Data availability
The code used to train and evaluate the AI model is publicly available at https://github.com/AlexanderBaikalov/auto-crypt-count-public. A subset of anonymized and representative histological image data used for model training and validation is included therein, in compliance with FAIR principles. Additional data may be made available upon reasonable request to the corresponding author (Emil Schüler: eschueler@mdanderson.org), subject to institutional and ethical guidelines.
References
-
Withers, H. & Elkind, M. Microcolony survival assay for cells of mouse intestinal mucosa exposed to radiation. Int. J. Radiation Biology Relat. Stud. Phys. Chem. Med. 17 (3), 261–267 (1970).
-
Franken, N. A. et al. Clonogenic assay of cells in vitro. Nat. Protoc. 1 (5), 2315–2319 (2006).
-
Von Maase, D., Overgaard, J. & H. and Microcolony survival assay for jejunal crypt cells exposed to radiation alone and combined with cancer chemotherapeutic Agents–Methodological problems. Int. J. Radiation Biology Relat. Stud. Phys. Chem. Med. 43 (1), 45–56 (1983).
-
Gunnlaugsson, A. et al. The effect on the small bowel of 5-FU and oxaliplatin in combination with radiation using a microcolony survival assay. Radiat. Oncol. 4, 1–7 (2009).
-
Von Maase, D. Interactions of radiation and 5-fluorouracil, cyclophosphamide or methotrexate in intestinal crypt cells. Int. J. Radiat. Oncol. Biol. Phys. 10 (1), 77–86 (1984).
-
Blott, P. & Trott, K. The effect of actinomycin D on split-dose recovery and repopulation in jejunal crypt cells in vivo. Radiother. Oncol. 15 (1), 73–78 (1989).
-
Parkash, V. et al. To count and how to count, that is the question: interobserver and intraobserver variability among pathologists in lymph node counting. Am. J. Clin. Pathol. 134 (1), 42–49 (2010).
-
Bueno, G. et al. An automated system for whole microscopic image acquisition and analysis. Microsc. Res. Tech. 77 (9), 697–713 (2014).
-
Dimitriou, N., Arandjelović, O. & Caie, P. D. Deep learning for whole slide image analysis: an overview. Front. Med. 6, 264 (2019).
-
Banerji, S. & Mitra, S. Deep learning in histopathology: A review. Wiley Interdisciplinary Reviews: Data Min. Knowl. Discovery. 12 (1), e1439 (2022).
-
Fu, J. et al. Exploring deep learning for estimating the isoeffective dose of FLASH irradiation from mouse intestinal histology images. Int. J. Radiat. Oncol. Biol. Phys. (2024).
-
Isensee, F. et al. nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation. Nat. Methods. 18 (2), 203–211 (2021).
-
Center, R. U. M. TIGER Grand Challenge. https://tiger.grand-challenge.org/Home/ (2024).
-
Spronck, J. et al. nnUNet meets pathology: bridging the gap for application to whole-slide images and computational biomarkers. In Medical Imaging with Deep Learning (2023).
-
Fedorov, A. et al. 3D slicer as an image computing platform for the quantitative imaging network. Magn. Reson. Imaging. 30 (9), 1323–1341 (2012).
-
Macenko, M. et al. A method for normalizing histology slides for quantitative analysis. In 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro (IEEE, 2009).
-
Suzuki, S. Topological structural analysis of digitized binary images by border following. Comput. Vis. Graphics Image Process. 30 (1), 32–46 (1985).
-
Liu, K. et al. Redefining FLASH RT: the impact of mean dose rate and dose per pulse in the gastrointestinal tract. Int. J. Radiat. Oncol. Biol. Phys. (2024).
-
Hagemann, R. F., Sigdestad, C. P. & Lesher, S. Intestinal crypt survival and total and per crypt levels of proliferative cellularity following irradiation: single x-ray exposures. Radiat. Res. 46 (3), 533–546 (1971).
-
Hagemann, R. F., Sigdestad, C. P. & Lesher, S. Intestinal crypt survival and total and per crypt levels of proliferative cellularity following irradiation: fractionated x-ray exposures. Radiat. Res. 47 (1), 149–158 (1971).
-
Potten, C. et al. The correction of intestinal microcolony counts for variation in size. Int. J. Radiation Biology Relat. Stud. Phys. Chem. Med. 40 (3), 321–326 (1981).
-
Potten, C. S. The significance of spontaneous and induced apoptosis in the Gastrointestinal tract of mice. Cancer Metastasis Rev. 11, 179–195 (1992).
-
Yau, H. & Cairnie, A. Cell-survival characteristics of intestinal stem cells and crypts of γ-irradiated mice. Radiat. Res. 80 (1), 92–107 (1979).
-
Liu, A. N. N. et al. A flexible Semi-automated assay for assessing Radiation-sensitization and toxicity in the mouse intestine. Anticancer Res. 44 (7), 2793–2803 (2024).
Acknowledgements
We thank Christine F. Wogan, MS, ELS, of MD Anderson’s Division of Radiation Oncology, for editorial contributions to this article.
Funding
Research reported in this publication was supported in part by the National Cancer Institute of the National Institutes of Health under R01CA266673, P30 CA016672; by the University Cancer Foundation via the Institutional Research Grant program at MD Anderson Cancer Center; by The University of Texas MD Anderson Cancer Center, Division of Radiation Oncology; by The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences Dr. John J. Kopchick Fellowship; by training fellowships from UTHealth Houston Center for Clinical and Translational Sciences Program (Grants No. TL1 TR003169; T32 TR004905), and by UTHealth Innovation for Cancer Prevention Research Training Program Pre-doctoral Fellowship (Cancer Prevention and Research Institute of Texas grant RP210042), and by the Klinikum rechts der Isar of the Technical University of Munich. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health or the Cancer Prevention and Research Institute of Texas.
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Baikalov, A., Wang, E., Neill, D. et al. A fully automated workflow for the digital image analysis of the intestinal microcolony survival assay. Sci Rep (2026). https://doi.org/10.1038/s41598-025-34719-4
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DOI: https://doi.org/10.1038/s41598-025-34719-4
