Incorporating biological modeling into patient-specific plan verification

被引:0
|
作者
Alexandrian, Ara N. [1 ]
Mavroidis, Panayiotis [2 ]
Narayanasamy, Ganesh [3 ]
McConnell, Kristen A. [1 ]
Kabat, Christopher N. [1 ]
George, Renil B. [1 ]
Defoor, Dewayne L. [1 ]
Kirby, Neil [1 ]
Papanikolaou, Nikos [1 ]
Stathakis, Sotirios [1 ]
机构
[1] Univ Texas Hlth Sci Ctr San Antonio, Dept Radiat Oncol, San Antonio, TX 78229 USA
[2] Univ N Carolina, Dept Radiat Oncol, Chapel Hill, NC 27515 USA
[3] Univ Arkansas Med Sci, Dept Radiat Oncol, Little Rock, AR 72205 USA
来源
关键词
IMRT QA; radiobiological QA; radiobiological verification; radiobiology; MODULATED RADIATION-THERAPY; COLLAPSED CONE CONVOLUTION; QUALITY-ASSURANCE; DOSE-CALCULATION; QUANTITATIVE-EVALUATION; PASSING RATES; NORMAL TISSUE; QA; ALGORITHM; TUMOR;
D O I
10.1002/acm2.12831
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Purpose Dose-volume histogram (DVH) measurements have been integrated into commercially available quality assurance systems to provide a metric for evaluating accuracy of delivery in addition to gamma analysis. We hypothesize that tumor control probability and normal tissue complication probability calculations can provide additional insight beyond conventional dose delivery verification methods. Methods A commercial quality assurance system was used to generate DVHs of treatment plan using the planning CT images and patient-specific QA measurements on a phantom. Biological modeling was performed on the DVHs produced by both the treatment planning system and the quality assurance system. Results The complication-free tumor control probability, P+, has been calculated for previously treated intensity modulated radiotherapy (IMRT) patients with diseases in the following sites: brain (-3.9% +/- 5.8%), head-neck (+4.8% +/- 8.5%), lung (+7.8% +/- 1.3%), pelvis (+7.1% +/- 12.1%), and prostate (+0.5% +/- 3.6%). Conclusion Dose measurements on a phantom can be used for pretreatment estimation of tumor control and normal tissue complication probabilities. Results in this study show how biological modeling can be used to provide additional insight about accuracy of delivery during pretreatment verification.
引用
收藏
页码:94 / 107
页数:14
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