An automatic system for in vitro cell migration studies
Journal article, 2009

This paper describes a system for in vitro cell migration analysis. Adult neural stem/progenitor cells are studied using time-lapse bright-field microscopy and thereafter stained immunohistochemically to find and distinguish undifferentiated glial progenitor cells and cells having differentiated into type-1 or type-2 astrocytes. The cells are automatically segmented and tracked through the time-lapse sequence. An extension to the Chan-Vese Level Set segmentation algorithm, including two new terms for specialized growing and pruning, made it possible to resolve clustered cells, and reduced the tracking error by 65%. We used a custom-built manual correction module to form a ground truth used as a reference for tracked cells that could be identified from the fluorescence staining. On average, the tracks were correct 95% of the time, using our new segmentation. The tracking, or association of segmented cells, was performed using a 2-state Hidden Markov Model describing the random behaviour of the cells. By re-estimating the motion model to conform with the segmented data we managed to reduce the number of tracking parameters to essentially only one. Upon characterization of the cell migration by the HMM state occupation function, it was found that glial progenitor cells were moving randomly 2/3 of the time, while the type-2 astrocytes showed a directed movement 2/3 of the time. This finding indicates possibilities for cell-type specific identification and cell sorting of live cells based on specific movement patterns in individual cell populations, which would have valuable applications in neurobiological research.

Microscopy

Video

Stem Cells

methods

Animals

Cultured

Cell Movement

physiology

Rats

Cells

Author

Johan Degerman

Chalmers, Signals and Systems, Signalbehandling och medicinsk teknik, Imaging and Image Analysis

T. Thorlin

University of Gothenburg

Jonas Faijerson

University of Gothenburg

Karin Althoff

Chalmers, Signals and Systems, Signalbehandling och medicinsk teknik, Imaging and Image Analysis

Peter S Eriksson

University of Gothenburg

R V D Put

Chalmers University of Technology

Tomas Gustavsson

Chalmers, Signals and Systems, Signalbehandling och medicinsk teknik, Imaging and Image Analysis

Journal of Microscopy

0022-2720 (ISSN) 1365-2818 (eISSN)

Vol. 233 1 178-191

Subject Categories

MEDICAL AND HEALTH SCIENCES

DOI

10.1111/j.1365-2818.2008.03108.x

PubMed

19196424