Centromere detection of human metaphase chromosome images using a candidate based method

Akila Subasinghe,Ruth Wilkins,Jagath Samarabandu,Joan H M Knoll,Peter K Rogan,Farrah Flegal,Yanxin Li

doi:10.12688/f1000research.9075.1

Abstract

Accurate detection of the human metaphase chromosome centromere is a critical element of cytogenetic diagnostic techniques, including chromosome enumeration, karyotyping and radiation biodosimetry. Existing centromere detection methods tends to perform poorly in the presence of irregular boundaries, shape variations and premature sister chromatid separation. We present a centromere detection algorithm that uses a novel contour partitioning technique to generate centromere candidates followed by a machine learning approach to select the best candidate that enhances the detection accuracy. The contour partitioning technique evaluates various combinations of salient points along the chromosome boundary using a novel feature set and is able to identify telomere regions as well as detect and correct for sister chromatid separation. This partitioning is used to generate a set of centromere candidates which are then evaluated based on a second set of proposed features. The proposed algorithm outperforms previously published algorithms and is shown to do so with a larger set of chromosome images. A highlight of the proposed algorithm is the ability to rank this set of centromere candidates and create a centromere confidence metric which may be used in post-detection analysis. When tested with a larger metaphase chromosome database consisting of 1400 chromosomes collected from 40 metaphase cell images, the proposed algorithm was able to accurately localize 1220 centromere locations yielding a detection accuracy of 87%.

Highlights

The centromere of a human chromosome (Figure 1) is the primary constriction to which the spindle fiber is attached during the cell division cycle
The complete data set used for developing and testing the algorithm discussed in this paper consists of 40 metaphase cell images, of which 38 consisted from irradiated samples obtained from cytogenetic biodosimetry laboratories and two were nonirradiated cells from a clinical cytogenetic laboratory
The expert was presented with the set of centromere candidates generated by the algorithm and was asked to select the candidate that closely represented the correct chromosomal location, while explicitly marking other candidates as non-centromeres

Summary

Introduction

The centromere of a human chromosome (Figure 1) is the primary constriction to which the spindle fiber is attached during the cell division cycle (mitosis). The reliable detection of the centromere by image analysis techniques is challenging due to the high morphological variations of chromosomes on microscope slides This variation is caused by various cell preparation and staining methods along with other factors that occur during mitosis. Premature sister chromatid separation can pose a significant challenge, since the degree of separation can vary from cell to cell, and even among chromosomes in the same cell In such cases, the width constriction can be missed by image processing algorithms, and can result in incorrect localization of a centromere on one of the sister chromatids

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Conclusion