Optimization and validation of automated dicentric chromosome analysis for radiological/nuclear triage applications.
Mutat Res Genet Toxicol Environ Mutagen
; 847: 503087, 2019 Nov.
Article
em En
| MEDLINE
| ID: mdl-31699339
ABSTRACT
Dicentric Chromosome Assay (DCA) is the most preferred cytogenetic technique for absorbed radiation dose assessment in exposed humans. However, DCA is somewhat impractical for triage application owing to its labor intensive and time consuming nature. Although lymphocyte culture for 48â¯h in vitro is inevitable for DCA, manual scoring of dicentric chromosomes (DCs) requires an additional time of 24-48â¯h, making the overall turnaround time of 72-96â¯h for dose estimation. To accelerate the speed of DC analysis for dose estimation, an automated tool was optimized and validated for triage mode of scoring. Several image training files were created to improve the specificity of automated DC analysis algorithm. Accuracy and efficiency of the automated (unsupervised) DC scoring was compared with the semi-automated scoring that involved human verification and correction of DCs (elimination of false positives and inclusion of true positives). DC scoring was performed by both automated and semi-automated modes for different doses of X-rays and γ-rays (0â¯Gy-5â¯Gy). Biodoses estimated from the frequencies of DCs detected by both automated (unsupervised) and semi-automated (supervised) scoring modes were grossly similar to the actual delivered doses in the range of 0.5 to 3â¯Gy of low LET radiation. We suggest that the automated DC tool can be effectively used for large scale radiological/nuclear incidents where a rapid segregation is essential for prioritizing moderately or severely exposed humans to receive appropriate medical countermeasures.
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Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Lesões por Radiação
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Radiometria
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Linfócitos
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Triagem
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Cromossomos Humanos
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Liberação Nociva de Radioativos
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Incidentes com Feridos em Massa
Limite:
Humans
Idioma:
En
Ano de publicação:
2019
Tipo de documento:
Article