ArticleJournal of applied clinical medical physics2025
Improving VMAT dose calculation accuracy and planning quality via a GPU-accelerated Fourier transform dose calculation algorithm.
Article in Journal of applied clinical medical physics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- Improving VMAT dose calculation accuracy and planning quality via a GPU-accelerated Fourier transform dose calculation algorithm.Journal of applied clinical medical physics · 2025Article
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5 authors.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundInverse planning typically utilizes fast, less accurate dose calculation algorithms during the iterative optimization process, thus leading to dose calculation errors (DCEs) and suboptimal plans that often require dose normalization and/or plan re-optimization. PURPOSE: A graphic processing unit (GPU) accelerated Fourier transform dose calculation (FTDC) was recently commissioned at our institution during the Eclipse treatment planning system (Varian Medical Systems) v18.0 upgrade. We hypothesize that FTDC could reduce DCEs and planning failure rates (PFRs) compared to its predecessor, multi-resolution dose calculation (MRDC), while improving efficiency through utilization of GPUs.
methodsFifty lung SBRT plans were optimized with MRDC and FTDC dose calculation algorithms. Acuros XB (AXB) was then used for final dose calculations. DCEs for target and organ-at-risk (OAR) were calculated as the percent difference between AXB and dose calculated at the final optimization step. Plan quality was assessed using an in-house planning scorecard where PFRs were calculated as the percentage of plans that had a plan score less than 90% with optimal plans scored at 100%.
resultsFTDC showed excellent agreement with AXB in terms of planning target volume (PTV) coverage, as PTV D95% DCE
conclusionsFTDC shows more accurate dose calculation accuracy compared to MRDC. Its use during the optimization process improved planning quality and efficiency assisted with GPUs.
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