ISSN: 1859 - 2872
Density correction of CT images in dose calculation of volumetric modulated arc therapy for some head and neck cancer using AAA and acuros XB algorithm on Eclipse treatment planning software
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Abstract
Objective: To analyze the effect of density correction in some dental artifact areas of CT image in the dose calculation of volumetric modulated arce therapy (VMAT) for head and neck cancers using the AAA (analysis anisotropy algorithm) and AXB (Acuros XB) algorithms on the treatment planning system (TPS) Eclipse v13.0. Subject and method: The 12 series of CT images along with 12 approved plans of 12 head and neck cancer patients had some dental artifact areas. Plans are made on Eclipse v13.0 treatment planning system using AAA and Acuros XB algorithms. Method: Copied each of the original simulated CT series into 2 study CT series: CT_AAA (without density correction) and CT_AXB (with density correction). Copied each original treated plans into 6 study plans: AAA_ReCal, AAA_ReOpt, AAA_AXB, AXB_ReCal, AXB_ReOpt, and AXB_AAA. Re-optimize plan and/or recalculate of these plans dose using the corresponding AAA, AXB algorithms. Compare and evaluate the dose distribution in several regions: air cavity, bone, tissue as well as density correction region to analyze the role of the density correction and the AXB algorithm in dose calculation. Result: In the air cavity region and bone region, the calculated dose using the AXB algorithm was significantly lower than the calculated dose using the AAA algorithm by 13.38% and 5.31% respectively (p<0.0001). For the AAA algorithm, the density correction did not affect the calculated dose much, on CT_AXB image series the calculated dose was higher than on the CT_AAA image series only about 1.47% (p<0.0001). For the AXB algorithm, the density correction had a relative influence on the dose calculation, in density correction region the calculated dose using the AXB algorithm was higher than the calculated dose using the AAA algorithm about 3.71% (p<0.0001). Quality assurance (QA) of AXB plans by Gamma Index method with parameter ∆D/∆d = 3%/3mm gave a higher pass rate than AAA plans by 1.01% (p<0.0001). The planning time (optimization and dose calculation) of VMAT plans using AXB algorithm was 2.05 times faster than using AAA algorithm (p<0.0001). Conclusion: In planning VMAT for some head and neck cancers, correction of CT images density in some dental artifact areas and the use of AXB algorithm is necessary to increase accuracy and reduce time in dose calculation for patients.
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References
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