Abstract

Three-dimensional (3D) spheroid arrays promise improved predictability due to their higher physiological relevance. They have the potential to improve drug screening outcomes in preclinical studies. Despite the advances, they can often lead to non-reproducible and unpredictable results. To support the development and subsequent analyses of spheroid arrays, we present a method for analyzing and evaluating cell viability in these. We provide a fast and easy-to-use fully automated workflow for the viability analysis in fluorescence images of cell aggregates within these arrays. The algorithm consists of multiple image processing algorithms for the segmentation and mapping of a priori knowledge about the array layout. The segmentation step is based on Otsu's thresholding followed by morphological filtering to obliterate the necessity of input parameters. No preprocessing is required. Besides, the algorithm offers the possibility of applying an additional flood fill algorithm. Subsequently, a k-means algorithm allows a fast image independent mapping of the grid to identify the cell aggregates. The complete workflow allows the extraction of essential metrics describing the viability of each cell aggregate. With our automated approach, we can show an increase in accuracy compared to simple manual segmentation. Additionally, the objectivity is increased by reducing human intervention. Furthermore, the needed analysis time is shortened and the information extraction and evaluation process is simplified.

Original languageEnglish
Title of host publication10th International Workshop on Innovative Simulation for Health Care, IWISH 2021
EditorsAgostino G. Bruzzone, Marco Frascio, Francesco Longo, Vera Novak
Pages27-35
Number of pages9
ISBN (Electronic)9788885741652
DOIs
Publication statusPublished - Sep 2021

Publication series

Name10th International Workshop on Innovative Simulation for Health Care, IWISH 2021

Keywords

  • Image Processing Methods
  • Fluorescence Microscopy
  • Image Analysis
  • Bioinformatics

Fingerprint

Dive into the research topics of 'Automated Evaluation of Cell Viability in Microfluidic Spheroid Arrays'. Together they form a unique fingerprint.

Cite this