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Monte Carlo dose calculation in dental amalgam phantom.
Mohd Zahri Abdul Aziz1, A L Yusoff2, N D Osman3
1Oncological and Radiological Science Cluster, Advance Medical and Dental Institute, Universiti Sains Malaysia, Kepala Batas 13200, Penang, Malaysia.
Journal of Medical Physics
|October 27, 2015
Summary
Metal amalgam in radiation therapy causes CT image artifacts, leading to dose calculation errors. A new technique reduces these artifacts and dose uncertainties from 46% to 2%, improving accuracy for electron beam therapy.
Area of Science:
- Medical Physics
- Radiotherapy
- Medical Imaging
Background:
- Accurate dose calculation is crucial in electron beam therapy, with tissue inhomogeneity being a key factor.
- Computed tomography (CT) images are essential for radiotherapy treatment planning.
- Metal artifacts in CT images, particularly from dental amalgam, significantly compromise dose calculation accuracy.
Purpose of the Study:
- To address the challenge of dose calculation errors caused by metal amalgam artifacts in CT images.
- To improve the accuracy of radiotherapy dose calculations in the presence of dental materials.
- To reduce dose uncertainties in electron beam therapy for head and neck treatments.
Main Methods:
- Applied a streak artifact reduction technique to correct CT images with metal amalgam.
- Corrected amalgam density data to assign accurate voxel density values.
- Utilized Monte Carlo (MC) calculations for dose assessment.
Main Results:
- The artifact reduction technique improved image quality, enhancing structure delineation and density assignment.
- Dose uncertainties due to metal amalgam were significantly reduced from 46% to 2% at d80.
- Accurate amalgam voxel density values were achieved post-correction.
Conclusions:
- The developed correction strategy effectively reduces dose calculation uncertainties caused by metal amalgam artifacts.
- This technique is particularly relevant for head and neck radiotherapy due to the presence of radiosensitive organs.
- The study recommends this strategy for enhancing accuracy in Monte Carlo-based dose calculations.
