Accurate cytogenetic biodosimetry through automated dicentric chromosome curation and metaphase cell selection

Accurate digital image analysis of abnormal microscopic structures relies on high quality images and on minimizing the rates of false positive (FP) and negative objects in images. Cytogenetic biodosimetry detects dicentric chromosomes (DCs) that arise from exposure to ionizing radiation, and determines radiation dose received based on DC frequency. Improvements in automated DC recognition increase the accuracy of dose estimates by reclassifying FP DCs as monocentric chromosomes or chromosome fragments. We also present image segmentation methods to rank high quality digital metaphase images and eliminate suboptimal metaphase cells. A set of chromosome morphology segmentation methods selectively filtered out FP DCs arising primarily from sister chromatid separation, chromosome fragmentation, and cellular debris. This reduced FPs by an average of 55% and was highly specific to these abnormal structures (≥97.7%) in three samples. Additional filters selectively removed images with incomplete, highly overlapped, or missing metaphase cells, or with poor overall chromosome morphologies that increased FP rates. Image selection is optimized and FP DCs are minimized by combining multiple feature based segmentation filters and a novel image sorting procedure based on the known distribution of chromosome lengths. Applying the same image segmentation filtering procedures to both calibration and test samples reduced the average dose estimation error from 0.4 Gy to \u3c0.2 Gy, obviating the need to first manually review these images. This reliable and scalable solution enables batch processing for multiple samples of unknown dose, and meets current requirements for triage radiation biodosimetry of high quality metaphase cell preparations

Chromatin Structure and Differential Accessibility of Homologous Human Mitotic Metaphase Chromosomes

The human mitotic metaphase chromosome is a product of complex chromatin restructuring during interphase. Metaphase chromosomes exhibit considerable plasticity in condensation. This is evident as distinct regions of accessible and compact chromatin fiber or epigenetic differences in histone and non-histone proteins. Such differences in chromatin condensation have been extensively described along the length of individual mitotic chromosomes but have not been recognized between homologous loci during metaphase. This thesis characterizes localized differences in condensation of homologous metaphase chromosomes that are related to differences in accessibility (DA) of associated DNA probe targets. Reproducible DA was observed for ~10% of locus-specific, short (1.5-5 kb) single copy (SC) DNA probes used in fluorescence in situ hybridization. To investigate the physical and structural organization of chromatin at locus-specific sites, we developed correlated atomic force and fluorescence microscopy imaging. Comparison of centromeric DNA and protein distribution patterns in fixed homologous chromosomes indicated that CENP-B and α-satellite DNA were distributed distinctly from one another and relative to observed centromeric ridge topography. At non-centromeic locations, short DNA probes that did not exhibit DA showed greater accessibility to the accessible chromatin topography on both homologs. Localized differential accessibility between chromosome homologs in metaphase was non-random and reproducible but not unique to known imprinted regions or specific chromosomes. Second, non-random DA was shown to be heritable within a 2 generation family. Third, DNA probe volume and depth measurements of hybridized metaphase chromosomes showed internal differences in chromatin accessibility of homologous regions by super-resolution 3D-structured illumination microscopy. Finally, genomic regions with equivalent accessibility were enriched for epigenetic marks of open interphase chromatin to a greater extent than regions with DA, suggesting that observed structural differences in accessibility may arise during or preceding metaphase chromosome compaction. Inhibition of the topoisomerase IIα-DNA cleavage complex mitigated DA by decreasing DNA superhelicity and axial metaphase chromosome condensation. Inter-homolog probe intensity ratios, depth, and volume between chromosomes treated with a catalytic inhibitor of topoisomerase IIα, were equalized compared to untreated cells. These data altogether suggest that DA is a reflection of allelic differences in metaphase chromosome compaction, dictated by the catenation state of the chromosome

Digital image analysis of mitotic chromosomes

Změny v počtu a ve struktuře chromozomů jsou příčinou řady vážných onemocnění. K odhalení chromozomálních změn slouží cytogenetická vyšetření, která nejčastěji vedou k sestavení karyotypu. Pro účely cytogenetických analýz se chromozomy vizualizují pomocí vhodných metod a nejčastěji se následně sestavují do karyotypu. Protože ruční stanovení karyotypu je časově i finančně náročné, vyvíjí se přístupy k automatickému karyotypování pomocí počítačového softwaru. Automatické karyotypovací systémy klasifikují chromozomy do tříd na základě identifikačních znaků, specifických pro každý chromozom. Automatickou klasifikaci však nejvíce limituje přítomnost překrývající se a silně ohnutých chromozomů, přítomných v téměř každé mitóze. Přesnost a spolehlivost karyotypovacích systémů stále závisí na zásahu uživatele. Cílem vývoje nových přístupů k automatickému karyotypování je tedy zejména překonání výše zmíněných problémů a dále vývoj takových klasifikačních metod, které umožňí klasifikaci chromozomů do párů bez lidské kontroly.Changes in chromosome number and structure may cause serious diseases. Cytogenetic tests leadin to set of karyotype are done for detecting these abnormalities. Chromosomes are visualised with proper methods and karyotype is made up most often. Manual karyotyping is time-consuming and expensive task. Because of this, researchers have been developing automated karyotyping systems. Karyotyping systems classify chromosomes into classes based on their characteristic features. Overlapping and bent chromosomes are limitations for automatic classification since they ocur at almost every mitosis. Accuracy and reliability of karyotyping systems still depend on the human intervention. Overcoming of these problems and development of fully automated system is the aim of modern approaches.

Integrated Development and Parallelization of Automated Dicentric Chromosome Identification Software to Expedite Biodosimetry Analysis

Manual cytogenetic biodosimetry lacks the ability to handle mass casualty events. We present an automated dicentric chromosome identification (ADCI) software utilizing parallel computing technology. A parallelization strategy combining data and task parallelism, as well as optimization of I/O operations, has been designed, implemented, and incorporated in ADCI. Experiments on an eight-core desktop show that our algorithm can expedite the process of ADCI by at least four folds. Experiments on Symmetric Computing, SHARCNET, Blue Gene/Q multi-processor computers demonstrate the capability of parallelized ADCI to process thousands of samples for cytogenetic biodosimetry in a few hours. This increase in speed underscores the effectiveness of parallelization in accelerating ADCI. Our software will be an important tool to handle the magnitude of mass casualty ionizing radiation events by expediting accurate detection of dicentric chromosomes

Image Processing Techniques for Detecting Chromosome Abnormalities

With the increasing use of Fluorescence In Situ Hybridization (FISH) probes as markers for certain genetic sequences, the requirement of a proper image processing framework is becoming a necessity to accurately detect these probe signal locations in relation to the centerline of the chromosome. Automated detection and length measurements based on the centerline relative to the centromere and the telomere coordinates would highly assist in clinical diagnosis of genetic disorders and thus improve its efficiency significantly. Although many image processing techniques have been developed for chromosomal analysis such as ’’karyotype analysis” to assist in laboratory diagnosis, they fail to provide reliable results in segmenting and extracting the centerline of chromosomes due to the high variability in shape of chromosomes on microscope slides. In this thesis we propose a hybrid algorithm that utilizes Gradient Vector Flow active contours, Discrete Curve Evolution based skeleton pruning and morphological thinning to provide a robust and accurate centerline of the chromosome, which is then used for the measurement of the FISH probe signals. Then this centerline information is used to detect the centromere location of the chromosome and the probe signal location distances were measured with respective to these landmarks. The ability to accurately detect FISH probe locations with respective to its centerline and other landmarks can provide the cytogeneticists with detailed information that could lead to a faster diagnosis