Organotchi: an open-source tool for the automated segmentation, morphological characterization, and longitudinal tracking of organoids
- 1Zoological Institute, Karlsruhe Institute of Technology (KIT), Germany; Institute of Biological and Chemical Systems - Functional Molecular Systems, Karlsruhe I
Abstract
Neural organoids are three-dimensional stem cell-derived models widely used to study brain development and model disease. Brightfield imaging offers a non-invasive readout of their growth and morphology, and recent advances have made automated organoid segmentation from such images increasingly attainable. Yet existing tools largely leave morphological characterization, quality assessment, and comparisons between conditions to manual or ad hoc analysis. Here we present Organotchi, an open-source tool that integrates automated segmentation with longitudinal morphological analysis of neural organoids. Organotchi quantifies ten morphological features, including area, perimeter, and eccentricity, and tracks cystic structures over time, reports variability within and between batches, and flags outlier organoids and segmentation failures, supporting objective organoid characterization and enhancing downstream analysis. As a proof of concept, we apply Organotchi to disease modelling, pharmacological perturbation, and protocol optimization in neural organoids. One use case assesses drug response in breast cancer spheroids, demonstrating its use beyond its development domain.
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BibTeX
@misc{branco2026organotchi,
title = {{Organotchi: an open-source tool for the automated segmentation, morphological characterization, and longitudinal tracking of organoids}},
author = {L. Branco and T. Lautenschlager and D. Andreeva and Z. Yentur and F. Castagnetti and T. Kagermeier and I. Potthof and P. Collignon and K. Potter Stephens and J. Matilainen and R. Mikut and S. Mayer},
howpublished = {bioRxiv},
year = {2026},
month = nov,
doi = {10.64898/2026.11.04.764279},
url = {https://www.biorxiv.org/content/10.64898/2026.11.04.764279v1},
note = {CC BY},
}
RIS
TY - UNPB
TI - Organotchi: an open-source tool for the automated segmentation, morphological characterization, and longitudinal tracking of organoids
AU - L. Branco
AU - T. Lautenschlager
AU - D. Andreeva
AU - Z. Yentur
AU - F. Castagnetti
AU - T. Kagermeier
AU - I. Potthof
AU - P. Collignon
AU - K. Potter Stephens
AU - J. Matilainen
AU - R. Mikut
AU - S. Mayer
PY - 2026
DA - 2026/11/04
PB - bioRxiv
DO - 10.64898/2026.11.04.764279
UR - https://www.biorxiv.org/content/10.64898/2026.11.04.764279v1
AB - Neural organoids are three-dimensional stem cell-derived models widely used to study brain development and model disease. Brightfield imaging offers a non-invasive readout of their growth and morphology, and recent advances have made automated organoid segmentation from such images increasingly attainable. Yet existing tools largely leave morphological characterization, quality assessment, and comparisons between conditions to manual or ad hoc analysis. Here we present Organotchi, an open-source tool that integrates automated segmentation with longitudinal morphological analysis of neural organoids. Organotchi quantifies ten morphological features, including area, perimeter, and eccentricity, and tracks cystic structures over time, reports variability within and between batches, and flags outlier organoids and segmentation failures, supporting objective organoid characterization and enhancing downstream analysis. As a proof of concept, we apply Organotchi to disease modelling, pharmacological perturbation, and protocol optimization in neural organoids. One use case assesses drug response in breast cancer spheroids, demonstrating its use beyond its development domain.
ER -