Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/24201
Title: A comparison between anisotropic analytical and multigrid superposition dose calculation algorithms in radiotherapy treatment planning
Authors: Wu, VWC 
Tse, TKH
Ho, CLM
Yeung, ECY
Keywords: Anisotropic analytical algorithm (AAA)
Dose calculation algorithm
Multigrid superposition (MGS) algorithm
Radiotherapy treatment planning
Issue Date: 2013
Publisher: Elsevier Science Inc
Source: Medical dosimetry, 2013, v. 38, no. 2, p. 209-214 How to cite?
Journal: Medical Dosimetry 
Abstract: Monte Carlo (MC) simulation is currently the most accurate dose calculation algorithm in radiotherapy planning but requires relatively long processing time. Faster model-based algorithms such as the anisotropic analytical algorithm (AAA) by the Eclipse treatment planning system and multigrid superposition (MGS) by the XiO treatment planning system are 2 commonly used algorithms. This study compared AAA and MGS against MC, as the gold standard, on brain, nasopharynx, lung, and prostate cancer patients. Computed tomography of 6 patients of each cancer type was used. The same hypothetical treatment plan using the same machine and treatment prescription was computed for each case by each planning system using their respective dose calculation algorithm. The doses at reference points including (1) soft tissues only, (2) bones only, (3) air cavities only, (4) soft tissue-bone boundary (Soft/Bone), (5) soft tissue-air boundary (Soft/Air), and (6) bone-air boundary (Bone/Air), were measured and compared using the mean absolute percentage error (MAPE), which was a function of the percentage dose deviations from MC. Besides, the computation time of each treatment plan was recorded and compared. The MAPEs of MGS were significantly lower than AAA in all types of cancers (p<0.001). With regards to body density combinations, the MAPE of AAA ranged from 1.8% (soft tissue) to 4.9% (Bone/Air), whereas that of MGS from 1.6% (air cavities) to 2.9% (Soft/Bone). The MAPEs of MGS (2.6%±2.1) were significantly lower than that of AAA (3.7%±2.5) in all tissue density combinations (p<0.001). The mean computation time of AAA for all treatment plans was significantly lower than that of the MGS (p<0.001). Both AAA and MGS algorithms demonstrated dose deviations of less than 4.0% in most clinical cases and their performance was better in homogeneous tissues than at tissue boundaries. In general, MGS demonstrated relatively smaller dose deviations than AAA but required longer computation time.
URI: http://hdl.handle.net/10397/24201
ISSN: 0958-3947
DOI: 10.1016/j.meddos.2013.02.001
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