A1 Refereed original research article in a scientific journal
Consistent and effective method to define the mouse estrous cycle stage by a deep learning-based model
Authors: Strauss Leena, Junnila Arttu, Wärri Anni, Manti Maria, Jiang Yiwen, Löyttyniemi Eliisa, Stener-Victorin Elisabet, Lagerquist Marie K, Kukoricza Krisztina, Heinosalo Taija, Blom Sami, Poutanen Matti
Publisher: Bioscientifica
Publication year: 2024
Journal: Journal of Endocrinology
Journal name in source: The Journal of endocrinology
Journal acronym: J Endocrinol
Article number: e230204
Volume: 261
Issue: 3
ISSN: 0022-0795
eISSN: 1479-6805
DOI: https://doi.org/10.1530/JOE-23-0204
Web address : https://joe.bioscientifica.com/view/journals/joe/aop/joe-23-0204/joe-23-0204.xml
Self-archived copy’s web address: https://research.utu.fi/converis/portal/detail/Publication/387633243
The mouse estrous cycle is divided into four stages: proestrus (P), estrus (E), metestrus (M) and diestrus (D). The estrous cycle affects reproductive hormone levels in a wide variety of tissues. Therefore, to obtain reliable results from female mice, it is important to know the estrous cycle stage during sampling. The stage can be analyzed from a vaginal smear under a microscope. However, it is time-consuming, and the results vary between evaluators. Here, we present an accurate and reproducible method for staging the mouse estrous cycle in digital whole slide images (WSIs) of vaginal smears. We developed a model using a deep convolutional neural network (CNN) in a cloud-based platform, Aiforia Create. The CNN was trained by supervised pixel-level multiclass semantic segmentation of image features from 171 hematoxylin-stained samples. The model was validated by comparing the results obtained by CNN with those of four independent researchers. The validation data included three separate studies comprising altogether 148 slides. The total agreement attested by the Fleiss kappa value between the validators and the CNN was excellent (0.75), and when D, E and P were analyzed separately, the kappa values were 0.89, 0.79 and 0.74, respectively. The M stage is short and not well defined by the researchers. Thus, identification of the M stage by the CNN was challenging due to the lack of proper ground truth, and the kappa value was 0.26. We conclude that our model is reliable and effective for classifying the estrous cycle stages in female mice.
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Funding information in the publication:
This work was supported by the Sigrid Juselius Foundation, Drug Research Doctoral Programme, University of Turku.
