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Shape factor analysis as a quantitative framework for assessing spheroid and organoid morphology and invasiveness
Brittany E Schutrum1, Jenny Deng1, Ju Hee Kim1
1Nancy E. and Peter C. Meinig School of Biomedical Engineering, Cornell University, Ithaca, New York 14850, USA.
APL Bioengineering
|July 2, 2026
Summary
We developed a new MATLAB algorithm to measure radial changes in spheroids and organoids. This method offers improved morphological analysis for in vitro studies compared to traditional ImageJ/FIJI shape factors.
Area of Science:
- * Biomedical Engineering
- * Cell Biology
- * Computational Biology
Background:
- * Morphological changes in spheroids and organoids are crucial indicators of tissue health and disease in vitro.
- * Quantifying these morphological changes presents a significant challenge.
- * Existing shape factors, often computed using ImageJ/FIFI, have limitations in classifying specific morphological features.
Purpose of the Study:
- * To develop and validate a novel algorithm for quantifying morphological variance in spheroids and organoids.
- * To compare the performance of the custom algorithm against conventional ImageJ/FIJI shape descriptors.
- * To guide researchers in selecting optimal methods for spheroid and organoid morphology classification.
Main Methods:
- * Development of a custom MATLAB algorithm inspired by clinical approaches to quantify radial length variance in invasive protrusions.
- * Analysis of digital phantoms to initially assess algorithm performance.
- * Comparative analysis using experimental spheroid and organoid image datasets against ImageJ/FIJI shape descriptors.
Main Results:
- * The custom MATLAB algorithm provides precise numerical readouts of morphological variance.
- * Demonstrated advantages and limitations of the new algorithm compared to conventional ImageJ/FIJI shape factors.
- * Validated the algorithm's utility on both digital phantoms and experimental biological samples.
Conclusions:
- * The developed MATLAB algorithm enhances phenotypic profiling of spheroids and organoids.
- * Offers valuable quantitative metrics for in vitro studies, including high-throughput and drug screening.
- * Provides a more robust method for classifying spheroid and organoid morphology.
