AbstractMalignant disease is a major cause of morbidity and mortality in western Europe. Cancers which form distant metastasis are difficult to contain. Measures to stimulate or inhibit movement of cancer cells may play an important part in metastasis biology. The movement behaviour of individual cells within a cluster may give new clues about cell-to-cell interactions. However, the recognition and tracking of individual cells in clusters is difficult for a fully automated imaging system.
A principal aim of this study was to develop a semi-automatic image processing system to enable assessment of cell movement in clustered cancer cell colonies. The system would also be adapted and applied for the segmentation and analysis of macroscopic images of leg ulcers.
A piecewise cubic spline interpolation was used to describe cells by their boundary. The spline model was extended into the time domain with a deterministic relocation technique to facilitate tracking of cells, thus forming a new adaptive spline model.
The method was applied to investigate the movement behaviour of clustered human colon cancer cells in vitro associated with an added movement stimulant. The results demonstrated that stimulated cells show more movement activity and higher velocities than control cells. The system was also applied to assess morphology of neutrophils in brightfield microscopy and results were compared with a region-based segmentation technique. Furthermore the system was applied to assess cell morphology in relation to intracellular chemical changes in neutrophils.
On a macroscopic level, the spline technique was used to segment the wound boundary in leg ulcer images. The spline was used to generate a profile of the wound edge at the boundary of leg ulcers to extract new wound assessment parameters based on hue, saturation and intensity.
In summary, these adaptive spline methods enable the assessment of cell movement behaviour in clustered cells. Differences in behaviour between stimulated cells and control cells can be quantified. The system is also proving to be useful in segmenting macroscopic images such as leg ulcer images. Thus this system should be of value in macroscopic analysis of wound healing and microscopic analysis of cell movement and cell behaviour.
|Date of Award||Jun 2001|