Radiation doses in cone-beam breast computed tomography: a Monte Carlo simulation study
Ying Yi1, Chao-Jen Lai, Tao Han
1Department of Imaging Physics, University of Texas MD Anderson Cancer Center, Houston, Texas 77030, USA.
Medical Physics
|April 2, 2011
Summary
Monte Carlo simulation accurately estimates breast radiation dose using simplified models. Homogeneous and ellipsoidal phantoms are sufficient for average dose calculations in cone beam breast computed tomography (CBBCT).
Area of Science:
- Medical Physics
- Radiological Imaging
- Computational Biology
Background:
- Accurate estimation of radiation dose in breast imaging is crucial for risk assessment.
- Cone beam breast computed tomography (CBBCT) offers potential for improved breast imaging but requires precise dose evaluation.
- Understanding spatial dose variation and mean glandular dose (MGD) is essential for optimizing CBBCT protocols.
Purpose of the Study:
- To develop and validate a Monte Carlo simulation method for estimating spatial dose variation, average dose, and MGD in real breasts using CBBCT images.
- To assess the feasibility of using simplified breast models (homogeneous, ellipsoidal, cylindrical) for dose estimation in CBBCT.
- To investigate the impact of breast composition (glandularity) on radiation dose.
Main Methods:
- Monte Carlo simulations were performed using structured breast models derived from CBBCT images of mastectomy specimens.
- Validation of the Monte Carlo method was conducted by comparing dose estimates with thermoluminescent dosimeter measurements.
- Dose estimations were performed for various models including homogeneous, ellipsoidal, and cylindrical phantoms to evaluate their suitability for representing real breasts.
Main Results:
- Monte Carlo simulations showed higher doses in glandular tissue compared to adipose tissue.
- Average doses estimated using homogeneous breast models were nearly identical to those from structured models (p=1).
- Ellipsoidal phantoms provided similar average dose estimates to structured models (rms difference 1.7%), while cylindrical phantoms showed significantly lower estimates (rms difference 7.7%).
- Normalized mean glandular doses (MGDs) decreased with increasing glandularity.
Conclusions:
- Homogeneous breast models derived from CBBCT images are sufficient for estimating average breast dose.
- Ellipsoidal digital phantoms with similar dimensions and glandularity can effectively represent real breasts for average dose estimation via Monte Carlo simulation.
- Structured breast models enable accurate MGD estimation, confirming that normalized MGDs decrease with increasing glandularity, consistent with prior research in CBBCT and mammography.
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