Development of a Miniaturized Version of Dicentric Chromosome Assay Tool for Radiological Triage

Abstract

Use of ionizing radiation (IR) in various industrial, medical and other applications can potentially increase the risk of medical, occupational or accidental human exposure. Additionally, in the event of a radiological or nuclear (R/N) incident, several tens of hundreds and thousands of people are likely to be exposed to IR. IR causes serious health effects including mortality from acute radiation syndrome and therefore it is imperative to determine the absorbed radiation dose, which will enable physicians in making an appropriate clinical 'life-saving' decision. The 'Dicentric Chromosome Assay (DCA)' is the gold standard for estimating the absorbed radiation dose but its performance is time consuming and laborious. Further, timely evaluation of dicentric chromosomes (DCs) for dose estimation in a large number of samples provides a bottleneck because of a limited number of trained personnel and a prolonged time for manual analysis. To circumvent some of these technical issues, we developed and optimized a miniaturized high throughput version of DCA (mini-DCA) in a 96-microtube matrix with bar-coded 1.4 ml tubes to enable the processing of a large number of samples. To increase the speed of DC analysis for radiation dose estimation, a semi-automated scoring was optimized using the Metafer DCScore algorithm. The accuracy of mini-DCA in dose estimation was verified and validated though comparison with conventional DCA performed in 15 ml conical tubes. The mini-DCA considerably reduced the sample processing time by a factor of 4 when compared to the conventional DCA. Further, the radiation doses estimated by mini-DCA using the triage mode of scoring (50 cells or 30 DCs) were similar to that of conventional DCA using 300-500 cells. The mini-DCA coupled with semi-automated DC scoring not only reduced the sample processing and analysis times by a factor of 4 but also enabled the processing of a large number of samples at once. Our mini-DCA method, once automated for high throughput robotic platforms, will be an effective radiological triage tool for mass casualty incidents.

Use of human lymphocyte G0 PCCs to detect intra- and inter-chromosomal aberrations for early radiation biodosimetry and retrospective assessment of radiation-induced effects

“…Several efforts have been continually made to reduce the turnaround time for DCA: (I) optimization of chromosome preparation [10], (II) automated dicentric chromosome scoring [11–18], (III) sample tracking [19], (IV) establishment of network for cytogenetic biodosimetry laboratories [20–22], (V) data generation through electronic scoring of digital images [23–26] and a triage mode of scoring either 50 cells or 30 dicentrics [27–29]. Although these efforts significantly reduce the turnaround time for dose estimation, in vitro culturing of lymphocytes for 48 hrs is still inevitable for performing the conventional DCA.…”

Establishing a Reference Dose–Response Calibration Curve for Dicentric Chromosome Aberrations to Assess Accidental Radiation Exposure in Saudi Arabia

“…Acknowledging that the DCA is currently the best-established cytogenetic technique for absorbed radiation dose assessment, it is somewhat impractical for triage of mass casualty events owing to its labor-intensive and time-consuming procedures. While lymphocyte culture for 48 h is inevitable, many research is directed to streamline DCA processes by automating DC scoring in metaphase images using machine learning image processing techniques (36)(37)(38)(39)(40). Hence, many image training classifiers were created to improve the specificity of automated DC analysis algorithm.…”

The Use of Image Processing and Analysis in Automated Biological Dosimetry

“…have used the DCScore module in Metafer to perform semi-automated DC scoring, to increase the rapidity of DC analysis [13].…”

“…Chromosome quality is a key determining factor for the success of automated or semi-automated scoring systems. When high-quality metaphase chromosomes are used, with no overlapping chromosomes or staining debris, the automated detection of DCs is highly accurate (> 92 -95 % of manual scoring) [13]. Another piece of software that has been developed for the automatic identification of DCs is Automated Dicentric Chromosome Identifier (ADCI), by Rogan group, which was initially released in 2010 [11,[15][16][17].…”