What is it about?
Quantification of radiation exposures remains a labour-intensive bottleneck for determining radiation exposures in radiation incidents or accidents. We used our ADCI software for estimating radiation dose that requires only images of blood cells from many potentially exposed individuals and a reliable internet connection. We show that In a large-scale radiation incident 1000 radiation-exposed samples can be analyzed in ~4 days. This is adequate to treat radiation overexposures for those who need it.
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Why is it important?
Streaming ADCI Online increases the capacity of locally installed ADCI software to handle radiation incidents of any magnitude. This surge capacity can fulfill burst requirements for analysis of large numbers of samples using parallelized cloud-based instances. When configured with an array of GPUbased cloud systems, ADCI Online can estimate radiation doses at population-scale with speeds comparable to either multiple dedicated or supercomputer systems. This paper has been peer reviewed and has been accepted for publication in an upcoming issue of the journal Radiation Protection Dosimetry.
Perspectives
Population-scale exposures with datasets derived from ex vivo irradiated samples on a supercomputer(1) substantially increase ADCI’s image processing speed, however these systems are not widely available to radiation biodosimetry laboratories. To achieve similar or faster results, we analyze samples with an array of lower throughput, globally available, cloud computer systems. Cloud computing outsources economically accessible computing hardware, storage, or software on-demand. Cloud-based resources would be useful in radiation cytogenetic biodosimetry because they can be allocated based on the workload, e.g., the number of samples and metaphase cell images analyzed. ADCI uses a secure zero-trust, cloud computing framework available from Amazon Web Services (AWS). ADCI Online can be accessed through AWS AppStream 2.0, a fully managed streaming service for Desktop software. Separation and encryption of sensitive data are key to cloud-based data protection. Users upload locally stored metaphase cell images to an AWS Simple Storage Service (S3) bucket which is subsequently linked to ADCI within an interactive streaming session. ADCI Online remotely enables rapid estimation of radiation exposures of uploaded samples, extending the capacity of a Desktop physical workstation with ADCI installed.
Dr Peter K Rogan
Western University
Read the Original
This page is a summary of: Radiation Exposure Determination in a Secure, Cloud-Based Online Environment, December 2021, Cold Spring Harbor Laboratory Press,
DOI: 10.1101/2021.12.09.471993.
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