Application of automation to the detection of radiation damage using FISH technology

A whole chromosome painting approach was employed to highlight the damaging effects of low-to-moderate doses of ionizing radiation. A detailed tally of damage involving the painted chromosomes 1 and 2 was compiled from visual analysis and compared with the results of an automatic image processing approach, where the possible outcomes were 'normal', 'abnormal', or 'rejected'. The performance of the automatic approach was tested using a set of 9000 bicolour metaphase images harvested from whole-blood cell culture following irradiation levels of 0.0, 0.5, 1.0 and 2.0 Gy. Every metaphase image in the set was analysed visually. The automatic analysis model was based on two simple image criteria to distinguish normal from abnormal; either an increase in the number of painted objects or a large asymmetry in the area distribution of the expected number of painted objects. A result was obtained without a full karyotype analysis. In practice, automatic analysis produced a set of images for review that were enriched by a factor of 3-4 in true abnormal images. Fast visual review of these images (approximately 200/h) selected the true abnormals. A comparison of the automatic analysis with the visual analysis showed that automated analysis correctly identified 60% of normal cells, 59% of abnormal cells and 73% of rejected cells.