BibTex Citation Data :
@article{JPA30102, author = {Fajar Miraz Fauzi and Siti Mutmainnah and Rio Rizky Rahmadani and Freddy Haryanto}, title = {Optimizing Dose Distribution with Direct Aperture Optimization: A MatRad-Based Analysis}, journal = {Journal of Physics and Its Applications}, volume = {8}, number = {3}, year = {2026}, keywords = {Bixel; Direct Aperture Optimization; Dosimetry; MatRad; Treatment Planning System}, abstract = { Advanced optimization algorithms like Direct Aperture Optimization (DAO) are integral to modern radiotherapy, yet research is often hindered by the limited accessibility of commercial Treatment Planning Systems. Open-source platforms like matRad provide a vital framework for such investigations. This study evaluates the dosimetric impact of DAO activation and its interplay with varying bixel resolutions (5×5 to 10×10 mm²) using matRad for a liver cancer case. Twelve treatment plans were generated and calculated using the ompMC Monte Carlo engine. Initial verification yielded a 3.14% mean relative statistical uncertainty, indicating that the stochastic uncertainty was relatively small compared with the dosimetric differences investigated. Twelve plans were assessed using Dose Volume Histograms (DVHs), Conformity Index (CI), and Homogeneity Index (HI). Results showed DAO significantly reduced stomach dose (e.g., 6.33% at 5×5 mm²; p=0.031). At 5×5 mm², heart and liver mean doses decreased by 7.15% and 1.83% respectively, though these changes were resolution-dependent and statistically non-significant. For targets, DAO at 5×5 mm² caused minor, non-significant mean dose increases for the GTV (1.3%), CTV (1.01%), and PTV (0.77%). Conversely, while maintaining target coverage, DAO activation produced a statistically significant degradation in dose conformity and homogeneity across all bixel sizes (p=0.031). These findings highlight an inherent optimization trade-off that DAO prioritizes steep dose gradients for maximal OAR protection at the expense of minor internal target dose heterogeneity. This study establishes matRad as an effective environment for elucidating optimization behaviors in radiotherapy planning. }, issn = {2622-5956}, doi = {10.14710/jpa.v8i3.30102}, url = {https://ejournal2.undip.ac.id/index.php/jpa/article/view/30102} }
Refworks Citation Data :
Advanced optimization algorithms like Direct Aperture Optimization (DAO) are integral to modern radiotherapy, yet research is often hindered by the limited accessibility of commercial Treatment Planning Systems. Open-source platforms like matRad provide a vital framework for such investigations. This study evaluates the dosimetric impact of DAO activation and its interplay with varying bixel resolutions (5×5 to 10×10 mm²) using matRad for a liver cancer case. Twelve treatment plans were generated and calculated using the ompMC Monte Carlo engine. Initial verification yielded a 3.14% mean relative statistical uncertainty, indicating that the stochastic uncertainty was relatively small compared with the dosimetric differences investigated. Twelve plans were assessed using Dose Volume Histograms (DVHs), Conformity Index (CI), and Homogeneity Index (HI). Results showed DAO significantly reduced stomach dose (e.g., 6.33% at 5×5 mm²; p=0.031). At 5×5 mm², heart and liver mean doses decreased by 7.15% and 1.83% respectively, though these changes were resolution-dependent and statistically non-significant. For targets, DAO at 5×5 mm² caused minor, non-significant mean dose increases for the GTV (1.3%), CTV (1.01%), and PTV (0.77%). Conversely, while maintaining target coverage, DAO activation produced a statistically significant degradation in dose conformity and homogeneity across all bixel sizes (p=0.031). These findings highlight an inherent optimization trade-off that DAO prioritizes steep dose gradients for maximal OAR protection at the expense of minor internal target dose heterogeneity. This study establishes matRad as an effective environment for elucidating optimization behaviors in radiotherapy planning.
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