of DeepFoci remained comparable to the variability between two experienced experts, the software maintained its sensitivity and fidelity across dramatically different IRIF counts per nucleus. In addition, information was extracted on IRIF 3D morphometric features and repair protein colocalization within IRIFs. This approach allowed multiparameter IRIF categorization of single- or multichannel data, thereby refining the analysis of DSB repair processes and classification of patient tumors, with the potential to identify specific cell subclones. The developed software improves IRIF quantification for various practical applications (radiotherapy monitoring, biodosimetry, etc.) and opens the door to advanced DSB focus analysis and, in turn, a better understanding of (radiation-induced) DNA damage and repair.
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