Author: Lotem Buchbinder Shadur, Shaheen Dewji, Martin Graffigna, Alejandro Rafael Martinez, Emmanuel Mate-Kole, Antonio McClain, Samuel Taylor, Jeffrey Wang 👨🔬
Affiliation: Student, Nuclear and Radiological Engineering and Medical Physics Programs, Georgia Institute of Technology 🌍
Purpose: DosInMe is an internal dosimetry visualization tool developed by the Radiological Engineering, Detection, and Dosimetry Laboratory at Georgia Tech to assist researchers and professionals in visualizing the metabolic transfer of radionuclides internalized in the human body. The software highlights radiation distribution and accumulation in various organs of interest.
Methods: DosInMe utilizes Blender and its Python API to simulate changes in radionuclide activity and dose as a function of time post-intake in human computational phantoms. Visualizations are informed by biokinetic models implemented using in-house Python codes, REDCAL and Bq2Sv, which support inhalation and injection exposure modes, respectively. These models are based on the Occupational Intake of Radionuclides (OIR) system published by the International Commission on Radiological Protection (ICRP). REDCAL incorporates stochastic uncertainty and sensitivity analysis, leveraging methods such as Latin Hypercube Sampling for variability assessment in parameters influencing biokinetic models. The phantom library integrates ICRP Publication 145 reference phantoms and extends to non-reference phantoms, including age-specific phantoms, enabling robust and customizable modeling capabilities. Recent advancements include support for complex decay chains, multi-radionuclide exposures, and a user-friendly graphical user interface (GUI) in a standalone executable application with detailed accompanying documentation.
Results: DosInMe addresses challenges in effectively visualizing radionuclide activity while maintaining clarity and precision, particularly for complex decay scenarios. REDCAL-enhanced modeling provides accurate time-dependent radionuclide activity and dose distribution simulations, capturing variability in energy deposition across tissues. For example, inhalation modeling for I-131 in REDCAL demonstrated agreement within 1.04% relative and 0.7% absolute difference compared to ICRP reference data, highlighting the system’s precision and versatility.
Conclusion: DosInMe integrates advanced biokinetic modeling with 3D anatomical visualization, facilitating identification of high radiation exposure areas and enabling accurate dose assessment and risk evaluation. The tool’s adaptability and rigor make it a valuable resource for radiological safety and internal dosimetry studies.