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Normalized mean glandular dose computation from mammography using GATE: a validation study.
Marios E Myronakis1, Marketa Zvelebil, Dimitra G Darambara
1Division of Radiotherapy and Imaging, The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, SW3 6JJ, UK. marios.myronakis@icr.ac.uk
This study introduces new modules for the Geant4 Application for Tomographic Emission (GATE) toolkit, enabling the calculation of normalized mean glandular dose (MGD) for mammography. This advancement aids in accurate breast dose assessment in medical imaging.
Area of Science:
- Medical Physics
- Radiation Dosimetry
- Computational Imaging
Background:
- Mean glandular dose (MGD) is crucial for assessing patient breast dose in mammography.
- Current Monte Carlo methods require normalized MGD derived from incident air kerma.
- The Geant4 Application for Tomographic Emission (GATE) toolkit lacks functionality for normalized MGD calculation.
Purpose of the Study:
- To extend the GATE toolkit with new modules for calculating normalized MGD in mammography.
- To validate the developed modules against published data and assess their accuracy.
- To investigate the impact of skin thickness and composition on normalized MGD.
Main Methods:
- Development of two new modules within the GATE toolkit.
- Utilized Monte Carlo simulations for normalized MGD computation in compressed breast phantoms.
- Validated results against published data across various half-value layers (HVLs).
- Investigated variations in normalized MGD by altering skin tissue properties.
Main Results:
- The extended GATE toolkit successfully provided normalized MGD values.
- Validated results showed good agreement with existing literature.
- Significant changes in normalized MGD were observed with variations in skin thickness and composition, particularly for breast thicknesses other than 5 cm.
Conclusions:
- The new GATE modules provide a reliable method for calculating normalized MGD.
- The findings highlight the importance of considering skin properties in breast dose estimation.
- Potential need for revising standard breast phantom models based on skin composition effects.
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