ArticleEJNMMI physics2025
Optimizing dosimetry in Y-90 microsphere radioembolization: GPU-accelerated Monte Carlo simulation versus conventional methods for high-volume setting.
Article in EJNMMI physics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Personalised Dosimetry in Nuclear Medicine: Bridging Physics, Biology and AI for Next Generation Radiopharmaceutical Therapy.Nuclear medicine and molecular imaging · 2026Review
- Towards practical radiopharmaceutical treatment planning: a review of dosimetry simplification techniques.Theranostics · 2026Review
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10 authors.
Funding
Abstract
backgroundYttrium-90 (
methodsA fast Monte Carlo simulation algorithm was developed using Graphics Processing Unit (GPU) acceleration and applied retrospectively to eight patients diagnosed with hepatocellular carcinoma or metastatic colorectal cancer. The dosimetric performance of the GPU-based approach was compared against direct Monte Carlo (MC) simulations, the Medical Internal Radiation Dose (MIRD) formalism, the Voxel S-value (VSV) method, and the Local Energy Deposition (LED) model. Voxel- and organ-level dose accuracy were quantified using metrics such as Mean Absolute Relative Error (MARE), Relative Standard Deviation (RSD), and D95 in dose volume histogram. Statistical comparisons were conducted using Shapiro-Wilk normality tests and repeated measures ANOVA to assess inter-method differences.
resultsThe GPU-based Monte Carlo code demonstrated high accuracy and computational efficiency. Using direct MC simulation as the reference, the GPU-based approach yielded the lowest voxel-level variability, with median RSDs in high-activity transverse regions reaching - 1.13%, indicating superior consistency. Corresponding MARE were 4.53% for the GPU method, compared to 6.71% for VSV and 49.36% for LED, confirming its dosimetric reliability. At the organ level, the GPU-based method achieved RSDs of 0.35% ± 0.80% (tumor), -0.45% ± 0.76% (liver), 1.41% ± 4.45% (lung), and - 1.43% ± 1.23% (spleen), significantly outperforming alternative models. Notably, VSV and LED substantially underestimated lung dose (-52.19% ± 23.87%, -53.71 ± 22.17%), highlighting their limited applicability in heterogeneous regions. In contrast, the dose of spleen (F = 3.26, p = 0.069) and kidneys (F = 3.22, p = 0.071) did not show statistically significant differences between methods. In terms of computational performance, the GPU-based code delivered a remarkable 1,296-fold speed-up over traditional MC simulations, enabling efficient voxel-level dosimetry suitable for clinical workflows.
conclusionThe GPU-based fast Monte Carlo simulation provides a highly accurate and computationally efficient tool for voxel-level dosimetry in CLINICAL TRIAL NUMBER: Not applicable.
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