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Radiation Exposure Determination in a Secure, Cloud-based Online Environment

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Background: In a major radiation incident, the speed of sample processing and interpretation of estimated exposures will be critical for triaging individuals. The Automated Dicentric Chromosome (DC) Identifier and Dose Estimator System (ADCI) selects and processes images to identify DCs and determines radiation dose without manual review. The goal of this study was to broaden accessibility and speed of this system with data parallelization while protecting data and software integrity. Methods: ADCI_Online is a secure web-streaming platform that can be accessed worldwide from distributed local nodes. Data and software are separated until they are linked for estimation of radiation exposures. Performance is assessed with data from multiple biodosimetry laboratories. Results: Dose estimates from ADCI_Online are identical to ADCI running on dedicated GPU-accelerated hardware. Metaphase image processing, automated image selection, calibration curve generation, and radiation dose estimation of a typical set of samples of unknown exposures were completed in(54,595 metaphase images) accelerated estimation of radiation doses to within clinically-relevant time frames. Conclusions: The ADCI_Online streaming platform is intended for on-demand, standardized radiation research assessment, biodosimetry proficiency testing, inter-laboratory comparisons, and training. The platform has the capacity to handle analytic bottlenecks in intermediate to large radiation accidents or events.


doi: 10.1101/2021.12.09.471993

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Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Citation of this paper:

Radiation Exposure Determination in a Secure, Cloud-based Online Environment Ben C. Shirley, Eliseos J Mucaki, Joan H.M. Knoll, Peter K Rogan bioRxiv 2021.12.09.471993; doi:

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