RadSter-4: Process control

Tuesday November 08, 2022 from 15:30 to 17:00

Room: Moon

RadSter-4.2 Designing product radiation shielding using Monte Carlo simulations

Daniel Badali, Canada

Staff Scientist
Triple Ring Technologies


Designing radiation shielding using Monte Carlo simulations

Daniel S Badali1, Tobias Funk1.

1Triple Ring Technologies, Newark, CA, United States

There is an increasing desire to use radiation sterilization for medical devices that contain components that are sensitive to radiation, such as electronics. To address this, manufacturers are exploring the use of shielding placed in a way that protects radiation-sensitive areas without compromising the sterility of the device.

In this presentation we use Monte Carlo simulations to explore how dose maps change when the radiation beam is partially blocked with such shielding. Monte Carlo simulations have emerged as a powerful tool to predict the dose delivered during radiation sterilization. Entire CAD models of the medical device can be imported and placed into a simulated beamline, and then the simulations calculate the 3D distribution of dose. This enables investigation into changes to the dose map as a result of effects such as:

  • variation of the device orientation
  • different sterilization modalities (i.e., gamma, e-beam, or X-ray)
  • placement and material of radiation shields

We used the Monte Carlo simulation library Geant4 to simulate a beam of 10 MeV electrons and partially blocked the beam with a 6 mm thick piece of lead. The resulting dose map is shown in the figure below and is compared to a heuristic model which assumes a perfectly absorbing shield. The simulations reveal that a significant portion of the beam is backscattered, leading to an increase in dose in front of the shield. Scatter also increases the dose behind the shield.

These results show that radiation shields can provide a good option to protect sensitive components of a device but need to be carefully designed to avoid unintended modifications of the planned dose map. Therefore, Monte Carlo simulations offer an ideal tool to explore the complete design space.

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